First-line pembrolizumab for metastatic NSCLC in lower-middle-income countries: bridging the efficacy-effectiveness

Ullas Batra1, Mansi Sharma1, Alexis Andrew Miller2

  • 1Department of Medical Oncology, Rajiv Gandhi Cancer Institute & Research Centre, Delhi, India.

Immunotherapy
|September 5, 2025
PubMed
Abstract

Insights

Pembrolizumab shows comparable effectiveness in advanced non-small cell lung cancer patients in lower-middle-income countries. Real-world data reveal survival benefits despite challenging prognostic factors.

Area of Science:

  • Oncology
  • Immunotherapy
  • Clinical Research

Background:

  • Pembrolizumab is a standard first-line treatment for advanced/metastatic non-small cell lung cancer (a/mNSCLC) without actionable mutations.
  • Limited real-world data exist for a/mNSCLC treatment outcomes in lower-middle-income countries (LMICs).

Purpose of the Study:

  • To evaluate the real-world effectiveness of first-line pembrolizumab-based therapy in a/mNSCLC patients from LMICs.
  • To assess overall survival (OS), progression-free survival (PFS), and disease control rate (DCR) in this population.

Main Methods:

  • Prospective analysis of 78 a/mNSCLC patients receiving first-line pembrolizumab from January 2019 to June 2024.
  • Assessment of survival endpoints, response rates, and conditional survival probabilities.
  • Next-generation sequencing (NGS) was performed to identify mutations, with PD-L1 expression and ECOG status also analyzed.

Main Results:

  • Median OS was 21 months and median PFS was 6.3 months with a median follow-up of 27 months.
  • Partial response (47.4%) and stable disease (16.7%) were observed at 2 months.
  • High PD-L1 expression (TPS ≥ 50%) correlated with reduced progression and mortality risk; KRAS mutations were noted in long-term survivors.

Conclusions:

  • Pembrolizumab-based therapy demonstrates comparable efficacy in LMIC a/mNSCLC patients, even with a higher burden of adverse prognostic factors.
  • Real-world data support its use, but further research in diverse settings is crucial for precise benefit estimation.