Guidelines for time-to-event end-point definitions in trials for pancreatic cancer. Results of the DATECAN initiative (Definition for the Assessment of Time-to-event End-points in CANcer trials).

BACKGROUND: Using potential surrogate end-points for overall survival (OS) such as Disease-Free- (DFS) or Progression-Free Survival (PFS) is increasingly common in randomised controlled trials (RCTs). However, end-points are too often imprecisely defined which largely contributes to a lack of homogeneity across trials, hampering comparison between them. The aim of the DATECAN (Definition for the Assessment of Time-to-event End-points in CANcer trials)-Pancreas project is to provide guidelines for standardised definition of time-to-event end-points in RCTs for pancreatic cancer. METHODS: Time-to-event end-points currently used were identified from a literature review of pancreatic RCT trials (2006-2009). Academic research groups were contacted for participation in order to select clinicians and methodologists to participate in the pilot and scoring groups (>30 experts). A consensus was built after 2 rounds of the modified Delphi formal consensus approach with the Rand scoring methodology (range: 1-9). RESULTS: For pancreatic cancer, 14 time to event end-points and 25 distinct event types applied to two settings (detectable disease and/or no detectable disease) were considered relevant and included in the questionnaire sent to 52 selected experts. Thirty experts answered both scoring rounds. A total of 204 events distributed over the 14 end-points were scored. After the first round, consensus was reached for 25 items; after the second consensus was reached for 156 items; and after the face-to-face meeting for 203 items. CONCLUSION: The formal consensus approach reached the elaboration of guidelines for standardised definitions of time-to-event end-points allowing cross-comparison of RCTs in pancreatic cancer.

Stage II colon cancer prognosis prediction by tumor gene expression profiling.

PURPOSE: This study mainly aimed to identify and assess the performance of a microarray-based prognosis predictor (PP) for stage II colon cancer. A previously suggested 23-gene prognosis signature (PS) was also evaluated. PATIENTS AND METHODS: Tumor mRNA samples from 50 patients were profiled using oligonucleotide microarrays. PPs were built and assessed by random divisions of patients into training and validation sets (TSs and VSs, respectively). For each TS/VS split, a 30-gene PP, identified on the TS by selecting the 30 most differentially expressed genes and applying diagonal linear discriminant analysis, was used to predict the prognoses of VS patients. Two schemes were considered: single-split validation, based on a single random split of patients into two groups of equal size (group 1 and group 2), and Monte Carlo cross validation (MCCV), whereby patients were repeatedly and randomly divided into TS and VS of various sizes. RESULTS: The 30-gene PP, identified from group 1 patients, yielded an 80% prognosis prediction accuracy on group 2 patients. MCCV yielded the following average prognosis prediction performance measures: 76.3% accuracy, 85.1% sensitivity, and 67.5% specificity. Improvements in prognosis prediction were observed with increasing TS size. The 30-gene PS were found to be highly-variable across TS/VS splits. Assessed on the same random splits of patients, the previously suggested 23-gene PS yielded a 67.7% mean prognosis prediction accuracy. CONCLUSION: Microarray gene expression profiling is able to predict the prognosis of stage II colon cancer patients. The present study also illustrates the usefulness of resampling techniques for honest performance assessment of microarray-based PPs.