Estimating and modeling relative survival

Stata Journal

Volumn 15, Issue 1, 2015, Pages 186-215

  Dickman, Paul W ^a   Coviello, Enzo ^b  

^a KAROLINSKA INSTITUTE   (Sweden)

^b Statistics and Epidemiology Unit   (Italy)

Author keywords

Cancer survival; Excess mortality; Life table; Period analysis; Poisson regression; Relative survival; st0376; strs; Survival analysis

Indexed keywords

EID: 85011378072     PISSN: 1536867X     EISSN: 15368734     Source Type: Journal    
DOI: 10.1177/1536867x1501500112     Document Type: Article

References (40)

1. Berkson, J. 1942. The calculation of survival rates. In Carcinoma and Other Malignant Lesions of the Stomach, ed. W. Walters, H. K. Gray, and J. T. Priestly, 467-484. Philadelphia: Sanders.
2. Brenner, H., V. Arndt, O. Gefeller, and T. Hakulinen. 2004. An alternative approach to age adjustment of cancer survival rates. European Journal of Cancer 40: 2317-2322.
3. Brenner, H., and O. Gefeller. 1996. An alternative approach to monitoring cancer patient survival. Cancer 78: 2004-2010.
4. Brenner, H., and T. Hakulinen. 2004. Are patients diagnosed with breast cancer before age 50 years ever cured? Journal of Clinical Oncology 22: 432-438.
5. Brenner, H., and T. Hakulinen. 2005. Age adjustment of cancer survival rates: Methods, point estimates and standard errors. British Journal of Cancer 93: 372-375.
6. Brenner, H., and T. Hakulinen. 2009. Up-to-date cancer survival: Period analysis and beyond. International Journal of Cancer 124: 1384-1390.
7. Brenner, H., and B. Rachet. 2004. Hybrid analysis for up-to-date long-term survival rates in cancer registries with delayed recording of incident cases. European Journal of Cancer 40: 2494-2501.
8. Breslow, N. E., and N. E. Day. 1987. Statistical Methods in Cancer Research: Vol. 2—The Design and Analysis of Cohort Studies. Lyon: IARC.
9. Coleman, M. P., P. Babb, P. Damiecki, P. Grosclaude, S. Honjo, J. Jones, G. Knerer, A. Pitard, M. Quinn, A. Sloggett, and B. De Stavola. 1999. Cancer Survival Trends in England and Wales, 1971–1995: Deprivation and NHS Region. London: Stationery Office.
10. Coviello, E., P. W. Dickman, K. Seppä, and A. Pokhrel. 2015. Estimating net survival using a life-table approach. Stata Journal 15: 173-185.
11. Coviello, V., and M. Boggess. 2004. Cumulative incidence estimation in the presence of competing risks. Stata Journal 4: 103-112.
12. Cronin, K. A., and E. J. Feuer. 2000. Cumulative cause-specific mortality for cancer patients in the presence of other causes: A crude analogue of relative survival. Statistics in Medicine 19: 1729-1740.
13. Danieli, C., L. Remontet, N. Bossard, L. Roche, and A. Belot. 2012. Estimating net survival: The importance of allowing for informative censoring. Statistics in Medicine 31: 775-786.
14. Dickman, P. W., and H. O. Adami. 2006. Interpreting trends in cancer patient survival. Journal of Internal Medicine 260: 103-117.
15. Dickman, P. W., A. Sloggett, M. Hills, and T. Hakulinen. 2004. Regression models for relative survival. Statistics in Medicine 23: 51-64.
16. Ederer, F., L. M. Axtell, and S. J. Cutler. 1961. The relative survival rate: A statistical methodology. National Cancer Institute Monograph 6: 101-121.
17. Ederer, F., and H. Heise. 1959. Instructions to IBM 650 programmers in processing survival computations, methodological note 10. End Results Evaluation Section, National Cancer Institute.
18. Eloranta, S., J. Adolfsson, P. C. Lambert, P. Stattin, O. Akre, T. M.-L. Andersson, and P. W. Dickman. 2013. How can we make cancer survival statistics more useful for patients and clinicians: An illustration using localized prostate cancer in Sweden. Cancer Causes Control 24: 505-515.
