OBJECTIVE: Standard survival methods can yield out-of-date estimates of long-term survival. Period analysis, based on life-table methodology, provides more up-to-date survival estimates by exploring survival during a restricted recent period of interest. It excludes the short-term survival of patients recruited at the start of the study. We use statistical models to further develop the method of period analysis, providing more up-to-date estimates of survival and the ability to explore differences in survival by covariates and adjust for case mix. METHODS: We use cancer registry data for colorectal cancer in Leicestershire, UK, to illustrate the use of Cox proportional hazards (CPH) models to estimate period and standard survival. We compare these estimates with those obtained using life-table methodology. RESULTS: Period estimates were slightly higher than the standard estimates as they reflect recent improvements in short-term survival. The results for period analysis using the life-table approach and using CPH models were similar. However, CPH models allowed further investigation of other risk factors and the ability to control for potential confounding variables. CONCLUSION: Using period survival estimates, more up-to-date information is available to clinicians and others with an interest in monitoring survival. Period CHP models offer all the advantages of statistical modeling, and are straightforward to fit in standard statistical packages.
OBJECTIVE: Standard survival methods can yield out-of-date estimates of long-term survival. Period analysis, based on life-table methodology, provides more up-to-date survival estimates by exploring survival during a restricted recent period of interest. It excludes the short-term survival of patients recruited at the start of the study. We use statistical models to further develop the method of period analysis, providing more up-to-date estimates of survival and the ability to explore differences in survival by covariates and adjust for case mix. METHODS: We use cancer registry data for colorectal cancer in Leicestershire, UK, to illustrate the use of Cox proportional hazards (CPH) models to estimate period and standard survival. We compare these estimates with those obtained using life-table methodology. RESULTS: Period estimates were slightly higher than the standard estimates as they reflect recent improvements in short-term survival. The results for period analysis using the life-table approach and using CPH models were similar. However, CPH models allowed further investigation of other risk factors and the ability to control for potential confounding variables. CONCLUSION: Using period survival estimates, more up-to-date information is available to clinicians and others with an interest in monitoring survival. Period CHP models offer all the advantages of statistical modeling, and are straightforward to fit in standard statistical packages.
Authors: Jenna Sykes; Sanja Stanojevic; Christopher H Goss; Bradley S Quon; Bruce C Marshall; Kristofer Petren; Josh Ostrenga; Aliza Fink; Alexander Elbert; Anne L Stephenson Journal: J Clin Epidemiol Date: 2015-10-03 Impact factor: 6.437