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Assessing the Prognostic Significance of Tumor-Infiltrating Lymphocytes in Patients With Melanoma Using Pathologic Features Identified by Natural Language Processing

IMPORTANCE: Although tumor-infiltrating lymphocytes (TILs) are an important histopathologic characteristic reflecting host immune response in patients with melanoma, their prognostic value remains controversial. Because manual review of medical records is labor intensive, a survival analysis using a...

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Autores principales: Yang, Jie, Lian, John W., Chin, Yen-Po (Harvey), Wang, Liqin, Lian, Anna, Murphy, George F., Zhou, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459191/
https://www.ncbi.nlm.nih.gov/pubmed/34550383
http://dx.doi.org/10.1001/jamanetworkopen.2021.26337
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author Yang, Jie
Lian, John W.
Chin, Yen-Po (Harvey)
Wang, Liqin
Lian, Anna
Murphy, George F.
Zhou, Li
author_facet Yang, Jie
Lian, John W.
Chin, Yen-Po (Harvey)
Wang, Liqin
Lian, Anna
Murphy, George F.
Zhou, Li
author_sort Yang, Jie
collection PubMed
description IMPORTANCE: Although tumor-infiltrating lymphocytes (TILs) are an important histopathologic characteristic reflecting host immune response in patients with melanoma, their prognostic value remains controversial. Because manual review of medical records is labor intensive, a survival analysis using a large patient cohort with comprehensive clinical and histopathologic characteristics is lacking. OBJECTIVE: To assess the prognostic significance of TILs among patients with cutaneous melanoma using a large cohort established through natural language processing (NLP) algorithms. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study analyzed the medical records of 14 436 patients with cutaneous melanoma at Brigham and Women’s Hospital between June 1, 2004, and December 31, 2019. Patients were followed up to death or censored at their last clinical visit. MAIN OUTCOME AND MEASURES: The primary outcome was overall survival (OS). Survival analysis was conducted using Kaplan-Meier curves, the log-rank test, and Cox proportional hazards regression analysis. RESULTS: A total of 14 436 patients with cutaneous melanoma were identified in the institution’s pathology information system. Using NLP, we established a study cohort of 2624 patients (1462 men [55.7%]; median age, 61 years [interquartile range, 50-72 years]) who had vertical growth phase melanoma with TIL status scored. Absent TILs were identified in 434 patients (16.5%), nonbrisk TILs in 1916 patients (73.0%), and brisk TILs in 274 patients (10.4%). The 5-year survival rate was 71.0% (95% CI, 65.5%-76.9%) among patients with an absence of TILs, 73.8% (95% CI, 71.1%-76.5%) among patients with nonbrisk TILs, and 85.2% (95% CI, 80.0%-90.7%) among patients with brisk TILs. Brisk TILs were significantly associated with improved OS (adjusted hazard ratio, 0.63; 95% CI, 0.42-0.95; P = .03; 14.2% OS advantage at 5 years), and nonbrisk TILs were not associated with improved OS (adjusted hazard ratio, 0.87; 95% CI, 0.68-1.11; P = .25), compared with the absence of TILs. CONCLUSIONS AND RELEVANCE: This study provides evidence based on a large patient cohort from a single institution that suggests that brisk TILs represent an independent prognostic factor for OS among patients with primary cutaneous melanoma. The study also suggests that NLP is a highly efficient tool to facilitate large-scale analyses that involve free-text clinical data.
