@article {592, title = {Survival versus years of healthy life: which is more powerful as a study outcome?}, journal = {Control Clin Trials}, volume = {20}, year = {1999}, month = {1999 Jun}, pages = {267-79}, abstract = {

Studies of interventions that are intended to improve patients{\textquoteright} health are often evaluated with survival as the primary outcome, even when a measure adjusted for quality of survival, such as years of healthy life (YHL), would seem more appropriate. The purpose of this article is to determine whether studies based on survival are more or less powerful than studies based on YHL in clinical trials where either measure might be appropriate. We used data from the Cardiovascular Health Study (CHS) to estimate the sample size that would be needed in studies of 156 different health conditions, for the two outcome measures. The median sample size for a 5-year study was 687 if survival was the endpoint and 484 for YHL. YHL usually required lower sample sizes than survival, although survival was more powerful for some health conditions. We also found that lengthy studies, and studies with many follow-up measures per person, did not have appreciably higher power than less intensive studies. We conclude that clinical investigations in which the goal is to improve health may often be performed more efficiently with YHL rather than survival as the primary outcome measure. Such studies can be short in duration, with relatively few measures per person of health status.

}, keywords = {Aged, Angina Pectoris, Female, Follow-Up Studies, Health Status, Humans, Life Expectancy, Male, Quality-Adjusted Life Years, Randomized Controlled Trials as Topic, Research Design, Sample Size, Survival Analysis, Time Factors, Treatment Outcome}, issn = {0197-2456}, doi = {10.1016/s0197-2456(98)00062-2}, author = {Diehr, P and Patrick, D L and Burke, G L and Williamson, J} } @article {634, title = {Patterns of self-rated health in older adults before and after sentinel health events.}, journal = {J Am Geriatr Soc}, volume = {49}, year = {2001}, month = {2001 Jan}, pages = {36-44}, abstract = {

OBJECTIVES: To describe and compare patterns of change in self-rated health for older adults before death and before and after stroke, myocardial infarction, congestive heart failure, cardiac procedure, hospital admission for cancer, and hip fracture.

DESIGN: "Event cohort," measuring time in months before and after the event.

SETTING: Four U.S. communities.

PARTICIPANTS: 5888 participants in the Cardiovascular Health Study (CHS), sampled from Medicare rolls and followed up to 8 years. Mean age at baseline was 73.

MEASUREMENTS: Self-rated health, including a category for death, assessed at 6-month intervals, and ascertainment of events.

METHODS: We examined the percentage that was healthy each month in the 5 years before death and in the 2 years before and after the other events, and compared the patterns to a "no event" group and to one another, using graphs and linear regression.

RESULTS: For people who died, health status declined slowly until about 9 months before death, when it dropped steeply. Comparing persons equally far from death, health was unrelated to age, but men and whites were healthier than women and blacks. Health for other events declined before the event, dropped steeply at the event, showed some recovery, and then declined further after the event. About 65\% to 80\% of the subjects were healthy 2 years before their event, but only 35\% to 65\% were healthy two years afterwards. Patterns were similar although less extreme for the "no event" group.

CONCLUSION: Visualizing trajectories of health helps us understand how serious health events changes health. Conclusions about change must be drawn with care because of a variety of possible biases. We have described the trajectories in detail. Work is now needed to explain, predict, and possibly prevent such changes in health.

}, keywords = {Aged, Cardiovascular Diseases, Cohort Studies, Death, Female, Follow-Up Studies, Health Status, Health Status Indicators, Hip Fractures, Hospitalization, Humans, Linear Models, Longitudinal Studies, Male, Random Allocation, Time Factors}, issn = {0002-8614}, doi = {10.1046/j.1532-5415.2001.49007.x}, author = {Diehr, P and Williamson, J and Patrick, D L and Bild, D E and Burke, G L} }