Hazard ratio funnel plots for survival comparisons.
P. Silcocks. Journal of epidemiology and community health, 63 (10):
856-61(October 2009)5278<m:linebreak></m:linebreak>JID: 7909766; aheadofprint;<m:linebreak></m:linebreak>Anàlisi de supervivència.
DOI: 10.1136/jech.2008.075069
Abstract
BACKGROUND: Funnel plots are a form of control chart that give a snapshot of many institutions at a particular moment in time. This paper describes how funnel plots may be constructed for survival analyses based on hazard ratios obtained from a Cox regression model with adjustment for covariates and allowance for overdispersion. METHOD: Analysis of simulated and real survival data. RESULTS: It describes how centred hazard ratio estimates adjusted for covariates can be obtained from a Cox regression and gives details of the necessary programming in Stata. Allowance for overdispersion can be made by multiplying the standard errors by a factor based on either the model or the log-rank chi(2) statistics. Simulated results and a real example are presented. CONCLUSION: Funnel plots based on hazard ratios are easier to interpret than multiple Kaplan-Meier survival plots, and in contrast to funnel plots based on survival at, say, 5 years, are less open to accusations of bias and use more information. The interpretation of such plots may be enhanced by using standard meta-analysis methods. Hazard ratio comparisons may now be added to the repertoire of techniques used by Cancer Registries, Primary Care Trusts, and other commissioners of healthcare.
%0 Journal Article
%1 Silcocks2009
%A Silcocks, P
%D 2009
%J Journal of epidemiology and community health
%K DataDisplay Humans Models ProportionalHazardsModels Statistical SurvivalAnalysis
%N 10
%P 856-61
%R 10.1136/jech.2008.075069
%T Hazard ratio funnel plots for survival comparisons.
%U http://www.ncbi.nlm.nih.gov/pubmed/19542076
%V 63
%X BACKGROUND: Funnel plots are a form of control chart that give a snapshot of many institutions at a particular moment in time. This paper describes how funnel plots may be constructed for survival analyses based on hazard ratios obtained from a Cox regression model with adjustment for covariates and allowance for overdispersion. METHOD: Analysis of simulated and real survival data. RESULTS: It describes how centred hazard ratio estimates adjusted for covariates can be obtained from a Cox regression and gives details of the necessary programming in Stata. Allowance for overdispersion can be made by multiplying the standard errors by a factor based on either the model or the log-rank chi(2) statistics. Simulated results and a real example are presented. CONCLUSION: Funnel plots based on hazard ratios are easier to interpret than multiple Kaplan-Meier survival plots, and in contrast to funnel plots based on survival at, say, 5 years, are less open to accusations of bias and use more information. The interpretation of such plots may be enhanced by using standard meta-analysis methods. Hazard ratio comparisons may now be added to the repertoire of techniques used by Cancer Registries, Primary Care Trusts, and other commissioners of healthcare.
%@ 1470-2738
@article{Silcocks2009,
abstract = {BACKGROUND: Funnel plots are a form of control chart that give a snapshot of many institutions at a particular moment in time. This paper describes how funnel plots may be constructed for survival analyses based on hazard ratios obtained from a Cox regression model with adjustment for covariates and allowance for overdispersion. METHOD: Analysis of simulated and real survival data. RESULTS: It describes how centred hazard ratio estimates adjusted for covariates can be obtained from a Cox regression and gives details of the necessary programming in Stata. Allowance for overdispersion can be made by multiplying the standard errors by a factor based on either the model or the log-rank chi(2) statistics. Simulated results and a real example are presented. CONCLUSION: Funnel plots based on hazard ratios are easier to interpret than multiple Kaplan-Meier survival plots, and in contrast to funnel plots based on survival at, say, 5 years, are less open to accusations of bias and use more information. The interpretation of such plots may be enhanced by using standard meta-analysis methods. Hazard ratio comparisons may now be added to the repertoire of techniques used by Cancer Registries, Primary Care Trusts, and other commissioners of healthcare.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Silcocks, P},
biburl = {https://www.bibsonomy.org/bibtex/2ae2079b6af08b33bac86c9be4fc87c80/jepcastel},
city = {and the NIHR Research Design Service for the East Midlands, United Kingdom.},
doi = {10.1136/jech.2008.075069},
interhash = {6bbb4837389256d806dcfd84ed34f2b2},
intrahash = {ae2079b6af08b33bac86c9be4fc87c80},
isbn = {1470-2738},
issn = {1470-2738},
journal = {Journal of epidemiology and community health},
keywords = {DataDisplay Humans Models ProportionalHazardsModels Statistical SurvivalAnalysis},
month = {10},
note = {5278<m:linebreak></m:linebreak>JID: 7909766; aheadofprint;<m:linebreak></m:linebreak>Anàlisi de supervivència},
number = 10,
pages = {856-61},
pmid = {19542076},
timestamp = {2023-02-03T11:44:35.000+0100},
title = {Hazard ratio funnel plots for survival comparisons.},
url = {http://www.ncbi.nlm.nih.gov/pubmed/19542076},
volume = 63,
year = 2009
}