Sargent, Daniel J.

Abstract Purpose: We examined the prognostic impact of specific KRAS mutations in patients with stage III colon adenocarcinoma receiving adjuvant FOLFOX alone or combined with cetuximab in a phase III trial (N0147). Analysis was restricted to BRAF–wild-type tumors, because BRAF mutation was associated with poor prognosis, and BRAF and KRAS mutations are mutually exclusive. Experimental Design: The seven most common KRAS mutations in codon 12 and codon 13 were examined in 2,478 BRAF–wild-type tumors. Because KRAS mutations in codon 12 (n = 779) or 13 (n = 220) were not predictive of adjuvant cetuximab benefit, study arms were pooled for analysis. Disease-free survival (DFS) was evaluated by HRs using Cox models. Results: KRAS mutations in codon 12 (multivariate HR, 1.52; 95% confidence interval, CI, 1.28–1.80; P < 0.0001) or codon 13 (multivariate HR, 1.36; 95% CI, 1.04–1.77; P = 0.0248) were significantly associated with shorter DFS compared with patients with wild-type KRAS/BRAF tumors, independent of covariates. KRAS codon 12 mutations were independently associated with proficient mismatch repair (P < 0.0001), proximal tumor site (P < 0.0001), low grade, age, and sex, whereas codon 13 mutations were associated with proximal site (P < 0.0001). Conclusion: KRAS mutations in either codon 12 or 13 are associated with inferior survival in patients with resected stage III colon cancer. These data highlight the importance of accurate molecular characterization and the significant role of KRAS mutations in both codons in the progression of this malignancy in the adjuvant setting. Clin Cancer Res; 20(11); 3033–43. ©2014 AACR.

Purpose We sought to test and validate the predictive utility of trichotomous tumor response (TriTR; complete response [CR] or partial response [PR] v stable disease [SD] v progressive disease [PD]), disease control rate (DCR; CR/PR/SD v PD), and dichotomous tumor response (DiTR; CR/PR v others) metrics using alternate cut points for PR and PD. The data warehouse assembled to guide the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 was used. Methods Data from 13 trials (5,480 patients with metastatic breast cancer, non–small-cell lung cancer, or colorectal cancer) were randomly split (60:40) into training and validation data sets. In all, 27 pairs of cut points for PR and PD were considered: PR (10% to 50% decrease by 5% increments) and PD (10% to 20% increase by 5% increments), for which 30% and 20% correspond to the RECIST categorization. Cox proportional hazards models with landmark analyses at 12 and 24 weeks stratified by study and number of lesions (fewer than three v three or more) and adjusted for average baseline tumor size were used to assess the impact of each metric on overall survival (OS). Model discrimination was assessed by using the concordance index (c-index). Results Standard RECIST cut points demonstrated predictive ability similar to the alternate PR and PD cut points. Regardless of tumor type, the TriTR, DiTR, and DCR metrics had similar predictive performance. The 24-week metrics (albeit with higher c-index point estimate) were not meaningfully better than the 12-week metrics. None of the metrics did particularly well for breast cancer. Conclusion Alternative cut points to RECIST standards provided no meaningful improvement in OS prediction. Metrics assessed at 12 weeks have good predictive performance.

AbstractIn cancer clinical trials, patients often experience a recurrence of disease prior to the outcome of interest, overall survival. Additionally, for many cancers, there is a cured fraction of the population who will never experience a recurrence. There is often interest in how different covariates affect the probability of being cured of disease and the time to recurrence, time to death, and time to death after recurrence. We propose a multi‐state Markov model with an incorporated cured fraction to jointly model recurrence and death in colon cancer. A Bayesian estimation strategy is used to obtain parameter estimates. The model can be used to assess how individual covariates affect the probability of being cured and each of the transition rates. Checks for the adequacy of the model fit and for the functional forms of covariates are explored. The methods are applied to data from 12 randomized trials in colon cancer, where we show common effects of specific covariates across the trials. Copyright © 2013 John Wiley & Sons, Ltd.

