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Estimation with Cox models: cause-specific survival analysis with misclassified cause of failure

(2012) EPIDEMIOLOGY. 23(2). p.194-202
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Abstract
While epidemiologic and clinical research often aims to analyze predictors of specific endpoints, time-to-the-specific-event analysis can be hampered by problems with cause ascertainment. Under typical assumptions of competing risks analysis (and missing-data settings), we correct the cause-specific proportional hazards analysis when information on the reliability of diagnosis is available. Our method avoids bias in effect estimates at low cost in variance, thus offering a perspective for better-informed decision making. The ratio of different cause-specific hazards can be estimated flexibly for this purpose. It thus complements an all-cause analysis. In a sensitivity analysis, this approach can reveal the likely extent and direction of the bias of a standard cause-specific analysis when the diagnosis is suspect. These 2 uses are illustrated in a randomized vaccine trial and an epidemiologic cohort study, respectively.
Keywords
SUBDISTRIBUTION, PNEUMOCOCCAL CONJUGATE VACCINE, TRIAL, GAMBIA, HAZARDS, ACCURACY, MORTALITY, DEATH CERTIFICATES, COMPETING RISKS, CORONARY-HEART-DISEASE

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Citation

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MLA
Van Rompaye, Bart, Shabbar Jaffar, and Els Goetghebeur. “Estimation with Cox Models: Cause-specific Survival Analysis with Misclassified Cause of Failure.” EPIDEMIOLOGY 23.2 (2012): 194–202. Print.
APA
Van Rompaye, B., Jaffar, S., & Goetghebeur, E. (2012). Estimation with Cox models: cause-specific survival analysis with misclassified cause of failure. EPIDEMIOLOGY, 23(2), 194–202.
Chicago author-date
Van Rompaye, Bart, Shabbar Jaffar, and Els Goetghebeur. 2012. “Estimation with Cox Models: Cause-specific Survival Analysis with Misclassified Cause of Failure.” Epidemiology 23 (2): 194–202.
Chicago author-date (all authors)
Van Rompaye, Bart, Shabbar Jaffar, and Els Goetghebeur. 2012. “Estimation with Cox Models: Cause-specific Survival Analysis with Misclassified Cause of Failure.” Epidemiology 23 (2): 194–202.
Vancouver
1.
Van Rompaye B, Jaffar S, Goetghebeur E. Estimation with Cox models: cause-specific survival analysis with misclassified cause of failure. EPIDEMIOLOGY. 2012;23(2):194–202.
IEEE
[1]
B. Van Rompaye, S. Jaffar, and E. Goetghebeur, “Estimation with Cox models: cause-specific survival analysis with misclassified cause of failure,” EPIDEMIOLOGY, vol. 23, no. 2, pp. 194–202, 2012.
@article{2069268,
  abstract     = {While epidemiologic and clinical research often aims to analyze predictors of specific endpoints, time-to-the-specific-event analysis can be hampered by problems with cause ascertainment. Under typical assumptions of competing risks analysis (and missing-data settings), we correct the cause-specific proportional hazards analysis when information on the reliability of diagnosis is available. Our method avoids bias in effect estimates at low cost in variance, thus offering a perspective for better-informed decision making. The ratio of different cause-specific hazards can be estimated flexibly for this purpose. It thus complements an all-cause analysis. In a sensitivity analysis, this approach can reveal the likely extent and direction of the bias of a standard cause-specific analysis when the diagnosis is suspect. These 2 uses are illustrated in a randomized vaccine trial and an epidemiologic cohort study, respectively.},
  author       = {Van Rompaye, Bart and Jaffar, Shabbar and Goetghebeur, Els},
  issn         = {1044-3983},
  journal      = {EPIDEMIOLOGY},
  keywords     = {SUBDISTRIBUTION,PNEUMOCOCCAL CONJUGATE VACCINE,TRIAL,GAMBIA,HAZARDS,ACCURACY,MORTALITY,DEATH CERTIFICATES,COMPETING RISKS,CORONARY-HEART-DISEASE},
  language     = {eng},
  number       = {2},
  pages        = {194--202},
  title        = {Estimation with Cox models: cause-specific survival analysis with misclassified cause of failure},
  url          = {http://dx.doi.org/10.1097/EDE.0b013e3182454cad},
  volume       = {23},
  year         = {2012},
}

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