ArticlePharmacoEconomics2018
The Future of Precision Medicine: Potential Impacts for Health Technology Assessment.
Article in PharmacoEconomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 50 papers, 5 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
50 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Drug pricing models, no 'one-size-fits-all' approach: a systematic review and critical evaluation of pricing models in an evolving pharmaceutical landscape.The European journal of health economics : HEPAC : health economics in prevention and care · 2025Pooled it
- Health economic evidence for the use of molecular biomarker tests in hematological malignancies: A systematic review.European journal of haematology · 2022Pooled it
- Guidance for the Harmonisation and Improvement of Economic Evaluations of Personalised Medicine.PharmacoEconomics · 2021Pooled it
- Guideline
- Promises of artificial intelligence in neuroradiology: a systematic technographic review.Neuroradiology · 2020Pooled it
- What Is Precision Psychotherapy?The Journal of medicine and philosophy · 2026Article
- Article
- Article
- Integrating Generative AI Into Patient-Centered Clinical Decision Support: Viewpoint on Research and Practice Considerations.Journal of medical Internet research · 2026Article
- Value-based health care frameworks for the health technology assessments of "omics" technologies: an international survey.International journal of technology assessment in health care · 2025Article
- A Practical Guide to Using Futures Methods in Health Care: Approaches, Applications, and Case Studies.Journal of medical Internet research · 2025Article
- A Review on Nanotechnologically Derived Phytomedicines for the Treatment of Hepatocellular Carcinoma: Recent Advances in Molecular Mechanism and Drug Targeting.Current drug targets · 2025Review
- Relevant factors for policy concerning comprehensive genomic profiling in oncology: stakeholder perspectives.BMC cancer · 2024Article
- Suitability of the Current Health Technology Assessment of Innovative Artificial Intelligence-Based Medical Devices: Scoping Literature Review.Journal of medical Internet research · 2024Article
- Risk Factors and Innovations in Risk Assessment for Melanoma, Basal Cell Carcinoma, and Squamous Cell Carcinoma.Cancers · 2024Review
- Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data.Journal of personalized medicine · 2023Review
- Can knowledgeable experts assess costs and outcomes as if they were ignorant? An experiment within precision medicine evaluation.International journal of technology assessment in health care · 2023Article
- Precision Medicine 2.0: How Digital Health and AI Are Changing the Game.Journal of personalized medicine · 2023Article
- How can we deliver on the promise of precision medicine in oncology and beyond? A practical roadmap for action.Health science reports · 2023Article
- Access to novel drugs and therapeutics for children and youth: Eliciting citizens' values to inform public funding decisions.Health expectations : an international journal of public participation in health care and health policy · 2023Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors.
Funding
Abstract
objectivePrecision medicine allows healthcare interventions to be tailored to groups of patients based on their disease susceptibility, diagnostic or prognostic information, or treatment response. We analysed what developments are expected in precision medicine over the next decade and considered the implications for health technology assessment (HTA) agencies.
methodsWe performed a pragmatic literature search to account for the large size and wide scope of the precision medicine literature. We refined and enriched these results with a series of expert interviews up to 1 h in length, including representatives from HTA agencies, research councils and researchers designed to cover a wide spectrum of precision medicine applications and research.
resultsWe identified 31 relevant papers and interviewed 13 experts. We found that three types of precision medicine are expected to emerge in clinical practice: complex algorithms, digital health applications and 'omics'-based tests. These are expected to impact upon each stage of the HTA process, from scoping and modelling through to decision-making and review. The complex and uncertain treatment pathways associated with patient stratification and fast-paced technological innovation are central to these effects. DISCUSSION: Innovation in precision medicine promises substantial benefits but will change the way in which some health services are delivered and evaluated. The shelf life of guidance may decrease, structural uncertainty may increase and new equity considerations will emerge. As biomarker discovery accelerates and artificial intelligence-based technologies emerge, refinements to the methods and processes of evidence assessments will help to adapt and maintain the objective of investing in healthcare that is value for money.
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What 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.