Evidence map›Paper›PMID 37426898›Full record

ArticlePharmacogenomics and personalized medicine2023

Genotyping of Patients with Adverse Drug Reaction or Therapy Failure: Database Analysis of a Pharmacogenetics Case Series Study.

Anna Bollinger, Céline K Stäuble, Chiara Jeiziner, Florine M Wiss, Kurt E Hersberger, Markus L Lampert, Henriette E Meyer Zu Schwabedissen, Samuel S Allemann

Open access · goldAbstract read
In one paragraph

Article in Pharmacogenomics and personalized medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 17% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. 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

8 authors at 1 institution in 1 country.

Anna BollingerDepartment of Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0000-0003-4616-2534
Céline K StäubleDepartment of Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0000-0002-2437-4803
Chiara JeizinerDepartment of Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0000-0002-1132-0240
Florine M WissDepartment of Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0009-0001-3618-4679
Kurt E HersbergerDepartment of Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0000-0001-8678-697X
Markus L LampertDepartment of Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0000-0001-7037-2799
Henriette E Meyer Zu SchwabedissenDepartment of Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0000-0003-0458-4579
Samuel S AllemannDepartment of Pharmaceutical Sciences, University of Basel, Basel, Switzerland.ORCID 0000-0003-4067-9401
University of Basel · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Pharmacogenetics (PGx) is an emerging aspect of personalized medicine with the potential to increase efficacy and safety of pharmacotherapy. However, PGx testing is still not routinely integrated into clinical practice. We conducted an observational case series study where PGx information from a commercially available panel test covering 30 genes was integrated into medication reviews. The aim of the study was to identify the drugs that are most frequently object of drug-gene-interactions (DGI) in the study population. Patients and Methods: In out-patient and in-patient settings, we recruited 142 patients experiencing adverse drug reaction (ADR) and/or therapy failure (TF). Collected anonymized data from the individual patient was harmonized and transferred to a structured database. Results: The majority of the patients had a main diagnosis of a mental or behavioral disorder (ICD-10: F, 61%), of musculoskeletal system and connective tissue diseases (ICD-10: M, 21%), and of the circulatory system (ICD-10: I, 11%). The number of prescribed medicines reached a median of 7 per person, resulting in a majority of patients with polypharmacy (≥5 prescribed medicines, 65%). In total, 559 suspected DGI were identified in 142 patients. After genetic testing, an association with at least one genetic variation was confirmed for 324 suspected DGI (58%) caused by 64 different drugs and 21 different genes in 141 patients. After 6 months, PGx-based medication adjustments were recorded for 62% of the study population, whereby differences were identified in subgroups. Conclusion: The data analysis from this study provides valuable insights for the main focus of further research in the context of PGx. The results indicate that most of the selected patients in our sample represent suitable target groups for PGx panel testing in clinical practice, notably those taking drugs for mental or behavioral disorder, circulatory diseases, immunological diseases, pain-related diseases, and patients experiencing polypharmacy.

Indexed as

clinical pharmacyclinical practicemedication reviewpersonalized medicinePGxpharmacogenomics

Identifiers

PMID37426898
PMCPMC10327911
OpenAlexW4382981648

What OpenQuestion holds

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LicenceCC BY-NC
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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.