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1.
J Cutan Pathol ; 47(3): 226-240, 2020 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-31697431

RESUMEN

PURPOSE: Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which would more reliably differentiate between benign and malignant melanocytic lesions. METHODS: We performed histolpathology - guided mass spectrometry (HGMS) profiling analysis on formalin-fixed, paraffin embedded tissue samples to identify differences at the proteomic level between different types of benign nevi and melanomas. A total of 756 cases, of which 357 cases of melanoma and 399 benign nevi, were included in the study. The specimens originated from both biopsies (376 samples) and tissue microarray (TMA) cores (380 samples). After obtaining mass spectra from each sample, classification models were built using a training set of biopsy specimens from 111 nevi and 100 melanomas. The classification algorithm developed on the training data set was validated on an independent set of 288 nevi and 257 melanomas from both biopsies and TMA cores. RESULTS: In the melanoma cohort, 239/257 (93%) cases classified correctly in the validation set, 3/257 (1.2%) classified incorrectly, and 15/257 (5.8%) classified as indeterminate. In the cohort of nevi, 282/288 (98%) cases classified correctly, 1/288 (0.3%) classified incorrectly, and 5/288 (1.7%) were indeterminate. HGMS showed a sensitivity of 98.76% and specificity of 99.65% in determining benign vs malignant. CONCLUSION: HGMS proteomic analysis is an objective and reliable test with minimal tissue requirements, which can be a helpful ancillary test in the diagnosis of challenging melanocytic lesions.


Asunto(s)
Aprendizaje Automático , Espectrometría de Masas/métodos , Melanoma/diagnóstico , Nevo/diagnóstico , Neoplasias Cutáneas/diagnóstico , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , Niño , Preescolar , Diagnóstico Diferencial , Femenino , Humanos , Masculino , Persona de Mediana Edad , Proteómica/métodos , Adulto Joven , Melanoma Cutáneo Maligno
2.
J Am Acad Dermatol ; 71(6): 1077-82, 2014 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-25308882

RESUMEN

BACKGROUND: Spitz nevi and Spitzoid malignant melanomas are uncommon and may be difficult to distinguish histopathologically. Identification of clinical features associated with these lesions may aid in diagnosis. OBJECTIVE: We sought to identify clinical characteristics associated with Spitz nevi and Spitzoid malignant melanomas. METHODS: We conducted a retrospective cohort study of Spitz nevi and Spitzoid malignant melanomas from the Yale University Spitzoid Neoplasm Repository diagnosed from years 1991 through 2008. Descriptive statistics and multivariate logistic regression were used to compare select patient- and tumor-level factors associated with each lesion. RESULTS: Our cohort included 484 Spitz nevi and 54 Spitzoid malignant melanomas. Spitz nevi were more common (P = .03) in females (65%; n = 316) compared with Spitzoid malignant melanomas (50%; n = 27), occurred more frequently in younger patients (mean age at diagnosis 22 vs 55 years; P < .001), and more likely presented as smaller lesions (diameter 7.6 vs 10.5 mm; P < .001). Increasing age (odds ratio 1.16, 95% CI [1.09, 1.14]; P< .001) and male gender (odds ratio 2.77, 95% CI [1.17, 6.55]; P< .02) predicted Spitzoid malignant melanoma diagnosis. LIMITATIONS: Small sample size, unmeasured confounding, and restriction to a single institution may limit the accuracy and generalizability of our findings. CONCLUSIONS: Age and gender help predict diagnosis of Spitz nevi and Spitzoid malignant melanomas.


Asunto(s)
Melanoma/patología , Nevo de Células Epitelioides y Fusiformes/patología , Neoplasias Cutáneas/patología , Piel/patología , Adolescente , Adulto , Factores de Edad , Anciano , Biopsia , Niño , Preescolar , Estudios Transversales , Diagnóstico Diferencial , Femenino , Humanos , Lactante , Masculino , Persona de Mediana Edad , Valor Predictivo de las Pruebas , Adulto Joven
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