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DOI 10.1038/s41397-019-0142-9

Медицинская библиотека · The pharmacogenomics journal · 2020

The effect of CYP2D6 variation on antipsychotic-induced hyperprolactinaemia: a systematic review and meta-analysis.

Calafato Maria Stella, Austin-Zimmerman Isabelle, Thygesen Johan H, Sairam Mani, Metastasio Antonio, Marston Louise, Abad-Santos Francisco, Bhat Anjali, Harju-Seppänen Jasmine, Irizar Haritz, Zartaloudi Eirini, Bramon Elvira

СтатьяМетаанализПоддержка исследования: вне правительства СШАСистематический обзорПеревод в очереди

Аннотация

Hyperprolactinemia is a known adverse drug reaction to antipsychotic treatment. Antipsychotic blood levels are influenced by cytochrome P450 enzymes, primarily CYP2D6. Variation in CYP450 genes may affect the risk of antipsychotic-induced hyperprolactinemia. We undertook a systematic review and meta-analysis to assess whether CYP2D6 functional genetic variants are associated with antipsychotic-induced hyperprolactinemia. The systematic review identified 16 relevant papers, seven of which were suitable for the meta-analysis (n = 303 participants including 134 extreme metabolisers). Participants were classified into four phenotype groups as poor, intermediate, extensive, and ultra-rapid metabolisers. A random effects meta-analysis was used and Cohen's d calculated as the effect size for each primary study. We found no significant differences in prolactin levels between CYP2D6 metabolic groups. Current evidence does not support using CYP2D6 genotyping to reduce risk of antipsychotic-induced hyperprolactinemia. However, statistical power is limited. Future studies with larger samples and including a range of prolactin-elevating drugs are needed.

Для цитирования: Calafato Maria Stella, Austin-Zimmerman Isabelle, Thygesen Johan H, Sairam Mani, Metastasio Antonio, Marston Louise, Abad-Santos Francisco, Bhat Anjali, Harju-Seppänen Jasmine, Irizar Haritz, Zartaloudi Eirini, Bramon Elvira. The effect of CYP2D6 variation on antipsychotic-induced hyperprolactinaemia: a systematic review and meta-analysis.. The pharmacogenomics journal. 2020. DOI: 10.1038/s41397-019-0142-9.

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