Dataset Information

Quantifying Treatment Benefit in Molecular Subgroups to Assess a Predictive Biomarker.

ABSTRACT: An increased interest has been expressed in finding predictive biomarkers that can guide treatment options for both mutation carriers and noncarriers. The statistical assessment of variation in treatment benefit (TB) according to the biomarker carrier status plays an important role in evaluating predictive biomarkers. For time-to-event endpoints, the hazard ratio (HR) for interaction between treatment and a biomarker from a proportional hazards regression model is commonly used as a measure of variation in TB. Although this can be easily obtained using available statistical software packages, the interpretation of HR is not straightforward. In this article, we propose different summary measures of variation in TB on the scale of survival probabilities for evaluating a predictive biomarker. The proposed summary measures can be easily interpreted as quantifying differential in TB in terms of relative risk or excess absolute risk due to treatment in carriers versus noncarriers. We illustrate the use and interpretation of the proposed measures with data from completed clinical trials. We encourage clinical practitioners to interpret variation in TB in terms of measures based on survival probabilities, particularly in terms of excess absolute risk, as opposed to HR. Clin Cancer Res; 22(9); 2114-20. ©2016 AACR.

SUBMITTER: Iasonos A

PROVIDER: S-EPMC4856220 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantifying Treatment Benefit in Molecular Subgroups to Assess a Predictive Biomarker.

Iasonos Alexia A Chapman Paul B PB Satagopan Jaya M JM

Clinical cancer research : an official journal of the American Association for Cancer Research 20160501 9

An increased interest has been expressed in finding predictive biomarkers that can guide treatment options for both mutation carriers and noncarriers. The statistical assessment of variation in treatment benefit (TB) according to the biomarker carrier status plays an important role in evaluating predictive biomarkers. For time-to-event endpoints, the hazard ratio (HR) for interaction between treatment and a biomarker from a proportional hazards regression model is commonly used as a measure of v ...[more]

PMID: 27141007

Similar Datasets

Project description:Combining bevacizumab with frontline chemotherapy statistically significantly improved progression-free survival (PFS) but not overall survival (OS) in the phase III GOG-0218 trial. Evaluation of candidate biomarkers was an exploratory objective. Patients with stage III (incompletely resected) or IV ovarian cancer were randomly assigned to receive six chemotherapy cycles with placebo or bevacizumab followed by single-agent placebo or bevacizumab. Five candidate tumor biomarkers were assessed by immunohistochemistry. The biomarker-evaluable population was categorized into high or low biomarker-expressing subgroups using median and quartile cutoffs. Associations between biomarker expression and efficacy were analyzed. All statistical tests were two-sided. The biomarker-evaluable population (n = 980) comprising 78.5% of the intent-to-treat population had representative baseline characteristics and efficacy outcomes. Neither prognostic nor predictive associations were seen for vascular endothelial growth factor (VEGF) receptor-2, neuropilin-1, or MET. Higher microvessel density (MVD; measured by CD31) showed predictive value for PFS (hazard ratio [HR] for bevacizumab vs placebo = 0.40, 95% confidence interval [CI] = 0.29 to 0.54, vs 0.80, 95% CI = 0.59 to 1.07, for high vs low MVD, respectively, P interaction = .003) and OS (HR = 0.67, 95% CI = 0.51 to 0.88, vs 1.10, 95% CI = 0.84 to 1.44, P interaction = .02). Tumor VEGF-A was not predictive for PFS but showed potential predictive value for OS using a third-quartile cutoff for high VEGF-A expression. These retrospective tumor biomarker analyses suggest a positive association between density of vascular endothelial cells (the predominant cell type expressing VEGF receptors) and tumor VEGF-A levels and magnitude of bevacizumab effect in ovarian cancer. The potential predictive value of MVD (CD31) and tumor VEGF-A is consistent with a mechanism of action driven by VEGF-A signaling blockade.

Project description:BACKGROUND:We have previously shown that podocalyxin-like protein (PODXL) is a prognostic biomarker for poor survival in gastric and esophageal adenocarcinoma treated with surgery up-front. The aim of the present study was to assess PODXL expression in tumors from patients treated with neoadjuvant?±?adjuvant (i.e. preoperative with or without postoperative) chemotherapy, with regard to histopathologic response, time to recurrence (TTR) and overall survival (OS). METHODS:The neoadjuvant cohort encompasses 148 consecutive patients who received neoadjuvant?±?adjuvant chemotherapy for resectable gastric or esophageal adenocarcinoma between 2008 and 2014. Immunohistochemical expression of PODXL was assessed in pre-neoadjuvant biopsies, resected primary tumors and lymph node metastases. Histopathologic response was evaluated using the Chirieac grading. TTR and OS were estimated using Kaplan-Meier and Cox regression analyses. To investigate a potential predictive role for PODXL, the neoadjuvant cohort was pooled with the previously reported surgery up-front cohort. RESULTS:The majority (>?95%) of the patients were treated with fluoropyrimidine- and oxaliplatin-based chemotherapy. Patients with high PODXL expression in their pre-neoadjuvant biopsies had a superior histopathologic response (notably 36% with no residual cancer cells) compared to those with negative or low PODXL expression, and were all recurrence-free at last follow-up. In the pooled cohort, no benefit of chemotherapy could be shown for PODXL negative cases, whereas PODXL positive (low or high) cases had a prolonged TTR and OS when treated with neoadjuvant?±?adjuvant chemotherapy compared to surgery alone. The potential predictive role of PODXL was further strengthened for TTR in Cox regression analyses, especially for patients treated with neoadjuvant fluoropyrimidine and oxaliplatin for a minimum of 8 weeks, with a significant interaction term in both unadjusted (p?=?0.006) and adjusted (p?=?0.024) analyses. The interaction term was not statistically significant for overall survival. CONCLUSIONS:Patients with resectable gastric or esophageal adenocarcinoma with high PODXL expression in their diagnostic biopsies have an excellent prognosis when treated with neoadjuvant?±?adjuvant fluoropyrimidine- and oxaliplatin-based chemotherapy. If the suggested predictive role of PODXL for benefit of chemotherapy can be confirmed, patients with PODXL negative tumors could be spared chemotherapy and treated with surgery alone.

Dataset Information

Quantifying Treatment Benefit in Molecular Subgroups to Assess a Predictive Biomarker.

Publications

Quantifying Treatment Benefit in Molecular Subgroups to Assess a Predictive Biomarker.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure