periodR - an R package to calculate long-term cancer survival estimates using period analysis.
OBJECTIVE
In this paper, a software package for the R language and system for statistical computing is presented for computation of long-term cancer survival estimates based on the period analysis approach. The period analysis approach provides up-to-date long-term survival estimates of concurrently diagnosed patients, enables early detection of recent changes in long-term prognosis of cancer patients and provides better survival predictions for recently and currently diagnosed patients than traditional cohort-based approaches.


METHODS
Computation of absolute and relative survival estimates (both conditional follow-up year-specific and cumulative survival estimates) and their standard errors is based on standard actuarial methodology. For relative survival estimation the "Ederer II" and "Hakulinen" method were implemented.


RESULTS
The package may be used for period analysis as well as traditional cohort-based survival estimation. The package further provides functions for the export of survival estimates for use with spreadsheet programs and for plotting survival curves. The application of period analysis is illustrated using stomach cancer data included in the package.


CONCLUSIONS
Application of period analysis has gradually increased in recent years but continues to be limited by availability of affordable and easy-to-use software tools. The presented R package aims at closing this gap and will further facilitate the use of period analysis for the research community working with population-based cancer registry data. The software is freely available for download on the website of the Saarland Cancer Registry at http://www.krebsregister.saarland.de/improve/periodR_en.html.
Holleczek
Bernd
B
Saarland Cancer Registry, Präsident-Baltz-Strasse 5, 66119 Saarbrücken, Germany. b.holleczek@gbe-ekr.saarland.de
Gondos
A
A
Brenner
H
H
D015331:Cohort Studies; D006801:Humans; D015233:Models, Statistical; D009369:Neoplasms / Q000401:mortality*; D011379:Prognosis; D018570:Risk Assessment; D012984:Software; D016019:Survival Analysis; D017741:Survivors