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Type 'q()' to quit R. > library(testthat) > library(dtComb) > # require(APtools) > # # library(usethis) > > test_check("dtComb") Method : TS Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Kappa Accuracy 0.6180251 0.8106509 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8843566 0.02475582 0.8358361 0.9328771 15.52591 2.316930e-54 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8843566 0.7858845 0.09847211 0.02770867 2 Combination log_leukocyte 0.8843566 0.8668349 0.01752173 0.01545491 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 3.553837 0.000379654 2 1.133732 0.256906853 3 -2.038473 0.041502637 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 55 5 60 Test - 27 82 109 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.36 (0.28, 0.43) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.67 (0.56, 0.77) Specificity * 0.94 (0.87, 0.98) Positive predictive value * 0.92 (0.82, 0.97) Negative predictive value * 0.75 (0.66, 0.83) Positive likelihood ratio 11.67 (4.92, 27.70) Negative likelihood ratio 0.35 (0.26, 0.48) False T+ proportion for true D- * 0.06 (0.02, 0.13) False T- proportion for true D+ * 0.33 (0.23, 0.44) False T+ proportion for T+ * 0.08 (0.03, 0.18) False T- proportion for T- * 0.25 (0.17, 0.34) Correctly classified proportion * 0.81 (0.74, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 4.576753 Optimal criterion : 0.6132604 ------------------------------------------------------------ Method : minimax Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Kappa Accuracy 0.5941517 0.7988166 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8822540 0.02459988 0.8340391 0.9304689 15.53885 1.893381e-54 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8822540 0.7858845 0.09636950 0.02492035 2 Combination log_leukocyte 0.8822540 0.8668349 0.01541912 0.01831867 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 3.8671004 0.0001101371 2 0.8417159 0.3999469867 3 -2.0384732 0.0415026367 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 54 6 60 Test - 28 81 109 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.36 (0.28, 0.43) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.66 (0.55, 0.76) Specificity * 0.93 (0.86, 0.97) Positive predictive value * 0.90 (0.79, 0.96) Negative predictive value * 0.74 (0.65, 0.82) Positive likelihood ratio 9.55 (4.34, 20.99) Negative likelihood ratio 0.37 (0.27, 0.50) False T+ proportion for true D- * 0.07 (0.03, 0.14) False T- proportion for true D+ * 0.34 (0.24, 0.45) False T+ proportion for T+ * 0.10 (0.04, 0.21) False T- proportion for T- * 0.26 (0.18, 0.35) Correctly classified proportion * 0.80 (0.73, 0.86) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 9.733051 Optimal criterion : 0.5895711 ------------------------------------------------------------ Method : logistic Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Kappa Accuracy 0.5851064 0.8205128 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8304464 0.03301157 0.7657449 0.8951479 10.010016 1.377308e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination mayoscore5 0.8304464 0.8301133 0.0003331113 0.002298783 2 Combination mayoscore4 0.8304464 0.7989674 0.0314790140 0.019410424 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.0311459027 0.020826168 z p-value 1 0.1449076 0.8847838 2 1.6217582 0.1048551 3 1.4955177 0.1347794 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 53 19 72 Test - 23 139 162 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.31 (0.25, 0.37) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.70 (0.58, 0.80) Specificity * 0.88 (0.82, 0.93) Positive predictive value * 0.74 (0.62, 0.83) Negative predictive value * 0.86 (0.79, 0.91) Positive likelihood ratio 5.80 (3.71, 9.07) Negative likelihood ratio 0.34 (0.24, 0.49) False T+ proportion for true D- * 0.12 (0.07, 0.18) False T- proportion for true D+ * 0.30 (0.20, 0.42) False T+ proportion for T+ * 0.26 (0.17, 0.38) False T- proportion for T- * 0.14 (0.09, 0.21) Correctly classified proportion * 0.82 (0.77, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.3442226 Optimal criterion : 0.5771153 ------------------------------------------------------------ Method : SL Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Kappa Accuracy 0.6021085 0.8290598 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8304464 0.03301563 0.7657369 0.8951558 10.008785 1.394542e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination mayoscore5 0.8304464 0.8301133 0.0003331113 0.002489113 2 Combination mayoscore4 0.8304464 0.7989674 0.0314790140 0.019270484 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.0311459027 0.020826168 z p-value 1 0.1338273 0.8935391 2 1.6335352 0.1023565 3 1.4955177 0.1347794 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 53 17 70 Test - 23 141 164 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.30 (0.24, 0.36) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.70 (0.58, 0.80) Specificity * 0.89 (0.83, 0.94) Positive predictive value * 0.76 (0.64, 0.85) Negative predictive value * 0.86 (0.80, 0.91) Positive likelihood ratio 6.48 (4.04, 10.40) Negative likelihood ratio 0.34 (0.24, 0.48) False T+ proportion for true D- * 0.11 (0.06, 0.17) False T- proportion for true D+ * 0.30 (0.20, 0.42) False T+ proportion for T+ * 0.24 (0.15, 0.36) False T- proportion for T- * 0.14 (0.09, 0.20) Correctly classified proportion * 0.83 (0.77, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 3.718027 Optimal criterion : 0.5897735 ------------------------------------------------------------ Method : scoring Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Kappa Accuracy 0.5819608 0.8247863 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination mayoscore5 0.8301133 0.8301133 0.0000000 NaN 0.000000 2 Combination mayoscore4 0.8301133 0.7989674 0.0311459 0.02082617 1.495518 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.0311459 0.02082617 1.495518 p-value 1 1.0000000 2 0.1347794 3 0.1347794 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 49 14 63 Test - 27 144 171 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.27 (0.21, 0.33) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.64 (0.53, 0.75) Specificity * 0.91 (0.86, 0.95) Positive predictive value * 0.78 (0.66, 0.87) Negative predictive value * 0.84 (0.78, 0.89) Positive likelihood ratio 7.28 (4.29, 12.33) Negative likelihood ratio 0.39 (0.29, 0.53) False T+ proportion for true D- * 0.09 (0.05, 0.14) False T- proportion for true D+ * 0.36 (0.25, 0.47) False T+ proportion for T+ * 0.22 (0.13, 0.34) False T- proportion for T- * 0.16 (0.11, 0.22) Correctly classified proportion * 0.82 (0.77, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 6.009625 Optimal criterion : 0.5561292 ------------------------------------------------------------ Method : PCL Samples : 427 Markers : 2 Events : B, M Standardization : range Cut points : Youden Kappa Accuracy 0.7137342 0.8641686 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9130098 0.01420537 0.8851678 0.9408518 29.07420 7.609053e-186 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9130098 0.7640463 0.1489635 0.01549650 9.612715 2 Combination V5 0.9130098 0.9458612 0.0328514 -0.01418123 -2.316541 3 V4 V5 0.7640463 0.9458612 0.1818149 -0.02590117 -7.019561 p-value 1 7.066057e-22 2 2.052877e-02 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 134 44 178 Test - 14 235 249 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.42 (0.37, 0.47) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.91 (0.85, 0.95) Specificity * 0.84 (0.79, 0.88) Positive predictive value * 0.75 (0.68, 0.81) Negative predictive value * 0.94 (0.91, 0.97) Positive likelihood ratio 5.74 (4.36, 7.57) Negative likelihood ratio 0.11 (0.07, 0.19) False T+ proportion for true D- * 0.16 (0.12, 0.21) False T- proportion for true D+ * 0.09 (0.05, 0.15) False T+ proportion for T+ * 0.25 (0.19, 0.32) False T- proportion for T- * 0.06 (0.03, 0.09) Correctly classified proportion * 0.86 (0.83, 0.90) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.7760336 Optimal criterion : 0.7476993 ------------------------------------------------------------ Method : PT Samples : 427 Markers : 2 Events : B, M Standardization : zScore Cut points : Youden Kappa Accuracy 0.7210713 0.8688525 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9229149 0.01309465 0.8972498 0.9485799 32.29677 7.763580e-229 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9229149 0.7640463 0.15886855 0.01672726 9.497582 2 Combination V5 0.9229149 0.9458612 0.02294633 -0.01256102 -1.826789 3 V4 V5 0.7640463 0.9458612 0.18181488 -0.02590117 -7.019561 p-value 1 2.148208e-21 2 6.773154e-02 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 132 40 172 Test - 16 239 255 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.40 (0.36, 0.45) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.89 (0.83, 0.94) Specificity * 0.86 (0.81, 0.90) Positive predictive value * 0.77 (0.70, 0.83) Negative predictive value * 0.94 (0.90, 0.96) Positive likelihood ratio 6.22 (4.64, 8.33) Negative likelihood ratio 0.13 (0.08, 