ArticleBMC cancer2021
Comparing the characteristics and predicting the survival of patients with head and neck melanoma versus body melanoma: a population-based study.
Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 26 citations in OpenAlex.
- Development and internal validation of machine learning models for predicting lymph node metastasis in cutaneous head and neck melanoma.Translational cancer research · 2026Article
- Establishment of multiple predictive models for early identification of the dengue cases in outpatient healthcare systems.Scientific reports · 2026Article
- Comparative study of cutaneous malignant melanoma according to anatomical site: plantar versus non-plantar melanoma.Archives of dermatological research · 2024Article
- Dermoscopy Training Course Improves Ophthalmologists' Accuracy in Diagnosing Atypical Pigmented Periorbital Skin Lesions.Diagnostics (Basel, Switzerland) · 2024Article
- Article
- Risk prediction and treatment assessment in glioma patients using SEER database: a prospective observational study.BMJ open · 2023Observational
- Uncovering the complex relationship between balding, testosterone and skin cancers in men.Nature communications · 2023Article
- The Impact of Clinical and Histopathological Factors on Disease Progression and Survival in Thick Cutaneous Melanomas.Biomedicines · 2023Article
- Anatomic Region of Cutaneous Melanoma Impacts Survival and Clinical Outcomes: A Population-Based Analysis.Cancers · 2023Article
- Gradient differences of immunotherapy efficacy in metastatic melanoma related to sunlight exposure pattern: A population-based study.Frontiers in oncology · 2022Article
- Development of an Early Warning Model for Predicting the Death Risk of Coronavirus Disease 2019 Based on Data Immediately Available on Admission.Frontiers in medicine · 2021Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrevious studies reported cutaneous melanoma in head and neck (HNM) differed from those in other regions (body melanoma, BM). Individualized tools to predict the survival of patients with HNM or BM remain insufficient. We aimed at comparing the characteristics of HNM and BM, developing and validating nomograms for predicting the survival of patients with HNM or BM.
methodsThe information of patients with HNM or BM from 2004 to 2015 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. The HNM group and BM group were randomly divided into training and validation cohorts. We used the Kaplan-Meier method and multivariate Cox models to identify independent prognostic factors. Nomograms were developed via the rms and dynnom packages, and were measured by the concordance index (C-index), the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and calibration plots.
resultsOf 70,605 patients acquired, 21% had HNM and 79% had BM. The HNM group contained more older patients, male sex and lentigo maligna melanoma, and more frequently had thicker tumors and metastases than the BM group. The 5-year cancer-specific survival (CSS) and overall survival (OS) rates were 88.1 ± 0.3% and 74.4 ± 0.4% in the HNM group and 92.5 ± 0.1% and 85.8 ± 0.2% in the BM group, respectively. Eight variables (age, sex, histology, thickness, ulceration, stage, metastases, and surgery) were identified to construct nomograms of CSS and OS for patients with HNM or BM. Additionally, four dynamic nomograms were available on web. The internal and external validation of each nomogram showed high C-index values (0.785-0.896) and AUC values (0.81-0.925), and the calibration plots showed great consistency.
conclusionsThe characteristics of HNM and BM are heterogeneous. We constructed and validated four nomograms for predicting the 3-, 5- and 10-year CSS and OS probabilities of patients with HNM or BM. These nomograms can serve as practical clinical tools for survival prediction and individual health management.
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