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Survival studies: competing risks, immortality and censoring

Adrian G Barnett, Christopher Oldmeadow and John R Attia
Med J Aust 2018; 208 (11): . || doi: 10.5694/mja17.00171
Published online: 18 June 2018

One of the simplest study designs is giving participants — with a headache, for example — an active pill or placebo at random and then observing their outcome of cured or not cured one hour later. Studies with such short time frames are rare, and meaningful outcomes, such as disease or death, often need to be followed up long after the initial contact, potentially decades later.


  • 1 Institute of Health and Biomedical Innovation and School of Public Health and Social Work, Queensland University of Technology, Brisbane, QLD
  • 2 Centre for Clinical Epidemiology and Biostatistics, University of Newcastle, Newcastle, NSW
  • 3 John Hunter Hospital, Newcastle, NSW


Correspondence: a.barnett@qut.edu.au

Series Editors

John R Attia

Michael P Jones


Acknowledgements: 

Adrian Barnett is supported by a National Health Medical Research Council Senior Research Fellowship (APP1117784).

Competing interests:

No relevant disclosures.

  • 1. Attia JR, Jones MP, Suthers B. Aiming for the truth: understanding the difference between validity and precision. Med J Aust 2016; 205: 392-394. <MJA full text>
  • 2. Attia JR, Jones MP, Hure A. Deconfounding confounding part 1: traditional explanations. Med J Aust 2017; 206: 244-245. <MJA full text>
  • 3. Attia JR, Oldmeadow C, Holliday EG, Jones MP. Deconfounding confounding part 2: using directed acyclic graphs (DAGs). Med J Aust 2017; 206: 480-483. <MJA full text>
  • 4. Strand LB, Clarke P, Graves N, et al. Time to publication for publicly funded clinical trials in Australia: an observational study. BMJ Open 2017; 7: e012212.
  • 5. Kalbfleisch JD, Prentice RL. The statistical analysis of failure time data. 2nd ed. New York: John Wiley, 2011.
  • 6. von Elm E, Altman DG, Egger M, et al. Strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ 2007; 335: 806.
  • 7. Lévesque LE, Hanley JA, Kezouh A, Suissa S. Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes. BMJ 2010; 340: b5087.
  • 8. Trentino KM, Swain SG, Burrows SA, et al. Measuring the incidence of hospital-acquired complications and their effect on length of stay using CHADx. Med J Aust 2013; 199: 543-547. <MJA full text>
  • 9. Barnett AG, Beyersmann J, Allignol A, et al. The time-dependent bias and its effect on extra length of stay due to nosocomial infection. Value Health 2011; 14: 381-386.
  • 10. Andersen PK, Geskus RB, De witte T, Putter H. Competing risks in epidemiology: possibilities and pitfalls. Int J Epidemiol 2012; 41: 861-870.
  • 11. Wolkewitz M, Cooper BS, Bonten MJM, et al. Interpreting and comparing risks in the presence of competing events. BMJ 2014; 349: g5060.
  • 12. Klein JP, Moeshberger ML. Survival analysis: techniques for censored and truncated data. 2nd ed. Springer, 2003: pp 63-87.

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