Prognostic significance of the peripheral blood CD4/CD8 ratio in lung cancer patients: A meta-analysis

Background Lung cancer is among the most prevailing and lethal malignant tumors globally, with patients generally exhibiting poor prognoses. The peripheral blood CD4/CD8 ratio serves as a commonly used indicator of immune status, yet its predictive value for treatment outcomes in lung cancer remains controversial. Method This study employed systematic review and meta-analysis methodologies. Web of Science, Embase, PubMed, and Cochrane Library were searched up to November 1, 2025. Based on the PICOS framework, prospective or retrospective studies evaluating the relationship of pre-treatment peripheral blood CD4/CD8 ratios with survival outcomes in lung cancer patients after immunotherapy, radiotherapy, or chemotherapy were included. Two researchers undertook literature screening, data extraction, and quality appraisal. The primary outcome measures were hazard ratios (HR) for progression-free survival (PFS) and overall survival (OS). Effect sizes were pooled via random-effects or fixed-effects models, alongside heterogeneity testing, sensitivity analyses, subgroup analyses, and publication bias testing. Results Nine studies were included, involving 840 patients. Meta-analysis revealed that patients with higher pre-treatment CD4/CD8 ratios demonstrated considerably improved PFS (HR = 0.64, 95% CI: []) and OS (HR = 0.68, 95% CI: []) compared to those with lower ratios. Heterogeneity was low, and sensitivity analyses corroborated robust conclusions. No substantial publication bias was identified. Conclusion This meta-analysis definitively confirms that the pre-treatment peripheral blood CD4/CD8 ratio is an effective candidate for predicting survival prognosis in lung cancer patients. This indicator offers convenient testing, low cost, and good reproducibility, demonstrating significant clinical translational advantages. Therefore, we recommend incorporating the CD4/CD8 ratio into clinical practice to assess patients' immune status and identify potentially treatment-responsive populations before therapy. This approach supports critical decision-making for developing personalized treatment strategies, ultimately improving patient survival outcomes.