Evidence map›Paper›PMID 41452617›Full record

Trial reportJAMA oncology2026

Enhancement of Patient-Centered Lung Cancer Screening: The MyLungHealth Randomized Clinical Trial.

Polina V Kukhareva, Haojia Li, Christian Balbin, Elizabeth R Stevens, Devin M Mann, Jorie M Butler, Tanner J Caverly, Guilherme Del Fiol, Kimberly A Kaphingst, Chelsey R Schlechter and 12 more

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in JAMA oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06338592 (The MyLungHealth Study Protocol), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

NCT06338592 nacompletednot on this map

The MyLungHealth Study Protocol: A Pragmatic Patient-Randomized Controlled Trial to Evaluate a Patient-Centered, Electronic Health Record-Integrated Intervention to Enhance Lung Cancer Screening in Primary Care

TypeinterventionalSponsorUniversity of UtahRan2024 to 2026Enrolled31,303ConditionsLung Cancer, Lung Neoplasms/DiagnosisArmsMyLungHealth, DecisionPrecision+
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

22 authors.

Polina V KukharevaDepartment of Biomedical Informatics, University of Utah, Salt Lake City.
Haojia LiStudy Design and Biostatistics Center, University of Utah, Salt Lake City.
Christian BalbinDepartment of Biomedical Informatics, University of Utah, Salt Lake City.
Elizabeth R StevensDepartment of Population Health, NYU Grossman School of Medicine, New York, New York.
Devin M MannDepartment of Population Health, NYU Grossman School of Medicine, New York, New York.
Jorie M ButlerDepartment of Biomedical Informatics, University of Utah, Salt Lake City.
Tanner J CaverlyCenter for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, Michigan.
Guilherme Del FiolDepartment of Biomedical Informatics, University of Utah, Salt Lake City.
Kimberly A KaphingstDepartment of Communication, University of Utah, Salt Lake City.
Chelsey R SchlechterHuntsman Cancer Institute, University of Utah Health, Salt Lake City.
Victoria L TiaseDepartment of Biomedical Informatics, University of Utah, Salt Lake City.
Angela FagerlinDepartment of Population Health Sciences, University of Utah, Salt Lake City.
Yue ZhangStudy Design and Biostatistics Center, University of Utah, Salt Lake City.
Rachel HessDepartment of Population Health Sciences, University of Utah, Salt Lake City.
Michael C FlynnDepartment of Internal Medicine, University of Utah, Salt Lake City.
Chakravarthy ReddyDepartment of Internal Medicine, University of Utah, Salt Lake City.
Douglas MartinDepartment of Biomedical Informatics, University of Utah, Salt Lake City.
Phillip B WarnerDepartment of Biomedical Informatics, University of Utah, Salt Lake City.
Claude NanjoDepartment of Biomedical Informatics, University of Utah, Salt Lake City.
Joshua ChoiDepartment of Biomedical Informatics, University of Utah, Salt Lake City.
Quyen Ngo-MetzgerDepartment of Health Systems Science, Kaiser Permanente School of Medicine, Pasadena, California.
Kensaku KawamotoDepartment of Biomedical Informatics, University of Utah, Salt Lake City.

Funding

UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
AHRQ HHS R18 HS028791NLM NIH HHS T15 LM007124
6 · The paper itself

Abstract

Importance: Lung cancer screening (LCS) with low-dose computed tomography (CT) remains underused in the US, partly because of incomplete smoking history documentation in electronic health records (EHRs) and limited time for shared decision-making in primary care. Objective: To determine whether a patient-facing, EHR-integrated tool combined with clinician-facing clinical decision support improves the identification of LCS-eligible patients and the ordering of low-dose CT compared with clinician-facing tools alone. Design, Setting, and Participants: This pragmatic, unstratified, randomized clinical trial with parallel groups was conducted from March 29, 2024, to March 28, 2025, at primary care clinics at University of Utah Health and New York University Langone Health. Adults aged 50 to 79 years with a documented smoking history, an active patient portal account, and a primary care visit in the preceding year were included. Study 1 enrolled patients with uncertain LCS eligibility (10 to 19 pack-years, unknown pack-years, or missing quit date); study 2 enrolled patients with documented eligibility (20 or more pack-years and currently smoking or quit smoking within 15 years). Interventions: The control included the clinician-facing Decision Precision+ tool (preventive care reminders and a shared decision-making tool). The intervention included the Decision Precision+ tool as well as the MyLungHealth tool, which collected detailed smoking history (study 1) and delivered personalized education and risk/benefit information (studies 1 and 2) via the patient portal in English and Spanish. Main Outcomes and Measures: The primary outcomes were the proportion of patients newly identified as eligible for LCS (study 1) and low-dose CT ordering rates (study 2) over 12 months. Analyses used intention-to-treat mixed-effects logistic regression. Results: There were 31 303 randomized participants, including 26 729 in study 1 (13 144 [49.2%] female; 13 580 [50.8%] male; median [IQR] age, 62 [55-69] years) and 4574 in study 2 (2230 [48.8%] female; 2344 [51.2%] male; median [IQR] age, 63 [56-69] years). In study 1, the MyLungHealth tool increased new LCS eligibility identification (635 of 13 412 [4.7%] vs 308 of 13 317 [2.3%]; adjusted odds ratio, 2.19; 95% CI, 1.99-2.42; P < .001). In study 2, low-dose CT ordering was higher in the intervention arm (474 of 2312 [20.5%] vs 434 of 2262 [19.2%]; adjusted odds ratio, 1.16; 95% CI, 1.04-1.30; P = .008). Conclusions and Relevance: In this randomized clinical trial, integrating a patient-centered tool into primary care EHR workflows increased the identification of patients eligible for LCS and the ordering of low-dose CTs. The relative increases in these primary outcomes were substantial, but absolute increases were more modest. Research on more intensive interventions is warranted to evaluate their ability to further improve LCS screening. Trial Registration: ClinicalTrials.gov Identifier: NCT06338592.

Indexed as

Early Detection of CancerLung NeoplasmsAgedDecision Support Systems, ClinicalElectronic Health RecordsFemaleHumansMaleMiddle AgedPatient-Centered CarePrimary Health CareSmokingTomography, X-Ray Computed

Identifiers

PMID41452617
PMCPMC12743306

What OpenQuestion holds

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Registered trials

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.