Evidence map›Paper›PMID 31095418›Full record

ArticleJCO clinical cancer informatics2019

Identifying Smoking Status and Smoking Cessation Using a Data Linkage Between the Kentucky Cancer Registry and Health Claims Data.

Michael Shayne Gallaway, Bin Huang, Quan Chen, Tom Tucker, Jaclyn McDowell, Eric Durbin, David Siegel, Eric Tai

Abstract read
In one paragraph

Article in JCO clinical cancer informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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  7. Development and Demonstration of Tobacco Treatment Measures for Cancer Registries: Novel Metrics for Quality Improvement.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023
    Article
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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

8 authors.

Michael Shayne GallawayCenters for Disease Control and Prevention, Atlanta, GA.
Bin HuangUniversity of Kentucky, Lexington, KY.
Quan ChenUniversity of Kentucky, Lexington, KY.
Tom TuckerUniversity of Kentucky, Lexington, KY.
Jaclyn McDowellUniversity of Kentucky, Lexington, KY.
Eric DurbinUniversity of Kentucky, Lexington, KY.
David SiegelCenters for Disease Control and Prevention, Atlanta, GA.
Eric TaiCenters for Disease Control and Prevention, Atlanta, GA.

Funding

University of Kentucky Markey Cancer Center Support Grant ECIA SupplementP30CA177558 · NCI · UNIVERSITY OF KENTUCKY · PI Bernard Mark Evers · 2013 to 2026
$38.3M
Intramural CDC HHS CC999999NCI NIH HHS P30 CA177558
6 · The paper itself

Abstract

purposeLinkage of cancer registry data with complementary data sources can be an informative way to expand what is known about patients and their treatment and improve delivery of care. The purpose of this study was to explore whether patient smoking status and smoking-cessation modalities data in the Kentucky Cancer Registry (KCR) could be augmented by linkage with health claims data.

methodsThe KCR conducted a data linkage with health claims data from Medicare, Medicaid, state employee insurance, Humana, and Anthem. Smoking status was defined as documentation of personal history of tobacco use (International Classification of Diseases, Ninth Revision [ICD-9] code V15.82) or tobacco use disorder (ICD-9 305.1) before and after a cancer diagnosis. Use of smoking-cessation treatments before and after the cancer diagnosis was defined as documentation of smoking-cessation counseling (Healthcare Common Procedure Coding System codes 99406, 99407, G0375, and G0376) or pharmacotherapy (eg, nicotine replacement therapy, bupropion, varenicline).

resultsFrom 2007 to 2011, among 23,703 patients in the KCR, we discerned a valid prediagnosis smoking status for 78%. KCR data only (72%), claims data only (6%), and a combination of both data sources (22%) were used to determine valid smoking status. Approximately 4% of patients with cancer identified as smokers (n = 11,968) and were provided smoking-cessation counseling, and 3% were prescribed pharmacotherapy for smoking cessation.

conclusionAugmenting KCR data with medical claims data increased capture of smoking status and use of smoking-cessation modalities. Cancer registries interested in exploring smoking status to influence treatment and research activities could consider a similar approach, particularly if their registry does not capture smoking status for a majority of patients.

Indexed as

Insurance Claim ReportingSmokingSmoking CessationAdultAgedAged, 80 and overFemaleHumansKentuckyMaleMedicareMiddle AgedNeoplasmsPrevalenceRegistriesSEER Program

Identifiers

PMID31095418
PMCPMC6549228

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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.