Developing real-world comparators for clinical trials in chemotherapy-refractory patients with gastric cancer or gastroesophageal junction cancer

Abstract

Background There are few third-line or later (3L+) treatment options for advanced/metastatic (adv/met) gastric cancer/gastroesophageal junction cancers (GC/GEJC). 3L+ Nivolumab demonstrated encouraging results in Asian patients in the ATTRACTION-2 study compared with placebo (12-month survival, 26% vs 11%), and in Western patients in the single-arm CheckMate 032 study (12-month survival, 44%). This analysis aimed to establish comparator cohorts of US patients receiving routine care in real-world (RW) clinical practice. Methods A 2-step matching process generated RW cohorts from Flatiron Health’s oncology database (January 1, 2011–April 30, 2017), for comparison with each trial: (1) clinical trial eligibility criteria were applied; (2) patients were frequency-matched with trial arms for baseline variables significantly associated with survival. Median overall survival (OS) was calculated by Kaplan–Meier analysis from last treatment until death. Results Of 742 adv/met GC/GEJC patients with at least 2 prior lines of therapy, matching generated 90 US RW ATTRACTION-2-matched patients (median OS: 3.5 months) versus 163 ATTRACTION-2 placebo patients (median OS: 4.1 months), and 100 US RW CheckMate 032-matched patients (median OS: 2.9 months) versus 42 CheckMate 032 nivolumab-treated patients (median OS: 8.5 months). Baseline characteristics were generally similar between clinical trial arms and RW-matched cohorts. Conclusions We successfully developed RW cohorts for comparison with data from clinical trials, with comparable baseline characteristics. Survival in US patients receiving RW care was similar to that seen in Asian patients receiving placebo in ATTRACTION-2; survival with nivolumab in CheckMate 032 appeared favorable compared with US RW clinical practice.

Real-World Treatment Patterns and Outcomes in Patients Receiving Second-Line Therapy for Advanced/Metastatic Esophageal Squamous Cell Carcinoma

“…Notably, the presence of two or more metastatic sites in each patient has been demonstrated to be an independent predictor of poor prognosis [ 19 ], but these data were unavailable in the Flatiron electronic health record dataset. Lines of therapy (and the treatment regimens used in each line) are determined algorithmically in line with previous studies of real-world outcomes in patients with adv/met GC/GEJC [ 25 , 26 ]; however, their accuracy cannot be confirmed, and reasons for discontinuation are unknown. Furthermore, data on prior surgeries are unavailable; prior surgery would have obvious implications on peri- and postoperative treatment selection.…”

Evolving Use of Real-World Evidence in the Regulatory Process: a Focus on Immuno-Oncology Treatment and Outcomes

“…While the CheckMate 032 results suggested similar efficacy for nivolumab in Western patients with GC/GEJC, there remained a need to bridge the placebo-controlled clinical trial data in Asian patients to a Western population. On this basis, a retrospective, observational study was conducted to evaluate baseline characteristics, survival outcomes and duration of therapy in US real-world SoC cohorts matched to patients with GC/GEJC who received ≥2 prior lines of therapy in the ATTRACTION-2 placebo arm or the CheckMate 032 nivolumab monotherapy arm [69].…”

“…In order to match patients from a US real-world database to the ATTRACTION-2 and CheckMate 032 arms, patients were identified who met inclusion/exclusion criteria similar to those used for ATTRACTION-2 and CheckMate 032. This was followed by frequency matching to align baseline characteristics in the real-world cohorts with the trial arms, with a focus on characteristics identified as significantly associated with OS in univariate analyses [69]. Figure 1 shows a schematic of the inclusion/exclusion criteria alignment and frequency-matching processes that resulted in the matched real-world cohorts used for the subsequent comparisons [69].…”

Using electronic health record data to identify comparator populations for comparative effectiveness research

“…One of the most compelling aspects of electronic health records (EHRs) is their ability to define real world patient populations with high degrees of clinical specificity relative to other realworld databases such as insurance claims or registries. Because EHRs in theory capture nearly all of the major clinical factors that clinicians consider when making therapy choices in practice, when available at scale, they can identify appropriate comparator populations for comparative effectiveness research with high degrees of clinical detail as well as sufficient sample size for evaluating outcomes that are meaningful as population studies [1][2][3]. These characteristics have the potential to make EHR-based studies highly valuable for comparative effectiveness researchers and health technology assessment (HTA) decision-makers.…”