Index to Predict 5-Year Mortality of Community-Dwelling Adults Aged 65 and Older Using Data from the National Health Interview Survey

Abstract

BACKGROUND: Prognostic information is becoming increasingly important for clinical decision-making.OBJECTIVE: To develop and validate an index to predict 5-year mortality among community-dwelling older adults. DESIGN AND PARTICIPANTS:A total of 24,115 individuals aged >65 who responded to the 1997-2000 National Health Interview Survey (NHIS) with follow-up through 31 December 2002 from the National Death Index; 16,077 were randomly selected for the development cohort and 8,038 for the validation cohort.MEASUREMENTS: 39 risk factors (functional measures, illnesses, behaviors, demographics) were included in a multivariable Cox proportional hazards model to determine factors independently associated with mortality. Risk scores were calculated for participants using points derived from the final model's beta coefficients. To evaluate external validity, we compared survival by quintile of risk between the development and validation cohorts.RESULTS: Seventeen percent of participants had died by the end of the study. The final model included 11 variables: age (1 point for 70-74 up to 7 points for >85); male: 3 points; BMI <25: 2 points; perceived health (good: 1 point, fair/poor: 2 points); emphysema: 2 points; cancer: 2 points; diabetes: 2 points; dependent in instrumental activities of daily living: 2 points; difficulty walking: 3 points; smoker-former: 1 point, smoker-current: 3 points; past year hospitalizationsone: 1 point, >2: 3 points. We observed close agreement between 5-year mortality in the two cohorts; which ranged from 5% in the lowest risk quintile to 50% in the highest risk quintile in the validation cohort.CONCLUSIONS: This validated mortality index can be used to account for participant life expectancy in analyses using NHIS data.

Multiple, but not traditional risk factors predict mortality in older people: the concord health and ageing in men project

“…The results of our analyses suggest that the model should perform well in other similarly defined populations. The predictive ability of our model is comparable to other studies of older people living in the community (Lee et al 2006;Schonberg et al 2009). …”

Development and Validation of a 10-Year Mortality Prediction Model: Meta-Analysis of Individual Participant Data From Five Cohorts of Older Adults in Developed and Developing Countries

“…Previous mortality prediction models were all developed using data from a single study and mostly from the United States and Europe (7-9,13,39-42) and therefore have limited generalizability in other populations (18). We found that the best set of predictors were age, comorbidities, lifestyle factors, and functional status, similar to previous models developed for community-dwelling older adults (7)(8)(9)13,40). In addition, although we included data from 16 countries with widely different mortality rates, our model showed similar discrimination to previous single-study models that had C statistics from 0.69 to 0.83 and less than 10% points difference between observed and predicted risk of mortality across deciles of risk (15).…”

“…In addition, participants in all cohorts were asked whether they had "heart disease," whereas in MHAS they were asked about "heart attack," and the frequency of vigorous physical activity were different between HRS, MHAS, and SABE (≥3 times/week), and ELSA and SHARE (≥1 time/week). We also did not have consistent measures of other potential predictors of mortality, such as number of recent hospitalizations (8) and size of the participant's social network (42) across the five cohorts. Moreover, cohorts lost up to 36% of their participants during follow-up, and this may have biased our results if loss to follow-up is associated both with the included predictors and with mortality (43).…”

“…However, all available mortality prediction models have been developed using data from a single study, but all from the United States and Western Europe (7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17), which greatly limits their validity for use even in other high-income countries, let alone in the developing countries. For instance, a model developed using data from the Health and Retirement Study (HRS) in the United States showed poor performance when it was applied to older adults in England (18).…”

Assessing the applicability of trial evidence to a target sample in the presence of heterogeneity of treatment effect

“…12 We focused on validated predictors of mortality in community-dwelling adults who were older adults [13][14][15] or had heart failure. [16][17][18][19] Predictors of the benefit outcome were age (years), gender, smoking status (never, ever, and current), history of diabetes mellitus, left ventricular ejection fraction (continuous), cardiothoracic ratio (continuous), pulse (b min À1 ), diuretic use, serum creatinine (mg/dl), serum sodium (mg/dl), history of chronic obstructive pulmonary disease, and history of stroke.…”