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  • Title: Malignant melanoma of the vulva in a nationwide, 25-year study of 219 Swedish females: predictors of survival.
    Author: Ragnarsson-Olding BK, Nilsson BR, Kanter-Lewensohn LR, Lagerlöf B, Ringborg UK.
    Journal: Cancer; 1999 Oct 01; 86(7):1285-93. PubMed ID: 10506715.
    Abstract:
    BACKGROUND: In an epidemiologic study of 219 Swedish females with vulvar melanoma, the authors previously established the incidence of this disease as 0.19 per 100,000 women, with a 3% annual decrease from 1960 to 1984 and a 5-year relative survival rate of 47%. After reviewing the medical histories of all of the 219 patients, the authors documented their precise clinical and histopathologic features, which, along with treatment, are assessed herein as predictors of survival. METHODS: Of 219 consecutive cases of vulvar melanoma collected from the Swedish National Cancer Registry, 21 were excluded because of inadequate data. Clinical and histopathologic materials from the remaining 198 cases were then reexamined. With a clinical three-stage system, lesion types and treatment modalities were assessed as survival factors in univariate and multivariate analyses. RESULTS: In univariate analysis, significant predictors of survival for patients at Stage I were tumor thickness, ulceration, number of mitoses, macroscopic amelanosis, preexisting nevi, extent of tumor invasion (lateral labia majora), and patient age. The mode of treatment was not significant. In multivariate analysis, staging (Stage I vs. II and III) and tumor thickness were independent predictors of survival. For Stage I only, tumor thickness, ulceration, and clinical amelanosis independently predicted survival time. CONCLUSIONS: To the authors' knowledge, this is the largest series of patients with vulvar melanoma ever reviewed, and an ethnically homogeneous and nationwide female population is represented. In this series, clinical stage, macroscopic amelanosis, and tumor characteristics such as tumor thickness and ulceration, rather than treatment mode, were the best factors for predicting the outcome of these patients.
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