{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T06:00:24Z","timestamp":1787896824986,"version":"build-2784847793"},"reference-count":48,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"9","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Clin Cancer Inform"],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:sec>\n            <jats:title>PURPOSE<\/jats:title>\n            <jats:p>Recurrences after curative resection in early-stage and locoregionally advanced non\u2013small cell lung cancer (NSCLC) are common, necessitating a nuanced understanding of associated risk factors. This study aimed to establish a natural language processing (NLP) system to efficiently curate recurrence data in NSCLC and analyze risk factors longitudinally.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>PATIENTS AND METHODS<\/jats:title>\n            <jats:p>Electronic health records of 6,351 patients with NSCLC with &gt;700,000 notes were obtained from Mount Sinai's data sets. A deep learning\u2013based customized NLP system was developed to identify cohorts experiencing recurrence. Recurrence types and rates over time were stratified by various clinical features. Cohort description analysis, Kaplan-Meier analysis for overall recurrence-free survival (RFS) and distant metastasis-free survival (DMFS), and Cox proportional hazards analysis were performed.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>RESULTS<\/jats:title>\n            <jats:p>\n              Of 1,295 patients with stage I\u2013IIIA NSCLC with surgical resections, 336 patients (25.9%) experienced recurrence, as identified through NLP. The NLP system achieved a precision of 94.3%, a recall of 93%, and an F1 score of 93.5. Among 336 patients, 52.4% had local\/regional recurrences, 44% distant metastases, and 3.6% unknown recurrence. RFS rates at years 1-5 were 93%, 81%, 73%, 67%, and 61%, respectively (96%, 89%, 84%, 80%, and 75% for distant metastasis). Stage-specific RFS rates at year 5 were 73% (IA), 62% (IB), 47% (IIA), 46% (IIB), and 20% (IIIA). Stage IB patients had a significantly higher likelihood of recurrence versus stage IA (adjusted hazard ratio [aHR], 1.63;\n              <jats:italic>P<\/jats:italic>\n              = .02). The RFS was lower in patients with clinically significant\n              <jats:italic>TP53<\/jats:italic>\n              alteration (\n              <jats:italic>v<\/jats:italic>\n              <jats:italic>TP53<\/jats:italic>\n              -negative or unknown significance), affecting overall RFS (aHR, 1.89;\n              <jats:italic>P<\/jats:italic>\n              = .007) and DMFS (aHR, 2.47;\n              <jats:italic>P<\/jats:italic>\n              = .009) among stage IA\/IB patients.\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>CONCLUSION<\/jats:title>\n            <jats:p>Our scalable NLP system enabled us to generate real-world insights into NSCLC recurrences, paving the way for predictive models for preventing, diagnosing, and treating NSCLC recurrence.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1200\/cci-24-00227","type":"journal-article","created":{"date-parts":[[2025,4,18]],"date-time":"2025-04-18T20:00:16Z","timestamp":1745006416000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":2,"title":["Decoding Recurrence in Early-Stage and Locoregionally Advanced Non\u2013Small Cell Lung Cancer: Insights From Electronic Health Records and Natural Language Processing"],"prefix":"10.1200","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6937-9931","authenticated-orcid":true,"given":"Kyeryoung","family":"Lee","sequence":"first","affiliation":[{"name":"GeneDx (Sema4), Stamford, CT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1578-9967","authenticated-orcid":true,"given":"Zongzhi","family":"Liu","sequence":"additional","affiliation":[{"name":"GeneDx (Sema4), Stamford, CT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6441-7591","authenticated-orcid":true,"given":"Qing","family":"Huang","sequence":"additional","affiliation":[{"name":"Lung Cancer Initiative, Johnson &amp; Johnson, New Brunswick, NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8239-129X","authenticated-orcid":true,"given":"David","family":"Corrigan","sequence":"additional","affiliation":[{"name":"GeneDx (Sema4), Stamford, CT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5232-5972","authenticated-orcid":true,"given":"Iftekhar","family":"Kalsekar","sequence":"additional","affiliation":[{"name":"Lung Cancer Initiative, Johnson &amp; Johnson, New Brunswick, NJ"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2120-1704","authenticated-orcid":true,"given":"Tomi","family":"Jun","sequence":"additional","affiliation":[{"name":"GeneDx (Sema4), Stamford, CT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9618-2819","authenticated-orcid":true,"given":"Gustavo","family":"Stolovitzky","sequence":"additional","affiliation":[{"name":"GeneDx (Sema4), Stamford, CT"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5113-8147","authenticated-orcid":true,"given":"William K.","family":"Oh","sequence":"additional","affiliation":[{"name":"GeneDx (Sema4), Stamford, CT"},{"name":"Icahn School of Medicine at Mount Sinai, New York, NY"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ravi","family":"Rajaram","sequence":"additional","affiliation":[{"name":"Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Wang","sequence":"additional","affiliation":[{"name":"GeneDx (Sema4), Stamford, CT"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"233","reference":[{"key":"e_1_3_7_2_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2021.0377"},{"key":"e_1_3_7_3_2","volume-title":"Lung Cancer Survival Rates","author":"American Cancer Society","unstructured":"American Cancer Society: Lung Cancer Survival Rates. https:\/\/www.cancer.org\/cancer\/types\/lung-cancer\/detection-diagnosis-staging\/survival-rates.html"},{"key":"e_1_3_7_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41571-020-00432-6"},{"key":"e_1_3_7_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.chest.2023.11.042"},{"key":"e_1_3_7_6_2","volume-title":"What Is Cancer Recurrence?","author":"American Cancer Society","unstructured":"American Cancer Society: What Is Cancer Recurrence? 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