Evidence map›Paper›PMID 23261867›Full record

ArticleCirculation2013

A systems approach to designing effective clinical trials using simulations.

Vincent A Fusaro, Prasad Patil, Chih-Lin Chi, Charles F Contant, Peter J Tonellato

Abstract read
In one paragraph

Article in Circulation, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Leaping the Data Chasm: Structuring Donation of Clinical Data for Healthcare Innovation and Modeling.Harvard health policy review : a student publication of the Harvard Interfaculty Initiative in Health Policy · 2015
    Article
  6. Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing.Proceedings of the ... USENIX Security Symposium. UNIX Security Symposium · 2014
    Article
  7. Article
  8. 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

5 authors.

Vincent A FusaroCenter for Biomedical Informatics Harvard Medical School, 10 Shattuck Street, Boston, MA 02115, USA.
Prasad Patil
Chih-Lin Chi
Charles F Contant
Peter J Tonellato

Funding

RESEARCH TRAINING-MEDICAL INFORMATICS 90T15LM007092 · NLM · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Nils Gehlenborg · 1992 to 2026
$32.8M
PREDICTIVE OPTIMAL ANTICLOTTING TREATMENT FOR SEGMENTED PATIENT POPULATIONSR01LM011566 · NLM · UNIVERSITY OF MISSOURI-COLUMBIA · PI TONELLATO, PETER J. · 2013 to 2016
$1.0M
Method for Prediction of Efficacy of Genetic-Based Prediction Models of PersonaliR01LM010130 · NLM · HARVARD MEDICAL SCHOOL · PI TONELLATO, PETER J. · 2009 to 2010
$967k
Repurposing Electronic Health Data for Serendipitous Therapy DiscoveryK99LM011020 · NLM · HARVARD MEDICAL SCHOOL · PI FUSARO, VINCENT A · 2011 to 2012
$255k
NLM NIH HHS K99 LM011020NLM NIH HHS K99LM011020NLM NIH HHS R01 LM010130NLM NIH HHS R01LM010130NLM NIH HHS R01 LM011566NLM NIH HHS T15LM007092
6 · The paper itself

Abstract

backgroundPharmacogenetics in warfarin clinical trials have failed to show a significant benefit in comparison with standard clinical therapy. This study demonstrates a computational framework to systematically evaluate preclinical trial design of target population, pharmacogenetic algorithms, and dosing protocols to optimize primary outcomes. METHODS AND

resultsWe programmatically created an end-to-end framework that systematically evaluates warfarin clinical trial designs. The framework includes options to create a patient population, multiple dosing strategies including genetic-based and nongenetic clinical-based, multiple-dose adjustment protocols, pharmacokinetic/pharmacodynamics modeling and international normalization ratio prediction, and various types of outcome measures. We validated the framework by conducting 1000 simulations of the applying pharmacogenetic algorithms to individualize dosing of warfarin (CoumaGen) clinical trial primary end points. The simulation predicted a mean time in therapeutic range of 70.6% and 72.2% (P=0.47) in the standard and pharmacogenetic arms, respectively. Then, we evaluated another dosing protocol under the same original conditions and found a significant difference in the time in therapeutic range between the pharmacogenetic and standard arm (78.8% versus 73.8%; P=0.0065), respectively.

conclusionsWe demonstrate that this simulation framework is useful in the preclinical assessment phase to study and evaluate design options and provide evidence to optimize the clinical trial for patient efficacy and reduced risk.

Indexed as

Systems TheoryAnimalsAnticoagulantsComputer SimulationDrug Evaluation, PreclinicalHumansModels, TheoreticalPharmacogeneticsRandomized Controlled Trials as TopicThrombosisWarfarinAnticoagulantsWarfarin

Identifiers

PMID23261867
PMCPMC3747989

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Registered trials

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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.