Evidence map›Paper›PMID 34738073›Full record

ArticleJNCI cancer spectrum2021

A Cost-Effectiveness Analysis of Lung Cancer Screening With Low-Dose Computed Tomography and a Diagnostic Biomarker.

Iakovos Toumazis, S Ayca Erdogan, Mehrad Bastani, Ann Leung, Sylvia K Plevritis

Open access · goldAbstract read
In one paragraph

Article in JNCI cancer spectrum, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 13% of its field
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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Natural history models for lung Cancer: A scoping review.Lung cancer (Amsterdam, Netherlands) · 2025
    Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Chest CT for Breast Cancer Diagnosis.Life (Basel, Switzerland) · 2022
    Article
  13. Article
  14. Article
  15. Biomarker-Based Lung Cancer Screening Eligibility: Implementation Considerations.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022
    Article
  16. Article
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

5 authors at 1 institution in 1 country.

Iakovos ToumazisDepartments of Biomedical Data Science and Radiology, Stanford University, Stanford, CA, USA.ORCID 0000-0002-3462-2137
S Ayca ErdoganDepartment of Radiology, Stanford University, Stanford, CA, USA.ORCID 0000-0002-1320-3347
Mehrad BastaniDepartments of Biomedical Data Science and Radiology, Stanford University, Stanford, CA, USA.ORCID 0000-0001-9571-9488
Ann LeungDepartment of Radiology, Stanford University, Stanford, CA, USA.
Sylvia K PlevritisDepartments of Biomedical Data Science and Radiology, Stanford University, Stanford, CA, USA.
Stanford University · US

Funding

Role of SDF1a pathway in prostate cancer relapse and metastasis post-radiotherapyR01CA159258 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI DUDA, DAN GABRIEL · 2011 to 2015
$1.6M
NCI NIH HHS R01 CA159258
6 · The paper itself

Abstract

Background: The Lung Computed Tomography Screening Reporting and Data System (Lung-RADS) reduces the false-positive rate of lung cancer screening but introduces prolonged periods of uncertainty for indeterminate findings. We assess the cost-effectiveness of a screening program that assesses indeterminate findings earlier via a hypothetical diagnostic biomarker introduced in place of Lung-RADS 3 and 4A guidelines. Methods: We evaluated the performance of the US Preventive Services Task Force (USPSTF) recommendations on lung cancer screening with and without a hypothetical noninvasive diagnostic biomarker using a validated microsimulation model. The diagnostic biomarker assesses the malignancy of indeterminate nodules, replacing Lung-RADS 3 and 4A guidelines, and is characterized by a varying sensitivity profile that depends on nodules' size, specificity, and cost. We tested the robustness of our findings through univariate sensitivity analyses. Results: A lung cancer screening program per the USPSTF guidelines that incorporates a diagnostic biomarker with at least medium sensitivity profile and 90% specificity, that costs $250 or less, is cost-effective with an incremental cost-effectiveness ratio lower than $100 000 per quality-adjusted life year, and improves lung cancer-specific mortality reduction while requiring fewer screening exams than the USPSTF guidelines with Lung-RADS. A screening program with a biomarker costing $750 or more is not cost-effective. The health benefits accrued and costs associated with the screening program are sensitive to the disutility of indeterminate findings and specificity of the biomarker, respectively. Conclusions: Lung cancer screening that incorporates a diagnostic biomarker, in place of Lung-RADS 3 and 4A guidelines, could improve the cost-effectiveness of the screening program and warrants further investigation.

Indexed as

Advisory CommitteesAnalysis of VarianceBiomarkers, TumorCost-Benefit AnalysisHumansLung NeoplasmsPractice Guidelines as TopicProgram EvaluationQuality-Adjusted Life YearsRadiation DosageSensitivity and SpecificityTomography, X-Ray ComputedUncertaintyUnited StatesBiomarkers, Tumor

Identifiers

PMID34738073
PMCPMC8564700
OpenAlexW3203907959

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.