Clinical prediction models for immunotherapy benefit in advanced solid tumors: Current evidence, challenges, and future directions in low-resource settings

Background

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of advanced solid tumours by producing durable responses and improving survival across multiple malignancies. However, only a subset of patients derives sustained clinical benefit, while many experience primary or acquired resistance. Reliable predictive biomarkers are therefore essential to optimize patient selection, minimize unnecessary toxicity, and improve the cost-effectiveness of immunotherapy. Although several biomarkers have been investigated, their predictive performance varies considerably across tumour types, and no single biomarker has demonstrated universal clinical applicability.