Evidence map›Paper›PMID 24881126›Full record

ReviewCanadian journal of psychiatry. Revue canadienne de psychiatrie2014

Pharmacogenetics of antipsychotics.

Eva J Brandl, James L Kennedy, Daniel J Müller

Abstract readReview
In one paragraph

Review in Canadian journal of psychiatry. Revue canadienne de psychiatrie, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Eva J Brandl
James L Kennedy
Daniel J Müller

Funding

Canadian Institutes of Health Research
6 · The paper itself

Abstract

objectiveDuring the past decades, increasing efforts have been invested in studies to unravel the influence of genetic factors on antipsychotic (AP) dosage, treatment response, and occurrence of adverse effects. These studies aimed to improve clinical care by predicting outcome of treatment with APs and thus allowing for individualized treatment strategies. We highlight most important findings obtained through both candidate gene and genome-wide association studies, including pharmacokinetic and pharmacodynamic factors.

methodsWe reviewed studies on pharmacogenetics of AP response and adverse effects published on PubMed until early 2012. Owing to the high number of published studies, we focused our review on findings that have been replicated in independent studies or are supported by meta-analyses.

resultsMost robust findings were reported for associations between polymorphisms of the cytochrome P450 system, the dopamine and the serotonin transmitter systems, and dosage, treatment response, and adverse effects, such as AP-induced weight gain or tardive dyskinesia. These associations were either detected for specific medications or for classes of APs.

conclusionFirst promising and robust results show that pharmacogenetics bear promise for a widespread use in future clinical practice. This will likely be achieved by developing algorithms that will include many genetic variants. However, further investigation is warranted to replicate and validate previous findings, as well as to identify new genetic variants involved in AP response and for replication of existing findings.

Indexed as

PharmacogeneticsPrecision MedicineAntipsychotic AgentsBrainCytochrome P-450 Enzyme SystemDopamineDose-Response Relationship, DrugGenetic MarkersHumansPolymorphism, GeneticPsychotic DisordersSerotoninTreatment OutcomeAntipsychotic AgentsCytochrome P-450 Enzyme SystemDopamineGenetic MarkersSerotonin

Identifiers

PMID24881126
PMCPMC4079237

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.