1. Capocaccia R, Gatta G, Roazzi P, Carrani E, Santaquilani M, De Angelis R, Tavilla A; The EUROCARE Working Group. The EUROCARE-3 database: methodology of data collection, standardisation, quality control and statistical analysis (full text PDF). Ann Oncol. 2003;14 Suppl 5:V14-V27.

2. Roazzi P, Capocaccia R, Santaquilani M, Carrani E; The EUROCARE Working Group. Electronic availability of EUROCARE-3 data: a tool for further analysis (full text PDF). Ann Oncol. 2003;14 Suppl 5:V150-V155.

3. De Angelis R, Capocaccia R, Hakulinen T, Soderman B, Verdecchia A. Mixture models for cancer survival analysis: application to population-based data with covariates. Stat Med. 1999 Feb 28;18(4):441-54.

4. De Angelis R, Capocaccia R, Verdecchia A. Estimating relative survival of Italian cancer patients from sparse cancer registries data. Tumori 1997 Jan-Feb;83(1):33-8.

5. Hakulinen T. Cancer survival corrected for heterogeneity in patient withdrawal. Biometrics. 1982 Dec;38(4):933-42.

6. Hakulinen T, Abeywickrama KH. A computer program package for relative survival analysis. Comput Programs Biomed. 1985;19(2-3):197-207.

1. Brenner H, Arndt V. Long-Term Survival Rates of Patients With Prostate Cancer in the Prostate-Specific Antigen Screening Era: Population-Based Estimates for the Year 2000 by Period Analysis. J Clin Oncol. 2004 Nov 30;

2. Brenner H, Rachet B. Hybrid analysis for up-to-date long-term survival rates in cancer registries with delayed recording of incident cases. Eur J Cancer. 2004 Nov;40(16):2494-501.

3. Brenner H, Arndt V, Gefeller O, Hakulinen T. An alternative approach to age adjustment of cancer survival rates. Eur J Cancer. 2004 Oct;40(15):2317-22.

4. Brenner H, Gefeller O, Hakulinen T. Period analysis for 'up-to-date' cancer survival data: theory, empirical evaluation, computational realisation and applications. Eur J Cancer. 2004 Feb;40(3):326-35.

5. Brenner H, Hakulinen T. Are patients diagnosed with breast cancer before age 50 years ever cured? J Clin Oncol. 2004 Feb 1;22(3):432-8. Epub 2003 Dec 22.

6. Brenner H, Hakulinen T. On crude and age-adjusted relative survival rates. J Clin Epidemiol. 2003 Dec;56(12):1185-91.

7. Brenner H, Spix C. Combining cohort and period methods for retrospective time trend analyses of long-term cancer patient survival rates. Br J Cancer. 2003 Oct 6;89(7):1260-5.

8. Brenner H. Up-to-date survival curves of children with cancer by period analysis. Br J Cancer. 2003 Jun 2;88(11):1693-7.

9. Brenner H, Hakulinen T. Very-long-term survival rates of patients with cancer. J Clin Oncol. 2002 Nov 1;20(21):4405-9.

10. Brenner H. Long-term survival rates of cancer patients achieved by the end of the 20th century: a period analysis. Lancet. 2002 Oct 12;360(9340):1131-5.

11. Brenner H, Hakulinen T. Advanced detection of time trends in long-term cancer patient survival: experience from 50 years of cancer registration in Finland. Am J Epidemiol. 2002 Sep 15;156(6):566-77.

12. Brenner H, Hakulinen T, Gefeller O. Computational realization of period analysis for monitoring cancer patient survival. Epidemiology. 2002 Sep;13(5):611-2.

13. Brenner H, Soderman B, Hakulinen T. Use of period analysis for providing more up-to-date estimates of long-term survival rates: empirical evaluation among 370,000 cancer patients in Finland. Int J Epidemiol. 2002 Apr;31(2):456-62.

14. Brenner H, Gefeller O, Hakulinen T. A computer program for period analysis of cancer patient survival. Eur J Cancer. 2002 Mar;38(5):690-5.

15. Brenner H, Hakulinen T. Up-to-date long-term survival curves of patients with cancer by period analysis. J Clin Oncol. 2002 Feb 1;20(3):826-32.

16. Brenner H, Kaatsch P, Burkhardt-Hammer T, Harms DO, Schrappe M, Michaelis J. Long-term survival of children with leukemia achieved by the end of the second millennium. Cancer. 2001 Oct 1;92(7):1977-83.

17. Brenner H, Gefeller O, Stegmaier C, Ziegler H. More up-to-date monitoring of long-term survival rates by cancer registries: an empirical example. Methods Inf Med. 2001 Jul;40(3):248-52.

18. Brenner H, Hakulinen T. Long-term cancer patient survival achieved by the end of the 20th century: most up-to-date estimates from the nationwide Finnish cancer registry. Br J Cancer. 2001 Aug 3;85(3):367-71.

19. Brenner H, Gefeller O. Deriving more up-to-date estimates of long-term patient survival. J Clin Epidemiol. 1997 Feb;50(2):211-6.

20. Brenner H, Gefeller O. An alternative approach to monitoring cancer patient survival. Cancer. 1996 Nov 1;78(9):2004-10.

21. Arndt V, Talback M, Gefeller O, Hakulinen T, Brenner H. Modification of SAS macros for a more efficient analysis of relative survival rates. Eur J Cancer. 2004 Mar;40(5):778-9.

Prevalence methods

1. Verdecchia A, De Angelis G, Capocaccia R. Estimation and projections of cancer prevalence from cancer registry data. Stat Med. 2002 Nov 30;21(22):3511-26.

2. Capocaccia R, Colonna M, Corazziari I, De Angelis R, Francisci S, Micheli A, Mugno E; EUROPREVAL Working Group. Measuring cancer prevalence in Europe: the EUROPREVAL project. Ann Oncol. 2002 Jun;13(6):831-9.

3. Corazziari I, Mariotto A, Capocaccia R. Correcting the completeness bias of observed prevalence. Tumori 1999 Sep-Oct;85(5):370-81.

4. Capocaccia R, De Angelis R. Estimating the completeness of prevalence based on cancer registry data. Stat Med 1997 Feb 28;16(4):425- 40.

5. Krogh V, Micheli A. Measure of cancer prevalence with a computerized program: an example on larynx cancer. Tumori. 1996 May-Jun;82(3):287-90.

Incidence methods

1. Stracci F, Sacchettini C. Italian Network of Cancer Registries. Methods. Epidemiol Prev. 2004 Mar-Apr;28(2 Suppl):12-6.

Morbidity methods

1. De Angelis G, De Angelis R, Frova L, Verdecchia A. MIAMOD: a computer package to estimate chronic disease morbidity using mortality and survival data. Comput Methods Programs Biomed 1994 Aug;44(2):99-107.

2. Verdecchia A, Capocaccia R, Egidi V, Golini A. A method for the estimation of chronic disease morbidity and trends from mortality data. Stat Med. 1989 Feb;8(2):201-16.