Regional Differences in the Safety of Telaprevir-Based Triple Therapy for Chronic Hepatitis C in Japan: / 医薬品情報学
Japanese Journal of Drug Informatics
;
: 57-65, 2018.
Artigo
em Inglês
| WPRIM
| ID: wpr-688353
ABSTRACT
Objective:
The objectives were to assess regional differences in the safety outcomes of telaprevir-based triple therapy(T/PR) in Japan and evaluate a suitable generalized linear mixed model for estimating regional differences.Design andMethods:
This study targeted individuals infected with genotype 1 chronic hepatitis C virus registered in a nationwide Japanese interferon database from December 2009 to August 2015. The rate of dropout from treatmentattributable to adverse events was calculated in every prefecture where ≥ 20 cases were reported. We constructed the following four models and evaluated the best-fit model based on Akaike information criterion (AIC) and Bayesian information criterion (BIC)1)prefecture as a fixed-effect,2)prefecture and identified confounding factors as fixed-effects,3)prefecture as a random-effect,and 4)prefecture as a random-effect and identified confounding factors as fixed-effects.Results:
A total of 25,989 individuals from 38 prefectures were registered during the study period;among them,1,591 from18 prefectures were included as the study population. The dropout rate ranged from 7.0 to 23.1%among 17 prefectures.The model considering prefecture as a random-effect and confounding factors as fixed-effects showed the best-fit for the databased on both the AIC (1,108.06)and BIC (1,113.41).Conclusion:
It is difficult to determine if regional differences exist in the safety outcomes of T/PR in Japan because of the limited number of cases. However, the model using prefecture as a random-effect and other confounding factors as fixed-effects would be suitable for estimating parameters that reflect the influence of the prefecture. Further studies using the model would help inform chronic hepatitis C treatment.
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Índice:
WPRIM (Pacífico Ocidental)
Tipo de estudo:
Estudo prognóstico
Idioma:
Inglês
Revista:
Japanese Journal of Drug Informatics
Ano de publicação:
2018
Tipo de documento:
Artigo
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