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INDANA: a meta-analysis on individual patient data in hypertension. Protocol and preliminary results

F Gueyffier1, F Boutitie, J P Boissel

  • 1Service de Pharmacologie Clinique, Lyon, France.

Therapie
|July 1, 1995
PubMed

Insights

This study on hypertension treatment identifies patient responders using individual patient data meta-analysis. The INDANA project aims to personalize hypertension therapy by distinguishing who benefits most from antihypertensive drugs.

Area of Science:

  • Cardiology
  • Pharmacology
  • Clinical Trials

Background:

  • Antihypertensive drug treatment effects are documented, but patient benefit varies significantly with baseline cardiovascular risk.
  • A small proportion of patients benefit from current hypertension treatments, prompting proposals to target high-risk individuals.
  • Justifying the limitation of treatment to high-risk patients requires validating several underlying assumptions.

Purpose of the Study:

  • To identify patient responders and non-responders to antihypertensive drug treatment through a comprehensive meta-analysis.
  • To validate assumptions underlying the proposed strategy of targeting high-risk patients for hypertension treatment.
  • To contribute to the individualization of hypertension treatment by selecting appropriate responders.

Main Methods:

  • The INDANA project utilizes a meta-analysis of individual patient data (IPD) to investigate treatment response.
  • The study addresses technical challenges associated with IPD meta-analysis for hypertension research.
  • Data collection for the INDANA project has been successfully concluded, confirming project feasibility.

Main Results:

  • The INDANA project is feasible, with data collection completed.
  • Main analysis results are anticipated for 1996.
  • Findings are expected to aid in selecting responders for hypertension treatment.

Conclusions:

  • The INDANA project provides a robust method for analyzing individual patient data in hypertension research.
  • The study's findings will support the personalized selection of patients for antihypertensive drug therapy.
  • This approach aims to optimize treatment outcomes by identifying individuals most likely to respond to hypertension medications.

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