Lifetime Data Anal - Estimating treatment effects on the marginal recurrent event mean in the presence of a terminating event.

Tópicos

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Resumo

In biomedical studies where the event of interest is recurrent (e.g., hospitalization), it is often the case that the recurrent event sequence is subject to being stopped by a terminating event (e.g., death). In comparing treatment options, the marginal recurrent event mean is frequently of interest. One major complication in the recurrent/terminal event setting is that censoring times are not known for subjects observed to die, which renders standard risk set based methods of estimation inapplicable. We propose two semiparametric methods for estimating the difference or ratio of treatment-specific marginal mean numbers of events. The first method involves imputing unobserved censoring times, while the second methods uses inverse probability of censoring weighting. In each case, imbalances in the treatment-specific covariate distributions are adjusted out through inverse probability of treatment weighting. After the imputation and/or weighting, the treatment-specific means (then their difference or ratio) are estimated nonparametrically. Large-sample properties are derived for each of the proposed estimators, with finite sample properties assessed through simulation. The proposed methods are applied to kidney transplant data.

Resumo Limpo

biomed studi event interest recurr eg hospit often case recurr event sequenc subject stop termin event eg death compar treatment option margin recurr event mean frequent interest one major complic recurrenttermin event set censor time known subject observ die render standard risk set base method estim inapplic propos two semiparametr method estim differ ratio treatmentspecif margin mean number event first method involv imput unobserv censor time second method use invers probabl censor weight case imbal treatmentspecif covari distribut adjust invers probabl treatment weight imput andor weight treatmentspecif mean differ ratio estim nonparametr largesampl properti deriv propos estim finit sampl properti assess simul propos method appli kidney transplant data

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