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Record W7084203846

A Swiss Cross-Sectional Study on Patients’ Perspectives on Chronic Pain Management, Analgesic Treatment, and Genetic Susceptibility

2025· article· en· W7084203846 on OpenAlexaff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsMicropharma (Canada)
Fundersnot available
KeywordsPharmacogeneticsAnalgesicChronic painPerspective (graphical)PharmacotherapyPharmacogenomicsRelevance (law)Genetic predispositionDrug
DOInot available

Abstract

fetched live from OpenAlex

Anna Bollinger,1 Céline K Stäuble,1,2 Isabelle O Urdieux,1 Henriette E Meyer zu Schwabedissen,1 Samuel S Allemann1 1Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland; 2Institute of Hospital Pharmacy, Stadtspital Zürich, Zürich, SwitzerlandCorrespondence: Anna Bollinger, Department of Pharmaceutical Sciences, University of Basel, Basel, Switzerland, Tel +41612076631, Email a.bollinger@unibas.chBackground: Chronic pain is a prevalent and complex condition that often results in inadequate pharmacotherapy due to interindividual variability in drug response. Pharmacogenetics (PGx) offers a promising approach to personalize pain management, particularly since many analgesic drugs are PGx actionable. However, knowledge about the clinical relevance and patient perspective on PGx in Swiss chronic pain care remains limited.Methods: We conducted a cross-sectional online survey among chronic pain patients in the German-speaking regions of Switzerland. The questionnaire was developed to (1) assess the proportion of patients currently or previously treated with PGx actionable drugs, (2) evaluate therapy satisfaction and the perception of being taken seriously by healthcare professionals (HCPs), and (3) explore patients’ awareness of PGx and their interest in genetic pain predisposition.Results: Among the 725 participants who completed the survey, most reported current or past use of PGx actionable drugs: 85% non-steroidal anti-inflammatory drugs (NSAIDs), 54% opioids, 38% co-analgesics (antidepressants), and 73% proton-pump-inhibitors (PPIs) used as adjunctive therapy. Over one-third of participants reported no use of any analgesic drug. Therapy dissatisfaction was reported by 33%, and 28% felt not taken seriously by HCPs. Notably, 97% had never been offered PGx testing by an HCP. Despite this, 60% expressed interest in knowing their genetic pain predisposition, even if it would not affect their treatment. This interest was significantly higher among younger participants and those who were dissatisfied or felt not taken seriously by HCPs.Conclusion: This study provides the first large-scale, representative insights into the use of PGx actionable drugs and treatment patterns in Swiss chronic pain care. In particular, the high prevalence of PGx actionable drug use and the strong patient interest in genetic information support not only the clinical, but also the biopsychosocial potential of PGx for chronic pain management.Keywords: pharmacogenetics, PGx testing, pain sensitivity, therapy satisfaction, chronic pain care, Switzerland

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.104
GPT teacher head0.511
Teacher spread0.408 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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