Challenges in the estimation of Net SURvival: The CENSUR working survival group
Tài liệu tham khảo
Muir, 1985, The cancer registry in cancer control: an overview
Parkin, 2008, The role of cancer registries in cancer control, Int J Clin Oncol, 13, 102, 10.1007/s10147-008-0762-6
Sant, 2007, Ten-year survival and risk of relapse for testicular cancer: a EUROCARE high resolution study, Eur J Cancer, 43, 585, 10.1016/j.ejca.2006.11.006
Allemani, 2013, Breast cancer survival in the US and Europe: a CONCORD high-resolution study, Int J Cancer, 132, 1170, 10.1002/ijc.27725
Percy, 1981, Accuracy of cancer death certificates and its effect on cancer mortality statistics, Am J Public Health, 71, 242, 10.2105/AJPH.71.3.242
Berkson, 1950, Calculation of survival rates for cancer, Mayo Clinic, 25, 270
Jensen, 1991, Purposes and uses of cancer registration
Ellis, 2014, Cancer incidence, survival and mortality: explaining the concepts, Int J Cancer, 135, 1774, 10.1002/ijc.28990
Estève, 1994
Perme, 2012, On estimation in relative survival, Biometrics, 68, 113, 10.1111/j.1541-0420.2011.01640.x
Danieli, 2012, Estimating net survival: the importance of allowing for informative censoring, Stat Med, 31, 775, 10.1002/sim.4464
Jooste, 2013, French Network of Cancer Registries (FRANCIM). Unbiased estimates of long-term net survival of solid cancers in France, Int J Cancer, 132, 2370, 10.1002/ijc.27857
De Angelis, 2014, Cancer survival in europe 1999–2007 by country and age: results of EUROCARE-5 – a population-based study, Lancet Oncol, 15, 23, 10.1016/S1470-2045(13)70546-1
Howlader, 2011
Coleman, 2008, Cancer survival in five continents: a worldwide population-based study (CONCORD), Lancet Oncol, 9, 730, 10.1016/S1470-2045(08)70179-7
Giorgi, 2005, Regression models for crude and relative survival: a comparative review, Rev Epidemiol Sante Publique, 53, 409, 10.1016/S0398-7620(05)84623-1
Putter, 2007, Tutorial in biostatistics: competing risks and multi-state models, Stat Med, 26, 2389, 10.1002/sim.2712
Ederer, 1959
Ederer, 1961, The relative survival rate: a statistical methodology, Natl Cancer Institute Monogr, 6, 101
Hakulinen, 1982, Cancer survival corrected for heterogeneity in patient withdrawal, Biometrics, 38, 933, 10.2307/2529873
Robins, 1993, Information recovery and bias adjustment in proportional hazards regression analysis of randomized trials using surrogate markers, 24
Estève, 1990, Relative survival and the estimation of net survival: elements for further discussion, Stat Med, 9, 529, 10.1002/sim.4780090506
Giorgi, 2003, A relative survival regression model using B-spline functions to model non-proportional hazards, Stat Med, 22, 2767, 10.1002/sim.1484
Dickman, 2004, Regression models for relative survival, Stat Med, 23, 51, 10.1002/sim.1597
Remontet, 2007, An overall strategy based on regression models to estimate relative survival and model the effects of prognostic factors in cancer survival studies, Stat Med, 26, 2214, 10.1002/sim.2656
Roche, 2013, Cancer net survival on registry data: use of the new unbiased Pohar-Perme estimator and magnitude of the bias with the classical methods, Int J Cancer, 132, 2359, 10.1002/ijc.27830
Grosclaude, 2013, 1
Montet, 2016
Monnereau, 2016
Grafféo, 2012, The impact of additional life-table variables on excess mortality estimates, Stat Med, 31, 4219, 10.1002/sim.5493
Dupont, 2013, Description of an approach based on maximum likelihood to adjust an excess hazard model with a random effect, Cancer Epidemiol, 37, 449, 10.1016/j.canep.2013.04.001
Belot, 2014, A joint frailty model to estimate the recurrence process and the disease-specific mortality process without needing the cause of death, Stat Med, 33, 3147, 10.1002/sim.6140
Monnereau, 2013, Unbiased estimates of long-term net survival of haematological malignancy patients detailed by major subtypes in France, Int J Cancer, 132, 2378, 10.1002/ijc.27889
Pohar, 2006, Relative survival analysis in R, Comput Methods Programs Biomed, 81, 272, 10.1016/j.cmpb.2006.01.004
Clerc-Urmès, 2014, Net survival estimation with stns, Stata J, 14, 87, 10.1177/1536867X1401400107
Grafféo, 2016, A log-rank-type test to compare net survival distributions, Biometrics, 72, 760, 10.1111/biom.12477
Mounier, 2015, Trends in excess mortality in follicular lymphoma at a population level, Eur J Haematol, 94, 120, 10.1111/ejh.12403
Mounier, 2015, Changes in dynamics of excess mortality rates and net survival after diagnosis of follicular lymphoma or diffuse large B-cell lymphoma: comparison between European population-based data (EUROCARE-5), Lancet Heamatol, 2, e481, 10.1016/S2352-3026(15)00155-6
Grzebyk M Flexrsurv: Flexible relative survival. R package version 1.3.
Meyer, 2014, Big data for population-based cancer research: the integrated cancer information and surveillance system, NC Med J, 75, 265