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Updated: Jan 17, 2026

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
Published on: March 8, 2022
Multivariate analysis and prediction model construction for distant metastasis of Acral Melanoma
Jiabin Deng1,2, Mengru Gao3, Hailin Yao1
1Department of Plastic Surgery, The First Affiliated Hospital of Anhui Medical University Hefei 230000, Anhui, China.
Objective:
To analyze the pathological characteristics of Acral Melanoma (AM) patients and identify the factors influencing distant metastasis, while constructing a predictive model for distant metastasis-free survival (DMFS).
Methods:
Conducted on 229 AM patients admitted to the Third People's Hospital of Bengbu and The First Affiliated Hospital of Anhui Medical University from January 1, 2012, to December 31, 2024. Data collected included gender, age, lesion location, initial diagnosis stage, trauma history, ulcer presence, Breslow thickness, mitotic rate, lactate dehydrogenase (LDH), albumin (Alb), and adjuvant therapy. DMFS was assessed through follow-up, with a deadline of March 31, 2025. Statistical analysis was performed to evaluate significant factors influencing distant metastasis.
Results:
The incidence of AM showed an increasing trend from 2012 to 2024. Of the 229 patients, 78 (34.06%) developed distant metastasis. The median follow-up period was 37 months, and 1-year, 3-year, and 5-year survival rates without distant metastasis were 93.45%, 74.24%, and 66.81%, respectively. Statistically significant factors affecting DMFS included initial diagnosis stage, ulcer presence, Breslow thickness, mitotic rate, LDH, and Alb levels (all P<0.05). Risk factors for distant metastasis included stage III at diagnosis, ulcer presence, lack of adjuvant therapy, elevated LDH, and low Alb levels.
Conclusions:
The study identified key pathological factors influencing distant metastasis in AM patients. The constructed nomogram model demonstrated good predictive accuracy, with AUC values of 0.895 and 0.879 in the training and validation sets, respectively. This model can aid in the clinical screening of AM patients at risk for distant metastasis.

