Abstract
INTRODUCTION: Sexual dysfunctions are a challenging side effect associated with antipsychotic treatment. This protocol outlines a systematic review and meta-analysis to assess the prevalence of overall sexual dysfunction, as well as the specific phases of sexual function affected by antipsychotic medications. Additionally, the analysis will explore the relationship between prolactin levels and sexual dysfunction. METHODS AND ANALYSIS: This protocol has been registered in the database of the International prospective register of systematic reviews (PROSPERO) under the registration number CRD42024573877. We will conduct a systematic search across electronic databases, including PubMed, MEDLINE, PsycINFO, Web of Science, the Cochrane Central Register of Controlled Trials (CENTRAL), Embase, and CINAHL, to identify relevant studies. Studies will be included if they meet predefined inclusion criteria, which include only controlled randomized trials assessing sexual functioning in patients receiving antipsychotic treatment. The antipsychotic medications of interest are amisulpride, aripiprazole, asenapine, brexpiprazole, cariprazine, chlorpromazine, clopenthixol, clozapine, droperidol, flupenthixol, fluphenazine, haloperidol, iloperidone, levomepromazine, loxapine, lurasidone, molindone, olanzapine, paliperidone, penfluridol, perphenazine, perazine, pimozide, prochlorperazine, quetiapine, risperidone, sertindole, sulpiride, thiothixene, thioridazine, trifluoperazine, ziprasidone, zuclopenthixol and zotepine. The primary outcome is the overall prevalence of sexual dysfunction among patients undergoing antipsychotic treatment, while the secondary outcomes include the domains of sexual dysfunction (e.g., desire, arousal, orgasm) and serum prolactin levels. A network meta-analysis (NMA) will be performed using random effects to combine all available evidence for each outcome, aimed to provide a comprehensive ranking of different antipsychotics. NMA will be performed in R within a frequentist paradigm. The Cochrane Risk of Bias tool and RoB 2.0 will be used to assess the risk of bias in studies. We will evaluate the quality of the evidence contributing to network estimates for the primary outcomes using the GRADE framework, and key factors that may affect the observed effects will be analysed for consistency across studies.