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. 2021 Mar 31:12:564097.
doi: 10.3389/fphar.2021.564097. eCollection 2021.

Association Between Digoxin Use and Cancer Incidence: A Propensity Score-Matched Cohort Study With Competing Risk Analysis

Chi-Jung Tai  1   2 , Yi-Hsin Yang  3   4 , Tzyy-Guey Tseng  5 , Fang-Rong Chang  1   6   7   8 , Hui-Chun Wang  1   6   7   8
Affiliations

Association Between Digoxin Use and Cancer Incidence: A Propensity Score-Matched Cohort Study With Competing Risk Analysis

Chi-Jung Tai et al. Front Pharmacol. .

Abstract

Background: Previous studies neglected death as a critical competing risk while estimating the cancer risk for digoxin users. Therefore, the current study aims to assess the effectiveness of digoxin on cancer prevention by competing risk analysis. Methods: We performed a population-based retrospective cohort study using the Taiwan National Health Insurance Research database between 1998 and 2010. After one-to-one propensity score-matching from 36,160 patients with defined criteria, we enrolled 758 patients both in digoxin and β-blocker group for further analysis. Results: The results showed that the digoxin group had higher all-cause mortality than the β-blocker group in the 4- year (10.4 vs. 4.9%) and 8 years (13.6 vs. 7.0%) follow-up. The subdistribution HR of cancer incidence in the digoxin group compared to the β-blocker group was 1.99 (95% confidence interval [CI]: 1.22-3.01) and 1.46 (95% CI: 1.01-2.15) in the 4 years and 8 years follow-up, respectively. Conclusions: The result of our study showed the usage of digoxin has no benefit in cancer prevention compared with β-blocker. The possibility of β-blocker as a new drug candidate for cancer prevention needs further clinical evaluation. The current study also emphasized the necessity of competing risk analysis applying to similar clinical researches.

Keywords: cancer; competing risk analysis; digoxin; propensity-score matching; β-blocker.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Study flow chart. Nhird, national health insurance research database.
FIGURE 2
FIGURE 2
Study design.
FIGURE 3
FIGURE 3
Cumulative cancer incidence between the two groups after 1:1 propensity-score matching by competing risk analysis.
See this image and copyright information in PMC

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