0.20) False T+ proportion for true D- * 0.14 (0.10, 0.19) False T- proportion for true D+ * 0.11 (0.06, 0.17) False T+ proportion for T+ * 0.23 (0.17, 0.30) False T- proportion for T- * 0.06 (0.04, 0.10) Correctly classified proportion * 0.87 (0.83, 0.90) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.2011047 Optimal criterion : 0.7485227 ------------------------------------------------------------ Method : minmax Samples : 427 Markers : 2 Events : B, M Standardization : range Cut points : Youden Kappa Accuracy 0.7137342 0.8641686 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9129613 0.01420369 0.8851226 0.9408001 29.07423 7.602924e-186 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9129613 0.7640463 0.14891504 0.01550892 9.601895 2 Combination V5 0.9129613 0.9458612 0.03289984 -0.01417787 -2.320507 3 V4 V5 0.7640463 0.9458612 0.18181488 -0.02590117 -7.019561 p-value 1 7.848795e-22 2 2.031347e-02 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 134 44 178 Test - 14 235 249 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.42 (0.37, 0.47) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.91 (0.85, 0.95) Specificity * 0.84 (0.79, 0.88) Positive predictive value * 0.75 (0.68, 0.81) Negative predictive value * 0.94 (0.91, 0.97) Positive likelihood ratio 5.74 (4.36, 7.57) Negative likelihood ratio 0.11 (0.07, 0.19) False T+ proportion for true D- * 0.16 (0.12, 0.21) False T- proportion for true D+ * 0.09 (0.05, 0.15) False T+ proportion for T+ * 0.25 (0.19, 0.32) False T- proportion for T- * 0.06 (0.03, 0.09) Correctly classified proportion * 0.86 (0.83, 0.90) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.7741983 Optimal criterion : 0.7476993 ------------------------------------------------------------ Method : TS Samples : 426 Markers : 2 Events : B, M Standardization : zScore Cut points : Youden Kappa Accuracy 0.7561164 0.8849765 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7656841 0.023577258 0.7194735 0.8118946 11.26866 1.874046e-29 V5 0.9456148 0.011516367 0.9230431 0.9681865 38.69404 0.000000e+00 Combination 0.9573306 0.009981014 0.9377682 0.9768930 45.82005 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9573306 0.7656841 0.1916466 0.022945425 8.352277 2 Combination V5 0.9573306 0.9456148 0.0117158 0.004703465 2.490887 3 V4 V5 0.7656841 0.9456148 0.1799308 -0.025903727 -6.946134 p-value 1 6.695923e-17 2 1.274248e-02 3 3.754326e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 136 38 174 Test - 11 241 252 Total 147 279 426 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.41 (0.36, 0.46) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.93 (0.87, 0.96) Specificity * 0.86 (0.82, 0.90) Positive predictive value * 0.78 (0.71, 0.84) Negative predictive value * 0.96 (0.92, 0.98) Positive likelihood ratio 6.79 (5.04, 9.16) Negative likelihood ratio 0.09 (0.05, 0.15) False T+ proportion for true D- * 0.14 (0.10, 0.18) False T- proportion for true D+ * 0.07 (0.04, 0.13) False T+ proportion for T+ * 0.22 (0.16, 0.29) False T- proportion for T- * 0.04 (0.02, 0.08) Correctly classified proportion * 0.88 (0.85, 0.91) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : -0.0356253 Optimal criterion : 0.7889694 ------------------------------------------------------------ Method : TS Samples : 426 Markers : 2 Events : B, M Standardization : zScore Cut points : Youden Kappa Accuracy 0.7935897 0.9061033 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7639773 0.023628096 0.7176671 0.8102875 11.17218 5.579611e-29 V5 0.9469437 0.011426279 0.9245486 0.9693387 39.11541 0.000000e+00 Combination 0.9581108 0.009944354 0.9386203 0.9776014 46.06743 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9581108 0.7639773 0.19413357 0.023104579 8.402385 2 Combination V5 0.9581108 0.9469437 0.01116719 0.004502031 2.480479 3 V4 V5 0.7639773 0.9469437 0.18296638 -0.025917621 -7.059536 p-value 1 4.375006e-17 2 1.312062e-02 3 1.670594e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 129 22 151 Test - 18 257 275 Total 147 279 426 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.35 (0.31, 0.40) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.88 (0.81, 0.93) Specificity * 0.92 (0.88, 0.95) Positive predictive value * 0.85 (0.79, 0.91) Negative predictive value * 0.93 (0.90, 0.96) Positive likelihood ratio 11.13 (7.42, 16.70) Negative likelihood ratio 0.13 (0.09, 0.21) False T+ proportion for true D- * 0.08 (0.05, 0.12) False T- proportion for true D+ * 0.12 (0.07, 0.19) False T+ proportion for T+ * 0.15 (0.09, 0.21) False T- proportion for T- * 0.07 (0.04, 0.10) Correctly classified proportion * 0.91 (0.87, 0.93) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.1561852 Optimal criterion : 0.798698 ------------------------------------------------------------ Method : PCL Samples : 169 Markers : 2 Events : not_needed, needed Standardization : range Cut points : Youden Kappa Accuracy 0.5826572 0.7928994 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8801514 0.02473710 0.8316676 0.9286352 15.36766 2.697409e-53 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8801514 0.7858845 0.09426689 0.02286677 2 Combination log_leukocyte 0.8801514 0.8668349 0.01331651 0.02075691 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 4.1224408 0.0000374879 2 0.6415459 0.5211680698 3 -2.0384732 0.0415026367 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 55 8 63 Test - 27 79 106 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.37 (0.30, 0.45) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.67 (0.56, 0.77) Specificity * 0.91 (0.83, 0.96) Positive predictive value * 0.87 (0.77, 0.94) Negative predictive value * 0.75 (0.65, 0.82) Positive likelihood ratio 7.29 (3.70, 14.36) Negative likelihood ratio 0.36 (0.26, 0.50) False T+ proportion for true D- * 0.09 (0.04, 0.17) False T- proportion for true D+ * 0.33 (0.23, 0.44) False T+ proportion for T+ * 0.13 (0.06, 0.23) False T- proportion for T- * 0.25 (0.18, 0.35) Correctly classified proportion * 0.79 (0.72, 0.85) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.4528311 Optimal criterion : 0.5787777 ------------------------------------------------------------ Method : PT Samples : 169 Markers : 2 Events : not_needed, needed Standardization : zScore Cut points : Youden Kappa Accuracy 0.5649482 0.7810651 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8765069 0.02522575 0.8270653 0.9259484 14.92550 2.249418e-50 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8765069 0.7858845 0.090622372 0.02115533 2 Combination log_leukocyte 0.8765069 0.8668349 0.009671993 0.02273917 3 ddimer log_leukocyte 0.7858845 0.8668349 0.080950378 -0.03971128 z p-value 1 4.2836663 1.838386e-05 2 0.4253451 6.705851e-01 3 -2.0384732 4.150264e-02 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 74 29 103 Test - 8 58 66 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.61 (0.53, 0.68) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.90 (0.82, 0.96) Specificity * 0.67 (0.56, 0.76) Positive predictive value * 0.72 (0.62, 0.80) Negative predictive value * 0.88 (0.78, 0.95) Positive likelihood ratio 2.71 (1.99, 3.67) Negative likelihood ratio 0.15 (0.07, 0.29) False T+ proportion for true D- * 0.33 (0.24, 0.44) False T- proportion for true D+ * 0.10 (0.04, 0.18) False T+ proportion for T+ * 0.28 (0.20, 0.38) False T- proportion for T- * 0.12 (0.05, 0.22) Correctly classified proportion * 0.78 (0.71, 0.84) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : -0.9067191 Optimal criterion : 0.5691057 ------------------------------------------------------------ Method : distance Distance : lorentzian Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.4611866 0.7278107 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8158116 0.03151922 0.7540351 0.8775881 10.01965 1.249433e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8158116 0.7858845 0.02992711 0.006444088 2 Combination log_leukocyte 0.8158116 0.8668349 0.05102327 -0.036056476 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.039711280 z p-value 1 4.644119 3.415312e-06 2 -1.415093 1.570412e-01 3 -2.038473 4.150264e-02 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 75 39 114 Test - 7 48 55 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.67 (0.60, 0.74) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.91 (0.83, 0.96) Specificity * 0.55 (0.44, 0.66) Positive predictive value * 0.66 (0.56, 0.74) Negative predictive value * 0.87 (0.76, 0.95) Positive likelihood ratio 2.04 (1.60, 2.60) Negative likelihood ratio 0.15 (0.07, 0.32) False T+ proportion for true D- * 0.45 (0.34, 0.56) False T- proportion for true D+ * 0.09 (0.04, 0.17) False T+ proportion for T+ * 0.34 (0.26, 0.44) False T- proportion for T- * 0.13 (0.05, 0.24) Correctly classified proportion * 0.73 (0.65, 0.79) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 2.454276 Optimal criterion : 0.4663583 ------------------------------------------------------------ Method : distance Distance : avg Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.5097389 0.7514793 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8526773 0.02810747 0.7975877 0.9077669 12.54746 4.104639e-36 