PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 15238369

ALLHAT: setting the record straight.

Barry R Davis·Curt D Furberg·Jackson T Wright·Jeffrey A Cutler·Paul Whelton·ALLHAT Collaborative Research Group
View original source ↗Export metadata ↓

Abstract

The findings of the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) have generated worldwide reaction from clinicians and researchers, including a recent commentary in this journal. Such response was expected for a trial of ALLHAT's size and scope, especially since its results challenged some widely held beliefs. This paper reviews key aspects of the ALLHAT design, analyses, findings, and conclusions to provide a perspective on the commentary about the trial's results and implications for clinical practice. Several of the most frequent comments regarding the study's results are addressed, particularly with respect to heart failure and diabetes outcomes. Responses to these comments reinforce the investigators' original conclusion that thiazide-type diuretics should remain the preferred first-step drug class for treating hypertension and should generally be a part of any multidrug regimen.

Explore related subjects

Antihypertensive AgentsCoronary DiseaseHumansHypertensionHypolipidemic AgentsRandomized Controlled Trials as TopicResearch DesignCommentJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, P.H.S.Review

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Barry R Davis, Curt D Furberg, Jackson T Wright, Jeffrey A Cutler, Paul Whelton, ALLHAT Collaborative Research Group. 2004-07-06. ALLHAT: setting the record straight.. https://doi.org/10.7326/0003-4819-141-1-200407060-00013

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2007

Tree-structured gatekeeping tests in clinical trials with hierarchically ordered multiple objectives.

This paper discusses a new class of multiple testing procedures, tree-structured gatekeeping procedures, with clinical trial applications. These procedures arise in clinical trials with hierarchically ordered multiple objectives, for example, in the context of multiple dose-control tests with logical restrictions or analysis of multiple endpoints. The proposed approach is based on the principle of closed testing and generalizes the serial and parallel gatekeeping approaches developed by Westfall and Krishen (J. Statist. Planning Infer. 2001; 99:25-41) and Dmitrienko et al. (Statist. Med. 2003; 22:2387-2400). The proposed testing methodology is illustrated using a clinical trial with multiple endpoints (primary, secondary and tertiary) and multiple objectives (superiority and non-inferiority testing) as well as a dose-finding trial with multiple endpoints.

Antihypertensive Agents↗
PubMed2007

Bayesian analysis of latent variable models with non-ignorable missing outcomes from exponential family.

To provide a comprehensive framework for analysing complex non-normal medical and biological data, we propose a Bayesian approach for a non-linear latent variable model with covariates, and non-ignorable missing data, under the exponential family of distributions. The non-ignorable missing mechanism is defined via a logistic regression model. Based on conjugate prior distributions, full conditional distributions for the implementation of Markov chain Monte Carlo methods in simulating observations from the joint posterior distribution are derived. These observations are used in computing the Bayesian estimates, as well as in implementing a path sampling procedure to evaluate the Bayes factor for model comparison. The proposed methods are illustrated using real data from a study on the non-adherence of hypertension patients.

Antihypertensive Agents↗
PubMed2007

Revisiting the relation between change and initial value: a review and evaluation.

The relation between initial disease status and subsequent change following treatment has attracted great interest in clinical research. However, statisticians have repeatedly warned against correlating/regressing change with baseline due to two methodological concerns known as mathematical coupling and regression to the mean. Oldham's method and Blomqvist's formula are the two most often adopted methods to rectify these problems. The aims of this article are to review briefly the proposed solutions in the statistical and psychological literature, and to clarify the popular misconception that Blomqvist's formula is superior to Oldham's method. We argue that this misconception is due to a failure to recognize that the heterogeneity of individual responses to treatment is a source of regression to the mean in the analysis of the relation between change and initial value. Furthermore, we demonstrate how each method actually answers different research questions, and how confusion arises when this is not always understood.

Antihypertensive Agents↗