Comparison of methods for calculating relative survival in population-based studies

Cancer Epidemiology

Volumn 36, Issue 1, 2012, Pages 16-21

  Rutherford, Mark J ^a   Dickman, Paul W ^b   Lambert, Paul C ^a,b  

^a UNIVERSITY OF LEICESTER   (United Kingdom)

^b KAROLINSKA INSTITUTE   (Sweden)

Author keywords

Age standardisation; Cancer registries; Population based studies; Relative survival

Indexed keywords

ADULT; AGE DISTRIBUTION; AGED; ARTICLE; CANCER SURVIVAL; COHORT ANALYSIS; CONTROLLED STUDY; FINLAND; FOLLOW UP; HUMAN; INTERMETHOD COMPARISON; POPULATION RESEARCH; PRIORITY JOURNAL; SIMULATION; THYROID CANCER;

AGE FACTORS; AGED; COMPUTER SIMULATION; FINLAND; HUMANS; MIDDLE AGED; MODELS, STATISTICAL; NEOPLASMS; POISSON DISTRIBUTION; REGISTRIES; SURVIVAL ANALYSIS; THYROID NEOPLASMS;

EID: 84855830952     PISSN: 18777821     EISSN: 1877783X     Source Type: Journal    
DOI: 10.1016/j.canep.2011.05.010     Document Type: Article

References (23)

1. Ederer F., Axtell L., SJ C. The relative survival rate: a statistical methodology. National Cancer Inst Monogr 1961, 6:101-121.
2. Ederer F., Heise H. Instructions to IBM 650 programmers in processing survival computations. Methodogical note no. 10, end results evaluation section 1959, National Cancer Institute, Bethseda, MD.
3. Hakulinen T. Cancer survival corrected for heterogeneity in patient withdrawal. Biometrics 1982, 38(December (4)):933-942.
4. Dickman P.W., Sloggett A., Hills M., Hakulinen T. Regression models for relative survival. Stat Med 2004, 23:51-64.
5. Hakulinen T., Tenkanen L. Regression analysis of relative survival rates. J R Stat Soc Ser C: Appl Stat 1987, 36(3):309-317.
6. Nelson C.P., Lambert P.C., Squire I.B., Jones D.R. Flexible parametric models for relative survival, with application in coronary heart disease. Stat Med 2007, 26(December):5486-5498.
7. Estève J., Benhamou E., Croasdale M., Raymond L. Relative survival and the estimation of net survival: elements for further discussion. Stat Med 1990, 9(5):529-538.
8. Brenner H., Hakulinen T. Period versus cohort modeling of up-to-date cancer survival. Int J Cancer 2008, 122(4):898-904.
9. Gondos A., Holleczek B., Janssen-Heijnen M., Brewster D.H., Bray F., Rosso S., et al. Model-based projections for deriving up-to-date cancer survival estimates: an international evaluation. Int J Cancer 2009, 125(11):2666-2672.
10. Lambert P.C., Smith L.K., Jones D.R., Botha J.L. Additive and multiplicative covariate regression models for relative survival incorporating fractional polynomials for time-dependent effects. Stat Med 2005, 24(24):3871-3885.
11. Talbäck M., Rosén M., Stenbeck M., Dickman P.W. Cancer patient survival in Sweden at the beginning of the third millennium-predictions using period analysis. Cancer Causes Control 2004, 15(November):967-976.
12. Pulte D., Gondos A., Brenner H. Expected long-term survival of patients diagnosed with acute myeloblastic leukemia during 2006-2010. Ann Oncol 2009, mdp309.
13. Reeves G.K., Beral V., Bull D., Quinn M. Estimating relative survival among people registered with cancer in England and Wales. Br J Cancer 1999, 79(January):18-22.
14. Lambert P.C., Royston P. Further development of flexible parametric models for survival analysis. Stata J 2009, 9(2):265-290.
15. Hakulinen T. On long-term relative survival rates. J Chronic Dis 1977, 30(7):431-443.
16. Pokhrel A., Hakulinen T. How to interpret the relative survival ratios of cancer patients. Eur J Cancer 2008, 44(17):2661-2667.
17. Bender R., Augustin T., Blettner M. Generating survival times to simulate Cox proportional hazards models. Stat Med 2005, 24(11):1713-1723.
18. Brenner H., Gefeller O. An alternative approach to monitoring cancer patient survival. Cancer 1996, 78(9):2004-2010.
19. Smith L.K., Lambert P.C., Botha J.L., Jones D.R. Providing more up-to-date estimates of patient survival: a comparison of standard survival analysis with period analysis using life-table methods and proportional hazards models. J Clin Epidemiol 2004 Jan, 57(January):14-20.
20. Remontet L., Bossard N., Belot A., Estève J. An overall strategy based on regression models to estimate relative survival and model the effects of prognostic factors in cancer survival studies. Stat. Med. 2007, 26(10):2214-2228.
21. Perme M.P., Henderson R., Stare J. An approach to estimation in relative survival regression. Biostatistics 2009, 10(1):136-146.
22. Brenner H., Arndt V., Gefeller O., Hakulinen T. An alternative approach to age adjustment of cancer survival rates. Eur J Cancer 2004, 40(15):2317-2322.
23. Brenner H., Hakulinen T. On crude and age-adjusted relative survival rates. J Clin Epidemiol 2003, 56(December):1185-1191.