P Silcocks1. 1. Trent Cancer Registry, and NIHR Research Design Service for East Midlands, Nottingham, UK. paul.silcocks@nhs.net
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.
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.
Authors: Sandy L Kwong; Susan L Stewart; Christopher A Aoki; Moon S Chen Journal: Cancer Epidemiol Biomarkers Prev Date: 2010-09-07 Impact factor: 4.254