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Computer-assisted measurement of primary tumor area is prognostic of recurrence-free survival in stage IB melanoma patients.
Rosenbaum, Brooke E; Schafer, Christine N; Han, Sung Won; Osman, Iman; Zhong, Hua; Brinster, Nooshin.
Afiliação
  • Rosenbaum BE; The Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York, NY, USA.
  • Schafer CN; The Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York, NY, USA.
  • Han SW; Department of Industrial Management Engineering, Korea University, Seoul, Republic of Korea.
  • Osman I; The Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York, NY, USA.
  • Zhong H; Department of Population Health, New York University School of Medicine, New York, NY, USA.
  • Brinster N; The Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York, NY, USA.
Mod Pathol ; 30(10): 1402-1410, 2017 10.
Article em En | MEDLINE | ID: mdl-28731044
ABSTRACT
Current staging guidelines are insufficient to predict which patients with thin primary melanoma are at high risk of recurrence. Computer-assisted image analysis may allow for more practical and objective histopathological analysis of primary tumors than traditional light microscopy. We studied a prospective cohort of stage IB melanoma patients treated at NYU Langone Medical Center from 2002 to 2014. Primary tumor width, manual area, digital area, and conformation were evaluated in a patient subset via computer-assisted image analysis. The associations between histologic variables and survival were evaluated using Cox proportional hazards model. Logistic regressions were used to build a classifier with clinicopathological characteristics to predict recurrence status. Of the 655 patients with stage IB melanoma studied, a subset of 149 patient tumors (63 recurred, 86 did not recur) underwent computer-assisted histopathological analysis. Increasing tumor width (hazard ratios (HR) 1.17, P=0.01) and digital area (HR 1.08, P<0.01) were significantly associated with worse recurrence-free survival, whereas non-contiguous conformation (HR 0.57, P=0.05) was significantly associated with better recurrence-free survival. The novel histopathological classifier composed of digital area, conformation, and baseline variables effectively distinguished recurrent cases from non-recurrent cases (AUC 0.733, 95% confidence interval (CI) 0.647-0.818), compared to the baseline classifier alone (AUC 0.635, 95% CI 0.545-0.724). Primary tumor cross-sectional area, width, and conformation measured via computer-assisted analysis may help identify high-risk patients with stage IB melanoma.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Cutâneas / Interpretação de Imagem Assistida por Computador / Melanoma / Recidiva Local de Neoplasia Tipo de estudo: Guideline / Prognostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Mod Pathol Assunto da revista: PATOLOGIA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Cutâneas / Interpretação de Imagem Assistida por Computador / Melanoma / Recidiva Local de Neoplasia Tipo de estudo: Guideline / Prognostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Mod Pathol Assunto da revista: PATOLOGIA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Estados Unidos
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