Random effects model

Statistics

Biochemistry

Immunology

Biomarker

Immune system

Mathematics

Meta-analysis

Internal medicine

Sample size determination

Confidence interval

Hazard ratio

Oncology

Medicine

Chemistry

Albumin

Subgroup analysis

Frontiers in Molecular Biosciences

Background: The albumin levels may potentially be used as a prognostic biomarker in patients with cancertreated with immune checkpoint inhibitors (ICIs) due to its close relationship with nutritional and inflammatory status. However, the available data is limited with heterogeneous patient cohorts, sample sizes and variable cut-offs. Therefore, we conducted a systematic review and meta-analysis to evaluate the association between survival outcomes and albumin levels in patients treated with ICIs. Methods: We conducted a systematic review using the PubMed, Web of Science, and Embase databases to filter the published studies up to 1 June 2022. The meta-analyses were performed with the generic inverse-variance method with a random-effects model due to the high degree of heterogeneity. The primary outcome measure was hazard ratio (HR) with 95% confidence intervals (CI). The study protocol was registered with the PROSPERO registry (Registration Number: CRD42022337746). Results: Thirty-six studies encompassing 8406 cancer patients with advanced disease were included in the meta-analyses. Almost half of the studies were conducted in NSCLC cohorts (n = 15), and 3.5 gr/dL was the most frequently used albumin cut-off in the included studies (n = 20). Patients with lower albumin levels had a significantly increased risk of death (HR: 1.65, 95% CI: 1.52–1.80, p &amp;lt; 0.0001) than patients with higher albumin levels. Subgroup analyses for study location, sample size, tumor type and albumin cut-off were demonstrated consistent results. Furthermore, in the subgroup analysis of eight studies using albumin levels as a continuous prognostic factor, every 1 gr/dL decrease in albumin levels was associated with significantly increased risk of death by a factor of 10% (HR: 1.10, 95% CI: 1.05–1.16, p = 0.0002). Similar to analyses with overall survival, the patients with lower albumin levels had an increased risk of progression or death compared to patients with higher albumin levels (HR: 1.76, 95% CI: 1.40–2.21, p &amp;lt; 0.001). Conclusion: The available evidence demonstrates that albumin levels may be a prognostic biomarker in advanced cancer patients treated with ICIs. Further research is needed to delineate the role of albumin levels in patients treated with ICIs in the adjuvant setting, as well as the possible benefit of therapeutic approaches to improve hypoalbuminemia.

The association between albumin levels and survival in patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis