Evidence map›Paper›PMID 26502985›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2016

A Framework for Prioritizing Research Investments in Precision Medicine.

Anirban Basu, Josh J Carlson, David L Veenstra

Abstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Artificial Intelligence Opportunities to Guide Precision Dosing Strategies.The journal of pediatric pharmacology and therapeutics : JPPT : the official journal of PPAG · 2024
    Article
  4. Review
  5. Article
  6. Review
  7. Testing for a Sweet Spot in Randomized Trials.Medical decision making : an international journal of the Society for Medical Decision Making · 2022
    Article
  8. Article
  9. Article
  10. Trends in the characteristics of human functional genomic data on the gene expression omnibus, 2001-2017.Laboratory investigation; a journal of technical methods and pathology · 2019
    Article
  11. Methodological Issues in Assessing the Economic Value of Next-Generation Sequencing Tests: Many Challenges and Not Enough Solutions.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2018
    Review
  12. Implementing Precision Medicine: The Ethical Challenges.Trends in pharmacological sciences · 2017
    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

3 authors.

Anirban BasuDepartment of Pharmacy, Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, WA, USA (AB, JJC, DLV)
Josh J CarlsonDepartment of Pharmacy, Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, WA, USA (AB, JJC, DLV)
David L VeenstraDepartment of Pharmacy, Pharmaceutical Outcomes Research and Policy Program, University of Washington, Seattle, WA, USA (AB, JJC, DLV)

Funding

Value of Information Methods for NHLBI TrialsR01HL126804 · NHLBI · UNIVERSITY OF WASHINGTON · PI BASU, ANIRBAN · 2015 to 2018
$2.7M
Personalized Medicine Economics Research PriMERU01AG047109 · NIA · UNIVERSITY OF WASHINGTON · PI VEENSTRA, DAVID L · 2013 to 2017
$2.2M
NHLBI NIH HHS R01 HL126804NIA NIH HHS U01 AG047109
6 · The paper itself

Abstract

introductionThe adoption of precision medicine (PM) has been limited in practice to date, and yet its promise has attracted research investments. Developing foundational economic approaches for directing proper use of PM and stimulating growth in this area from multiple perspectives is thus quite timely.

methodsBuilding on our previously developed expected value of individualized care (EVIC) framework, we conceptualize new decision-relevant metrics to better understand and forecast the expected value of PM. Several aspects of behavior at the patient, physician, and payer levels are considered that can inform the rate and manner in which PM innovations diffuse throughout the relevant population. We illustrate this framework and the methods using a retrospective evaluation of the use of OncotypeDx genomic test among breast cancer patients.

resultsThe enriched metrics can help inform many facets of PM decision making, such as evaluating alternative reimbursement levels for PM tests, implementation and education programs for physicians and patients, and decisions around research investments by manufacturers and public entities. We replicated prior published results on evaluation of OncotypeDx among breast cancer patients but also illustrated that those results are based on assumptions that are often not met in practice. Instead, we show how incorporating more practical aspects of behavior around PM could lead to drastically different estimates of value.

conclusionWe believe that the framework and the methods presented can provide decision makers with more decision-relevant tools to explore the value of PM. There is a growing recognition that data on adoption is important to decision makers. More research is needed to develop prediction models for potential diffusion of PM technologies.

Indexed as

Decision MakingPrecision MedicineResearchBreast NeoplasmsFemaleGenetic TestingHumansInsurance CoverageMarkov Chainsbreast cancerdiffusionEVICgenomic testprecision medicine

Identifiers

PMID26502985
PMCPMC5845804

What OpenQuestion holds

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Registered trials

None linked

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.