S. Narod, Can advanced-stage ovarian cancer be cured?, Nat Rev Clin Oncol, vol.13, pp.255-61, 2016.

M. J. Crowder, Multivariate Survival Analysis and Competing Risks

R. Giorgi, Challenges in the estimation of net SURvival: the CENSUR working survival group, Rev Epidemiol Sante Publique, vol.64, pp.367-71, 2016.

J. J. Dignam, L. Huang, L. Ries, M. Reichman, A. Mariotto et al., Estimating breast Cancer-specific and other-cause mortality in clinical trial and population-based Cancer registry cohorts, Cancer, vol.115, pp.5272-83, 2009.

R. Schaffar, B. Rachet, A. Belot, and L. M. Woods, Estimation of net survival for cancer patients: relative survival setting more robust to some assumption violations than cause-specific setting, a sensitivity analysis on empirical data, Eur J Cancer, vol.72, pp.78-83, 2017.

P. S. Pinheiro, C. R. Morris, L. Liu, T. J. Bungum, and S. F. Altekruse, The impact of followup type and missed deaths on population-based cancer survival studies for Hispanics and Asians, J Natl Cancer Inst Monogr, pp.210-217, 2014.

C. Percy, . Stanek-e-3rd, and L. Gloeckler, Accuracy of cancer death certificates and its effect on cancer mortality statistics, Am J Public Health, vol.71, pp.242-50, 1981.

K. D. Skyrud, F. Bray, and B. Møller, A comparison of relative and cause-specific survival by cancer site, age and time since diagnosis, Int J Cancer, vol.135, pp.196-203, 2014.

D. Sarfati, T. Blakely, and N. Pearce, Measuring cancer survival in populations: relative survival vs cancer-specific survival, Int J Epidemiol, vol.39, pp.598-610, 2010.

B. Van-rompaye, S. Jaffar, and E. Goetghebeur, Estimation with Cox models: cause-specific survival analysis with misclassified cause of failure, Epidemiology, vol.23, pp.194-202, 2012.

J. M. Robins, Information recovery and bias adjustment in proportional hazards regression analysis of randomized trials using surrogate markers, Proceedings of the biopharmaceutical section, p.3, 1993.

M. P. Perme, J. Stare, and J. Estève, On estimation in relative survival, Biometrics, vol.68, pp.113-133, 2012.

S. Komukai and S. Hattori, Doubly robust estimator for net survival rate in analyses of cancer registry data, Biometrics, vol.73, pp.124-157, 2017.

J. Esteve, E. Benhamou, M. Croasdale, and L. Raymond, Relative survival and the estimation of net survival: elements for further discussion, Stat Med, vol.9, pp.529-567, 1990.

R. Giorgi, M. Abrahamowicz, C. Quantin, P. Bolard, J. Esteve et al., A relative survival regression model using B-spline functions to model nonproportional hazards, Stat Med, vol.22, pp.2767-84, 2003.
URL : https://hal.archives-ouvertes.fr/hal-00427428

L. Remontet, N. Bossard, A. Belot, and J. Esteve, An overall strategy based on regression models to estimate relative survival and model the effects of prognostic factors in cancer survival studies, Stat Med, vol.26, pp.2214-2242, 2007.
URL : https://hal.archives-ouvertes.fr/hal-00492901

C. Danieli, L. Remontet, N. Bossard, L. Roche, and A. Belot, Estimating net survival: the importance of allowing for informative censoring, Stat Med, vol.31, pp.775-86, 2012.
URL : https://hal.archives-ouvertes.fr/hal-02296991

R. Schaffar, B. Rachet, A. Belot, and L. Woods, Cause-specific or relative survival setting to estimate population-based net survival from cancer? An empirical evaluation using women diagnosed with breast cancer in Geneva between 1981 and 1991 and followed for 20 years after diagnosis, Cancer Epidemiol, vol.39, pp.465-72, 2015.

B. Cheuvart and L. Ryan, Adjusting for age-related competing mortality in longterm cancer clinical trials, Statist Med, vol.10, pp.65-77, 1991.

N. E. Breslow, Contribution to discussion of papeer by DR Cox, J Roy Statist Assoc, B, vol.34, pp.216-223, 1972.

D. R. Cox, Regression models and life-tables, J R Stat Soc Ser B Methodol, vol.34, pp.187-202, 1972.

R. H. Byrd, P. Lu, J. Nocedal, and C. Zhu, A limited memory algorithm for bound constrained optimization, SIAM J Sci Comput, vol.16, pp.1190-208, 1995.

N. Grafféo, F. Castell, A. Belot, and R. Giorgi, A log-rank-type test to compare net survival distributions, Biometrics, vol.72, pp.760-769, 2016.

J. Jais, H. Varet, and . Survexp, Fr: relative survival, AER and SMR based on French death rates (R package version 1.0)

D. P. Byar and S. B. Green, The choice of treatment for cancer patients based on covariate information, Bull Cancer, vol.67, pp.477-90, 1980.

D. Andrews and A. Herzberg, Prognostic variables for survival in a randomized comparison of treatments for prostatic cancer, pp.261-74, 1985.

A. Augustin, L. Gouill, S. Gressin, R. Bertaut, A. Monnereau et al., Survival benefit of mantle cell lymphoma patients enrolled in clinical trials; a joint study from the LYSA group and French cancer registries, J Cancer Res Clin Oncol, vol.144, pp.629-664, 2017.
URL : https://hal.archives-ouvertes.fr/inserm-01624838

J. A. Goungounga and R. Giorgi, Commentary on: survival benefit of mantle cell lymphoma patients enrolled in clinical trials; a joint study from the LYSA group and French cancer registries, J Cancer Res Clin Oncol, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01873143

C. J. Newschaffer, K. Otani, M. K. Mcdonald, and L. T. Penberthy, Causes of death in elderly prostate Cancer patients and in a comparison nonprostate Cancer cohort, J Natl Cancer Inst, vol.92, pp.613-634, 2000.

P. Baili, A. Micheli, R. De-angelis, H. K. Weir, S. Francisci et al., Life tables for world-wide comparison of relative survival for cancer (CONCORD study), Tumori, vol.94, p.658, 2008.

A. M. Stroup, H. Cho, S. M. Scoppa, H. K. Weir, and A. B. Mariotto, The impact of statespecific life tables on relative survival, J Natl Cancer Inst Monogr, pp.218-245, 2014.

A. Morisot, F. Bessaoud, P. Landais, X. Rébillard, B. Trétarre et al., Prostate cancer: net survival and cause-specific survival rates after multiple imputation, BMC Med Res Methodol, vol.15, p.54, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01913539

B. Penninckx, W. M. Van-de-voorde, A. Casado, N. Reed, C. Moulin et al., A systemic review of toxic death in clinical oncology trials: an Achilles' heel in safety reporting revisited, Br J Cancer, vol.107, pp.1-6, 2012.

P. H. Zahl, A linear non-parametric regression model for the excess intensity, Scand J Stat, vol.23, pp.353-64, 1996.

J. Kalbfleisch and R. Prentice, In: The statistical analysis of failure time data, pp.247-77, 2011.

A. R. Kodre and M. P. Perme, Informative censoring in relative survival, Stat Med, vol.32, pp.4791-802, 2013.

N. Grafféo, V. Jooste, and G. R. , The impact of additional life-table variables on excess mortality estimates, Stat Med, vol.31, pp.4219-4249, 2012.

K. Pavli?, P. Perme, and M. , Using pseudo-observations for estimation in relative survival, Biostatistics, 2018.