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8526773 0.7858845 0.06679282 0.01341188 2 Combination log_leukocyte 0.8526773 0.8668349 0.01415756 -0.03158989 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 4.9801253 6.354311e-07 2 -0.4481673 6.540325e-01 3 -2.0384732 4.150264e-02 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 82 42 124 Test - 0 45 45 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.73 (0.66, 0.80) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 1.00 (0.96, 1.00) Specificity * 0.52 (0.41, 0.63) Positive predictive value * 0.66 (0.57, 0.74) Negative predictive value * 1.00 (0.92, 1.00) Positive likelihood ratio 2.07 (1.67, 2.57) Negative likelihood ratio 0.00 (0.00, NaN) False T+ proportion for true D- * 0.48 (0.37, 0.59) False T- proportion for true D+ * 0.00 (0.00, 0.04) False T+ proportion for T+ * 0.34 (0.26, 0.43) False T- proportion for T- * 0.00 (0.00, 0.08) Correctly classified proportion * 0.75 (0.68, 0.81) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 4.695 Optimal criterion : 0.5172414 ------------------------------------------------------------ Method : distance Distance : taneja Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.5097389 0.7514793 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8292683 0.03037543 0.7697335 0.8888030 10.83996 2.225804e-27 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8292683 0.7858845 0.04338380 0.008661867 2 Combination log_leukocyte 0.8292683 0.8668349 0.03756658 -0.034551575 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.039711280 z p-value 1 5.008596 5.482843e-07 2 -1.087261 2.769214e-01 3 -2.038473 4.150264e-02 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 82 42 124 Test - 0 45 45 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.73 (0.66, 0.80) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 1.00 (0.96, 1.00) Specificity * 0.52 (0.41, 0.63) Positive predictive value * 0.66 (0.57, 0.74) Negative predictive value * 1.00 (0.92, 1.00) Positive likelihood ratio 2.07 (1.67, 2.57) Negative likelihood ratio 0.00 (0.00, NaN) False T+ proportion for true D- * 0.48 (0.37, 0.59) False T- proportion for true D+ * 0.00 (0.00, 0.04) False T+ proportion for T+ * 0.34 (0.26, 0.43) False T- proportion for T- * 0.00 (0.00, 0.08) Correctly classified proportion * 0.75 (0.68, 0.81) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 14.71666 Optimal criterion : 0.5172414 ------------------------------------------------------------ Method : distance Distance : kumar-johnson Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.5311416 0.7633136 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8550603 0.02794623 0.8002867 0.9098339 12.70512 5.538107e-37 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8550603 0.7858845 0.06917578 0.01566473 2 Combination log_leukocyte 0.8550603 0.8668349 0.01177460 -0.03024832 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 4.4160199 1.005348e-05 2 -0.3892647 6.970804e-01 3 -2.0384732 4.150264e-02 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 77 35 112 Test - 5 52 57 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.66 (0.59, 0.73) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.94 (0.86, 0.98) Specificity * 0.60 (0.49, 0.70) Positive predictive value * 0.69 (0.59, 0.77) Negative predictive value * 0.91 (0.81, 0.97) Positive likelihood ratio 2.33 (1.80, 3.03) Negative likelihood ratio 0.10 (0.04, 0.24) False T+ proportion for true D- * 0.40 (0.30, 0.51) False T- proportion for true D+ * 0.06 (0.02, 0.14) False T+ proportion for T+ * 0.31 (0.23, 0.41) False T- proportion for T- * 0.09 (0.03, 0.19) Correctly classified proportion * 0.76 (0.69, 0.83) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 591219439 Optimal criterion : 0.5367255 ------------------------------------------------------------ Method : add Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Transform : none MaxPower : 0.4 Kappa Accuracy 0.6111597 0.8376068 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8321119 0.03343251 0.7665854 0.8976384 9.933802 2.967208e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination mayoscore5 0.8321119 0.8301133 0.001998668 0.008575444 0.2330687 2 Combination mayoscore4 0.8321119 0.7989674 0.033144570 0.014496381 2.2864031 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.031145903 0.020826168 1.4955177 p-value 1 0.81570805 2 0.02223069 3 0.13477938 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 50 12 62 Test - 26 146 172 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.26 (0.21, 0.33) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.66 (0.54, 0.76) Specificity * 0.92 (0.87, 0.96) Positive predictive value * 0.81 (0.69, 0.90) Negative predictive value * 0.85 (0.79, 0.90) Positive likelihood ratio 8.66 (4.91, 15.28) Negative likelihood ratio 0.37 (0.27, 0.51) False T+ proportion for true D- * 0.08 (0.04, 0.13) False T- proportion for true D+ * 0.34 (0.24, 0.46) False T+ proportion for T+ * 0.19 (0.10, 0.31) False T- proportion for T- * 0.15 (0.10, 0.21) Correctly classified proportion * 0.84 (0.78, 0.88) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 4.173453 Optimal criterion : 0.5819454 ------------------------------------------------------------ Method : multiply Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.6262644 0.8461538 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8323618 0.03345711 0.7667870 0.8979365 9.933964 2.962381e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination mayoscore5 0.8323618 0.8301133 0.002248501 0.008385484 0.2681421 2 Combination mayoscore4 0.8323618 0.7989674 0.033394404 0.014743916 2.2649616 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.031145903 0.020826168 1.4955177 p-value 1 0.78858996 2 0.02351504 3 0.13477938 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 49 9 58 Test - 27 149 176 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.25 (0.19, 0.31) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.64 (0.53, 0.75) Specificity * 0.94 (0.89, 0.97) Positive predictive value * 0.84 (0.73, 0.93) Negative predictive value * 0.85 (0.78, 0.90) Positive likelihood ratio 11.32 (5.87, 21.81) Negative likelihood ratio 0.38 (0.28, 0.51) False T+ proportion for true D- * 0.06 (0.03, 0.11) False T- proportion for true D+ * 0.36 (0.25, 0.47) False T+ proportion for T+ * 0.16 (0.07, 0.27) False T- proportion for T- * 0.15 (0.10, 0.22) Correctly classified proportion * 0.85 (0.79, 0.89) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 39.67165 Optimal criterion : 0.5877748 ------------------------------------------------------------ Method : divide Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.415848 0.7350427 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.7796469 0.03302067 0.7149276 0.8443662 8.468843 2.478418e-17 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination mayoscore5 0.7796469 0.8301133 0.05046636 -0.02425697 -2.0804888 2 Combination mayoscore4 0.7796469 0.7989674 0.01932045 -0.03913811 -0.4936481 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.03114590 0.02082617 1.4955177 p-value 1 0.03748072 2 0.62155475 3 0.13477938 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 50 36 86 Test - 26 122 148 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.37 (0.31, 0.43) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.66 (0.54, 0.76) Specificity * 0.77 (0.70, 0.84) Positive predictive value * 0.58 (0.47, 0.69) Negative predictive value * 0.82 (0.75, 0.88) Positive likelihood ratio 2.89 (2.08, 4.01) Negative likelihood ratio 0.44 (0.32, 0.61) False T+ proportion for true D- * 0.23 (0.16, 0.30) False T- proportion for true D+ * 0.34 (0.24, 0.46) False T+ proportion for T+ * 0.42 (0.31, 0.53) False T- proportion for T- * 0.18 (0.12, 0.25) Correctly classified proportion * 0.74 (0.67, 0.79) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.9199383 Optimal criterion : 0.4300466 ------------------------------------------------------------ Method : subtract Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Transform : none MaxPower : 0.1 Kappa Accuracy 0.4233659 0.7393162 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.7787308 0.03314605 0.7137658 0.8436959 8.409171 4.129183e-17 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination mayoscore5 0.7787308 0.8301133 0.05138241 -0.02471542 -2.0789618 2 Combination mayoscore4 0.7787308 0.7989674 0.02023651 -0.03948703 -0.5124849 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.03114590 0.02082617 1.4955177 p-value 1 0.03762087 2 0.60831166 3 0.13477938 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 50 35 85 Test - 26 123 149 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.36 (0.30, 0.43) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.66 (0.54, 0.76) Specificity * 0.78 (0.71, 0.84) Positive predictive value * 0.59 (0.48, 0.69) Negative predictive value * 0.83 (0.75, 0.88) Positive likelihood ratio 2.97 (2.13, 4.15) Negative likelihood ratio 0.44 (0.32, 0.61) False T+ proportion for true D- * 0.22 (0.16, 0.29) False T- proportion for true D+ * 0.34 (0.24, 0.46) False T+ proportion for T+ * 