Evidence map›Paper›PMID 41414825›Full record

ArticleEpidemiology and health2025

Cohort profile: the KDCA-Tuberculosis-NHIS cohort linking tuberculosis surveillance and health insurance data in Korea.

Dawoon Jeong, Jinsun Kim, Seung Won Lee, Hongjo Choi, Hojoon Sohn, Jieun Kim, Hyewon Lee, Hyeran Jeong, Seung Eun Lee, Young-Joon Park and 5 more

Abstract read
In one paragraph

Article in Epidemiology and health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

15 authors.

Dawoon JeongDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
Jinsun KimDivision of Tuberculosis Policy, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.
Seung Won LeeInstitute for Immunology and Immunological Disease, Yonsei University College of Medicine, Seoul, Korea.
Hongjo ChoiDivision of Health Policy and Management, Korea University College of Health Science, Seoul, Korea.
Hojoon SohnDepartment of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea.
Jieun KimDivision of Tuberculosis Policy, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.
Hyewon LeeDivision of Tuberculosis Policy, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.
Hyeran JeongDivision of Tuberculosis Policy, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.
Seung Eun LeeDivision of Tuberculosis Policy, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.
Young-Joon ParkDivision of Tuberculosis Policy, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.
Jaiyong KimDepartment of Big Data Research and Development, National Health Insurance Service, Wonju, Korea.
Eun Mi KimDepartment of Big Data Research and Development, National Health Insurance Service, Wonju, Korea.
Minji KooDepartment of Big Data Research and Development, National Health Insurance Service, Wonju, Korea.
Hoyeon JangDepartment of Big Data Research and Development, National Health Insurance Service, Wonju, Korea.
Young Ae KangInstitute for Immunology and Immunological Disease, Yonsei University College of Medicine, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite a steady decline in incidence, tuberculosis (TB) remains a substantial public health burden in Korea, particularly among older adults. Existing national TB surveillance systems lack sufficiently comprehensive data to assess long-term outcomes and health disparities. The K-TB-N cohort integrates data from 3 national sources: the Korean Tuberculosis Surveillance System (2011-2022), the National Health Insurance Database (2010-2022), and mortality data from Statistics Korea (2010-2022). After data cleaning and linkage, the final cohort included 373,812 patients (375,440 episodes) with either drug-susceptible TB or drug- resistant TB. TB notifications declined by approximately 60% over the study period, while the median patient age continued to rise. Treatment success improved over time, accompanied by reductions in lost to follow-up. However, mortality during treatment increased, with more than half of deaths attributed to non-TB causes such as pneumonia, cancer, and cardiovascular disease. Post-treatment mortality also remained high, particularly among patients with drug-resistant TB. The K-TB-N cohort provides a comprehensive, linked dataset for advancing research on TB epidemiology, treatment outcomes, comorbidities, and health disparities. It enables evaluations of public health interventions, long-term prognosis, and strategies for post-TB care. This cohort will remain a valuable resource for shaping data-driven TB control policies in aging and high-burden settings.

Indexed as

National Health ProgramsPopulation SurveillanceTuberculosisAdolescentAdultAgedAged, 80 and overChildCohort StudiesDatabases, FactualFemaleHumansIncidenceMaleMiddle AgedRepublic of KoreaK-TB-N cohortLinkageTuberculosis

Identifiers

PMID41414825
PMCPMC12884042

What OpenQuestion holds

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LicenceCC BY
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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.