Citations

Alcohol consumption is associated with a modest increased risk of colon cancer, but its relationship with colon cancer survival has not been elucidated. Using data from a phase III randomized adjuvant trial, we assessed the association of alcohol consumption with colon cancer outcomes. Patients completed a risk factor questionnaire before randomization to FOLFOX or FOLFOX + cetuximab (N = 1984). Information was collected on lifestyle factors, including smoking, physical activity and consumption of different types of alcohol. Cox models assessed the association between alcohol consumption and outcomes of disease‐free survival (DFS), time‐to‐recurrence (TTR) and overall survival (OS), adjusting for age, sex, study arm, body mass, smoking, physical activity and performance status. No statistically significant difference in outcomes between ever and never drinkers were noted [hazard ratio (HR)DFS = 0.86, HRTTR = 0.87, HROS = 0.86, p‐values = 0.11–0.17]. However, when considering alcohol type, ever consumers of red wine (n = 628) had significantly better outcomes than never consumers (HRDFS = 0.80, HRTTR = 0.81, HROS = 0.78, p‐values = 0.01–0.02). Favorable outcomes were confirmed in patients who consumed 1‐30 glasses/month of red wine (n = 601, HR = 0.80–0.83, p‐values = 0.03–0.049); there was a suggestion of more favorable outcomes in patients who consumed >30 glasses/month of red wine (n = 27, HR = 0.33–0.38, p‐values = 0.05–0.06). Beer and liquor consumption were not associated with outcomes. Although alcohol consumption was not associated with colon cancer outcomes overall, mild to moderate red wine consumption was suggestively associated with longer OS, DFS and TTR in stage III colon cancer patients.

Large sample sizes are required in randomized clinical trials designed to meet typical one‐sided 2.5% α‐level and 80% power. This may not be achievable when the disease is rare. We simulated a series of two‐arm superiority trials over a 15‐year period. The design parameters examined were the α‐level and the number of trials conducted over the 15‐year period (thus, trial sample size). Different disease severities and accrual rates were considered. The future treatment effect was characterized by its associated hazard rate; different hypotheses of how treatments improve over time were considered. We defined the total survival benefit as the relative difference of the hazard rates at year 15 versus year 0. The optimal design was defined by maximizing the expected total survival benefit, provided that the risk of selecting at year 15 a treatment inferior to the initial control treatment remains below 1%. Compared with two larger trials with typical one‐sided 2.5% α‐level, performing a series of small trials with relaxed α‐levels leads on average to larger survival benefits over a 15‐year research horizon, but also to higher risk of selecting a worse treatment at the end of the research period. Under reasonably optimistic assumptions regarding the future treatment effects, optimal designs outperform traditional ones when the disease is severe (baseline median survival ≤ 1 year) and the accrual is ≥100 patients per year, whereas no major improvement is observed in diseases with better prognosis. Trial designs aiming to maximize survival gain over a long research horizon across a series of trials are worth discussing in the context of rare diseases. Copyright © 2016 John Wiley & Sons, Ltd.

Purpose Factors associated with early mortality after surgery and treatment with adjuvant chemotherapy in colon cancer are poorly understood. We aimed to characterize the determinants of early mortality in a large cohort of colon cancer trial participants. Methods A pooled analysis of 37,568 patients in 25 randomized trials of adjuvant systemic therapy was conducted. Multivariable logistic regression models with several definitions of early mortality (30, 60, and 90 days, and 6 months) were constructed, adjusting for clinically and statistically significant variables. A nomogram for 6-month mortality was developed and validated. Results Median age among patients was 61 years, patient demographics included 54% men and 90% White, 29% and 71% had stage II and III disease, respectively, and 79%, 20%, and 1% had an Eastern Cooperative Oncology Group performance status (PS) of 0, 1, and ≥ 2, respectively. Early mortality was low: 0.3% at 30 days, 0.6% at 60 days, 0.8% at 90 days, and 1.4% at 6 months. Of those patients who died by 6 months post–random assignment, 40% had documented disease recurrence prior to death. Early disease recurrence was associated with a markedly increased risk of death during the first 6 months post-treatment (hazard ratio, 82.6; 95%CI, 66.9 to 102.1). In prognostic analyses, advanced age, male sex, poorer PS, increasing ratio of positive to examined lymph nodes, earlier decade of enrollment, and higher tumor stage and grade predicted a greater likelihood of early mortality, whereas treatment received was not strongly predictive. A multivariable model for 6-month mortality showed strong optimism-adjusted discrimination (concordance index, 0.73) and calibration. Conclusion Early mortality was infrequent but more prevalent in patients with advanced age and a PS of ≥ 2, underscoring the need to carefully consider the risk-to-benefit ratio when making treatment decisions in these subgroups.

