Skip to main content
Erschienen in: European Journal of Epidemiology 9/2008

01.09.2008 | Methods

Survival analysis: up from Kaplan–Meier–Greenwood

verfasst von: Olli S. Miettinen

Erschienen in: European Journal of Epidemiology | Ausgabe 9/2008

Einloggen, um Zugang zu erhalten

Abstract

In the type of survival analysis that now is routine, only the points of follow-up at which deaths from the cause at issue occurred make contributions to the Greenwood standard error (SE) of the survival rate’s Kaplan–Meier (KM) point estimate. An equivalent of this ‘KMG’ analysis draws from defined subintervals of the survival period being addressed. The data on each subinterval consist of the number of deaths from the cause at issue and the amount of population–time of follow-up, d j and T j , together with the duration of the interval, t j . The KM point estimate is replicated by \( \exp [-{\sum \nolimits_{j} ({{{d_{j} }/ \mathord{{\vphantom {{d_{j}}{T_{j}}}} \kern-\nulldelimiterspace} {T_{j} }}})t_{j}}], \) and the KMG interval estimate is replicated by treating the {d j } as a set of point estimates of Poisson parameters {λ j }, thus taking the SE of \( \sum \nolimits_{j}({{{d_{j} } \mathord{{\vphantom {{d_{j} } {T_{j} }}} \kern-\nulldelimiterspace} {T_{j}}}})t_{j}\) to be \([{\sum \nolimits _{j} d_{j} ({{{t_{j} } / \mathord{{\vphantom {{t_{j} } {T_{j} }}} \kern-\nulldelimiterspace} {T_{j} }}})^{2} }]^{{{1/ \mathord{{\vphantom {1 2}} \kern-\nulldelimiterspace} 2}}}.\) In both the KMG analysis and this equivalent of it, the SE used to derive the survival rate’s lower confidence limit needs to be augmented by a factor that accounts for the loss of information due to censorings subsequent to the last ‘failure’ in the survival period at issue. But, SE-based interval estimation of survival rate actually needs to be replaced by a first-principles counterpart of it. A suitable point of departure in this is first-principles asymptotic interval estimation of the Poisson parameter \( \lambda =\sum \nolimits _{j}{\lambda_{j}}, \) if not the exact counterpart of this. A confidence limit for the survival rate can then be based on suitable augmentation or contraction of the {d j } set to \( \{ d_{j}^{*} \} \) consistent with a given limit for λ, the corresponding survival-rate limit being \( \exp [-{\sum \nolimits _{j} ({{{d_{j}^{ *} } \mathord{/ {\vphantom {{d_{j}^{ *} } {T_{j} }}} \kern-\nulldelimiterspace} {T_{j}}}})t_{j}}]. \) Suitable augmentation is constituted by an identical addition to each \(d_{j}^{1/2},\) suitable contraction by an identical subtraction from each \(d_{j}^{1/2} \ge 1.\)
Anhänge
Nur mit Berechtigung zugänglich
Literatur
1.
Zurück zum Zitat The International Early Lung Cancer Action Program investigators. Survival of patients with Stage I lung cancer detected on CT screening. N Engl J Med. 2006;355(17):1763–71. doi:10.1056/NEJMoa060476.CrossRef The International Early Lung Cancer Action Program investigators. Survival of patients with Stage I lung cancer detected on CT screening. N Engl J Med. 2006;355(17):1763–71. doi:10.​1056/​NEJMoa060476.CrossRef
3.
Zurück zum Zitat Greenwood M. A report on the natural duration of cancer. In: Reports on public health and medical subjects, vol. 33. His Majesty’s Stationery Office: London; 1926. p. 1–26. Greenwood M. A report on the natural duration of cancer. In: Reports on public health and medical subjects, vol. 33. His Majesty’s Stationery Office: London; 1926. p. 1–26.
4.
Zurück zum Zitat Miettinen OS. Estimability and estimation in case-referent studies. Am J Epidemiol. 1976;103:30–6.PubMed Miettinen OS. Estimability and estimation in case-referent studies. Am J Epidemiol. 1976;103:30–6.PubMed
6.
Zurück zum Zitat Peto R, Pike MC, Armitage P, Breslow NE, Cox DR, Howard SV, et al. Design and analysis of randomized clinical trials requiring prolonged observation of each patient. II. Analysis and examples. Br J Cancer. 1977;35(1):1–39.PubMed Peto R, Pike MC, Armitage P, Breslow NE, Cox DR, Howard SV, et al. Design and analysis of randomized clinical trials requiring prolonged observation of each patient. II. Analysis and examples. Br J Cancer. 1977;35(1):1–39.PubMed
8.
Zurück zum Zitat Collett D. Modelling survival data in medical research. 2nd ed. Boca Raton: Chapman & Hall/CRC; 2003. Collett D. Modelling survival data in medical research. 2nd ed. Boca Raton: Chapman & Hall/CRC; 2003.
Metadaten
Titel
Survival analysis: up from Kaplan–Meier–Greenwood
verfasst von
Olli S. Miettinen
Publikationsdatum
01.09.2008
Verlag
Springer Netherlands
Erschienen in
European Journal of Epidemiology / Ausgabe 9/2008
Print ISSN: 0393-2990
Elektronische ISSN: 1573-7284
DOI
https://doi.org/10.1007/s10654-008-9278-7

Weitere Artikel der Ausgabe 9/2008

European Journal of Epidemiology 9/2008 Zur Ausgabe