Evidence map›Paper›PMID 36497238›Full record

ArticleCancers2022

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

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 and 8 more

Abstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Life Course Trajectories of Body Mass Index and Risk of Cancer in Adulthood: Systematic Review and Meta-Analysis.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
    Pooled it
  2. Article
  3. Exploring Clinical Pathways to a Metastatic Lung Cancer Diagnosis: A Latent Class Analysis Using North Carolina Multipayer Claims Data.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Observational
  11. Therapeutic Vaccination in Lung Cancer: Past Attempts, Current Approaches and Future Promises.Journal of respiratory biology and translational medicine · 2025
    Article
  12. Article
  13. Review
  14. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Monica Zigman SuchslandDepartment of Family Medicine, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0001-7007-6973
Lesleigh KowalskiDepartment of Family Medicine, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0002-1742-6628
Hannah A BurkhardtDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0002-9386-5569
Maria G PradoDepartment of Family Medicine, University of Washington, Seattle, WA 98195, USA.
Larry G KesslerDepartment of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA 98195, USA.
Meliha YetisgenDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA.
Maggie A AuDepartment of Family Medicine, University of Washington, Seattle, WA 98195, USA.
Kari A StephensDepartment of Family Medicine, University of Washington, Seattle, WA 98195, USA.
Farhood FarjahDepartment of Surgery, University of Washington, Seattle, WA 98195, USA.
Anneliese M SchleyerDepartment of Medicine, University of Washington, Seattle, WA 98195, USA.
Fiona M WalterWolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 4NS, UK.
Richard D NealUniversity of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK.ORCID 0000-0002-3544-2744
Kevin LybargerDepartment of Information Sciences and Technology, George Mason University, Fairfax, VA 22039, USA.ORCID 0000-0001-5798-2664
Caroline A ThompsonDepartment of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.ORCID 0000-0001-9990-9756
Morhaf Al AchkarDepartment of Family Medicine, University of Washington, Seattle, WA 98195, USA.ORCID 0000-0002-4160-0550
Elizabeth A SarmaHealthcare Delivery Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20892, USA.
Grace TurnerDepartment of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA.
Matthew ThompsonDepartment of Family Medicine, University of Washington, Seattle, WA 98195, USA.

Funding

University of Washington Biomedical Informatics and Data Science Research Training ProgramT15LM007442 · NLM · UNIVERSITY OF WASHINGTON · PI JOHN H. GENNARI, Andrea L. Hartzler · 2002 to 2026
$19.6M
Cancer Research UK C8640/A23385NCI NIH HHS HHSN261201800004CNLM NIH HHS T15 LM007442
6 · The paper itself

Abstract

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.

Indexed as

ambulatory carediagnosisdiagnostic intervalslung cancernatural language processing

Identifiers

PMID36497238
PMCPMC9740627

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.