Evidence map›Paper›PMID 40841505›Full record

ArticleClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2026

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

Gökhan Şahin, Caner Acar, Haydar Çağatay Yüksel, Salih Tunbekici, Fatma Pınar Açar, Gülçin Çelebi, Burçak Karaca

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Article in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Gökhan ŞahinDepartment of Medical Oncology, Ege University Faculty of Medicine, 35100, İzmir, Türkiye. gkhn7sn@gmail.com.ORCID http://orcid.org/0000-0003-1478-9383
Caner AcarDepartment of Medical Oncology, Ege University Faculty of Medicine, 35100, İzmir, Türkiye.ORCID http://orcid.org/0000-0002-9782-6807
Haydar Çağatay YükselDepartment of Medical Oncology, Ege University Faculty of Medicine, 35100, İzmir, Türkiye.ORCID http://orcid.org/0000-0001-8857-2983
Salih TunbekiciDepartment of Medical Oncology, Ege University Faculty of Medicine, 35100, İzmir, Türkiye.ORCID http://orcid.org/0000-0001-8804-7636
Fatma Pınar AçarDepartment of Medical Oncology, Ege University Faculty of Medicine, 35100, İzmir, Türkiye.ORCID http://orcid.org/0009-0000-2749-8732
Gülçin ÇelebiDepartment of Internal Medicine, Ege University Faculty of Medicine, İzmir, Türkiye.ORCID http://orcid.org/0000-0002-5551-0409
Burçak KaracaDepartment of Medical Oncology, Ege University Faculty of Medicine, 35100, İzmir, Türkiye.ORCID http://orcid.org/0000-0003-2638-1625

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite 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.

methodsWe 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.

resultsAmong 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%).

conclusionsRoutine 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.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorIpilimumabMelanomaNivolumabSkin NeoplasmsAdultAgedAged, 80 and overFemaleHumansL-Lactate DehydrogenaseLymphocytesMaleMiddle AgedMonocytesBiomarkers, TumorIpilimumabL-Lactate DehydrogenaseNivolumabAdvanced melanomaDynamic biomarkersImmune checkpoint inhibitors (ICIs)Immunotherapy response predictionLymphocyte-to-monocyte ratio (LMR)Neutrophil-to-lymphocyte ratio (NLR)

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.