Evidence map›Paper›PMID 39980388›Full record

ArticleJournal of the National Cancer Institute2025

Body composition and checkpoint inhibitor treatment outcomes in advanced melanoma: a multicenter cohort study.

Mark Schuiveling, Laurens S Ter Maat, Isabella A J Van Duin, Rik J Verheijden, Max F Troenokarso, Pim Moeskops, Joost J C Verhoeff, Sjoerd G Elias, Wouter A C van Amsterdam, Femke Burgers and 18 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the National Cancer Institute, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

28 authors.

Mark SchuivelingDepartment of Medical Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.ORCID 0000-0002-2631-7271
Laurens S Ter MaatImage Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.ORCID 0000-0002-4879-9187
Isabella A J Van DuinDepartment of Medical Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Rik J VerheijdenDepartment of Medical Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Max F TroenokarsoDepartment of Medical Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Pim MoeskopsQuantib (currently DeepHealth), Rotterdam, The Netherlands.
Joost J C VerhoeffDepartment of Radiotherapy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Sjoerd G EliasDepartment of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Wouter A C van AmsterdamDepartment of Data Science and Biostatistics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Femke BurgersDepartment of Medical Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands.
Franchette W P J Van den BerkmortelDepartment of Medical Oncology, Zuyderland Medical Center, Sittard-Geleen, The Netherlands.
Marye J Boers-SonderenDepartment of Medical Oncology, Radboudumc, Radboud University, Nijmegen, The Netherlands.
Martijn F BoomsmaDepartment of Radiology, Isala Zwolle, Zwolle, The Netherlands.
Jan Willem De GrootIsala Oncology Center, Isala Zwolle, Zwolle, The Netherlands.
John B A G HaanenDepartment of Medical Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands.ORCID 0000-0001-5884-7704
Geke A P HospersDepartment of Medical Oncology, UMC Groningen, University of Groningen, Groningen, The Netherlands.
Djura PiersmaDepartment of Medical Oncology, Medisch Spectrum Twente, Enschede, The Netherlands.
Gerard VreugdenhilDepartment of Medical Oncology, Maxima Medical Center, Veldhoven, The Netherlands.
Hans M WestgeestDepartment of Internal Medicine, Amphia Hospital, Breda, The Netherlands.
Ellen KapiteijnDepartment of Medical Oncology, Leiden University Medical Center, Leiden University, Leiden, The Netherlands.
Mariette LabotsDepartment of Medical Oncology, UMC, Vrije Universiteit Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands.
Wouter B VeldhuisQuantib (currently DeepHealth), Rotterdam, The Netherlands.ORCID 0000-0002-9798-6843
Paul J Van DiestDepartment of Pathology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.ORCID 0000-0003-0658-2745
Pim A De JongDepartment of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Josien P W PluimImage Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Tim LeinerQuantib (currently DeepHealth), Rotterdam, The Netherlands.ORCID 0000-0003-1885-5499
Mitko VetaMedical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.ORCID 0000-0003-1711-3098
Karijn P M SuijkerbuijkDepartment of Medical Oncology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.

Funding

The Netherlands Organization for Health Research and DevelopmentZonMw 848101007
6 · The paper itself

Abstract

backgroundThe association of body composition with checkpoint inhibitor outcomes in melanoma is a matter of ongoing debate. In this study, we aim to investigate body mass index (BMI) alongside computed tomography (CT)-derived body composition metrics in the largest cohort to date.

methodsPatients treated with first-line anti-PD1 ± anti-CTLA4 for advanced melanoma were retrospectively identified from 11 melanoma centers in The Netherlands. From baseline CT scans, 5 body composition metrics were extracted: subcutaneous adipose tissue index, visceral adipose tissue index, skeletal muscle index, density, and gauge. These metrics were correlated in univariable and multivariable Cox proportional hazards analysis with progression-free survival, overall survival, and melanoma-specific survival (PFS, OS, and MSS).

resultsA total of 1471 eligible patients were included. Median PFS and OS were 9.1 and 38.1 months, respectively. Worse PFS was observed in underweight patients (multivariable hazard ratio [HR] = 1.86, 95% CI = 1.14 to 3.06). Furthermore, prolonged OS was observed in patients with higher skeletal muscle density (multivariable HR = 0.88, 95% CI = 0.81 to 0.97) and gauge (multivariable HR = 0.61, 95% CI = 0.82 to 0.998), whereas higher visceral adipose tissue index was associated with worse OS (multivariable HR = 1.12, 95% CI = 1.04 to 1.22). No association with survival outcomes was found for overweight, obesity, or subcutaneous adipose tissue.

conclusionOur findings suggest that underweight BMI is associated with worse PFS, whereas higher skeletal muscle density and lower visceral adipose tissue index were associated with improved OS. These associations were independent of known prognostic factors, including sex, age, performance status, and extent of disease. No significant association between higher BMI and survival outcomes was observed.

Indexed as

Body CompositionImmune Checkpoint InhibitorsMelanomaSkin NeoplasmsAdultAgedAged, 80 and overBody Mass IndexFemaleHumansIntra-Abdominal FatMaleMiddle AgedMuscle, SkeletalNetherlandsProgrammed Cell Death 1 ReceptorImmune Checkpoint InhibitorsProgrammed Cell Death 1 Receptor

Identifiers

PMID39980388
PMCPMC12145918

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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.