PurposeThe association of deficient DNA mismatch repair (dMMR) with prognosis in patients with colon cancer treated with adjuvant fluorouracil, leucovorin, and oxaliplatin (FOLFOX) chemotherapy remains unknown.Patients and MethodsResected, stage III colon carcinomas from patients (N = 2,686) randomly assigned to FOLFOX ± cetuximab (North Central Cancer Treatment Group N0147 trial) were analyzed for mismatch repair (MMR) protein expression and mutations in BRAFV600E(exon 15) and KRAS (codons 12 and 13). Association of biomarkers with disease-free survival (DFS) was determined using Cox models. A validation cohort (Cancer and Leukemia Group B 88903 trial) was used.ResultsdMMR was detected in 314 (12%) of 2,580 tumors, of which 49.3% and 10.6% had BRAFV600Eor KRAS mutations, respectively. MMR status was not prognostic overall (adjusted hazard ratio [HR], 0.82; 95% CI, 0.64 to 1.07; P = .14), yet significant interactions were found between MMR and primary tumor site (Pinteraction= .009) and lymph node category (N1 v N2; Pinteraction= .014). Favorable DFS was observed for dMMR versus proficient MMR proximal tumors (HR, 0.71; 95% CI, 0.53 to 0.94; P = .018) but not dMMR distal tumors (HR, 1.71; 95% CI, 0.99 to 2.95; P = .056), adjusting for mutations and covariates. Any survival benefit of dMMR was lost in N2 tumors. Mutations in BRAFV600E(HR, 1.37; 95% CI, 1.08 to 1.70; P = .009) or KRAS (HR, 1.44; 95% CI, 1.21 to 1.70; P < .001) were independently associated with worse DFS. The observed MMR by tumor site interaction was validated in an independent cohort of stage III colon cancers (Pinteraction= .037).ConclusionThe prognostic impact of MMR depended on tumor site, and this interaction was validated in an independent cohort. Among dMMR cancers, proximal tumors had favorable outcome, whereas distal or N2 tumors had poor outcome. BRAF or KRAS mutations were independently associated with adverse outcome.

Background Biomarkers have many distinct purposes, and depending on their intended use, the validation process varies substantially. Purpose The goal of this article is to provide an introduction to the topic of biomarkers, and then to discuss three specific types of biomarkers, namely, prognostic, predictive, and surrogate. Results A principle challenge for biomarker validation from a statistical perspective is the issue of multiplicity. In general, the solution to this multiplicity challenge is well known to statisticians: pre-specification and replication. Critical requirements for prognostic marker validation include uniform treatment, complete follow-up, unbiased case selection, and complete ascertainment of the many possible confounders that exist in the context of an observational sample. In the case of predictive biomarker validation, observational data are clearly inadequate and randomized controlled trials are mandatory. Within the context of randomization, strategies for predictive marker validation can be grouped into two categories: retrospective versus prospective validation. The critical validation criteria for a surrogate endpoint is to ensure that if a trial uses a surrogate endpoint, the trial will result in the same inferences as if the trial had observed the true endpoint. The field of surrogate endpoint validation has now moved to the multi-trial or meta-analytic setting as the preferred method. Conclusions Biomarkers are a highly active research area. For all biomarker developmental and validation studies, the importance of fundamental statistical concepts remains the following: pre-specification of hypotheses, randomization, and replication. Further statistical methodology research in this area is clearly needed as we move forward.

Purpose With improved patient care, better diagnosis, and more treatment options after tumor recurrence, outcomes after fluorouracil (FU) -based treatment are expected to have improved over time in early-stage colon cancer. Data from 18,449 patients enrolled onto 21 phase III trials conducted from 1978 to 2002 were evaluated for potential differences in time to recurrence (TTR), time from recurrence to death (TRD), and overall survival (OS) with regard to FU-based adjuvant regimens. Methods Trials were predefined as old versus newer era using initial accrual before or after 1995. Outcomes were compared between patients enrolled onto old- or newer-era trials, stratified by stage. Results Within the first 3 years, recurrence rates were lower in newer- versus old-era trials for patients with stage II disease, with no differences among those with stage III disease. Both TRD and OS were significantly longer in newer-era trials overall and within each stage. The lymph node (LN) ratio (ie, number of positive nodes divided by total nodes harvested) in those with stage III disease declined over time. TTR improved slightly, with larger number of LNs examined in both stages. Conclusion Improved TRD in newer trials supports the premise that more aggressive intervention (oxaliplatin- and irinotecan-based chemotherapy and/or surgery for recurrent disease) improves OS for patients previously treated in the adjuvant setting. Lower recurrence rates with identical treatments in those with stage II disease enrolled onto newer-era trials reflect stage migration over time, calling into question historical data related to the benefit of FU-based adjuvant therapy in such patients.