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spelling pubmed-84591912021-10-07 Assessing the Prognostic Significance of Tumor-Infiltrating Lymphocytes in Patients With Melanoma Using Pathologic Features Identified by Natural Language Processing Yang, Jie Lian, John W. Chin, Yen-Po (Harvey) Wang, Liqin Lian, Anna Murphy, George F. Zhou, Li JAMA Netw Open Original Investigation IMPORTANCE: Although tumor-infiltrating lymphocytes (TILs) are an important histopathologic characteristic reflecting host immune response in patients with melanoma, their prognostic value remains controversial. Because manual review of medical records is labor intensive, a survival analysis using a large patient cohort with comprehensive clinical and histopathologic characteristics is lacking. OBJECTIVE: To assess the prognostic significance of TILs among patients with cutaneous melanoma using a large cohort established through natural language processing (NLP) algorithms. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study analyzed the medical records of 14 436 patients with cutaneous melanoma at Brigham and Women’s Hospital between June 1, 2004, and December 31, 2019. Patients were followed up to death or censored at their last clinical visit. MAIN OUTCOME AND MEASURES: The primary outcome was overall survival (OS). Survival analysis was conducted using Kaplan-Meier curves, the log-rank test, and Cox proportional hazards regression analysis. RESULTS: A total of 14 436 patients with cutaneous melanoma were identified in the institution’s pathology information system. Using NLP, we established a study cohort of 2624 patients (1462 men [55.7%]; median age, 61 years [interquartile range, 50-72 years]) who had vertical growth phase melanoma with TIL status scored. Absent TILs were identified in 434 patients (16.5%), nonbrisk TILs in 1916 patients (73.0%), and brisk TILs in 274 patients (10.4%). The 5-year survival rate was 71.0% (95% CI, 65.5%-76.9%) among patients with an absence of TILs, 73.8% (95% CI, 71.1%-76.5%) among patients with nonbrisk TILs, and 85.2% (95% CI, 80.0%-90.7%) among patients with brisk TILs. Brisk TILs were significantly associated with improved OS (adjusted hazard ratio, 0.63; 95% CI, 0.42-0.95; P = .03; 14.2% OS advantage at 5 years), and nonbrisk TILs were not associated with improved OS (adjusted hazard ratio, 0.87; 95% CI, 0.68-1.11; P = .25), compared with the absence of TILs. CONCLUSIONS AND RELEVANCE: This study provides evidence based on a large patient cohort from a single institution that suggests that brisk TILs represent an independent prognostic factor for OS among patients with primary cutaneous melanoma. The study also suggests that NLP is a highly efficient tool to facilitate large-scale analyses that involve free-text clinical data. American Medical Association 2021-09-22 /pmc/articles/PMC8459191/ /pubmed/34550383 http://dx.doi.org/10.1001/jamanetworkopen.2021.26337 Text en Copyright 2021 Yang J et al. JAMA Network Open. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the CC-BY License.
spellingShingle Original Investigation
Yang, Jie
Lian, John W.
Chin, Yen-Po (Harvey)
Wang, Liqin
Lian, Anna
Murphy, George F.
Zhou, Li
Assessing the Prognostic Significance of Tumor-Infiltrating Lymphocytes in Patients With Melanoma Using Pathologic Features Identified by Natural Language Processing
title Assessing the Prognostic Significance of Tumor-Infiltrating Lymphocytes in Patients With Melanoma Using Pathologic Features Identified by Natural Language Processing
title_full Assessing the Prognostic Significance of Tumor-Infiltrating Lymphocytes in Patients With Melanoma Using Pathologic Features Identified by Natural Language Processing
title_fullStr Assessing the Prognostic Significance of Tumor-Infiltrating Lymphocytes in Patients With Melanoma Using Pathologic Features Identified by Natural Language Processing
title_full_unstemmed Assessing the Prognostic Significance of Tumor-Infiltrating Lymphocytes in Patients With Melanoma Using Pathologic Features Identified by Natural Language Processing
title_short Assessing the Prognostic Significance of Tumor-Infiltrating Lymphocytes in Patients With Melanoma Using Pathologic Features Identified by Natural Language Processing
title_sort assessing the prognostic significance of tumor-infiltrating lymphocytes in patients with melanoma using pathologic features identified by natural language processing
topic Original Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459191/
https://www.ncbi.nlm.nih.gov/pubmed/34550383
http://dx.doi.org/10.1001/jamanetworkopen.2021.26337
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