Validation C-index Research Articles

Nomograms for Predicting Local Recurrence, Distant Metastases, and Overall Survival for Patients With Locally Advanced Rectal Cancer on the Basis of European Randomized Clinical Trials

The purpose of this study was to develop accurate models and nomograms to predict local recurrence, distant metastases, and survival for patients with locally advanced rectal cancer treated with long-course chemoradiotherapy (CRT) followed by surgery and to allow for a selection of patients who may benefit most from postoperative adjuvant chemotherapy and close follow-up. All data (N = 2,795) from five major European clinical trials for rectal cancer were pooled and used to perform an extensive survival analysis and to develop multivariate nomograms based on Cox regression. Data from one trial was used as an external validation set. The variables used in the analysis were sex, age, clinical tumor stage stage, tumor location, radiotherapy dose, concurrent and adjuvant chemotherapy, surgery procedure, and pTNM stage. Model performance was evaluated by the concordance index (c-index). Risk group stratification was proposed for the nomograms. The nomograms are able to predict events with a c-index for external validation of local recurrence (LR; 0.68), distant metastases (DM; 0.73), and overall survival (OS; 0.70). Pathologic staging is essential for accurate prediction of long-term outcome. Both preoperative CRT and adjuvant chemotherapy have an added value when predicting LR, DM, and OS rates. The stratification in risk groups allows significant distinction between Kaplan-Meier curves for outcome. The easy-to-use nomograms can predict LR, DM, and OS over a 5-year period after surgery. They may be used as decision support tools in future trials by using the three defined risk groups to select patients for postoperative chemotherapy and close follow-up (http://www.predictcancer.org).

LONG-TERM SURVIVAL PROBABILITY IN MEN WITH CLINICALLY LOCALIZED PROSTATE CANCER: A CASE-CONTROL, PROPENSITY MODELING STUDY STRATIFIED BY RACE, AGE, TREATMENT AND COMORBIDITIES

We used a propensity risk scoring approach to model long-term survival for men with clinically localized prostate cancer. We developed comprehensive lookup tables for estimating survival probability stratified by patient age, race, readily available clinical variables, comorbidities and treatment type. We retrospectively identified a cohort of 1611 men with clinically localized prostate cancer (patients) and 4538 age, race and comorbidity matched controls. Based on demographic and clinical variables propensity risk scoring was used to develop smoothed survival prediction models for patients and controls. Based on these models tables were created to provide 10-year overall survival estimates. The tables are stratified by patient age, race, comorbidity, prostate specific antigen, cancer grade, and treatment type when applicable. Mean patient age was 67.0 years and median baseline prostate specific antigen was 8.5 ng/ml. Of the patients 68% had biopsy cancer grade 2, 39% were black, 29% received conservative treatment, 43% underwent radical prostatectomy and 27% were treated with radiation therapy. Crude and cancer specific 10-year survival rates were 67% and 93%, respectively. Validation C-index values were 0.63 for the cancer specific model and 0.69 for the overall survival model. These lookup tables provide physicians and patients with realistic estimates of 10-year survival and allow them to compare the impact of cancer vs noncancer factors on patient mortality.