ArticleFrontiers in endocrinology2022
Dyslipidemia Risk in Thyroid Cancer Patients: A Nationwide Population-Based Cohort Study.
Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- Association Between Graves' Disease and the Risk of Thyroid Carcinoma: The Role of Clinical, Metabolic, Hormonal, Immunological, and Ultrasound Biomarkers.Metabolites · 2026Review
- Mendelian randomization analysis of lipidomic profiles and thyroid cancer risk in European populations.Discover oncology · 2025Article
- Adjusting for Confounders in Outcome Studies Using the Korea National Health Insurance Claim Database: A Review of Methods and Applications.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2024Review
- Big Data Research in the Field of Endocrine Diseases Using the Korean National Health Information Database.Endocrinology and metabolism (Seoul, Korea) · 2023Review
- Relationship between Changes in Blood Glucose and Blood Lipid Levels and the Risk of Thyroid Cancer in Patients with Type 2 Diabetes Mellitus.Disease markers · 2023Article
- Dyslipidemia in diffuse large B-cell lymphoma based on the genetic subtypes: a single-center study of 259 Chinese patients.Frontiers in oncology · 2023Article
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5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Thyroid cancer (TC) prevalence has been rapidly increasing. While the relationship between thyroid hormones and lipids has been widely investigated, studies regarding dyslipidemia in patients with TC have been scarce and controversial. We aimed to investigate dyslipidemia risk after TC diagnosis compared to the general population without TC. Method: A population-based prospective study was conducted using data from the Korean National Health Insurance Service-National Sample Cohort Database 2.0 (NHIS-NSC DB 2.0), with health insurance claim data of 1,108,369 subjects between 2002 and 2015. The final study sample comprised 466,735 adult subjects without TC or dyslipidemia diagnoses before the index year, 2009. Bidirectional analyses were performed using prospective and retrospective concepts. In the prospective analysis, Kaplan-Meier estimates were calculated and log-rank tests and univariable and multivariable Cox regression analyses were performed to determine the relationship between TC and dyslipidemia. The retrospective analysis involved 1:5 nested case-control matching based on dyslipidemia status and conditional logistic regression analysis. Results: No significant difference in dyslipidemia incidence was observed between TC patients and the control group, in either the prospective matched (log-rank P = 0.483) or non-matched (log-rank P = 0.424) analyses, or the retrospective analysis (P = 0.3724). In the prospective analysis, 193 patients after TC diagnosis showed similar risk of developing dyslipidemia with the 466,542 controls during the median 7 years of follow-up (unadjusted hazard ratio [HR], 1.102; 95% confidence interval [CI], 0.878-1.383; adjusted HR, 0.932; 95% CI, 0.707-1.230). Multiple propensity score-adjusted models showed similar results, and 114 patients and 570 matched controls showed an HR of 0.818 (95% CI, 0.598-1.120). In the retrospective comparison of dyslipidemia risk in 170 patients and 277,864 controls, the odds ratio was 0.822 (95% CI, 0.534-1.266). Conclusions: Dyslipidemia risk was not significantly different between patients with TC and the general population, in both prospective and retrospective analyses.
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