How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States
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 inter...
| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Cancers |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-6694/14/23/5756 |
| _version_ | 1797463559640186880 |
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| author | Monica Zigman Suchsland Lesleigh Kowalski Hannah A. Burkhardt Maria G. Prado Larry G. Kessler Meliha Yetisgen Maggie A. Au Kari A. Stephens Farhood Farjah Anneliese M. Schleyer Fiona M. Walter Richard D. Neal Kevin Lybarger Caroline A. Thompson Morhaf Al Achkar Elizabeth A. Sarma Grace Turner Matthew Thompson |
| author_facet | Monica Zigman Suchsland Lesleigh Kowalski Hannah A. Burkhardt Maria G. Prado Larry G. Kessler Meliha Yetisgen Maggie A. Au Kari A. Stephens Farhood Farjah Anneliese M. Schleyer Fiona M. Walter Richard D. Neal Kevin Lybarger Caroline A. Thompson Morhaf Al Achkar Elizabeth A. Sarma Grace Turner Matthew Thompson |
| author_sort | Monica Zigman Suchsland |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T17:52:27Z |
| format | Article |
| id | doaj.art-91b6f582c2734879bbb5625922235055 |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-09T17:52:27Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-91b6f582c2734879bbb56259222350552023-11-24T10:38:09ZengMDPI AGCancers2072-66942022-11-011423575610.3390/cancers14235756How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United StatesMonica Zigman Suchsland0Lesleigh Kowalski1Hannah A. Burkhardt2Maria G. Prado3Larry G. Kessler4Meliha Yetisgen5Maggie A. Au6Kari A. Stephens7Farhood Farjah8Anneliese M. Schleyer9Fiona M. Walter10Richard D. Neal11Kevin Lybarger12Caroline A. Thompson13Morhaf Al Achkar14Elizabeth A. Sarma15Grace Turner16Matthew Thompson17Department of Family Medicine, University of Washington, Seattle, WA 98195, USADepartment of Family Medicine, University of Washington, Seattle, WA 98195, USADepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USADepartment of Family Medicine, University of Washington, Seattle, WA 98195, USADepartment of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA 98195, USADepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USADepartment of Family Medicine, University of Washington, Seattle, WA 98195, USADepartment of Family Medicine, University of Washington, Seattle, WA 98195, USADepartment of Surgery, University of Washington, Seattle, WA 98195, USADepartment of Medicine, University of Washington, Seattle, WA 98195, USAWolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 4NS, UKUniversity of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UKDepartment of Information Sciences and Technology, George Mason University, Fairfax, VA 22039, USADepartment of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USADepartment of Family Medicine, University of Washington, Seattle, WA 98195, USAHealthcare Delivery Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20892, USADepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USADepartment of Family Medicine, University of Washington, Seattle, WA 98195, USAThe 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.https://www.mdpi.com/2072-6694/14/23/5756lung cancerdiagnosisambulatory carenatural language processingdiagnostic intervals |
| spellingShingle | Monica Zigman Suchsland Lesleigh Kowalski Hannah A. Burkhardt Maria G. Prado Larry G. Kessler Meliha Yetisgen Maggie A. Au Kari A. Stephens Farhood Farjah Anneliese M. Schleyer Fiona M. Walter Richard D. Neal Kevin Lybarger Caroline A. Thompson Morhaf Al Achkar Elizabeth A. Sarma Grace Turner Matthew Thompson How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States Cancers lung cancer diagnosis ambulatory care natural language processing diagnostic intervals |
| title | How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States |
| title_full | How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States |
| title_fullStr | How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States |
| title_full_unstemmed | How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States |
| title_short | How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States |
| title_sort | how timely is diagnosis of lung cancer cohort study of individuals with lung cancer presenting in ambulatory care in the united states |
| topic | lung cancer diagnosis ambulatory care natural language processing diagnostic intervals |
| url | https://www.mdpi.com/2072-6694/14/23/5756 |
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