期刊
ANNALS OF SURGERY
卷 253, 期 6, 页码 1155-1164出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/SLA.0b013e318214beba
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- Cancer Institute New South Wales
- Australian National Health and Medical Research Council
- Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital
Background: Studies which have found that histologic features of metastatic melanoma in sentinel lymph nodes (SNs) were predictive of survival have differed considerably in their design and results. We investigated in detail the influence of SN tumor characteristics and clinical and primary tumor parameters on clinical outcomes in a large cohort of patients treated in a single center. Methods: In SN-positive melanoma patients, the association of clinical, primary tumor, and SN tumor features [maximum size (MaxSize), % cross-sectional area of SN occupied by tumor (% CS), tumor-penetrative depth (TPD), intranodal location of tumor, extranodal spread (ENS), and perinodal lymphatic invasion (PLI)] with disease-free (DFS), distant metastasis-free (DMFS), and melanoma-specific (MSS) survival was analyzed. Results: In 409 SN-positive patients, independent predictors of poorer DFS were primary tumor features [anatomic site: head/neck (HR = 3.65, 95% CI 1.65-8.08) and limbs (HR = 2.46, 95% CI 1.21-4.98) compared with trunk; ulceration (HR = 1.70, 95% CI 1.15-2.51); satellites (HR = 2.85, 95% CI 1.49-5.44)], SN tumor features [MaxSize (HR = 1.53, 95% CI 1.04-2.26); ENS in SN (HR = 2.05, 95% CI 1.06-4.00); PLI (HR = 1.85, 95% CI 1.11-3.07)], and positive CLND (HR = 1.92, 95% CI 1.26-2.91). Factors independently predictive of poorer MSS were age >= 50 years (HR 1.64, 95% CI 1.01-2.67), primary tumor features [ulceration (HR = 2.55, 95% CI 1.44-4.52); satellites (HR = 3.95, 95% CI 1.83-8.49)], and ENS in SN (HR = 2.34, 95% CI 1.06-5.13). Conclusions: The use of clinical, primary tumor, and SN tumor characteristics shown to be independent predictors of clinical outcomes in melanoma patients will assist in accurate prediction of prognosis and optimize clinical management.
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