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How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States.
Zigman Suchsland, Monica; Kowalski, Lesleigh; Burkhardt, Hannah A; Prado, Maria G; Kessler, Larry G; Yetisgen, Meliha; Au, Maggie A; Stephens, Kari A; Farjah, Farhood; Schleyer, Anneliese M; Walter, Fiona M; Neal, Richard D; Lybarger, Kevin; Thompson, Caroline A; Achkar, Morhaf Al; Sarma, Elizabeth A; Turner, Grace; Thompson, Matthew.
Afiliação
  • Zigman Suchsland M; Department of Family Medicine, University of Washington, Seattle, WA 98195, USA.
  • Kowalski L; Department of Family Medicine, University of Washington, Seattle, WA 98195, USA.
  • Burkhardt HA; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA.
  • Prado MG; Department of Family Medicine, University of Washington, Seattle, WA 98195, USA.
  • Kessler LG; Department of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA 98195, USA.
  • Yetisgen M; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA.
  • Au MA; Department of Family Medicine, University of Washington, Seattle, WA 98195, USA.
  • Stephens KA; Department of Family Medicine, University of Washington, Seattle, WA 98195, USA.
  • Farjah F; Department of Surgery, University of Washington, Seattle, WA 98195, USA.
  • Schleyer AM; Department of Medicine, University of Washington, Seattle, WA 98195, USA.
  • Walter FM; Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 4NS, UK.
  • Neal RD; The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK.
  • Lybarger K; University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK.
  • Thompson CA; Department of Information Sciences and Technology, George Mason University, Fairfax, VA 22039, USA.
  • Achkar MA; Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Sarma EA; Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA 92182, USA.
  • Turner G; Department of Family Medicine, University of Washington, Seattle, WA 98195, USA.
  • Thompson M; Healthcare Delivery Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20892, USA.
Cancers (Basel) ; 14(23)2022 Nov 23.
Article em En | MEDLINE | ID: mdl-36497238
The diagnosis of lung cancer in ambulatory settings is often challenging due to non-specific clinical presentation, but there are currently no clinical quality measures (CQMs) in the United States used to identify areas for practice improvement in diagnosis. We describe the pre-diagnostic time intervals among a retrospective cohort of 711 patients identified with primary lung cancer from 2012-2019 from ambulatory care clinics in Seattle, Washington USA. Electronic health record data were extracted for two years prior to diagnosis, and Natural Language Processing (NLP) applied to identify symptoms/signs from free text clinical fields. Time points were defined for initial symptomatic presentation, chest imaging, specialist consultation, diagnostic confirmation, and treatment initiation. Median and interquartile ranges (IQR) were calculated for intervals spanning these time points. The mean age of the cohort was 67.3 years, 54.1% had Stage III or IV disease and the majority were diagnosed after clinical presentation (94.5%) rather than screening (5.5%). Median intervals from first recorded symptoms/signs to diagnosis was 570 days (IQR 273-691), from chest CT or chest X-ray imaging to diagnosis 43 days (IQR 11-240), specialist consultation to diagnosis 72 days (IQR 13-456), and from diagnosis to treatment initiation 7 days (IQR 0-36). Symptoms/signs associated with lung cancer can be identified over a year prior to diagnosis using NLP, highlighting the need for CQMs to improve timeliness of diagnosis.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos