Computer experiments for epidemiological studies : theory, methodology and models

Guo, Zebin

doi:10.32657/10356/50491

Cited by 1 publication

(3 citation statements)

References 110 publications

(208 reference statements)

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“…Nevertheless, the authors of this study emphasised that smoking does not have a distinct benefit for vitiligo development 34 . It is worth mentioning that extensive clinical studies have established a strong association between smoking and the incidence and severity of vitiligo 35–37 . The exposure to smoke has been discovered to stimulate the activation of inflammasomes and the accumulation of free radicals in both the circulatory system and local keratinocytes of the skin 38–41 .…”

Section: Discussionmentioning

confidence: 89%

“…34 It is worth mentioning that extensive clinical studies have established a strong association between smoking and the incidence and severity of vitiligo. [35][36][37] The exposure to smoke has been discovered…”

Section: Methodsmentioning

confidence: 99%

“…1.32-100.5)] and with smoking history [RERI = 6.54 (95% CI: 0.67-19.83), AP = 0.64 (95% CI: 0.04-0.80), S = 3.48 (95% CI: 1.17-10. 36)]. Earlier onset age of vitiligo and greater BSA involvement might be two independent risk factors for DM in vitiligo patients.…”

mentioning

confidence: 99%

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Influences of vitiligo‐associated characteristics on the occurrence of diabetes mellitus: Interactive analysis of a cross‐sectional study

Zhu

Kang

et al. 2023

Experimental Dermatology

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The risk of diabetes mellitus (DM) in vitiligo patients is higher than that in non‐vitiligo population. Our goal was to explore the influencing factors for DM in vitiligo patients. A matched‐pair design of 107 cases with DM and 428 controls without DM was conducted among vitiligo patients in Xijing hospital from January 2010 to October 2021. The baseline characteristics of patients were analysed based on standard descriptive statistics. The vitiligo‐associated characteristics were analysed by logistic regression to identify influencing factors of DM. Interaction analysis was performed to explore the additive interactions between vitiligo‐associated characteristics and baseline characteristics. After adjustment for the baseline characteristics, the severity of vitiligo [odds ratio (OR) = 2.47, 95% confidence interval (CI): 1.47–4.14] and onset age of vitiligo (OR = 0.98, 95% CI: 0.97–0.99) had a significant correlation with occurrence of DM. The severity of vitiligo had additive interaction with family history of diabetes [relative excess risk due to interaction (RERI) = 132.51 (95% CI: 5.51–1100.20), attributable proportion (AP) = 0.91 (95% CI: 0.17–0.95), synergy index (S) = 11.53 (95% CI: 1.32–100.5)] and with smoking history [RERI = 6.54 (95% CI: 0.67–19.83), AP = 0.64 (95% CI: 0.04–0.80), S = 3.48 (95% CI: 1.17–10.36)]. Earlier onset age of vitiligo and greater BSA involvement might be two independent risk factors for DM in vitiligo patients. Interaction assessment identified the severity of vitiligo as additive interaction factors with diabetes family history and with smoking history for the DM occurrence.

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Section: Discussionmentioning

confidence: 89%

Section: Methodsmentioning

confidence: 99%