Evidence map›Paper›PMID 22037040›Full record

ReviewNature reviews. Drug discovery2011

Quantifying factors for the success of stratified medicine.

Mark R Trusheim, Breon Burgess, Sean Xinghua Hu, Theresa Long, Steven D Averbuch, Aiden A Flynn, Alfons Lieftucht, Abhijit Mazumder, Judy Milloy, Peter M Shaw and 5 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Drug discovery, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. About gladiators and a sacred disease.Biomedical journal · 2022
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
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  16. Pharmacogenomics of preterm birth prevention and treatment.BJOG : an international journal of obstetrics and gynaecology · 2016
    Review
  17. Article
  18. Article
  19. Article
  20. Article
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

15 authors.

Mark R TrusheimMassachusetts Institute of Technology, Sloan School of Management and Center for Biomedical Innovation, 100 Main Street, Cambridge, Massachusetts 02139, USA. Trusheim@mit.edu
Breon Burgess
Sean Xinghua Hu
Theresa Long
Steven D Averbuch
Aiden A Flynn
Alfons Lieftucht
Abhijit Mazumder
Judy Milloy
Peter M Shaw
David Swank
Jian Wang
Ernst R Berndt
Federico Goodsaid
Michael C Palmer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Co-developing a drug with a diagnostic to create a stratified medicine - a therapy that is targeted to a specific patient population on the basis of a clinical characteristic such as a biomarker that predicts treatment response - presents challenges for product developers, regulators, payers and physicians. With the aim of developing a shared framework and tools for addressing these challenges, here we present an analysis using data from case studies in oncology and Alzheimer's disease, coupled with integrated computational modelling of clinical outcomes and developer economic value, to quantify the effects of decisions related to key issues such as the design of clinical trials. This illustrates how such analyses can aid the coordination of diagnostic and drug development, and the selection of optimal development and commercialization strategies. It also illustrates the impact of the interplay of these factors on the economic feasibility of stratified medicine, which has important implications for public policy makers.

Indexed as

Alzheimer DiseaseClinical Trials, Phase III as TopicComputational BiologyHumansMedicineNeoplasmsResearch Design

Identifiers

PMID22037040

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.