@article{mark_anstrom_sun_clapp-channing_tsiatis_davidson-ray_lee_bardy_2008, title={Quality of life with defibrillator therapy or amiodarone in heart failure}, volume={359}, ISSN={["0028-4793"]}, DOI={10.1056/NEJMoa0706719}, abstractNote={BACKGROUND
Implantable cardioverter-defibrillator (ICD) therapy significantly prolongs life in patients at increased risk for sudden death from depressed left ventricular function. However, whether this increased longevity is accompanied by deterioration in the quality of life is unclear.


METHODS
In a randomized trial, we compared ICD therapy or amiodarone with state-of-the-art medical therapy alone in 2521 patients who had stable heart failure with depressed left ventricular function. We prospectively measured quality of life at baseline and at months 3, 12, and 30; data collection was 93 to 98% complete. The Duke Activity Status Index (which measures cardiac physical functioning) and the Medical Outcomes Study 36-Item Short-Form Mental Health Inventory 5 (which measures psychological well-being) were prespecified primary outcomes. Multiple additional quality-of-life outcomes were also examined.


RESULTS
Psychological well-being in the ICD group, as compared with medical therapy alone, was significantly improved at 3 months (P=0.01) and at 12 months (P=0.003) but not at 30 months. No clinically or statistically significant differences in physical functioning among the study groups were observed. Additional quality-of-life measures were improved in the ICD group at 3 months, 12 months, or both, but there was no significant difference at 30 months. ICD shocks in the month preceding a scheduled assessment were associated with a decreased quality of life in multiple domains. The use of amiodarone had no significant effects on the primary quality-of-life outcomes.


CONCLUSIONS
In a large primary-prevention population with moderately symptomatic heart failure, single-lead ICD therapy was not associated with any detectable adverse quality-of-life effects during 30 months of follow-up.}, number={10}, journal={NEW ENGLAND JOURNAL OF MEDICINE}, author={Mark, Daniel B. and Anstrom, Kevin J. and Sun, Jie L. and Clapp-Channing, Nancy E. and Tsiatis, Anastasios A. and Davidson-Ray, Linda and Lee, Kerry L. and Bardy, Gust H.}, year={2008}, month={Sep}, pages={999–1008} }
 @article{anstrom_tsiatis_2001, title={Utilizing propensity scores to estimate causal treatment effects with censored time-lagged data}, volume={57}, ISSN={["0006-341X"]}, DOI={10.1111/j.0006-341X.2001.01207.x}, abstractNote={Summary. Observational studies frequently are conducted to compare long‐term effects of treatments. Without randomization, patients receiving one treatment are not guaranteed to be prognostically comparable to those receiving another treatment. Furthermore, the response of interest may be right‐censored because of incomplete follow‐up. Statistical methods that do not account for censoring and confounding may lead to biased estimates. This article presents a method for estimating treatment effects in nonrandomized studies with right‐censored responses. We review the assumptions required to estimate average causal effects and derive an estimator for comparing two treatments by applying inverse weights to the complete cases. The weights are determined according to the estimated probability of receiving treatment conditional on covariates and the estimated treatment‐specific censoring distribution. By utilizing martingale representations, the estimator is shown to be asymptotically normal and an estimator for the asymptotic variance is derived. Simulation results are presented to evaluate the properties of the estimator. These methods are applied to an observational data set of acute coronary syndrome patients from Duke University Medical Center to estimate the effect of a treatment strategy on the mean 5‐year medical cost.}, number={4}, journal={BIOMETRICS}, author={Anstrom, KJ and Tsiatis, AA}, year={2001}, month={Dec}, pages={1207–1218} }