Objective. The drug efficacy may differ among different statins, and evidence from head-to-head comparisons is sparse and inconsistent. The study is aimed at comparing the lipid-lowering/increasing effects of 7 different statins in patients with dyslipidemia, cardiovascular diseases, or diabetes mellitus by conducting systematic review and network meta-analyses (NMA) of the lipid changes after certain statins’ use. Methods. In this study, we searched four electronic databases for randomized controlled trials (RCTs) published through February 25, 2020, comparing the lipid-lowering efficacy of no less than two of the included statins (or statin vs. placebo). Three reviewers independently extracted data in duplicate. Firstly, mixed treatment overall comparison analyses, in the form of frequentist NMAs, were conducted using STATA 15.0 software. Then, subgroup analyses were conducted according to different baseline diseases. At last, sensitivity analyses were conducted according to age and follow-up duration. The trial was registered with PROSPERO (number CRD42018108799). Results. As a result, seven statin monotherapy treatments in 50 studies (51956 participants) were used for the analyses. The statins included simvastatin (SIM), fluvastatin (FLU), atorvastatin (ATO), rosuvastatin (ROS), lovastatin (LOV), pravastatin (PRA), and pitavastatin (PIT). In terms of LDL-C lowering, rosuvastatin ranked 1st with a surface under cumulated ranking (SUCRA) value of 93.1%. The comparative treatment efficacy for LDL-C lowering was ROS>ATO>PIT>SIM>PRA>FLU>LOV>PLA. All of the other ranking and NMA results were reported in SUCRA plots and league tables. Conclusions. According to the NMAs, it can be concluded that rosuvastatin ranked 1st in LDL-C, ApoB-lowering efficacy and ApoA1-increasing efficacy. Lovastatin ranked 1st in TC- and TG-lowering efficacy, and fluvastatin ranked 1st in HDL-C-increasing efficacy. The results should be interpreted with caution due to some limitations in our review. However, they can provide references and evidence-based foundation for drug selection in both statin monotherapies and statin combination therapies.

Our result supported the hypothesis that DRD2 affected risperidone treatment. DRD1 had no significant effect on the response to risperidone, whereas DRD3 might be associated with an improvement in negative symptoms. Larger observational studies are warranted to verify these findings and identify other genetic factors involved.

Background: Pharmacogenetics study was added into 2 bioequivalence trials of aripiprazole. The correlation between CYP2D6 polymorphisms and aripiprazole pharmacokinetics (PK) was analyzed. Materials & methods: A total of 140 subjects were included. A total of 26 CYP2D6 gene alleles were detected. The plasma concentration of aripiprazole was measured by liquid chromatography-tandem mass spectrometry (LC–MS/MS). SPSS Statistics 21 was used to analyze the correlation between CYP2D6 polymorphisms and aripiprazole PK parameters. Results: All of the four PK parameters were significantly influenced by CYP2D6 rs1058164 and rs28371699. t1/2 and area under the concentration-time curve (AUC0–∞) exhibited significant difference between CYP2D6 extensive metabolizers and intermediate metabolizers. Conclusion: Aripiprazole PK was greatly influenced by CYP2D6. Attention should be paid to the possible dose adjustment for CYP2D6 intermediate metabolizer population when the drug is used in Chinese patients.

What is known and objective Dopamine D2 receptor (DRD2) polymorphisms are inconsistently associated with elevated prolactin levels related to risperidone treatment. The aim of this systematic review and meta‐analysis was to investigate whether DRD2 polymorphisms could modulate prolactin levels in patients treated with risperidone. Methods Three electronic databases (PubMed, EMBASE and the Cochrane Library) were searched for studies investigating the effect of DRD2 polymorphisms on prolactin levels in patients treated with risperidone until May 2018. Summary standard mean differences (SMDs) and 95% confidence intervals (CIs) were calculated with Hedges' g tests for effect estimates using random effects models. The heterogeneity, sensitivity, univariable meta‐regression, subgroup analyses and publication biases were calculated. Results and discussion After initially identifying 886 studies, 772 patients from eight studies were included. Summary SMDs indicated that compared with A1 non‐carriers, Taq1A A1 carriers did not have different risperidone‐related prolactin levels (SMD: 0.13; 95% CI: −0.18 to 0.43; P = 0.423) among patients with schizophrenia (SCZ; SMD: 0.07; 95% CI: −0.14 to 0.29; P = 0.505) or among those without SCZ (SMD: 0.16; 95% CI: −0.39 to 0.71; P = 0.562). There was no significant difference between Del carriers and Del non‐carriers with regard to risperidone‐related prolactin levels (SMD: −0.00; 95% CI: −0.59 to 0.58; P = 0.996). In an Asian subgroup analysis, we also noted that compared with Taq1A A1A2 carriers, Taq1A A1A1 carriers had lower prolactin levels (SMD: −0.34; 95% CI: −0.66 to −0.02; P = 0.040). However, there was no significant difference in prolactin levels between A1A1 carriers and A2A2 carriers (SMD: −0.27; 95% CI: −0.60 to 0.05; P = 0.098), or between A2 carriers and A2 non‐carriers (SMD: 0.29; 95% CI: −0.01 to 0.59; P = 0.059). Based on univariable meta‐regression analyses, the effects of publication year, study design, ethnicity, comparison groups and study quality could bias the identified association of DRD2 Taq1A with risperidone‐related prolactin levels. What is new and conclusion The findings of this study suggest that there is no significant difference between Taq1A A1 carriers and non‐A1 carriers with regard to risperidone‐related prolactin levels. As there were few A1 homozygotes, large prospective studies with robust designs are still needed to investigate whether A1A1 could affect risperidone‐related prolactin levels in the Asian population.