0.41 (0.31, 0.52) False T- proportion for T- * 0.17 (0.12, 0.25) Correctly classified proportion * 0.74 (0.68, 0.79) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : -0.009800306 Optimal criterion : 0.4363757 ------------------------------------------------------------ Method : baseinexp Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.5333542 0.7820513 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8294470 0.03339911 0.7639860 0.8949081 9.863946 5.965780e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination mayoscore5 0.8294470 0.8301133 0.0006662225 -0.01050571 2 Combination mayoscore4 0.8294470 0.7989674 0.0304796802 0.01246286 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.0311459027 0.02082617 z p-value 1 -0.06341531 0.9494358 2 2.44564069 0.0144595 3 1.49551773 0.1347794 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 60 35 95 Test - 16 123 139 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.41 (0.34, 0.47) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.79 (0.68, 0.87) Specificity * 0.78 (0.71, 0.84) Positive predictive value * 0.63 (0.53, 0.73) Negative predictive value * 0.88 (0.82, 0.93) Positive likelihood ratio 3.56 (2.60, 4.88) Negative likelihood ratio 0.27 (0.17, 0.42) False T+ proportion for true D- * 0.22 (0.16, 0.29) False T- proportion for true D+ * 0.21 (0.13, 0.32) False T+ proportion for T+ * 0.37 (0.27, 0.47) False T- proportion for T- * 0.12 (0.07, 0.18) Correctly classified proportion * 0.78 (0.72, 0.83) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 42074.25 Optimal criterion : 0.5679547 ------------------------------------------------------------ Method : expinbase Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.634248 0.8461538 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8327781 0.03330306 0.7675053 0.8980509 9.992419 1.645164e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination mayoscore5 0.8327781 0.8301133 0.00266489 0.005956647 0.4473809 2 Combination mayoscore4 0.8327781 0.7989674 0.03381079 0.016781852 2.0147236 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.03114590 0.020826168 1.4955177 p-value 1 0.65460007 2 0.04393362 3 0.13477938 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 52 12 64 Test - 24 146 170 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.27 (0.22, 0.34) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.68 (0.57, 0.79) Specificity * 0.92 (0.87, 0.96) Positive predictive value * 0.81 (0.70, 0.90) Negative predictive value * 0.86 (0.80, 0.91) Positive likelihood ratio 9.01 (5.12, 15.85) Negative likelihood ratio 0.34 (0.24, 0.48) False T+ proportion for true D- * 0.08 (0.04, 0.13) False T- proportion for true D+ * 0.32 (0.21, 0.43) False T+ proportion for T+ * 0.19 (0.10, 0.30) False T- proportion for T- * 0.14 (0.09, 0.20) Correctly classified proportion * 0.85 (0.79, 0.89) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 71476.25 Optimal criterion : 0.6082612 ------------------------------------------------------------ Method : distance Distance : kulczynski_d Samples : 427 Markers : 2 Events : B, M Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.8028959 0.911007 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9558994 0.01024731 0.9358151 0.9759838 44.48968 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9558994 0.7640463 0.19185314 0.023907918 8.024670 2 Combination V5 0.9558994 0.9458612 0.01003826 0.003230843 3.107010 3 V4 V5 0.7640463 0.9458612 0.18181488 -0.025901175 -7.019561 p-value 1 1.017994e-15 2 1.889898e-03 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 128 18 146 Test - 20 261 281 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.34 (0.30, 0.39) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.86 (0.80, 0.92) Specificity * 0.94 (0.90, 0.96) Positive predictive value * 0.88 (0.81, 0.93) Negative predictive value * 0.93 (0.89, 0.96) Positive likelihood ratio 13.41 (8.54, 21.05) Negative likelihood ratio 0.14 (0.10, 0.22) False T+ proportion for true D- * 0.06 (0.04, 0.10) False T- proportion for true D+ * 0.14 (0.08, 0.20) False T+ proportion for T+ * 0.12 (0.07, 0.19) False T- proportion for T- * 0.07 (0.04, 0.11) Correctly classified proportion * 0.91 (0.88, 0.94) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 5712500 Optimal criterion : 0.8003487 ------------------------------------------------------------ Method : distance Distance : euclidean Samples : 427 Markers : 2 Events : B, M Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.7724983 0.8969555 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9498450 0.01104071 0.9282056 0.9714844 40.74421 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination V4 0.9498450 0.7640463 0.185798702 0.025327648 2 Combination V5 0.9498450 0.9458612 0.003983823 0.001039312 3 V4 V5 0.7640463 0.9458612 0.181814879 -0.025901175 z p-value 1 7.335806 2.203917e-13 2 3.833136 1.265201e-04 3 -7.019561 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 126 22 148 Test - 22 257 279 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.35 (0.30, 0.39) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.85 (0.78, 0.90) Specificity * 0.92 (0.88, 0.95) Positive predictive value * 0.85 (0.78, 0.90) Negative predictive value * 0.92 (0.88, 0.95) Positive likelihood ratio 10.80 (7.19, 16.21) Negative likelihood ratio 0.16 (0.11, 0.24) False T+ proportion for true D- * 0.08 (0.05, 0.12) False T- proportion for true D+ * 0.15 (0.10, 0.22) False T+ proportion for T+ * 0.15 (0.10, 0.22) False T- proportion for T- * 0.08 (0.05, 0.12) Correctly classified proportion * 0.90 (0.86, 0.92) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 96.29212 Optimal criterion : 0.7724983 ------------------------------------------------------------ Method : distance Distance : manhattan Samples : 427 Markers : 2 Events : B, M Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.8028959 0.911007 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9558994 0.01024731 0.9358151 0.9759838 44.48968 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9558994 0.7640463 0.19185314 0.023907918 8.024670 2 Combination V5 0.9558994 0.9458612 0.01003826 0.003230843 3.107010 3 V4 V5 0.7640463 0.9458612 0.18181488 -0.025901175 -7.019561 p-value 1 1.017994e-15 2 1.889898e-03 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 128 18 146 Test - 20 261 281 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.34 (0.30, 0.39) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.86 (0.80, 0.92) Specificity * 0.94 (0.90, 0.96) Positive predictive value * 0.88 (0.81, 0.93) Negative predictive value * 0.93 (0.89, 0.96) Positive likelihood ratio 13.41 (8.54, 21.05) Negative likelihood ratio 0.14 (0.10, 0.22) False T+ proportion for true D- * 0.06 (0.04, 0.10) False T- proportion for true D+ * 0.14 (0.08, 0.20) False T+ proportion for T+ * 0.12 (0.07, 0.19) False T- proportion for T- * 0.07 (0.04, 0.11) Correctly classified proportion * 0.91 (0.88, 0.94) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 114.25 Optimal criterion : 0.8003487 ------------------------------------------------------------ Method : distance Distance : chebyshev Samples : 427 Markers : 2 Events : B, M Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.7377893 0.8782201 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9458612 0.7640463 0.1818149 0.02590117 7.019561 2 Combination V5 0.9458612 0.9458612 0.0000000 NaN 0.000000 3 V4 V5 0.7640463 0.9458612 0.1818149 -0.02590117 -7.019561 p-value 1 2.225663e-12 2 1.000000e+00 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 130 34 164 Test - 18 245 263 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.38 (0.34, 0.43) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.88 (0.81, 0.93) Specificity * 0.88 (0.83, 0.91) Positive predictive value * 0.79 (0.72, 0.85) Negative predictive value * 0.93 (0.89, 0.96) Positive likelihood ratio 7.21 (5.23, 9.93) Negative likelihood ratio 0.14 (0.09, 0.21) False T+ proportion for true D- * 0.12 (0.09, 0.17) False T- proportion for true D+ * 0.12 (0.07, 0.19) False T+ proportion for T+ * 0.21 (0.15, 0.28) False T- proportion for T- * 0.07 (0.04, 0.11) Correctly classified proportion * 0.88 (0.84, 0.91) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 90.43 Optimal criterion : 0.7565146 ------------------------------------------------------------ Method : distance Distance : kumar-johnson Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.5311416 0.7633136 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8550603 0.02794623 0.8002867 0.9098339 12.70512 5.538107e-37 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8550603 0.7858845 0.06917578 0.01566473 2 Combination log_leukocyte 0.8550603 0.8668349 0.01177460 -0.03024832 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 4.4160199 1.005348e-05 2 -0.3892647 6.970804e-01 3 -2.0384732 4.150264e-02 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 77 35 112 Test - 5 52 57 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.66 (0.59, 0.73) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.94 (0.86, 0.98) Specificity * 0.60 (0.49, 0.70) Positive predictive value * 