Computer-assisted measurement of primary tumor area is prognostic of recurrence-free survival in stage IB melanoma patients
- Authors
- Rosenbaum, Brooke E.; Schafer, Christine N.; Han, Sung Won; Osman, Iman; Zhong, Hua; Brinster, Nooshin
- Issue Date
- 10월-2017
- Publisher
- NATURE PUBLISHING GROUP
- Citation
- MODERN PATHOLOGY, v.30, no.10, pp.1402 - 1410
- Indexed
- SCIE
SCOPUS
- Journal Title
- MODERN PATHOLOGY
- Volume
- 30
- Number
- 10
- Start Page
- 1402
- End Page
- 1410
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/82097
- DOI
- 10.1038/modpathol.2017.64
- ISSN
- 0893-3952
- 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.
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