Brief Report: Real-World Eligibility for Clinical Trials in Patients With Extensive-Stage SCLC at a Tertiary Care Center

Overview

Journal JTO Clin Res Rep

Date 2024 Aug 2

PMID 39091596

Authors

Navdeep Dehar

Mahbuba Meem

Ishita Aggarwal

Wilma Hopman

Pierre-Olivier Gaudreau

Andrew Robinson

Andrea S Fung

Affiliations

Soon will be listed here.

Abstract

Introduction: The CASPIAN and IMpower133 trials revealed a significant survival benefit of chemotherapy plus immunotherapy in patients with extensive-stage SCLC. The current study characterizes the proportion of real-world patients who would have met eligibility for these trials and highlights factors influencing eligibility in the real-world setting.

Methods: A retrospective analysis of patient data was conducted for stage IV patients with SCLC treated at the Cancer Centre of Southeastern Ontario, Canada. Trial eligibility was based on criteria used in the IMpower133 and CASPIAN trials. Data were summarized using descriptive statistics. Overall survival was assessed using the Kaplan-Meier method.

Results: Of the 116 patients included, only 12.1% met the overall eligibility criteria for the IMpower133 trial, and 14.7% for the CASPIAN trial. The most common reasons for ineligibility included: Eastern Cooperative Oncology Group (ECOG) 2 or greater (77.5%), inadequate organ function (48%), and the presence of brain metastases at diagnosis (37.3%). Sixty-one patients (59.8%) met two or more major ineligibility criteria. If trial eligibility was expanded to include ECOG 2 patients, an additional 10.3% would have met eligibility. The median overall survival for all-comers was 6.5 months.

Conclusions: Only a small minority of real-world patients with extensive-stage SCLC would have met eligibility for the IMpower133 and CASPIAN trials, with ECOG greater than or equal to 2, inadequate organ function, and brain metastases comprising the most common reasons for trial ineligibility. Future clinical trials should expand the inclusion criteria to better represent real-world patient populations.

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