Literature DB >> 18355506

Using the National Death Index to validate the noninformative censoring assumption of survival estimation.

YingXing Wu1, Anthony P Furnary, Gary L Grunkemeier.   

Abstract

BACKGROUND: In survival analysis, a patient who is missing complete follow-up is included in the analysis as a censored observation. The analysis makes the assumption that the censoring is noninformative; that is, that a censored patient has the same risk of death as those who have complete follow-up. We tested this assumption in a large, long-term follow-up study.
METHODS: From 1986 through 2003, 14,495 patients underwent isolated coronary artery bypass grafting procedures. Of 13,963 eligible patients, 2312 were lost to follow-up. We obtained National Death Index data to complete our follow-up, and then compared survival between the original data and the complete National Death Index-augmented data.
RESULTS: The National Death Index data revealed 855 additional deaths and increased the total follow-up years from 86,810 to 102,157. Survival estimates and regression models did not differ between the original and National Death Index-augmented data.
CONCLUSIONS: Patients lost to follow-up might not differ with regard to survival from those with complete data. The requirement for 95% completeness is somewhat arbitrary. The quality and type of follow-up is more important than the percentage in time-related analyses.

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Year:  2008        PMID: 18355506     DOI: 10.1016/j.athoracsur.2007.12.013

Source DB:  PubMed          Journal:  Ann Thorac Surg        ISSN: 0003-4975            Impact factor:   4.330


  4 in total

1.  Latent Classes of Neuropsychiatric Symptoms in NACC Controls and Conversion to Mild Cognitive Impairment or Dementia.

Authors:  Jeannie-Marie S Leoutsakos; Sarah N Forrester; Constantine G Lyketsos; Gwenn S Smith
Journal:  J Alzheimers Dis       Date:  2015       Impact factor: 4.472

2.  Trajectories of neuropsychiatric symptoms over time in healthy volunteers and risk of MCI and dementia.

Authors:  Jeannie-Marie S Leoutsakos; Elizabeth A Wise; Constantine G Lyketsos; Gwenn S Smith
Journal:  Int J Geriatr Psychiatry       Date:  2019-09-02       Impact factor: 3.485

3.  Differential losses to follow-up that are outcome-dependent can vitiate a clinical trial: Simulation results.

Authors:  Richard F Potthoff
Journal:  J Biopharm Stat       Date:  2017-10-30       Impact factor: 1.051

4.  An evaluation of the impact of missing deaths on overall survival analyses of advanced non-small cell lung cancer patients conducted in an electronic health records database.

Authors:  Gillis Carrigan; Samuel Whipple; Michael D Taylor; Aracelis Z Torres; Anala Gossai; Brandon Arnieri; Melisa Tucker; Philip P Hofmeister; Peter Lambert; Sandra D Griffith; William B Capra
Journal:  Pharmacoepidemiol Drug Saf       Date:  2019-03-14       Impact factor: 2.890

  4 in total

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