Association between ColDx assay result and recurrence-free interval in stage II colon cancer patients on CALGB (Alliance) 9581.

455 Background: Only 15-25% of pts with stage II colon cancer (CC) experience recurrence and conventional staging methods neither allow accurate identification of low (L) and high-risk (H) subgroups nor predict benefit of adjuvant chemotherapy. The ColDx assay (Almac Diagnostics) is a 634-probeset gene expression signature shown to be independently prognostic for recurrence-free interval (RFI). The objective of this study was to assess the ability of ColDx to classify stage II CC pts at L- and H-risk of relapse. Methods: This validation study was conducted using formalin fixed paraffin embedded biospecimens and clinical data from CALGB 9581, a phase III trial of edrecolomab v. observation in pts with normal risk, stage II CC. 1,454 CALGB 9,581 pts met eligibility criteria. A case-cohort sampling design was used to randomly select (RS) 514 pts from 901 eligible pts with available tissue; supplemented by 49 non-RS recurrent pts (total 563). Risk status for each pt was based on a positive or negative ColDx score using a pre-specified cutpoint, 0.4377. The Self Prentice method was used to test the association between ColDx categories and RFI (distant recurrence or death due to primary disease). Results: Initial results in 563 pts were erroneous due to a quality failure in a batch of reagent. 524 samples were re-labeled, re-ordered, and re-assayed using reagents that passed quality control (36 samples had insufficient material; 95 failed ColDx QC). Final analysis comprised 393 pts, 360 RS (58 events; 16%); 33 non-RS events. 216 pts (55%) were predicted H (62 events); 177 (45%) pts were predicted L (29 events). H pts exhibited significantly worse RFI (univariable hazard ratio (HR), 2.0; 95% CI, 1.3-3.3; p < 0.01). ColDx remained significant after adjustment for prognostic factors; HR, 2.1 (95% CI, 1.3-3.4; p < 0.01). Conclusions: The ColDx assay result is associated with RFI in the CALGB 9,581 sub-sample and is independent from other prognostic factors, including MSI. Further investigation is needed to establish the role of this classifier in guiding treatment decisions in this patient population.

Duke Scholars

Author Donna Niedzwiecki Biostatistics & Bioinformatics, Division of Biostatistics