ArticleFrontiers in medicine2023
A prognostic nomogram for the cancer-specific survival of white patients with invasive melanoma at BANS sites based on the Surveillance, Epidemiology, and End Results database.
Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Bridging gaps throughout a patient's journey with melanoma: a systematic review.Melanoma management · 2025Review
- Development of Nomograms to Predict the Probability of Recurrence at Specific Sites in Patients with Cutaneous Melanoma.Cancers · 2025Article
- Development and validation of machine learning model to predict early death of melanoma brain metastasis patients.Frontiers in oncology · 2025Article
- Advanced lung cancer inflammation index is associated with prognosis in skin cancer patients: a retrospective cohort study.Frontiers in oncology · 2024Article
- Deep-learning-based survival prediction of patients with lower limb melanoma.Discover oncology · 2023Article
Corrections and comments
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Authors and funding
12 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The purpose of this study was to develop a comprehensive nomogram for the cancer-specific survival (CSS) of white patients with invasive melanoma at back, posterior arm, posterior neck, and posterior scalp (BANS) sites and to determine the validity of the nomogram by comparing it with the conventional American Joint Committee on Cancer (AJCC) staging system. Methods: This study analyzed the patients with invasive melanoma in the Surveillance, Epidemiology, and End Results (SEER) database. R software was used to randomly divide the patients into training and validation cohorts at a ratio of 7:3. Multivariable Cox regression was used to identify predictive variables. The new survival nomogram was compared with the AJCC prognosis model using the concordance index (C-index), area under the receiver operating characteristic (ROC) curve (AUC), net reclassification index (NRI), integrated discrimination index (IDI), calibration plotting, and decision-curve analysis (DCA). Results: A novel nomogram was established to determine the 3-, 5-, and 8-year CSS probabilities of patients with invasive melanoma. According to the nomogram, the Age at Diagnosis had the greatest influence on CSS in invasive melanoma, followed by Bone Metastasis, AJCC, Stage, Liver Metastasis, Histologic Subtype, Brain Metastasis, Ulceration, and Primary Site. The nomogram had a higher C-index than the AJCC staging system in both the training (0.850 versus 0.799) and validation (0.829 versus 0.783) cohorts. Calibration plotting demonstrated that the model had good calibration ability. The nomogram outperformed the AJCC staging system in terms of AUC, NRI, IDI, and DCA. Conclusion: This was the first study to develop and evaluate a comprehensive nomogram for the CSS of white patients with invasive melanoma at BANS sites using the SEER database. The novel nomogram can assist clinical staff in predicting the 3-, 5-, and 8-year CSS probabilities of patients with invasive melanoma more accurately than can the AJCC staging system.
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