Dataset Information

Increased risk of diabetes in cancer survivors: a pooled analysis of 13 population-based cohort studies.

ABSTRACT:

Background

Diabetes is considered as an established risk factor for cancer development. However, the link between diabetes among cancer survivors remains inconclusive. The hypothesis of this study was to assess the hazard ratio (HR) of incidence of diabetes in cancer survivors compared with the HR in the general population.

Patients and methods

A comprehensive literature search was performed in PubMed, Embase, and the Cochrane Library from database inception to 15 December 2020 for population-based cohort studies. Summary effect estimates were combined using random-effects models. We also performed subgroup analyses to test sources of heterogeneity and the stability of the results stratified by various study and participant characteristics.

Results

Thirteen population-based cohort studies involving 1 686 595 participants were analyzed. The HR for the development of diabetes in cancer survivors was 1.39 [95% confidence interval (CI) 1.29-1.50; I² = 82.3%; P < 0.001] compared with that in noncancer controls, among which survivors of hematological, gynecologic, breast, colorectal and urinary tract cancer (all P < 0.05) showed consistent significant results, whereas no significant increased risk was observed for other cancer types. The effects were more prominent in populations of shorter cancer survival duration (<1 year) (HR 2.09, 95% CI 1.32-3.32; P = 0.009). Moreover, cancer survivors with a longer follow-up period (>10 years) had a relatively higher risk of diabetes (HR 1.54, 95% CI 1.34-1.77) than those with a shorter follow-up period.

Conclusions

In this large pooled analysis of population-based cohorts, evidence supports the hypothesis that the risk of developing diabetes is increased in cancer survivors compared with the general population. We should interpret the results with caution for considerable interstudy heterogeneity. However, health policy makers should take this as a challenge for the early prevention and effective intervention of diabetes.

SUBMITTER: Xiao Y

PROVIDER: S-EPMC8327494 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionCancer and cardiovascular disease remain leading causes of death and disability worldwide, which places a heavy burden on public health systems and causes widespread suffering. Because these entities have highly overlapping risk factors, including hyperlipidemia, hypertension, diabetes, obesity, smoking and other lifestyle factors, many studies have reported that they have similar etiological mechanisms. Accumulating evidence indicates that there is an increased risk of cardiovascular disease among cancer survivors compared with the general population. However, whether cancer is associated with an increased risk of cardiovascular disease remains controversial.Methods and analysisWe will conduct and report the meta-analysis strictly based on the Cochrane Handbook for Systematic Reviews and the Meta-analysis of Observational Studies in Epidemiology guidelines combined with the Preferred Reporting Items for Systematic Reviews and Meta-analysis for Protocols (PRISM-P). This meta-analysis was registered with PROSPERO (registration number CRD42022307056). We will search for studies published from database inception to December 1, 2021, regardless of language or date, in three electronic databases (PubMed, EMBASE, and Cochrane Library) to identify and appraise cohort studies examining the relationship between cancer and subsequent cardiovascular disease risk. The literature screening, inclusion and data extraction will be conducted independently by two investigators using pre-designed standardized data extraction forms. A senior investigator will be consulted in cases of disagreement. We will assess risk of bias in the included cohort studies using the Newcastle-Ottawa Scale (NOS). Quantitative synthesis will be conducted using a random-effects model. To explore potential sources of heterogeneity, we will carry out multiple sensitivity analysis, meta-regression and subgroup analysis according to baseline characteristics. Publication bias will be evaluated through visual inspection of funnel plot asymmetry as well as by Begg's rank correlation test and Egger's weighted linear regression test.

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