Literature DB >> 7846414

Considerations in choice of a clinical endpoint for AIDS clinical trials. Terry Beirn Community Programs for Clinical Research on AIDS (CPCRA).

J D Neaton1, D N Wentworth, F Rhame, C Hogan, D I Abrams, L Deyton.   

Abstract

In most clinical trials of antiretroviral therapy for patients infected with HIV, the major outcome variable has been the combined clinical endpoint of any new or recurrent AIDS defining event. We review features of combined endpoints and use data from the Terry Beirn Community Programs for Clinical Research on AIDS (CPCRA) to evaluate this outcome measure in terms of relevance, diagnostic certainty and sensitivity. We conclude that this endpoint is not relevant because: (i) the 19 different events constituting the combined endpoint are equally weighted in analyses even though they vary considerably in terms of risk of death; and (ii) events after the first are ignored, thus the event profile of patients is not taken into account in making treatment comparisons. We also conclude that power may be low with use of this endpoint if treatments under study do not have an immediate impact on disease progression, if some events which occur soon after randomization represent a disease process that has already begun to incubate, or if treatment differences for the various events constituting the combined endpoint are differentially effected by treatment. Since the ease and certainty of diagnosis of each of the 19 events also vary, we recommend that survival be the primary endpoint of antiretroviral trials, and that all opportunistic events experienced by patients, not just the first, be collected and summarized. Trial reports should include comparisons of incidence of each event by treatment group so that readers can rank events as they please. A single summary measure which considers severity and the entire event profile, as described here, would also be useful for assessing the impact of treatments on quality of life. Further research on approaches for weighting and combining multiple outcome measures is needed.

Entities:  

Mesh:

Year:  1994        PMID: 7846414     DOI: 10.1002/sim.4780131919

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  18 in total

1.  Power and sample size calculations for the Wilcoxon-Mann-Whitney test in the presence of death-censored observations.

Authors:  Roland A Matsouaka; Rebecca A Betensky
Journal:  Stat Med       Date:  2014-11-13       Impact factor: 2.373

2.  A hierarchical rank test for crossover trials with censored data.

Authors:  Erica Brittain; Dean Follmann
Journal:  Stat Med       Date:  2011-12-05       Impact factor: 2.373

3.  Risk of all-cause mortality associated with nonfatal AIDS and serious non-AIDS events among adults infected with HIV.

Authors:  Jacqueline Neuhaus; Brian Angus; Justyna D Kowalska; Alberto La Rosa; Jim Sampson; Deborah Wentworth; Amanda Mocroft
Journal:  AIDS       Date:  2010-03-13       Impact factor: 4.177

4.  Nonparametric Benefit-Risk Assessment Using Marker Process in the Presence of a Terminal Event.

Authors:  Yifei Sun; Chiung-Yu Huang; Mei-Cheng Wang
Journal:  J Am Stat Assoc       Date:  2017-04-12       Impact factor: 5.033

5.  Exploring causality mechanism in the joint analysis of longitudinal and survival data.

Authors:  Lei Liu; Cheng Zheng; Joseph Kang
Journal:  Stat Med       Date:  2018-06-07       Impact factor: 2.373

Review 6.  Can we predict the prognosis of HIV infection? How to use the findings of a prospective study.

Authors:  N Low; M Egger
Journal:  Sex Transm Infect       Date:  1998-04       Impact factor: 3.519

Review 7.  Ups and downs--and ups in the antiviral therapy of HIV infection.

Authors:  I V Weller; I Williams
Journal:  Genitourin Med       Date:  1996-02

8.  Surrogate markers now provide physicians with the best means to manage antiretroviral therapy: the case for.

Authors:  G J Moyle; B G Gazzard; T Peto
Journal:  Genitourin Med       Date:  1997-06

9.  Annotation: wanted--a simple and meaningful HIV staging system.

Authors:  W el-Sadr; J D Neaton
Journal:  Am J Public Health       Date:  1997-04       Impact factor: 9.308

10.  Joint modeling of longitudinal, recurrent events and failure time data for survivor's population.

Authors:  Qing Cai; Mei-Cheng Wang; Kwun Chuen Gary Chan
Journal:  Biometrics       Date:  2017-03-23       Impact factor: 2.571

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.