Background: Platelet indices (PIs) – including platelet count (PC), plateletcrit (PCT), mean platelet volume, and platelet distribution width (PDW) – are routinely assessed in clinical practice. Although observational studies have reported associations between PIs and lung cancer outcomes, the dose–response relationship and causality remain unestablished. This study aims to determine prognostic thresholds of PIs and elucidate their causal roles in lung cancer. Methods: We systematically reviewed PubMed, Medline, and Web of Science (through December 2024) for studies on PIs and lung cancer prognosis. Hazard ratios (HRs) were pooled via random-effects models. Dose–response thresholds were identified using restricted cubic splines and generalized least squares. Two-sample Mendelian randomization (MR) analyses with inverse variance weighting assessed causality, complemented by sensitivity analyses (MR-Egger, weighted median). Results: In the meta-analysis of 62 studies (N = 38,562 patients), elevated PC (HR = 1.016, 95% CI: 1.009 to 1.024) and PCT (HR = 1.704, 95% CI: 1.040–2.790) independently predicted poorer overall survival. A nonlinear dose–response relationship revealed that each 10 9 /L increase in PC conferred a 4.2% higher risk of adverse prognosis in non-small cell lung cancer (HR = 1.042, 95% CI: 1.029 to 1.056), with a critical threshold at 177.5 × 10 9 /mL. MR analyses demonstrated population-specific causality: a 1-SD increase in PC elevated lung cancer risk by 33% in East Asians (OR = 1.33, P < .001), while in Europeans, equivalent increments in PC and PCT increased small cell lung cancer (SCLC) risk by 17% (OR = 1.17, P = .01) and 19% (OR = 1.19, P < .001), respectively. Additionally, higher PDW was causally linked to a 6% increased lung cancer risk (OR = 1.06, P = .02). Conclusion: This first study integrating dose–response meta-analysis and MR evidence identifies PC and PCT as robust prognostic biomarkers for lung cancer, with population-specific causal effects. The identified PC threshold (177.5 × 10 9 /mL) provides a clinically actionable tool for NSCLC risk stratification, highlighting the translational potential of routine PIs monitoring in oncology practice.
Yuan et al. (2026) studied this question.