Propensity scores in the presence of effect modification: A case study using the comparison of mortality on hemodialysis versus peritoneal dialysis

Purpose. To control for confounding bias from non-random treatment assignment in observational data, both traditional multivariable models and more recently propensity score approaches have been applied. Our aim was to compare a propensity score-stratified model with a traditional multivariable-adjusted model, specifically in estimating survival of hemodialysis (HD) versus peritoneal dialysis (PD) patients. Methods. Using the Dutch End-Stage Renal Disease Registry, we constructed a propensity score, predicting PD assignment from age, gender, primary renal disease, center of dialysis, and year of first renal replacement therapy. We developed two Cox proportional hazards regression models to estimate survival on PD relative to HD, a propensity score-stratified model stratifying on the propensity score and a multivariable-adjusted model, and tested several interaction terms in both models. Results. The propensity score performed well: it showed a reasonable fit, had a good c-statistic, calibrated well and balanced the covariates. The main-effects multivariable-adjusted model and the propensity score-stratified univariable Cox model resulted in similar relative mortality risk estimates of PD compared with HD (0.99 and 0.97, respectively) with fewer significant covariates in the propensity model. After introducing the missing interaction variables for effect modification in both models, the mortality risk estimates for both main effects and interactions remained comparable, but the propensity score model had nearly as many covariates because of the additional interaction variables. Conclusion. Although the propensity score performed well, it did not alter the treatment effect in the outcome model and lost its advantage of parsimony in the presence of effect modification

The utility of health at different stages in life:A quantitative approach

Thirty students and thirty-five elderly people compared the quality of life of imaginary patients of different ages suffering from end-stage renal disease. By manipulating the time the imaginary patients had to be on a transplantation waiting list, the utility of health at different periods of life could be compared. Except for the very young, respondents found health in the early periods of life to be twice as important as in the last decade of life. Health at age 35 had an utility somewhere between these two extremes. The responses of the elderly people showed remarkable resemblance to the students' responses, suggesting that the results reflect a general ethical standard. The values found were tested by means of a factorial design and found to fulfill the qualifications of an interval scale.</p

The utility of health at different stages in life: A quantitative approach

Thirty students and thirty-five elderly people compared the quality of life of imaginary patients of different ages suffering from end-stage renal disease. By manipulating the time the imaginary patients had to be on a transplantation waiting list, the utility of health at different periods of life could be compared. Except for the very young, respondents found health in the early periods of life to be twice as important as in the last decade of life. Health at age 35 had an utility somewhere between these two extremes. The responses of the elderly people showed remarkable resemblance to the students' responses, suggesting that the results reflect a general ethical standard. The values found were tested by means of a factorial design and found to fulfill the qualifications of an interval scale.utility measurement quality of life QALY's age