0.69 (0.59, 0.77) Negative predictive value * 0.91 (0.81, 0.97) Positive likelihood ratio 2.33 (1.80, 3.03) Negative likelihood ratio 0.10 (0.04, 0.24) False T+ proportion for true D- * 0.40 (0.30, 0.51) False T- proportion for true D+ * 0.06 (0.02, 0.14) False T+ proportion for T+ * 0.31 (0.23, 0.41) False T- proportion for T- * 0.09 (0.03, 0.19) Correctly classified proportion * 0.76 (0.69, 0.83) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 591219439 Optimal criterion : 0.5367255 ------------------------------------------------------------ Method : expinbase Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Transform : none Kappa Accuracy 0.4611866 0.7278107 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.368940 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.724870 4.301880e-37 Combination 0.8059994 0.03238126 0.7425333 0.8694655 9.449894 3.391735e-21 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8059994 0.7858845 0.02011494 0.004700711 2 Combination log_leukocyte 0.8059994 0.8668349 0.06083544 -0.037218061 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.039711280 z p-value 1 4.279127 1.876274e-05 2 -1.634568 1.021397e-01 3 -2.038473 4.150264e-02 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 75 39 114 Test - 7 48 55 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.67 (0.60, 0.74) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.91 (0.83, 0.96) Specificity * 0.55 (0.44, 0.66) Positive predictive value * 0.66 (0.56, 0.74) Negative predictive value * 0.87 (0.76, 0.95) Positive likelihood ratio 2.04 (1.60, 2.60) Negative likelihood ratio 0.15 (0.07, 0.32) False T+ proportion for true D- * 0.45 (0.34, 0.56) False T- proportion for true D+ * 0.09 (0.04, 0.17) False T+ proportion for T+ * 0.34 (0.26, 0.44) False T- proportion for T- * 0.13 (0.05, 0.24) Correctly classified proportion * 0.73 (0.65, 0.79) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 5.885304 Optimal criterion : 0.4663583 ------------------------------------------------------------ Method : divide Samples : 426 Markers : 2 Events : B, M Standardization : zScore Cut points : Youden Transform : none Kappa Accuracy 0.09917447 0.4624413 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7656841 0.02357726 0.7194735 0.8118946 11.2686579 1.874046e-29 V5 0.9456148 0.01151637 0.9230431 0.9681865 38.6940422 0.000000e+00 Combination 0.4948675 0.02840052 0.4392035 0.5505315 -0.1807192 8.565880e-01 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.4948675 0.7656841 0.2708166 -0.03810087 -7.107884 2 Combination V5 0.4948675 0.9456148 0.4507473 -0.03007011 -14.989882 3 V4 V5 0.7656841 0.9456148 0.1799308 -0.02590373 -6.946134 p-value 1 1.178353e-12 2 8.550550e-51 3 3.754326e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 132 214 346 Test - 15 65 80 Total 147 279 426 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.81 (0.77, 0.85) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.90 (0.84, 0.94) Specificity * 0.23 (0.18, 0.29) Positive predictive value * 0.38 (0.33, 0.43) Negative predictive value * 0.81 (0.71, 0.89) Positive likelihood ratio 1.17 (1.08, 1.27) Negative likelihood ratio 0.44 (0.26, 0.74) False T+ proportion for true D- * 0.77 (0.71, 0.82) False T- proportion for true D+ * 0.10 (0.06, 0.16) False T+ proportion for T+ * 0.62 (0.57, 0.67) False T- proportion for T- * 0.19 (0.11, 0.29) Correctly classified proportion * 0.46 (0.41, 0.51) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : -0.6597063 Optimal criterion : 0.1309341 ------------------------------------------------------------ Method : add Samples : 426 Markers : 2 Events : B, M Standardization : zScore Cut points : Youden Transform : none MaxPower : 1 Kappa Accuracy 0.7254061 0.870892 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7639773 0.02362810 0.7176671 0.8102875 11.17218 5.579611e-29 V5 0.9469437 0.01142628 0.9245486 0.9693387 39.11541 0.000000e+00 Combination 0.9234389 0.01309908 0.8977652 0.9491126 32.32586 3.030698e-229 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9234389 0.7639773 0.15946163 0.01679697 9.493474 2 Combination V5 0.9234389 0.9469437 0.02350474 -0.01252298 -1.876930 3 V4 V5 0.7639773 0.9469437 0.18296638 -0.02591762 -7.059536 p-value 1 2.234604e-21 2 6.052775e-02 3 1.670594e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 132 40 172 Test - 15 239 254 Total 147 279 426 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.40 (0.36, 0.45) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.90 (0.84, 0.94) Specificity * 0.86 (0.81, 0.90) Positive predictive value * 0.77 (0.70, 0.83) Negative predictive value * 0.94 (0.90, 0.97) Positive likelihood ratio 6.26 (4.68, 8.39) Negative likelihood ratio 0.12 (0.07, 0.19) False T+ proportion for true D- * 0.14 (0.10, 0.19) False T- proportion for true D+ * 0.10 (0.06, 0.16) False T+ proportion for T+ * 0.23 (0.17, 0.30) False T- proportion for T- * 0.06 (0.03, 0.10) Correctly classified proportion * 0.87 (0.84, 0.90) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.2019101 Optimal criterion : 0.75459 ------------------------------------------------------------ Method : polyreg Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Kappa Accuracy 0.620438 0.8106509 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8978133 0.02269863 0.8533248 0.9423018 17.52587 9.093761e-69 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8978133 0.7858845 0.11192879 0.02754269 2 Combination log_leukocyte 0.8978133 0.8668349 0.03097841 0.01669678 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 4.063829 4.827425e-05 2 1.855352 6.354598e-02 3 -2.038473 4.150264e-02 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 64 14 78 Test - 18 73 91 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.46 (0.38, 0.54) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.78 (0.68, 0.86) Specificity * 0.84 (0.74, 0.91) Positive predictive value * 0.82 (0.72, 0.90) Negative predictive value * 0.80 (0.71, 0.88) Positive likelihood ratio 4.85 (2.96, 7.94) Negative likelihood ratio 0.26 (0.17, 0.40) False T+ proportion for true D- * 0.16 (0.09, 0.26) False T- proportion for true D+ * 0.22 (0.14, 0.32) False T+ proportion for T+ * 0.18 (0.10, 0.28) False T- proportion for T- * 0.20 (0.12, 0.29) Correctly classified proportion * 0.81 (0.74, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.4313803 Optimal criterion : 0.6195683 ------------------------------------------------------------ Method : ridgereg Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Kappa Accuracy 0.6306141 0.816568 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8832352 0.02565267 0.8329569 0.9335135 14.93939 1.826382e-50 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8832352 0.7858845 0.09735071 0.03112651 2 Combination log_leukocyte 0.8832352 0.8668349 0.01640034 0.01194894 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 3.127582 0.001762507 2 1.372535 0.169896988 3 -2.038473 0.041502637 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 58 7 65 Test - 24 80 104 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.38 (0.31, 0.46) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.71 (0.60, 0.80) Specificity * 0.92 (0.84, 0.97) Positive predictive value * 0.89 (0.79, 0.96) Negative predictive value * 0.77 (0.68, 0.85) Positive likelihood ratio 8.79 (4.26, 18.13) Negative likelihood ratio 0.32 (0.23, 0.45) False T+ proportion for true D- * 0.08 (0.03, 0.16) False T- proportion for true D+ * 0.29 (0.20, 0.40) False T+ proportion for T+ * 0.11 (0.04, 0.21) False T- proportion for T- * 0.23 (0.15, 0.32) Correctly classified proportion * 0.82 (0.75, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.5060528 Optimal criterion : 0.6268573 ------------------------------------------------------------ Method : lassoreg Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Kappa Accuracy 0.5819608 0.8247863 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination mayoscore5 0.8301133 0.8301133 0.0000000 NaN 0.000000 2 Combination mayoscore4 0.8301133 0.7989674 0.0311459 0.02082617 1.495518 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.0311459 0.02082617 1.495518 p-value 1 1.0000000 2 0.1347794 3 0.1347794 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 49 14 63 Test - 27 144 171 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.27 (0.21, 0.33) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.64 (0.53, 0.75) Specificity * 0.91 (0.86, 0.95) Positive predictive value * 0.78 (0.66, 0.87) Negative predictive value * 0.84 (0.78, 0.89) Positive likelihood ratio 7.28 (4.29, 12.33) Negative likelihood ratio 0.39 (0.29, 0.53) False T+ proportion for true D- * 0.09 (0.05, 0.14) False T- proportion for true D+ * 0.36 (0.25, 0.47) False T+ proportion for T+ * 0.22 (0.13, 0.34) False T- proportion for T- * 0.16 (0.11, 0.22) Correctly classified proportion * 0.82 (0.77, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.3514807 Optimal criterion : 0.5561292 ------------------------------------------------------------ Method : elasticreg Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Kappa Accuracy 0.6021085 0.8290598 