19. Estève, J., E. Benhamou, M. Croasdale, and L. Raymond. 1990. Relative survival and the estimation of net survival: Elements for further discussion. Statistics in Medicine 9: 529-538.
20. Gamel, J. W., and R. L. Vogel. 2001. Non-parametric comparison of relative versus cause-specific survival in Surveillance, Epidemiology and End Results (SEER) programme breast cancer patients. Statistical Methods in Medical Research 10: 339-352.
21. Giorgi, R., M. Abrahamowicz, C. Quantin, P. Bolard, J. Estève, J. Gouvernet, and J. Faivre. 2003. A relative survival regression model using B-spline functions to model non-proportional hazards. Statistics in Medicine 22: 2767-2784.
22. Greenwood, M. 1926. The errors of sampling of the survivorship table. In Reports on Public Health and Medical Subjects, Volume 33. London: Her Majesty’s Stationery Office.
23. Hakulinen, T. 1977. On long-term relative survival rates. Journal of Chronic Diseases 30: 431-443.
24. Hakulinen, T. 1982. Cancer survival corrected for heterogeneity in patient withdrawal. Biometrics 38: 933-942.
25. Hakulinen, T., K. Seppä, and P. C. Lambert. 2011. Choosing the relative survival method for cancer survival estimation. European Journal of Cancer47: 2202-2210.
26. Hakulinen, T., and L. Tenkanen. 1987. Regression analyses of relative survival rates. Applied Statistics 36: 309-317.
27. Hinchliffe, S. R., and P. C. Lambert. 2013. Extending the flexible parametric survival model for competing risks. Stata Journal 13: 344-355.
28. Howlader, N., L. A. G. Ries, A. B. Mariotto, M. E. Reichman, J. Ruhl, and K. A. Cronin. 2010. Improved estimates of cancer-specific survival rates from populationbased data. Journal of the National Cancer Institute 102: 1584-1598.
29. Lambert, P. C., P. W. Dickman, and M. J. Rutherford. 2014. Comparison of approaches to estimating age-standardized net survival. Submitted.
30. Lambert, P. C., P. W. Dickman, C. L. Weston, and J. R. Thompson. 2010. Estimating the cure fraction in population-based cancer studies by using finite mixture models. Journal of the Royal Statistical Society, Series C 59: 35-55.
31. Lambert, P. C., and P. Royston. 2009. Further development of flexible parametric models for survival analysis. Stata Journal 9: 265-290.
32. Lambert, P. C., L. K. Smith, D. R. Jones, and J. L. Botha. 2005. Additive and multiplicative covariate regression models for relative survival incorporating fractional polynomials for time-dependent effects. Statistics in Medicine 24: 3871-3885.
33. Nelson, C. P., P. C. Lambert, I. B. Squire, and D. R. Jones. 2008. Relative survival: What can cardiovascular disease learn from cancer? European Heart Journal 29: 941-947.
34. Pohar Perme, M., J. Stare, and J. Estève. 2012. On estimation in relative survival. Biometrics 68: 113-120.
35. Pokhrel, A., and T. Hakulinen. 2008. How to interpret the relative survival ratios of cancer patients. European Journal of Cancer 44: 2661-2667.
36. Pokhrel, A., and T. Hakulinen. 2009. Age-standardisation of relative survival ratios of cancer patients in a comparison between countries, genders and time periods. European Journal of Cancer 45: 642-647.
37. Rutherford, M. J., P. W. Dickman, and P. C. Lambert. 2012. Comparison of methods for calculating relative survival in population-based studies. Cancer Epidemiology 36: 16-21.
38. Seppä, K., T. Hakulinen, and A. Pokhrel. Forthcoming. Choosing the net survival method for cancer survival estimation. European Journal of Cancer.
39. Suissa, S. 1999. Relative excess risk: An alternative measure of competitve risk. American Journal of Epidemiology 150: 279-282.
40. Tsiatis, A. A. 2005. Competing Risks. In Encyclopedia of Biostatistics, ed. P. Armitage and T. Colton, 2nd ed., 1025-1035. Chichester, UK: Wiley.