Evidence map›Paper›PMID 41183085›Full record

ArticleJournal of the National Cancer Institute2026

Personalizing lung cancer screening recommendations for heterogeneous populations: a microsimulation study.

Joshua B Rager, Pianpian Cao, Rodney A Hayward, Rafael Meza, Hormuzd A Katki, Jeremy B Sussman, Tanner J Caverly

Abstract read
In one paragraph

Article in Journal of the National Cancer Institute, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Joshua B RagerDivision of General Internal Medicine and Geriatrics, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States.ORCID 0000-0001-9557-5672
Pianpian CaoDepartment of Public Health, College of Health and Human Sciences, Purdue University, West Lafayette, IN, United States.ORCID 0000-0001-8886-9672
Rodney A HaywardCenter for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, United States.ORCID 0000-0003-0683-7250
Rafael MezaBC Cancer Research Institute, Vancouver, British Columbia, Canada.ORCID 0000-0002-1076-5037
Hormuzd A KatkiDivision of Cancer Epidemiology and Genetics, US Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda, MD, United States.ORCID 0000-0003-2002-0095
Jeremy B SussmanCenter for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, United States.ORCID 0000-0002-2158-3618
Tanner J CaverlyCenter for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, United States.ORCID 0000-0002-6560-0547

Funding

Department of Veterans Affairs Health Systems Research VA HSR IIR 21-152HSRD VA I01 HX003505
6 · The paper itself

Abstract

backgroundThere is little guidance on how to personalize recommendations for lung cancer screening that accounts for the variation in expected net benefit from screening. We sought to explore the individual and population implications of identifying net benefit thresholds where lung cancer screening could be encouraged, discouraged, or offered as an option through neutral shared decision making due to screening being highly preference sensitive.

methodsWith a simulated US population of 40- to 80-year-old individuals who had ever smoked, we used microsimulation to estimate individualized quality-adjusted life-years saved with lung cancer screening. We then identified 2 net benefit thresholds for lung cancer screening that account for a range of patient preferences and scientific uncertainties and compared this approach with the current United States Preventive Services Task Force (USPSTF) guidelines.

resultsOur simulated population included 59 million people. In total, 15 million were USPSTF eligible; of those, 53% (8 million) maintained net benefit, even after accounting for unfavorable preferences about screening. Of the USPSTF population, 3% (450 000) are considered low net benefit (routinely discourage) and 47% (7 million) are in an intermediate gray area, where net benefit depends on patient preferences about lung cancer screening (offer-neutral shared decision making). Among adults who had ever smoked, 2.5 million are high net benefit but excluded by current USPSTF criteria; 20.5 million US adults who had ever smoked are intermediate net benefit but currently excluded by USPSTF criteria.

conclusionsWe estimate that half of the USPSTF lung cancer screening-eligible population is in a high-net-benefit group where lung cancer screening could be routinely encouraged. Current lung cancer screening eligibility criteria likely exclude many ever-smokers who are high net benefit and many more with intermediate net benefit.

Indexed as

Early Detection of CancerLung NeoplasmsPrecision MedicineAdultAgedAged, 80 and overComputer SimulationDecision Making, SharedFemaleHumansMaleMass ScreeningMiddle AgedPatient PreferencePractice Guidelines as TopicQuality-Adjusted Life Years

Identifiers

PMID41183085
PMCPMC13396146

What OpenQuestion holds

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Registered trials

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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.