ArticleCancers2023
Development and Validation of a Predictive Model for Metastatic Melanoma Patients Treated with Pembrolizumab Based on Automated Analysis of Whole-Body [
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed, 7 citations in OpenAlex.
- Efficacy and safety of regorafenib in patients with advanced pretreated melanoma: results of the RegoMel phase II clinical trial.ESMO open · 2026Trial
- Beyond target lesions: Prognostic value of longitudinal AI-derived whole-body [European journal of nuclear medicine and molecular imaging · 2026Article
- Prognostic value of TMTV and Dmax calculated fromEuropean journal of nuclear medicine and molecular imaging · 2026Article
- Interpretable predictions from whole-body FDG-PET/CT using parameters associated with clinical outcome.Communications medicine · 2026Article
- Artificial intelligence-assisted assessment of metabolic response to tebentafusp in metastatic uveal melanoma: a long axial field-of-view [European journal of nuclear medicine and molecular imaging · 2026Article
- Pretreatment PET dissemination features as biomarkers for survival outcomes in melanoma patients treated with immune-checkpoint inhibitors.Scientific reports · 2025Article
- Precision Oncology in Melanoma: Changing Practices.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Review
- Total metabolic tumor volume onJournal for immunotherapy of cancer · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundAntibodies that inhibit the programmed cell death protein 1 (PD-1) receptor offer a significant survival benefit, potentially cure (i.e., durable disease-free survival following treatment discontinuation), a substantial proportion of patients with advanced melanoma. Most patients however fail to respond to such treatment or acquire resistance. Previously, we reported that baseline total metabolic tumour volume (TMTV) determined by whole-body [18F]FDG PET/CT was independently correlated with survival and able to predict the futility of treatment. Manual delineation of [18F]FDG-avid lesions is however labour intensive and not suitable for routine use. A predictive survival model is proposed based on automated analysis of baseline, whole-body [18F]FDG images.
methodsLesions were segmented on [18F]FDG PET/CT using a deep-learning approach and derived features were investigated through Kaplan-Meier survival estimates with univariate logrank test and Cox regression analyses. Selected parameters were evaluated in multivariate Cox survival regressors.
resultsIn the development set of 69 patients, overall survival prediction based on TMTV, lactate dehydrogenase levels and presence of brain metastases achieved an area under the curve of 0.78 at one year, 0.70 at two years. No statistically significant difference was observed with respect to using manually segmented lesions. Internal validation on 31 patients yielded scores of 0.76 for one year and 0.74 for two years.
conclusionsAutomatically extracted TMTV based on whole-body [18F]FDG PET/CT can aid in building predictive models that can support therapeutic decisions in patients treated with immune-checkpoint blockade.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.