Literature DB >> 24623573

A weighted cumulative sum (WCUSUM) to monitor medical outcomes with dependent censoring.

Rena Jie Sun1, John D Kalbfleisch, Douglas E Schaubel.   

Abstract

We develop a weighted cumulative sum (WCUSUM) to evaluate and monitor pre-transplant waitlist mortality of facilities in the context where transplantation is considered to be dependent censoring. Waitlist patients are evaluated multiple times in order to update their current medical condition as reflected in a time-dependent variable called the Model for End-Stage Liver Disease (MELD) score. Higher MELD scores are indicative of higher pre-transplant death risk. Moreover, under the current liver allocation system, patients with higher MELD scores receive higher priority for liver transplantation. To evaluate the waitlist mortality of transplant centers, it is important to take this dependent censoring into consideration. We assume a 'standard' transplant practice through a transplant model and utilize inverse probability censoring weights to construct a WCUSUM. We evaluate the properties of a weighted zero-mean process as the basis of the proposed WCUSUM. We then discuss a resampling technique to obtain control limits. The proposed WCUSUM is illustrated through the analysis of national transplant registry data.
Copyright © 2014 John Wiley & Sons, Ltd.

Entities:  

Keywords:  control limits; cumulative sum (CUSUM); dependent censoring; failure time data; inverse probability weights; quality control; quality improvement; resampling; risk adjustment

Mesh:

Year:  2014        PMID: 24623573      PMCID: PMC4200511          DOI: 10.1002/sim.6139

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  12 in total

1.  Correcting for noncompliance and dependent censoring in an AIDS Clinical Trial with inverse probability of censoring weighted (IPCW) log-rank tests.

Authors:  J M Robins; D M Finkelstein
Journal:  Biometrics       Date:  2000-09       Impact factor: 2.571

2.  Estimating differences in restricted mean lifetime using observational data subject to dependent censoring.

Authors:  Min Zhang; Douglas E Schaubel
Journal:  Biometrics       Date:  2010-10-29       Impact factor: 2.571

3.  Transplant center quality assessment using a continuously updatable, risk-adjusted technique (CUSUM).

Authors:  D A Axelrod; M K Guidinger; R A Metzger; R H Wiesner; R L Webb; R M Merion
Journal:  Am J Transplant       Date:  2006-02       Impact factor: 8.086

4.  A risk-adjusted CUSUM in continuous time based on the Cox model.

Authors:  Pinaki Biswas; John D Kalbfleisch
Journal:  Stat Med       Date:  2008-07-30       Impact factor: 2.373

5.  Commentary on "The UK Scheme for a Mandatory Continuous Monitoring of Early Transplant Outcome in all Kidney Transplant Centres" by Collett D, Sibanda N, Pioh S, Bradley A, and Rudge C.

Authors:  John D Kalbfleisch
Journal:  Transplantation       Date:  2009-10-27       Impact factor: 4.939

6.  Marker processes in survival analysis.

Authors:  N P Jewell; J D Kalbfleisch
Journal:  Lifetime Data Anal       Date:  1996       Impact factor: 1.588

7.  A risk-adjusted O-E CUSUM with monitoring bands for monitoring medical outcomes.

Authors:  Rena Jie Sun; John D Kalbfleisch
Journal:  Biometrics       Date:  2013-02-05       Impact factor: 2.571

8.  Risk-adjusted monitoring of binary surgical outcomes.

Authors:  S H Steiner; R J Cook; V T Farewell
Journal:  Med Decis Making       Date:  2001 May-Jun       Impact factor: 2.583

9.  SRTR center-specific reporting tools: Posttransplant outcomes.

Authors:  D M Dickinson; T H Shearon; J O'Keefe; H-H Wong; C L Berg; J D Rosendale; F L Delmonico; R L Webb; R A Wolfe
Journal:  Am J Transplant       Date:  2006       Impact factor: 8.086

10.  Monitoring surgical performance using risk-adjusted cumulative sum charts.

Authors:  S H Steiner; R J Cook; V T Farewell; T Treasure
Journal:  Biostatistics       Date:  2000-12       Impact factor: 5.899

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