Journal: American Journal of Respiratory and Critical Care Medicine

Article Title: A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL

doi: 10.1164/rccm.201607-1397OC

Figure Lengend Snippet: Model Performance at Different Institutions: Predictions Using Full Information without Calibration *

Article Snippet: The AUC for different institutions ranged from 0.82 to 0.92 ( ). table ft1 table-wrap mode="anchored" t5 Table 4. caption a7 Institution Prevalence of N2 Disease in that Cohort ( % ) AUC ROC (95% CI) Hosmer-Lemeshow P Value † Brier Score ‡ MD Anderson Cancer Center (development cohort) 160/633 (25) 0.86 (0.82–0.89) 0.62 0.125 Cleveland Clinic (validation) 87/310 (28) 0.87 (0.83–0.91) 0.03 0.129 Johns Hopkins (validation) 107/186 (58) 0.82 (0.76–0.89) <0.001 0.181 Henry Ford Hospital (validation) 102/226 (45) 0.92 (0.88–0.95) <0.001 0.139 Open in a separate window Definition of abbreviations : AUC ROC = area under the receiver operating characteristic curve; CI = confidence interval.

Techniques: Biomarker Discovery

Journal: American Journal of Respiratory and Critical Care Medicine

Article Title: A Prediction Model to Help with the Assessment of Adenopathy in Lung Cancer: HAL

doi: 10.1164/rccm.201607-1397OC

Figure Lengend Snippet: Model Performance When Used on External Validation Cohort for Different Clinical Scenarios

Article Snippet: The AUC for different institutions ranged from 0.82 to 0.92 ( ). table ft1 table-wrap mode="anchored" t5 Table 4. caption a7 Institution Prevalence of N2 Disease in that Cohort ( % ) AUC ROC (95% CI) Hosmer-Lemeshow P Value † Brier Score ‡ MD Anderson Cancer Center (development cohort) 160/633 (25) 0.86 (0.82–0.89) 0.62 0.125 Cleveland Clinic (validation) 87/310 (28) 0.87 (0.83–0.91) 0.03 0.129 Johns Hopkins (validation) 107/186 (58) 0.82 (0.76–0.89) <0.001 0.181 Henry Ford Hospital (validation) 102/226 (45) 0.92 (0.88–0.95) <0.001 0.139 Open in a separate window Definition of abbreviations : AUC ROC = area under the receiver operating characteristic curve; CI = confidence interval.

Techniques: Biomarker Discovery