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8307795 0.03301944 0.7660626 0.8954964 10.017719 1.274097e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination mayoscore5 0.8307795 0.8301133 0.0006662225 0.002906457 2 Combination mayoscore4 0.8307795 0.7989674 0.0318121252 0.018974388 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.0311459027 0.020826168 z p-value 1 0.2292215 0.81869674 2 1.6765824 0.09362417 3 1.4955177 0.13477938 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 53 17 70 Test - 23 141 164 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.30 (0.24, 0.36) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.70 (0.58, 0.80) Specificity * 0.89 (0.83, 0.94) Positive predictive value * 0.76 (0.64, 0.85) Negative predictive value * 0.86 (0.80, 0.91) Positive likelihood ratio 6.48 (4.04, 10.40) Negative likelihood ratio 0.34 (0.24, 0.48) False T+ proportion for true D- * 0.11 (0.06, 0.17) False T- proportion for true D+ * 0.30 (0.20, 0.42) False T+ proportion for T+ * 0.24 (0.15, 0.36) False T- proportion for T- * 0.14 (0.09, 0.20) Correctly classified proportion * 0.83 (0.77, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.3233906 Optimal criterion : 0.5897735 ------------------------------------------------------------ Method : splines Samples : 427 Markers : 2 Events : B, M Standardization : none Cut points : Youden Kappa Accuracy 0.8131379 0.9133489 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.023575820 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.011453762 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9648116 0.008915868 0.9473368 0.9822864 52.13307 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9648116 0.7640463 0.2007653 0.02235353 8.981369 2 Combination V5 0.9648116 0.9458612 0.0189504 0.00731021 2.592320 3 V4 V5 0.7640463 0.9458612 0.1818149 -0.02590117 -7.019561 p-value 1 2.674172e-19 2 9.533113e-03 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 137 26 163 Test - 11 253 264 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.38 (0.34, 0.43) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.93 (0.87, 0.96) Specificity * 0.91 (0.87, 0.94) Positive predictive value * 0.84 (0.78, 0.89) Negative predictive value * 0.96 (0.93, 0.98) Positive likelihood ratio 9.93 (6.87, 14.36) Negative likelihood ratio 0.08 (0.05, 0.14) False T+ proportion for true D- * 0.09 (0.06, 0.13) False T- proportion for true D+ * 0.07 (0.04, 0.13) False T+ proportion for T+ * 0.16 (0.11, 0.22) False T- proportion for T- * 0.04 (0.02, 0.07) Correctly classified proportion * 0.91 (0.88, 0.94) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.292811 Optimal criterion : 0.8324857 ------------------------------------------------------------ Method : sgam Samples : 427 Markers : 2 Events : B, M Standardization : none Cut points : Youden Kappa Accuracy 0.7986701 0.9086651 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9570619 0.01001306 0.9374367 0.9766871 45.64655 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9570619 0.7640463 0.19301560 0.02340541 8.246622 2 Combination V5 0.9570619 0.9458612 0.01120072 0.00397771 2.815871 3 V4 V5 0.7640463 0.9458612 0.18181488 -0.02590117 -7.019561 p-value 1 1.629342e-16 2 4.864520e-03 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 129 20 149 Test - 19 259 278 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.35 (0.30, 0.40) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.87 (0.81, 0.92) Specificity * 0.93 (0.89, 0.96) Positive predictive value * 0.87 (0.80, 0.92) Negative predictive value * 0.93 (0.90, 0.96) Positive likelihood ratio 12.16 (7.94, 18.63) Negative likelihood ratio 0.14 (0.09, 0.21) False T+ proportion for true D- * 0.07 (0.04, 0.11) False T- proportion for true D+ * 0.13 (0.08, 0.19) False T+ proportion for T+ * 0.13 (0.08, 0.20) False T- proportion for T- * 0.07 (0.04, 0.10) Correctly classified proportion * 0.91 (0.88, 0.93) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.4239775 Optimal criterion : 0.799937 ------------------------------------------------------------ Method : nsgam Samples : 427 Markers : 2 Events : B, M Standardization : none Cut points : Youden Kappa Accuracy 0.8264062 0.9203747 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.023575820 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.011453762 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9649085 0.008884253 0.9474956 0.9823213 52.32949 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9649085 0.7640463 0.20086215 0.022425947 8.956686 2 Combination V5 0.9649085 0.9458612 0.01904727 0.007075755 2.691907 3 V4 V5 0.7640463 0.9458612 0.18181488 -0.025901175 -7.019561 p-value 1 3.345843e-19 2 7.104482e-03 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 135 21 156 Test - 13 258 271 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.37 (0.32, 0.41) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.91 (0.85, 0.95) Specificity * 0.92 (0.89, 0.95) Positive predictive value * 0.87 (0.80, 0.91) Negative predictive value * 0.95 (0.92, 0.97) Positive likelihood ratio 12.12 (8.01, 18.34) Negative likelihood ratio 0.09 (0.06, 0.16) False T+ proportion for true D- * 0.08 (0.05, 0.11) False T- proportion for true D+ * 0.09 (0.05, 0.15) False T+ proportion for T+ * 0.13 (0.09, 0.20) False T- proportion for T- * 0.05 (0.03, 0.08) Correctly classified proportion * 0.92 (0.89, 0.94) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.3394315 Optimal criterion : 0.8368933 ------------------------------------------------------------ Method : ridgereg Samples : 426 Markers : 2 Events : B, M Standardization : zScore Cut points : Youden Kappa Accuracy 0.8034637 0.9084507 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7656841 0.023577258 0.7194735 0.8118946 11.26866 1.874046e-29 V5 0.9456148 0.011516367 0.9230431 0.9681865 38.69404 0.000000e+00 Combination 0.9628898 0.009270001 0.9447209 0.9810587 49.93417 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9628898 0.7656841 0.19720576 0.022337481 8.828469 2 Combination V5 0.9628898 0.9456148 0.01727501 0.006314292 2.735859 3 V4 V5 0.7656841 0.9456148 0.17993075 -0.025903727 -6.946134 p-value 1 1.061181e-18 2 6.221776e-03 3 3.754326e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 137 29 166 Test - 10 250 260 Total 147 279 426 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.39 (0.34, 0.44) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.93 (0.88, 0.97) Specificity * 0.90 (0.85, 0.93) Positive predictive value * 0.83 (0.76, 0.88) Negative predictive value * 0.96 (0.93, 0.98) Positive likelihood ratio 8.97 (6.34, 12.69) Negative likelihood ratio 0.08 (0.04, 0.14) False T+ proportion for true D- * 0.10 (0.07, 0.15) False T- proportion for true D+ * 0.07 (0.03, 0.12) False T+ proportion for T+ * 0.17 (0.12, 0.24) False T- proportion for T- * 0.04 (0.02, 0.07) Correctly classified proportion * 0.91 (0.88, 0.93) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.3029858 Optimal criterion : 0.8280301 ------------------------------------------------------------ Method : ridgereg Samples : 426 Markers : 2 Events : B, M Standardization : zScore Cut points : Youden Kappa Accuracy 0.8082036 0.9107981 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7639773 0.02362810 0.7176671 0.8102875 11.17218 5.579611e-29 V5 0.9469437 0.01142628 0.9245486 0.9693387 39.11541 0.000000e+00 Combination 0.9633531 0.00925252 0.9452185 0.9814877 50.07858 0.000000e+00 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9633531 0.7639773 0.19937581 0.022431525 8.888197 2 Combination V5 0.9633531 0.9469437 0.01640943 0.006199303 2.646980 3 V4 V5 0.7639773 0.9469437 0.18296638 -0.025917621 -7.059536 p-value 1 6.210855e-19 2 8.121411e-03 3 1.670594e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 137 28 165 Test - 10 251 261 Total 147 279 426 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.39 (0.34, 0.44) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.93 (0.88, 0.97) Specificity * 0.90 (0.86, 0.93) Positive predictive value * 0.83 (0.76, 0.88) Negative predictive value * 0.96 (0.93, 0.98) Positive likelihood ratio 9.29 (6.52, 13.23) Negative likelihood ratio 0.08 (0.04, 0.14) False T+ proportion for true D- * 0.10 (0.07, 0.14) False T- proportion for true D+ * 0.07 (0.03, 0.12) False T+ proportion for T+ * 0.17 (0.12, 0.24) False T- proportion for T- * 0.04 (0.02, 0.07) Correctly classified proportion * 0.91 (0.88, 0.94) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.3136548 Optimal criterion : 0.8316144 ------------------------------------------------------------ Method : scoring Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Kappa Accuracy 0.6174848 0.8106509 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8668349 0.7858845 0.08095038 0.03971128 2 Combination log_leukocyte 0.8668349 0.8668349 0.00000000 NaN 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 2.038473 0.04150264 2 0.000000 1.00000000 3 -2.038473 0.04150264 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 53 3 56 Test - 29 84 113 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.33 (0.26, 0.41) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.65 (0.53, 0.75) Specificity * 0.97 (0.90, 0.99) Positive predictive value * 0.95 (0.85, 0.99) Negative predictive value * 0.74 (0.65, 0.82) Positive likelihood ratio 18.74 (6.10, 57.64) Negative likelihood ratio 0.37 (0.27, 0.49) False T+ proportion for true D- * 0.03 (0.01, 0.10) False T- proportion for true D+ * 0.35 (0.25, 0.47) False T+ proportion for T+ * 0.05 (0.01, 0.15) False T- proportion for T- * 0.26 (0.18, 0.35) Correctly classified proportion * 0.81 (0.74, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 25.92 Optimal criterion : 0.6118587 ------------------------------------------------------------ Method : minimax Samples : 169 Markers : 2 Events : not_needed, needed Standardization : none Cut points : Youden Kappa Accuracy 0.5941517 0.7988166 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8822540 0.02459988 0.8340391 0.9304689 15.53885 1.893381e-54 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8822540 0.7858845 0.09636950 0.02492035 2 Combination log_leukocyte 0.8822540 0.8668349 0.01541912 0.01831867 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 3.8671004 0.0001101371 2 0.8417159 0.3999469867 3 -2.0384732 0.0415026367 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 54 6 60 Test - 28 81 109 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.36 (0.28, 0.43) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.66 (0.55, 0.76) Specificity * 0.93 (0.86, 0.97) Positive predictive value * 0.90 (0.79, 0.96) Negative predictive value * 0.74 (0.65, 0.82) Positive likelihood ratio 9.55 (4.34, 20.99) Negative likelihood ratio 0.37 (0.27, 0.50) False T+ proportion for true D- * 0.07 (0.03, 0.14) False T- proportion for true D+ * 0.34 (0.24, 0.45) False T+ proportion for T+ * 0.10 (0.04, 0.21) False T- proportion for T- * 0.26 (0.18, 0.35) Correctly classified proportion * 0.80 (0.73, 0.86) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 9.733051 Optimal criterion : 0.5895711 ------------------------------------------------------------ Method : logistic Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Kappa Accuracy 0.5851064 0.8205128 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8304464 0.03301157 0.7657449 0.8951479 10.010016 1.377308e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination mayoscore5 0.8304464 0.8301133 0.0003331113 0.002298783 2 Combination mayoscore4 0.8304464 0.7989674 0.0314790140 0.019410424 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.0311459027 0.020826168 z p-value 1 0.1449076 0.8847838 2 1.6217582 0.1048551 3 1.4955177 0.1347794 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 53 19 72 Test - 23 139 162 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.31 (0.25, 0.37) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.70 (0.58, 0.80) Specificity * 0.88 (0.82, 0.93) Positive predictive value * 0.74 (0.62, 0.83) Negative predictive value * 0.86 (0.79, 0.91) Positive likelihood ratio 5.80 (3.71, 9.07) Negative likelihood ratio 0.34 (0.24, 0.49) False T+ proportion for true D- * 0.12 (0.07, 0.18) False T- proportion for true D+ * 0.30 (0.20, 0.42) False T+ proportion for T+ * 0.26 (0.17, 0.38) False T- proportion for T- * 0.14 (0.09, 0.21) Correctly classified proportion * 0.82 (0.77, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.3442226 Optimal criterion : 0.5771153 ------------------------------------------------------------ Method : SL Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Kappa Accuracy 0.6021085 0.8290598 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8304464 0.03301563 0.7657369 0.8951558 10.008785 1.394542e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination mayoscore5 0.8304464 0.8301133 0.0003331113 0.002489113 2 Combination mayoscore4 0.8304464 0.7989674 0.0314790140 0.019270484 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.0311459027 0.020826168 z p-value 1 0.1338273 0.8935391 2 1.6335352 0.1023565 3 1.4955177 0.1347794 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 53 17 70 Test - 23 141 164 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.30 (0.24, 0.36) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.70 (0.58, 0.80) Specificity * 0.89 (0.83, 0.94) Positive predictive value * 0.76 (0.64, 0.85) Negative predictive value * 0.86 (0.80, 0.91) Positive likelihood ratio 6.48 (4.04, 10.40) Negative likelihood ratio 0.34 (0.24, 0.48) False T+ proportion for true D- * 0.11 (0.06, 0.17) False T- proportion for true D+ * 0.30 (0.20, 0.42) False T+ proportion for T+ * 0.24 (0.15, 0.36) False T- proportion for T- * 0.14 (0.09, 0.20) Correctly classified proportion * 0.83 (0.77, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 3.718027 Optimal criterion : 0.5897735 ------------------------------------------------------------ Method : TS Samples : 234 Markers : 2 Events : 1, 0 Standardization : none Cut points : Youden Kappa Accuracy 0.6289641 0.8461538 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value mayoscore5 0.8301133 0.03284641 0.7657355 0.8944910 10.050209 9.167278e-24 mayoscore4 0.7989674 0.03391821 0.7324889 0.8654458 8.814361 1.203698e-18 Combination 0.8321952 0.03350061 0.7665352 0.8978552 9.916094 3.543536e-23 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination mayoscore5 0.8321952 0.8301133 0.002081945 0.007798712 0.2669601 2 Combination mayoscore4 0.8321952 0.7989674 0.033227848 0.015255285 2.1781204 3 mayoscore5 mayoscore4 0.8301133 0.7989674 0.031145903 0.020826168 1.4955177 p-value 1 0.78949985 2 0.02939708 3 0.13477938 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 50 10 60 Test - 26 148 174 Total 76 158 234 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.26 (0.20, 0.32) True prevalence * 0.32 (0.27, 0.39) Sensitivity * 0.66 (0.54, 0.76) Specificity * 0.94 (0.89, 0.97) Positive predictive value * 0.83 (0.71, 0.92) Negative predictive value * 0.85 (0.79, 0.90) Positive likelihood ratio 10.39 (5.58, 19.35) Negative likelihood ratio 0.37 (0.27, 0.50) False T+ proportion for true D- * 0.06 (0.03, 0.11) False T- proportion for true D+ * 0.34 (0.24, 0.46) False T+ proportion for T+ * 0.17 (0.08, 0.29) False T- proportion for T- * 0.15 (0.10, 0.21) Correctly classified proportion * 0.85 (0.79, 0.89) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 8.75037 Optimal criterion : 0.5946036 ------------------------------------------------------------ Method : PCL Samples : 427 Markers : 2 Events : B, M Standardization : range Cut points : Youden Kappa Accuracy 0.7137342 0.8641686 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9130098 0.01420537 0.8851678 0.9408518 29.07420 7.609053e-186 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9130098 0.7640463 0.1489635 0.01549650 9.612715 2 Combination V5 0.9130098 0.9458612 0.0328514 -0.01418123 -2.316541 3 V4 V5 0.7640463 0.9458612 0.1818149 -0.02590117 -7.019561 p-value 1 7.066057e-22 2 2.052877e-02 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 134 44 178 Test - 14 235 249 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.42 (0.37, 0.47) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.91 (0.85, 0.95) Specificity * 0.84 (0.79, 0.88) Positive predictive value * 0.75 (0.68, 0.81) Negative predictive value * 0.94 (0.91, 0.97) Positive likelihood ratio 5.74 (4.36, 7.57) Negative likelihood ratio 0.11 (0.07, 0.19) False T+ proportion for true D- * 0.16 (0.12, 0.21) False T- proportion for true D+ * 0.09 (0.05, 0.15) False T+ proportion for T+ * 0.25 (0.19, 0.32) False T- proportion for T- * 0.06 (0.03, 0.09) Correctly classified proportion * 0.86 (0.83, 0.90) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.7760336 Optimal criterion : 0.7476993 ------------------------------------------------------------ Method : minmax Samples : 427 Markers : 2 Events : B, M Standardization : range Cut points : Youden Kappa Accuracy 0.7137342 0.8641686 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9129613 0.01420369 0.8851226 0.9408001 29.07423 7.602924e-186 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9129613 0.7640463 0.14891504 0.01550892 9.601895 2 Combination V5 0.9129613 0.9458612 0.03289984 -0.01417787 -2.320507 3 V4 V5 0.7640463 0.9458612 0.18181488 -0.02590117 -7.019561 p-value 1 7.848795e-22 2 2.031347e-02 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 134 44 178 Test - 14 235 249 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.42 (0.37, 0.47) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.91 (0.85, 0.95) Specificity * 0.84 (0.79, 0.88) Positive predictive value * 0.75 (0.68, 0.81) Negative predictive value * 0.94 (0.91, 0.97) Positive likelihood ratio 5.74 (4.36, 7.57) Negative likelihood ratio 0.11 (0.07, 0.19) False T+ proportion for true D- * 0.16 (0.12, 0.21) False T- proportion for true D+ * 0.09 (0.05, 0.15) False T+ proportion for T+ * 0.25 (0.19, 0.32) False T- proportion for T- * 0.06 (0.03, 0.09) Correctly classified proportion * 0.86 (0.83, 0.90) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.7741983 Optimal criterion : 0.7476993 ------------------------------------------------------------ Method : PT Samples : 427 Markers : 2 Events : B, M Standardization : zScore