ArticleThe British journal of dermatology2021
Validation of a clinicopathological and gene expression profile model for sentinel lymph node metastasis in primary cutaneous melanoma.
Article in The British journal of dermatology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06566404 (Gene Expression Profiles and ctDNA for Risk Stratification in Patients With Melanoma Eligible for Lymph Node Sentinel Biopsy), which is not on this map. Cited by 33 papers.
What it found
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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.
Gene Expression Profiles and ctDNA for Risk Stratification in Patients With Melanoma Eligible for Lymph Node Sentinel Biopsy (CORRESPOND): an Observational Prospective Study.
Who cites it
33 citing papers in PubMed, 54 citations in OpenAlex.
- Comparing the i31-SLNB and the MIA Nomogram for Sentinel Lymph Node Biopsy Positivity Prediction in Cutaneous Melanoma: A Prospective Cohort Analysis.Dermatology and therapy · 2026Article
- Review
- A deep learning-clinical nomogram hybrid for predicting sentinel lymph node metastasis in melanoma.Journal of the European Academy of Dermatology and Venereology : JEADV · 2026Article
- Independent Dutch Validation Study of CP-GEP (Merlin Assay) for the Prediction of Nodal Metastasis and Long-Term Outcome in Patients with Primary Cutaneous Melanoma.Annals of surgical oncology · 2026Article
- [A multi-molecular predictive model for lymph node metastasis in papillary thyroid carcinoma based on machine learning algorithms].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025Article
- Molecular and Genetic Markers for Malignant Melanoma: Implications for Prognosis and Therapy.Dermatopathology (Basel, Switzerland) · 2025Review
- Review
- Validation of a Clinicopathologic and Gene Expression Model for Predicting Sentinel Node Metastasis in Melanoma: A Multicenter Danish Cohort Study.Journal of surgical oncology · 2025Article
- Enhanced Risk Stratification for Sentinel Lymph Node Biopsy in Head and Neck Melanoma Using the Merlin Assay (CP-GEP).Annals of surgical oncology · 2025Article
- 97 Machine learning algorithms in the prognosis of cutaneous melanoma: a population-based study.Discover oncology · 2025Article
- Declining Clinical Utility of Tools for Predicting Sentinel Lymph Node Biopsy Status: A Single Institution Experience from 2000 to 2021.Annals of surgical oncology · 2025Article
- Society of Surgical Oncology Consensus Statement: Assessing the Evidence for and Utility of Gene Expression Profiling of Primary Cutaneous Melanoma.Annals of surgical oncology · 2025Article
- The Dutch Early-Stage Melanoma (D-ESMEL) study: a discovery set and validation cohort to predict the absolute risk of distant metastases in stage I/II cutaneous melanoma.European journal of epidemiology · 2025Article
- Rapidly Evolving Pre- and Post-surgical Systemic Treatment of Melanoma.American journal of clinical dermatology · 2024Review
- Validation of the Melanoma Institute of Australia's Sentinel Lymph Node Biopsy Risk Prediction Tool for Cutaneous Melanoma.Annals of surgical oncology · 2024Article
- Review
- A Narrative Review of Current Knowledge on Cutaneous Melanoma.Clinics and practice · 2024Review
- LncRNA LINC00847 Accelerates Melanoma Progression by Regulating MiR-133a-3p/TGFBR1 Axis.Combinatorial chemistry & high throughput screening · 2024Article
- Perspectives in Melanoma: meeting report from the Melanoma Bridge (December 1st-3rd, 2022-Naples, Italy).Journal of translational medicine · 2023Article
- Cost evaluation of the Merlin assay for predicting melanoma sentinel lymph node biopsy metastasis.International journal of dermatology · 2023Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe Clinicopathological and Gene Expression Profile (CP-GEP) model was developed to accurately identify patients with T1-T3 primary cutaneous melanoma at low risk for nodal metastasis.
objectivesTo validate the CP-GEP model in an independent Dutch cohort of patients with melanoma.
methodsPatients (aged ≥ 18 years) with primary cutaneous melanoma who underwent sentinel lymph node biopsy (SLNB) between 2007 and 2017 at the Erasmus Medical Centre Cancer Institute were eligible. The CP-GEP model combines clinicopathological features (age and Breslow thickness) with the expression of eight target genes involved in melanoma metastasis (ITGB3, PLAT, SERPINE2, GDF15, TGFBR1, LOXL4, CXCL8 and MLANA). Using the pathology result of SLNB as the gold standard, performance measures of the CP-GEP model were calculated, resulting in CP-GEP high risk or low risk for nodal metastasis.
resultsIn total, 210 patients were included in the study. Most patients presented with T2 (n = 94, 45%) or T3 (n = 70, 33%) melanoma. Of all patients, 27% (n = 56) had a positive SLNB, with nodal metastasis in 0%, 30%, 54% and 16% of patients with T1, T2, T3 and T4 melanoma, respectively. Overall, the CP-GEP model had a negative predictive value (NPV) of 90·5% [95% confidence interval (CI) 77·9-96.2], with an NPV of 100% (95% CI 72·2-100) in T1, 89·3% (95% CI 72·8-96·3) in T2 and 75·0% (95% CI 30·1-95·4) in T3 melanomas. The CP-GEP indicated high risk in all T4 melanomas.
conclusionsThe CP-GEP model is a noninvasive and validated tool that accurately identified patients with primary cutaneous melanoma at low risk for nodal metastasis. In this validation cohort, the CP-GEP model has shown the potential to reduce SLNB procedures in patients with melanoma.
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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.