Literature DB >> 8974210

Approached to monitoring the results of long-term disease prevention trials: examples from the Women's Health Initiative.

L Freedman1, G Anderson, V Kipnis, R Prentice, C Y Wang, J Rossouw, J Wittes, D DeMets.   

Abstract

We contrast monitoring therapeutic trials with monitoring prevention trails. We argue that in monitoring prevention trials one should place more emphasis on formally defined global measures of health, not simply on a single targeted disease, particularly when an intervention may reduce the incidence of some diseases but increase the incidence of others. We describe one approach, illustrated by the Women's Health Initiative. For each of several sets of hypothetical interim results ("scenarios"), members of the Data and Safety Monitoring Committee (DSMC) were asked whether they would continue or stop the trial. In parallel with this exercise, various statistical methods of monitoring that are based on (1) the primary targeted disease, (2) a combination of various disease outcomes, or (3) a mixture of both were applied to these scenarios. One objective was to find a statistical approach that mirrors the majority view of the DSMC. A second objective was to stimulate discussion among DSMC members in preparation for their task of monitoring the trial as the real data become available. We found that no single method fully matched the majority vote of the DSMC. However, a mixed approach requiring the primary outcome to be significant and the global index to be "supportive," with separate monitoring of adverse effects, corresponded with the majority vote quite well. This approach maintains the emphasis on the primary hypothesis while assuring that broader safety and ethical issues of multiple diseases are incorporated.

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Year:  1996        PMID: 8974210     DOI: 10.1016/s0197-2456(96)00016-5

Source DB:  PubMed          Journal:  Control Clin Trials        ISSN: 0197-2456


  7 in total

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Authors:  Ivair R Silva; Joshua J Gagne; Mehdi Najafzadeh; Martin Kulldorff
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2.  Physical activity, weight control, and breast cancer risk and survival: clinical trial rationale and design considerations.

Authors:  Rachel Ballard-Barbash; Sally Hunsberger; Marianne H Alciati; Steven N Blair; Pamela J Goodwin; Anne McTiernan; Rena Wing; Arthur Schatzkin
Journal:  J Natl Cancer Inst       Date:  2009-04-28       Impact factor: 13.506

3.  A rank test for bivariate time-to-event outcomes when one event is a surrogate.

Authors:  Pamela A Shaw; Michael P Fay
Journal:  Stat Med       Date:  2016-04-05       Impact factor: 2.373

4.  Cancer incidence and mortality during the intervention and postintervention periods of the Women's Health Initiative dietary modification trial.

Authors:  Cynthia A Thomson; Linda Van Horn; Bette J Caan; Aaron K Aragaki; Rowan T Chlebowski; JoAnn E Manson; Thomas E Rohan; Lesley F Tinker; Lewis H Kuller; Lifang Hou; Dorothy S Lane; Karen C Johnson; Mara Z Vitolins; Ross L Prentice
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-09-25       Impact factor: 4.254

5.  Using multiple risk models with preventive interventions.

Authors:  Mitchell H Gail
Journal:  Stat Med       Date:  2012-06-26       Impact factor: 2.373

6.  Utility-based designs for randomized comparative trials with categorical outcomes.

Authors:  Thomas A Murray; Peter F Thall; Ying Yuan
Journal:  Stat Med       Date:  2016-05-18       Impact factor: 2.373

7.  The Need for Combined Assessment of Multiple Outcomes in Noninferiority Trials in Oncology.

Authors:  Ismail Jatoi; Mitchell H Gail
Journal:  JAMA Oncol       Date:  2020-03-01       Impact factor: 31.777

  7 in total

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