Diagnostic and prognostic risk factors analysis for distant metastasis in melanoma: a population-based study

Author:

Sun Junwei12,Wang Mingyu3,Kan Zhisheng2

Affiliation:

1. Peking University China-Japan Friendship School of Clinical Medicine, Beijing

2. Department of Neurosurgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

3. Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China

Abstract

Background We aimed to develop tools that could predict the occurrence of distant metastases in melanoma and its prognosis based on clinical and pathological characteristics. Materials and methods We obtained data from the Surveillance, Epidemiology, and End Results (SEER) database of melanoma patients diagnosed between 2010 and 2019. Logistic analyses were performed to identify independent risk factors associated with distant metastasis. Additionally, multivariate Cox analyses were conducted to determine independent prognostic factors for patients with distant metastasis. Two nomograms were established and evaluated with the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Furthermore, we performed a retrospective analysis of melanoma with distant metastasis from our institute between March 2018 and June 2022. Results Of the total 19 396 melanoma patients, 352 (1.8%) had distant metastases at the time of diagnosis. The following clinical and pathological characteristics were identified as independent risk factors for distant metastasis in melanoma: N stage, tumor size, ulceration, mitosis, primary tumor site, and pathological subtype. Furthermore, tumor size, pathological subtype, and radiotherapy were identified as independent prognostic factors. The results of the training and validation cohorts’ ROC curves, calibration, DCA, and Kaplan–Meier survival curves demonstrate the effectiveness of the two nomograms. The retrospective study results from our center supported the results from the SEER database. Conclusion The clinical and pathological characteristics of melanoma can predict a patient’s risk of metastasis and prognosis, and the two nomograms are expected to be effective tools to guide therapy decisions.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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