Statins use and prognosis in lung cancer patients treated with immune checkpoint inhibitors: evidence from a meta-analysis
In brief
Statins cut death risk by roughly 25% in lung cancer patients on immunotherapy
A meta-analysis of 12 retrospective studies (5,156 patients) found that taking statins was linked to a 24% lower overall mortality and an 18% reduction in disease progression among those treated with immune checkpoint inhibitors. The benefit persisted after multivariate adjustment but was not seen in unadjusted or very large cohorts, and the evidence remains limited to observational data, prompting a call for prospective trials.
- Journal
- Frontiers in immunology (Q1)
- Published
- 1 September 2026
- Study design
- Systematic review / meta-analysis of RCTs
- Evidence level
- Level 1, High (CEBM 1a)
- Authors
- Dandan Liang, Qinghua Liu, Min Liu, Yi Li
- PMID
- 42746176
- DOI
- 10.3389/fimmu.2026.1910678
Why clinicians should know about it
- Picked for Pulmonary and Respiratory Medicine (top studies of the week, 20 September 2026): Statins use and prognosis in lung cancer patients treated with
- Picked for Oncology and Radiation Oncology (top studies of the week, 20 September 2026): Statins improve survival in lung cancer patients on ICIs
Abstract
BACKGROUND: Lung cancer remains one of the most common and lethal malignancies worldwide. The advent of immune checkpoint inhibitors (ICIs) has substantially improved survival outcomes in patients with advanced disease; nevertheless, a considerable proportion of patients exhibit suboptimal responses to ICI monotherapy. In recent years, statins have garnered attention for their potential immunomodulatory and anti-inflammatory properties. Preclinical evidence suggests that statins may enhance antitumor immune responses by modulating the tumor microenvironment and facilitating antigen presentation. However, existing clinical data remain inconclusive regarding whether statin use influences prognosis in lung cancer patients receiving ICIs. Accordingly, this meta-analysis was undertaken to evaluate the impact of statin use on survival outcomes in this patient population, with the aim of informing clinical decision-making regarding combination strategies. METHODS: We systematically searched PubMed, Embase, the Cochrane Library, and Web of Science for clinical studies published from database inception to June 2026 that examined the association between statin use and outcomes in lung cancer patients treated with ICIs. Two investigators independently screened the literature, extracted data, and assessed the risk of bias using the Newcastle-Ottawa Scale (NOS). The primary endpoints were overall survival (OS) and progression-free survival (PFS). A meta-analysis was performed using Stata 15.0 software. RESULTS: Twelve studies comprising 5,156 participants were included. Pooled analysis demonstrated that statin use was associated with significantly improved OS (HR = 0.76, 95% CI (0.63, 0.91), P = 0.003) and PFS (HR = 0.82, 95% CI (0.69, 0.96), P = 0.017). Subgroup analyses revealed that the survival benefit remained significant for both OS and PFS in multivariate-adjusted estimates. In univariate analyses and in larger studies (n > 500), the benefits did not attain statistical significance. Geographically, statins significantly improved OS in non-Asian populations, whereas the PFS benefit in these populations did not reach significance. CONCLUSIONS: This meta-analysis indicates that statin use is associated with significantly prolonged OS and PFS in lung cancer patients receiving ICIs, suggesting a potential role for statins in augmenting ICI efficacy. However, given that the included studies were predominantly retrospective observational designs, these findings should be interpreted with caution. Prospective, large-scale randomized controlled trials are warranted to confirm the survival benefits of combined statin and ICI therapy and to define the optimal timing and target population for such combination. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD420261420311.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.