Evidence map›Paper›PMID 38212272›Full record

ArticleCancer prevention research (Philadelphia, Pa.)2024

Acceptability of Personalized Lung Cancer Screening Program Among Primary Care Providers.

Paul J Resong, Jiangong Niu, Gabrielle F Duhon, Lewis E Foxhall, Sanjay Shete, Robert J Volk, Iakovos Toumazis

Open access · greenAbstract read
In one paragraph

Article in Cancer prevention research (Philadelphia, Pa.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 29% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.

  1. Pooled it
  2. Updates in Lung Cancer Screening: A Decade of Evidence.Seminars in respiratory and critical care medicine · 2025
    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

7 authors at 2 institutions in 1 country.

Paul J ResongDepartment of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0001-7256-986X
Jiangong NiuDepartment of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0001-5643-5490
Gabrielle F DuhonDepartment of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0009-0007-4380-7356
Lewis E FoxhallDepartment of Clinical Cancer Prevention, Division of OVP, Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-8646-0192
Sanjay SheteDepartment of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0001-7622-376X
Robert J VolkDepartment of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0001-8811-5854
Iakovos ToumazisDepartment of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas.ORCID 0000-0002-3462-2137
The University of Texas MD Anderson Cancer Center · USUniversity of Nevada, Reno · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
Optimizing Personalized Screening and Diagnostic Decisions for Lung Cancer Based on Dynamic Risk Assessment and Life ExpectancyR37CA271187 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Iakovos Toumazis · 2022 to 2026
$2.8M
NCI NIH HHS P30 CA016672NCI NIH HHS R37 CA271187
6 · The paper itself

Abstract

Current lung cancer screening (LCS) guidelines rely on age and smoking history. Despite its benefit, only 5%-15% of eligible patients receive LCS. Personalized screening strategies select individuals based on their lung cancer risk and may increase LCS's effectiveness. We assess current LCS practices and the acceptability of personalized LCS among primary care providers (PCP) in Texas. We surveyed 32,983 Texas-based PCPs on an existing network (Protocol 2019-1257; PI: Dr. Shete) and 300 attendees of the 2022 Texas Academy of Family Physicians (TAFP) conference. We analyzed the responses by subgroups of interest. Using nonparametric bootstrap, we derived an enriched dataset to develop logistic regression models to understand current LCS practices and acceptability of personalized LCS. Response rates were 0.3% (n = 91) and 15% (n = 60) for the 2019-1257 and TAFP surveys, respectively. Most (84%) respondents regularly assess LCS in their practice. Half of the respondents were interested in adopting personalized LCS. The majority (66%) of respondents expressed concerns regarding time availability with the personalized LCS. Most respondents would use biomarkers as an adjunct to assess eligibility (58%), or to help guide indeterminate clinical findings (63%). There is a need to enhance the engagement of Texas-based PCPs in LCS. Most of the respondents expressed interest in personalized LCS. Time availability was the main concern related to personalized LCS. Findings from this project highlight the need for better education of Texas-based PCPs on the benefits of LCS, and the development of efficient decision tools to ensure successful implementation of personalized LCS. PREVENTION RELEVANCE: Personalized LCS facilitated by a risk model and/or a biomarker test is proposed as an alternative to existing programs. Acceptability of personalized approach among PCPs is unknown. The goal of this study is to assess the acceptability of personalized LCS among PCPs.

Indexed as

Lung NeoplasmsEarly Detection of CancerHumansMass ScreeningPrimary Health CareTexasTomography, X-Ray Computed

Identifiers

PMID38212272
PMCPMC10926168
OpenAlexW4390766461

What OpenQuestion holds

Textmetadata
LicenceTDM
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.