SynthesisPharmacoEconomics2008
Pharmacoeconomic evaluations of pharmacogenetic and genomic screening programmes: a systematic review on content and adherence to guidelines.
Synthesis in PharmacoEconomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 7 of them syntheses that pooled 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.
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.
Who cites it
28 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Pooled it
- Economic evaluation in psychiatric pharmacogenomics: a systematic review.The pharmacogenomics journal · 2021Pooled it
- Guidance for the Harmonisation and Improvement of Economic Evaluations of Personalised Medicine.PharmacoEconomics · 2021Pooled it
- Economic Evaluations of Pharmacogenetic and Pharmacogenomic Screening Tests: A Systematic Review. Second Update of the Literature.PloS one · 2016Pooled it
- Improving the Efficiency and Quality of the Value Assessment Process for Companion Diagnostic Tests: The Companion test Assessment Tool (CAT).Journal of managed care & specialty pharmacy · 2015Pooled it
- Is individualized medicine more cost-effective? A systematic review.PharmacoEconomics · 2014Pooled it
- Cost effectiveness of pharmacogenomics: a critical and systematic review.PharmacoEconomics · 2010Pooled it
- Innovations in Health Care-A Conceptual Framework.International journal of environmental research and public health · 2021Article
- Evidence gaps in economic analyses of hearing healthcare: A systematic review.EClinicalMedicine · 2021Article
- Modelling for policy: The five principles of the Neglected Tropical Diseases Modelling Consortium.PLoS neglected tropical diseases · 2020Review
- A cost-effectiveness analysis of maternal CYP2D6 genetic testing to guide treatment for postpartum pain and avert infant adverse events.The pharmacogenomics journal · 2018Article
- The economic case for precision medicine.Expert review of precision medicine and drug development · 2018Article
- Cost-effectiveness of pharmacogenetic-guided treatment: are we there yet?The pharmacogenomics journal · 2017Review
- Economic Evaluation in Stratified Medicine: Methodological Issues and Challenges.Frontiers in pharmacology · 2016Article
- Pharmacogenetics of antiepileptic drugs: A brief review.The mental health clinician · 2016Review
- Article
- Key emerging themes for assessing the cost-effectiveness of reporting incidental findings.Genetics in medicine : official journal of the American College of Medical Genetics · 2015Article
- A Naturalistic Study of the Effectiveness of Pharmacogenetic Testing to Guide Treatment in Psychiatric Patients With Mood and Anxiety Disorders.The primary care companion for CNS disorders · 2015Article
- Concepts of 'personalization' in personalized medicine: implications for economic evaluation.PharmacoEconomics · 2015Article
- Economic evaluations of personalized medicine: existing challenges and current developments.Pharmacogenomics and personalized medicine · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The fields of pharmacogenetics and pharmacogenomics have become important practical tools to progress goals in medical and pharmaceutical research and development. As more screening tests are being developed, with some already used in clinical practice, consideration of cost-effectiveness implications is important. A systematic review was performed on the content of and adherence to pharmacoeconomic guidelines of recent pharmacoeconomic analyses performed in the field of pharmacogenetics and pharmacogenomics. Economic analyses of screening strategies for genetic variations, which were evidence-based and assumed to be associated with drug efficacy or safety, were included in the review. The 20 papers included cover a variety of healthcare issues, including screening tests on several cytochrome P450 (CYP) enzyme genes, thiopurine S-methyltransferase (TMPT) and angiotensin-converting enzyme (ACE) insertion deletion (ACE I/D) polymorphisms. Most economic analyses reported that genetic screening was cost effective and often even clearly dominated existing non-screening strategies. However, we found a lack of standardization regarding aspects such as the perspective of the analysis, factors included in the sensitivity analysis and the applied discount rates. In particular, an important limitation of several studies related to the failure to provide a sufficient evidence-based rationale for an association between genotype and phenotype. Future economic analyses should be conducted utilizing correct methods, with adherence to guidelines and including extensive sensitivity analyses. Most importantly, genetic screening strategies should be based on good evidence-based rationales. For these goals, we provide a list of recommendations for good pharmacoeconomic practice deemed useful in the fields of pharmacogenetics and pharmacogenomics, regardless of country and origin of the economic analysis.
Indexed as
Identifiers
18563949What OpenQuestion holds
Registered trials
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.