Flexible parametric models for relative survival, with application in coronary heart disease.
Relative survival is frequently used in population-based studies as a method for estimating disease-related mortality without the need for information on cause of death. We propose an extension to relative survival of a flexible parametric model proposed by Royston and Parmar for censored survival data. The model provides smooth estimates of the relative survival and excess mortality rates by using restricted cubic splines on the log cumulative excess hazard scale. The approach has several advantages over some of the more standard relative survival models, which adopt a piecewise approach, the main being the ability to model time on a continuous scale, the survival and hazard functions are obtained analytically and it does not use split-time data.
Nelson
Christopher P
CP
Centre for Biostatistics and Genetic Epidemiology, Department of Health Sciences, University of Leicester, Leicester, U.K. cn46@le.ac.uk <cn46@le.ac.uk>
Lambert
Paul C
PC
Squire
Iain B
IB
Jones
David R
DR
D000368:Aged; D000465:Algorithms; D001699:Biometry / Q000379:methods; D003198:Computer Simulation; D003324:Coronary Artery Disease / Q000401:mortality; D003627:Data Interpretation, Statistical; D004739:England / Q000453:epidemiology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D016017:Odds Ratio; D011379:Prognosis; D012044:Regression Analysis; D013269:Stochastic Processes; D016019:Survival Analysis; D013997:Time Factors