How Timely Is Diagnosis of Lung Cancer? Cohort Study of Individuals with Lung Cancer Presenting in Ambulatory Care in the United States

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...

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Bibliographic Details
Published in:Cancers Vol. 14; no. 23; p. 5756
Main Authors: 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
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 23-11-2022
MDPI
Subjects:
Ambulatory care
Ambulatory medical care
Cancer therapies
Chest
Codes
Cohort analysis
Comorbidity
Computed tomography
Diagnosis
Drug dosages
Electronic health records
Electronic medical records
Ethnicity
Health care policy
Histology
Information processing
Language
Lung cancer
Medical diagnosis
Medical prognosis
Medical screening
Medicine
Methods
Oncology
Patients
Radiation
Sarcoma
Thoracic surgery
Tomography
United States
United States > US
lung cancer
diagnosis
ambulatory care
natural language processing
diagnostic intervals
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Summary: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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ISSN:2072-6694
2072-6694
DOI:10.3390/cancers14235756