Dynamic blood-based biomarkers predict early response to ipilimumab and nivolumab in advanced melanoma.

Abstract

Background: Despite the therapeutic advances of immune checkpoint inhibitors in advanced melanoma, early identification of treatment non-responders remains a major clinical need. Dynamic changes in peripheral blood biomarkers may provide a cost-effective and non-invasive strategy to monitor treatment response during the early phase of immunotherapy.

Methods: We retrospectively analyzed 70 patients with advanced melanoma treated with combination ipilimumab and nivolumab between 2017 and 2025. Dynamic changes in neutrophil-to-lymphocyte ratio (ΔNLR), lymphocyte-to-monocyte ratio (ΔLMR), platelet-to-lymphocyte ratio (ΔPLR), systemic immune-inflammation index (ΔSII), eosinophil count (ΔEosinophils), and lactate dehydrogenase (ΔLDH) were calculated as the ratio of post-treatment (prior to the third cycle) to pre-treatment (baseline) values. ROC analysis and logistic regression models assessed each biomarker's predictive value for objective response. Each delta marker was tested in a separate multivariate model adjusted for clinical covariates identified through univariate analysis.

Results: Among 70 patients, 28 (40.0%) achieved an objective response. ΔNLR and ΔLMR showed the strongest discriminative performance (AUCs: 0.836 and 0.793, respectively). In multivariate models incorporating univariate-selected clinical covariates, high ΔNLR (OR = 20.3, 95% CI 4.65-88.45) and low ΔLMR (OR = 22.66, 95% CI 5.07-101.34) remained independently associated with non-response (both p < 0.001). These biomarkers also improved the predictive performance of the clinical model (ΔAUC: + 7.7%).

Conclusions: Routine assessment of early dynamic changes in ΔNLR and ΔLMR after two cycles of ipilimumab-nivolumab therapy can enable timely identification of non-responders in advanced melanoma, allowing early discontinuation or switching of treatment to avoid unnecessary toxicity and cost. These biomarkers rely on standard blood counts and are readily applicable in clinical practice. Nevertheless, the retrospective single-center design and moderate sample size limit the generalizability of our findings, and prospective validation in larger, independent cohorts is warranted.