Weighted pseudo-values for partly unobserved group membership in paediatric stem cell transplantation studies

Author:

Mittlböck Martina1ORCID,Pötschger Ulrike2ORCID,Heinzl Harald1ORCID

Affiliation:

1. Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Austria

2. Children’s Cancer Research Institute, Vienna, Austria

Abstract

Generalised pseudo-values have been suggested to evaluate the impact of allogeneic stem cell transplantation on childhood leukaemia. The approach compares long-term survival of two cohorts defined by the availability or non-availability of suitable donors for stem cell transplantation. A patient's cohort membership becomes known only after completed donor search with or without an identified donor. If a patient suffers an event during donor search, stem cell transplantation will no longer be indicated. In such a case, donor search will be ceased and cohort membership will remain unknown. The generalised pseudo-values approach considers donor identification as binary time-dependent covariate and uses inverse-probability-of-censoring weighting to adjust for non-identified donors. The approach leads to time-consuming computations due to multiple redefinitions of the risk set for pseudo-value calculation and an explicit adjustment for waiting-time bias. Here, the problem is looked at from a different angle. By considering the probability that a donor would have been identified after ceasing of donor search, weights for common pseudo-values are defined. This leads to a faster alternative approach as only a single risk set is necessary. Extensive computer simulations show that both, the generalised and the new weighted pseudo-values approach, provide approximately unbiased estimates. Confidence interval coverage is satisfactory for typical clinical scenarios. In situations, where donor identification takes considerably longer than usual, the weighted pseudo-values approach is preferable. Both approaches complement each other as they have different potential in addressing further aspects of the underlying medical question.

Publisher

SAGE Publications

Subject

Health Information Management,Statistics and Probability,Epidemiology

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