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DOI 10.1136/bmjopen-2017-017392

Медицинская библиотека · BMJ open · 2018

Comparative efficacy and acceptability of antiepileptic drugs for classical trigeminal neuralgia: a Bayesian network meta-analysis protocol.

Qin Zongshi, Xie Shang, Mao Zhi, Liu Yan, Wu Jiani, Furukawa Toshi A, Kwong Joey S W, Tian Jinhui, Liu Zhishun

СтатьяПеревод пока не подготовлен

Аннотация

INTRODUCTION

Trigeminal neuralgia (TN) affects 4 to 28.9/100 000 people worldwide, and antiepileptic drugs such as carbamazepine and oxcarbazepine are the firstline treatment options. However, the efficacy and safety of other antiepileptic drugs remain unclear due to insufficient direct comparisons.

OBJECTIVE

To compare the efficacy and acceptability of all currently available antiepileptic agents for the treatment of patients with classical TN.

METHODS

We will search the PubMed, EMBASE, Cochrane Library and Web of Science databases for unpublished or undergoing research listed in registry platforms. We will include all randomised controlled trials comparing two different antiepileptic drugs or one antiepileptic drug with placebo in patients with classical TN. The primary outcomes will be the proportion of responders and the number of subjects who dropout during the treatment. The secondary outcomes will include the two primary outcomes but in the follow-up period, changes in the self-reporting assessment scale for neuralgia and quality of life assessment. In terms of network meta-analysis, we will fit our model to a Bayesian framework using the JAGS and pcnetmeta packages of the R project.

ETHICS AND DISSEMINATION: This protocol will not disseminate any private patient data. The results of this review will be disseminated through peer reviewed publication.

PROSPERO REGISTRATION NUMBER: CRD42016048640.

Для цитирования: Qin Zongshi, Xie Shang, Mao Zhi, Liu Yan, Wu Jiani, Furukawa Toshi A, Kwong Joey S W, Tian Jinhui, Liu Zhishun. Comparative efficacy and acceptability of antiepileptic drugs for classical trigeminal neuralgia: a Bayesian network meta-analysis protocol.. BMJ open. 2018. DOI: 10.1136/bmjopen-2017-017392.

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