Evidence map›Paper›PMID 38137466›Full record

ArticleBiomedicines2023

Effect of CYP2C19 Pharmacogenetic Testing on Predicting Citalopram and Escitalopram Tolerability and Efficacy: A Retrospective, Longitudinal Cohort Study.

Mahmood Mahajna, Rami Abu Fanne, Matitiahu Berkovitch, Elias Tannous, Shlomo Vinker, Ilan Green, Ilan Matok

Abstract read
In one paragraph

Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
  4. Article
  5. Review
  6. Observational
  7. Review
  8. Review
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

7 authors.

Mahmood MahajnaDepartment of Clinical Pharmacy, The Hebrew University, Jerusalem 9112002, Israel.
Rami Abu FanneDepartment of Cardiology, Hillel Yaffe Medical Center, Hadera 3200003, Israel.
Matitiahu BerkovitchDepartment of Clinical Pharmacology and Toxicology, Shamir Medical Center Affiliated with Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel.
Elias TannousHillel Yaffe Medical Center, Hadera 3810000, Israel.
Shlomo VinkerLeumit Health Care Services, Tel Aviv 6812509, Israel.
Ilan GreenLeumit Health Care Services, Tel Aviv 6812509, Israel.ORCID 0000-0002-9435-7152
Ilan MatokDepartment of Clinical Pharmacy, The Hebrew University, Jerusalem 9112002, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background-Various antidepressant agents are metabolized by the CYP2C19 enzyme, including Citalopram and Escitalopram. Variation in CYP2C19 expression might give rise to different plasma concentrations of the active metabolites, potentially affecting both drugs' efficacy and tolerability. Aim-The aim of this study was to evaluate differences in the Escitalopram and Citalopram efficacy and tolerability between different CYP2C19 genotype-based metabolizing categories in outpatients suffering from major depressive disorder (MDD). Methods-In a retrospective, longitudinal cohort study of electronic medical-record data, 283 patients with MDD who were prescribed Escitalopram or Citalopram with the available CYP2C19-genotyping test were enrolled. The primary efficacy end point was adverse drug reactions recorded in the medical files. A proportional-odds, multilevel-regression model for longitudinal ordinal data was used to estimate the relation between the CYP2C19 genotype and adverse drug reactions, adjusting for potential confounding variables and other explanatory variables. Latent-class analysis (LCA) was utilized to detect the presence of clinically significant subgroups and their relation to an individual's metabolizing status for CYP2D6/CYP2C19. Results-With poor CYP2C19 metabolizers as a reference, for each unit difference in the activity score of the CYP2C19 phenotype, the odds ratio for drug intolerability was lowered by 0.73 (95% credible intervals: 0.56-0.89), adjusting for significant covariates. In addition, applying LCA, we identified two qualitatively different subgroups: the first group (61.85%) exhibited multiple side effects, low compliance, and frequent treatment changes, whereas the second group (38.15%) demonstrated fewer side effects, good adherence, and fewer treatment changes. The CYP2C19 phenotype was substantially associated with the group membership. Conclusions-We found a positive association between the CYP2C19 activity scores, as inferred from the genotype, and both the efficacy of and tolerability to both Es/Citalopram. LCA enabled valuable insights into the underlying structure of the population; the CYP2C19 phenotype has a predictive value that discriminates between low-adherence, low-drug-tolerance, and low-response patients and high-adherence, high-drug-tolerance, and high-response patients. Personalized medicine based on CYP2C19 genotyping could evolve as a promising new avenue towards mitigating Escitalopram and Citalopram therapy and the associated side effects and enhancing treatment success.

Indexed as

adverse effectsefficacypharmacogeneticphenotypeSSRI

Identifiers

PMID38137466
PMCPMC10740827

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Registered trials

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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.