ArticleJAMA network open2021
Assessing the Prognostic Significance of Tumor-Infiltrating Lymphocytes in Patients With Melanoma Using Pathologic Features Identified by Natural Language Processing.
Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.
- Natural language processing in dermatology: A systematic literature review and state of the art.Journal of the European Academy of Dermatology and Venereology : JEADV · 2024Pooled it
- Spatial T lymphocyte infiltration into the primary melanoma tumor associates with survival.Melanoma research · 2026Article
- Article
- Clinical and Pathological Predictors of Unfavourable Outcomes in Thin and In Situ Melanomas: A Retrospective Cohort Study from Taiwan.Acta dermato-venereologica · 2026Article
- Large Language Models for Clinical Narrative Processing: Methods, Applications, and Challenges.Methods and protocols · 2026Article
- From Immunobiology to Clinical Application: Tumor-Infiltrating Lymphocytes in Melanoma.Journal of personalized medicine · 2026Review
- Artificial Intelligence in Histopathological Analysis for Predicting Immunotherapy Response in Cutaneous Melanoma.International journal of molecular sciences · 2025Review
- Development and Evaluation of Natural Language Processing Methods for Extracting Key Melanoma Pathology Concepts.Studies in health technology and informatics · 2025Article
- Establishing a Validation Framework of Treatment Discontinuation in Claims Data Using Natural Language Processing and Electronic Health Records.Clinical pharmacology and therapeutics · 2025Article
- Pathologist-Read vs AI-Driven Assessment of Tumor-Infiltrating Lymphocytes in Melanoma.JAMA network open · 2025Article
- Scalable information extraction from free text electronic health records using large language models.BMC medical research methodology · 2025Article
- Melanoma progression and prognostic models drawn from single-cell, spatial maps of benign and malignant tumors.Science advances · 2024Article
- Role of tumor-infiltrating lymphocytes in melanoma prognosis and treatment strategies: A systematic review and meta-analysis.Heliyon · 2024Article
- Tumor-infiltrating lymphocytes as a prognostic and predictive factor for Melanoma.Expert review of molecular diagnostics · 2024Review
- Just how transformative will AI/ML be for immuno-oncology?Journal for immunotherapy of cancer · 2024Review
- Cross‑talk between lymphangiogenesis and malignant melanoma cells: New opinions on tumour drainage and immunization (Review).Oncology letters · 2024Review
- Current status of artificial intelligence methods for skin cancer survival analysis: a scoping review.Frontiers in medicine · 2024Article
- Acute remote ischemic conditioning enhances (CD3+)- but not (FoxP3+)-T-cell invasion in the tumor center and increases IL 17 and TNF-alpha expression in a murine melanoma model.Frontiers in immunology · 2024Article
- Clock-like Mutation Signature May Be Prognostic for Worse Survival Than Signatures of UV Damage in Cutaneous Melanoma.Cancers · 2023Article
- Tumor-infiltrating lymphocytes as a predictive biomarker of cutaneous immune-related adverse events after immune checkpoint blockade in patients with advanced melanoma.Journal of the American Academy of Dermatology · 2023Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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