Purpose Fluorouracil plus leucovorin (FU + LV) adjuvant chemotherapy reduced the risk of recurrence and death across all time points in a pooled analysis of 20,898 patients with colon cancer from 18 randomized studies. The impact of oxaliplatin added to FU + LV on the time course of recurrence and survival remains unknown. Patients and Methods A total of 12,233 patients enrolled to the randomized trials C-07, C-08, N0147, MOSAIC (Adjuvant Treatment of Colon Cancer), and XELOXA (Adjuvant XELOX) were pooled to examine the impact of oxaliplatin and tumor-specific factors on the time course of recurrence and death. For each end point, continuous-time risk was modeled over 6 years post treatment in all oxaliplatin-treated patients and patients concurrently randomized to FU + LV with or without oxaliplatin; the latter analyses supported time-dependent treatment comparisons. Results Addition of oxaliplatin significantly reduced the risk of recurrence within the first 14 months post treatment for patients with stage II disease and within the first 4 years for patients with stage III disease. Oxaliplatin also significantly reduced risk of death from 2 to 6 years post treatment for patients with stage III disease, with no differences in timing of outcomes between treatment groups (ie, oxaliplatin did not simply postpone recurrence or death compared with FU + LV alone). Patients with stage II disease receiving oxaliplatin did not exhibit a significant reduction in risk of death in the first 6 years post treatment. Recurrence risk peaked near 14 months for both treatments, and risk of recurrence and death increased with increased tumor and nodal burden. Conclusions These analyses support the addition of oxaliplatin to fluoropyrimidine-based adjuvant therapy in patients with stage III disease and underscore the need for adequate surveillance of patients with colon cancer during the first 3 years after adjuvant therapy.

The American Joint Committee on Cancer (AJCC) has increasingly recognized the need for more personalized probabilistic predictions than those delivered by ordinal staging systems, particularly through the use of accurate risk models or calculators. However, judging the quality and acceptability of a risk model is complex. The AJCC Precision Medicine Core conducted a 2‐day meeting to discuss characteristics necessary for a quality risk model in cancer patients. More specifically, the committee established inclusion and exclusion criteria necessary for a risk model to potentially be endorsed by the AJCC. This committee reviewed and discussed relevant literature before creating a checklist unique to this need of AJCC risk model endorsement. The committee identified 13 inclusion and 3 exclusion criteria for AJCC risk model endorsement in cancer. The emphasis centered on performance metrics, implementation clarity, and clinical relevance. The facilitation of personalized probabilistic predictions for cancer patients holds tremendous promise, and these criteria will hopefully greatly accelerate this process. Moreover, these criteria might be useful for a general audience when trying to judge the potential applicability of a published risk model in any clinical domain. CA Cancer J Clin 2016;66:370–374. © 2016 American Cancer Society.