Cut points : Youden Kappa Accuracy 0.7210713 0.8688525 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value V4 0.7640463 0.02357582 0.7178385 0.8102541 11.19988 4.082964e-29 V5 0.9458612 0.01145376 0.9234122 0.9683101 38.92705 0.000000e+00 Combination 0.9229149 0.01309465 0.8972498 0.9485799 32.29677 7.763580e-229 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) z 1 Combination V4 0.9229149 0.7640463 0.15886855 0.01672726 9.497582 2 Combination V5 0.9229149 0.9458612 0.02294633 -0.01256102 -1.826789 3 V4 V5 0.7640463 0.9458612 0.18181488 -0.02590117 -7.019561 p-value 1 2.148208e-21 2 6.773154e-02 3 2.225663e-12 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 132 40 172 Test - 16 239 255 Total 148 279 427 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.40 (0.36, 0.45) True prevalence * 0.35 (0.30, 0.39) Sensitivity * 0.89 (0.83, 0.94) Specificity * 0.86 (0.81, 0.90) Positive predictive value * 0.77 (0.70, 0.83) Negative predictive value * 0.94 (0.90, 0.96) Positive likelihood ratio 6.22 (4.64, 8.33) Negative likelihood ratio 0.13 (0.08, 0.20) False T+ proportion for true D- * 0.14 (0.10, 0.19) False T- proportion for true D+ * 0.11 (0.06, 0.17) False T+ proportion for T+ * 0.23 (0.17, 0.30) False T- proportion for T- * 0.06 (0.04, 0.10) Correctly classified proportion * 0.87 (0.83, 0.90) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 0.2011047 Optimal criterion : 0.7485227 ------------------------------------------------------------ Method : SL Samples : 169 Markers : 2 Events : not_needed, needed Standardization : range Cut points : Youden Kappa Accuracy 0.6217653 0.8106509 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8828147 0.02526699 0.8332923 0.9323371 15.15078 7.487171e-52 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8828147 0.7858845 0.09693019 0.02916104 2 Combination log_leukocyte 0.8828147 0.8668349 0.01597981 0.01390314 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 3.323962 0.000887483 2 1.149367 0.250404540 3 -2.038473 0.041502637 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 69 19 88 Test - 13 68 81 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.52 (0.44, 0.60) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.84 (0.74, 0.91) Specificity * 0.78 (0.68, 0.86) Positive predictive value * 0.78 (0.68, 0.86) Negative predictive value * 0.84 (0.74, 0.91) Positive likelihood ratio 3.85 (2.56, 5.80) Negative likelihood ratio 0.20 (0.12, 0.34) False T+ proportion for true D- * 0.22 (0.14, 0.32) False T- proportion for true D+ * 0.16 (0.09, 0.26) False T+ proportion for T+ * 0.22 (0.14, 0.32) False T- proportion for T- * 0.16 (0.09, 0.26) Correctly classified proportion * 0.81 (0.74, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 1.200113 Optimal criterion : 0.6230726 ------------------------------------------------------------ Method : SL Samples : 169 Markers : 2 Events : not_needed, needed Standardization : zScore Cut points : Youden Kappa Accuracy 0.6217653 0.8106509 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8828147 0.02526699 0.8332923 0.9323371 15.15078 7.487171e-52 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8828147 0.7858845 0.09693019 0.02916104 2 Combination log_leukocyte 0.8828147 0.8668349 0.01597981 0.01390314 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 3.323962 0.000887483 2 1.149367 0.250404540 3 -2.038473 0.041502637 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 69 19 88 Test - 13 68 81 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.52 (0.44, 0.60) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.84 (0.74, 0.91) Specificity * 0.78 (0.68, 0.86) Positive predictive value * 0.78 (0.68, 0.86) Negative predictive value * 0.84 (0.74, 0.91) Positive likelihood ratio 3.85 (2.56, 5.80) Negative likelihood ratio 0.20 (0.12, 0.34) False T+ proportion for true D- * 0.22 (0.14, 0.32) False T- proportion for true D+ * 0.16 (0.09, 0.26) False T+ proportion for T+ * 0.22 (0.14, 0.32) False T- proportion for T- * 0.16 (0.09, 0.26) Correctly classified proportion * 0.81 (0.74, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : -0.3210567 Optimal criterion : 0.6230726 ------------------------------------------------------------ Method : SL Samples : 169 Markers : 2 Events : not_needed, needed Standardization : tScore Cut points : Youden Kappa Accuracy 0.6217653 0.8106509 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8828147 0.02526699 0.8332923 0.9323371 15.15078 7.487171e-52 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8828147 0.7858845 0.09693019 0.02916104 2 Combination log_leukocyte 0.8828147 0.8668349 0.01597981 0.01390314 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 3.323962 0.000887483 2 1.149367 0.250404540 3 -2.038473 0.041502637 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 69 19 88 Test - 13 68 81 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.52 (0.44, 0.60) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.84 (0.74, 0.91) Specificity * 0.78 (0.68, 0.86) Positive predictive value * 0.78 (0.68, 0.86) Negative predictive value * 0.84 (0.74, 0.91) Positive likelihood ratio 3.85 (2.56, 5.80) Negative likelihood ratio 0.20 (0.12, 0.34) False T+ proportion for true D- * 0.22 (0.14, 0.32) False T- proportion for true D+ * 0.16 (0.09, 0.26) False T+ proportion for T+ * 0.22 (0.14, 0.32) False T- proportion for T- * 0.16 (0.09, 0.26) Correctly classified proportion * 0.81 (0.74, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 5.407424 Optimal criterion : 0.6230726 ------------------------------------------------------------ Method : SL Samples : 169 Markers : 2 Events : not_needed, needed Standardization : mean Cut points : Youden Kappa Accuracy 0.6217653 0.8106509 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8828147 0.02526699 0.8332923 0.9323371 15.15078 7.487171e-52 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8828147 0.7858845 0.09693019 0.02916104 2 Combination log_leukocyte 0.8828147 0.8668349 0.01597981 0.01390314 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 3.323962 0.000887483 2 1.149367 0.250404540 3 -2.038473 0.041502637 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 69 19 88 Test - 13 68 81 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.52 (0.44, 0.60) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.84 (0.74, 0.91) Specificity * 0.78 (0.68, 0.86) Positive predictive value * 0.78 (0.68, 0.86) Negative predictive value * 0.84 (0.74, 0.91) Positive likelihood ratio 3.85 (2.56, 5.80) Negative likelihood ratio 0.20 (0.12, 0.34) False T+ proportion for true D- * 0.22 (0.14, 0.32) False T- proportion for true D+ * 0.16 (0.09, 0.26) False T+ proportion for T+ * 0.22 (0.14, 0.32) False T- proportion for T- * 0.16 (0.09, 0.26) Correctly classified proportion * 0.81 (0.74, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 8.221031 Optimal criterion : 0.6230726 ------------------------------------------------------------ Method : SL Samples : 169 Markers : 2 Events : not_needed, needed Standardization : deviance Cut points : Youden Kappa Accuracy 0.6217653 0.8106509 Area Under the Curves of markers and combination score : AUC SE.AUC LowerLimit UpperLimit z p.value ddimer 0.7858845 0.03416018 0.7189318 0.8528372 8.36894 5.813887e-17 log_leukocyte 0.8668349 0.02882818 0.8103327 0.9233371 12.72487 4.301880e-37 Combination 0.8828147 0.02526699 0.8332923 0.9323371 15.15078 7.487171e-52 ------------------------------------------------------------ Area Under the Curve comparison of markers and combination score : Marker1 (A) Marker2 (B) AUC (A) AUC (B) |A-B| SE(|A-B|) 1 Combination ddimer 0.8828147 0.7858845 0.09693019 0.02916104 2 Combination log_leukocyte 0.8828147 0.8668349 0.01597981 0.01390314 3 ddimer log_leukocyte 0.7858845 0.8668349 0.08095038 -0.03971128 z p-value 1 3.323962 0.000887483 2 1.149367 0.250404540 3 -2.038473 0.041502637 ------------------------------------------------------------ Confusion matrix : Outcome + Outcome - Total Test + 69 19 88 Test - 13 68 81 Total 82 87 169 Point estimates and 95% CIs: -------------------------------------------------------------- Apparent prevalence * 0.52 (0.44, 0.60) True prevalence * 0.49 (0.41, 0.56) Sensitivity * 0.84 (0.74, 0.91) Specificity * 0.78 (0.68, 0.86) Positive predictive value * 0.78 (0.68, 0.86) Negative predictive value * 0.84 (0.74, 0.91) Positive likelihood ratio 3.85 (2.56, 5.80) Negative likelihood ratio 0.20 (0.12, 0.34) False T+ proportion for true D- * 0.22 (0.14, 0.32) False T- proportion for true D+ * 0.16 (0.09, 0.26) False T+ proportion for T+ * 0.22 (0.14, 0.32) False T- proportion for T- * 0.16 (0.09, 0.26) Correctly classified proportion * 0.81 (0.74, 0.87) -------------------------------------------------------------- * Exact CIs ------------------------------------------------------------ Cut-off Results : Optimal cut-off method : Youden Optimal cut-off point : 8.221031 Optimal criterion : 0.6230726 ------------------------------------------------------------ [ FAIL 0 | WARN 2 | SKIP 0 | PASS 271 ] [ FAIL 0 | WARN 2 | SKIP 0 | PASS 271 ] > > proc.time() user system elapsed 35.54 1.15 36.68