Purpose Phase II clinical trials inform go/no-go decisions for proceeding to phase III trials, and appropriate end points in phase II trials are critical for facilitating this decision. Phase II solid tumor trials have traditionally used end points such as tumor response defined by Response Evaluation Criteria for Solid Tumors (RECIST). We previously reported that absolute and relative changes in tumor measurements demonstrated potential, but not convincing, improvement over RECIST to predict overall survival (OS). We have evaluated the metrics by using additional measures of clinical utility and data from phase III trials. Methods Resampling methods were used to assess the clinical utility of metrics to predict phase III outcomes from simulated phase II trials. In all, 2,000 phase II trials were simulated from four actual phase III trials (two positive for OS and two negative for OS). Cox models for three metrics landmarked at 12 weeks and adjusted for baseline tumor burden were fit for each phase II trial: absolute changes, relative changes, and RECIST. Clinical utility was assessed by positive predictive value and negative predictive value, that is, the probability of a positive or negative phase II trial predicting an effective or ineffective phase III conclusion, by prediction error, and by concordance index (c-index). Results Absolute and relative change metrics had higher positive predictive value and negative predictive value than RECIST in five of six treatment comparisons and lower prediction error curves in all six. However, differences were negligible. No statistically significant difference in c-index across metrics was found. Conclusion The absolute and relative change metrics are not meaningfully better than RECIST in predicting OS.

Purpose In recent retrospective analyses of early-stage colorectal cancer (CRC), low and high body mass index (BMI) scores were associated with worsened outcomes. Whether BMI is a prognostic or predictive factor in metastatic CRC (mCRC) is unclear. Patients and Methods Individual data from 21,149 patients enrolled onto 25 first-line mCRC trials during 1997 to 2012 were pooled. We assessed both prognostic and predictive effects of BMI on overall survival and progression-free survival, and we accounted for patient and tumor characteristics and therapy type (targeted v nontargeted). Results BMI was prognostic for overall survival (P < .001) and progression-free survival (P < .001), with an L-shaped pattern. That is, risk of progression and/or death was greatest for low BMI; risk decreased as BMI increased to approximately 28 kg/m 2 , and then it plateaued. Relative to obese patients, patients with a BMI of 18.5 kg/m 2 had a 27% increased risk of having a PFS event (95% CI, 20% to 34%) and a 50% increased risk of death (95% CI, 43% to 56%). Low BMI was associated with poorer survival for men than women (interaction P < .001). BMI was not predictive of treatment effect. Conclusion Low BMI is associated with an increased risk of progression and death among the patients enrolled on the mCRC trials, with no increased risk for elevated BMI, in contrast to the adjuvant setting. Possible explanations include negative effects related to cancer cachexia in patients with low BMI, increased drug delivery or selection bias in patients with high BMI, and potential for an interaction between BMI and molecular signaling pathways.

Abstract Purpose: To determine the frequency and prognostic association of molecular markers by anatomic tumor site in patients with stage III colon carcinomas. Experimental Design: In a randomized trial of adjuvant FOLFOX ± cetuximab, BRAFV600E and KRAS (exon 2) mutations and DNA mismatch repair (MMR) proteins were analyzed in tumors (N = 3,018) in relationship to tumor location, including subsite. Cox models were used to assess clinical outcome, including overall survival (OS). Results: KRAS codon 12 mutations were most frequent at the splenic flexure and cecum; codon 13 mutations were evenly distributed. BRAF mutation frequency sharply increased from transverse colon to cecum in parallel with deficient (d) MMR. Nonmutated BRAF and KRAS tumors progressively decreased from sigmoid to transverse (all P &lt; 0.0001). Significantly, poorer OS was found for mutant KRAS in distal [HR, 1.98; 95% confidence interval (CI), 1.49–2.63; P &lt; 0.0001] versus proximal (1.25; 95% CI, 0.97–1.60; P = 0.079) cancers. BRAF status and outcome were not significantly associated with tumor site. Proximal versus distal dMMR tumors had significantly better outcome. An interaction test was significant for tumor site by KRAS (Padjusted = 0.043) and MMR (Padjusted = 0.010) for OS. Significant prognostic differences for biomarkers by tumor site were maintained in the FOLFOX arm. Tumor site was independently prognostic with a stepwise improvement from cecum to sigmoid (OS: Padjusted = 0.001). Conclusions: Mutation in BRAF or KRAS codon 12 was enriched in proximal cancers whereas nonmutated BRAF/KRAS was increased in distal tumors. Significant differences in outcome for KRAS mutations and dMMR were found by tumor site, indicating that their interpretation should occur in the context of tumor location. Clin Cancer Res; 21(23); 5294–304. ©2015 AACR.