This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Hakulinen T, Seppä K, Lambert PC. Choosing the relative survival method for cancer survival estimation. Eur J Cancer 2011; 47: 2202–10.HakulinenTSeppäKLambertPCChoosing the relative survival method for cancer survival estimation20114722021010.1016/j.ejca.2011.03.011Search in Google Scholar
Primic-Žakelj M, Zadnik V, Žagar T, Zakotnik B. Preživetje bolnikov z rakom v Sloveniji 1991-2005. Ljubljana: Onkološki inštitut Ljubljana, Register raka RS, 2009.Primic-ŽakeljMZadnikVŽagarTZakotnikBOnkološki inštitut Ljubljana, Register raka RSLjubljana2009Search in Google Scholar
Coleman MP, Quaresma M, Berrino F, Lutz JM, De Angelis R, Capocaccia R. et al. Cancer survival in five continents: a worldwide population-based study (CONCORD). Lancet Oncol 2008; 9: 730–56.ColemanMPQuaresmaMBerrinoFLutzJMDe AngelisRCapocacciaRCancer survival in five continents: a worldwide population-based study (CONCORD)200897305610.1016/S1470-2045(08)70179-7Search in Google Scholar
Allemani C, Weir HK, Carreira H, Harewood R, Spika D, Wang XS. et al. Global surveillance of cancer survival 1995-2009: analysis of individual data for 25,676,887 patients from 279 population-based registries in 67 countries (CONCORD-2). Lancet 2015; 14: 977-1010.AllemaniCWeirHKCarreiraHHarewoodRSpikaDWangXSGlobal surveillance of cancer survival 1995-2009: analysis of individual data for 25,676,887 patients from 279 population-based registries in 67 countries (CONCORD-2)201514977101010.1016/S0140-6736(14)62038-9Search in Google Scholar
De Angelis R, Francisci S, Baili P, Marchesi F, Roazzi P, Belot A. et al. The EUROCARE-4 database on cancer survival in Europe: data standardisation, quality control and methods of statistical analysis. Eur J Cancer 2009; 45: 909–30.De AngelisRFrancisciSBailiPMarchesiFRoazziPBelotAThe EUROCARE-4 database on cancer survival in Europe: data standardisation, quality control and methods of statistical analysis2009459093010.1016/j.ejca.2008.11.003Search in Google Scholar
De Angelis R, Sant M, Coleman MP, Francisci S, Baili P, Pierannunzio D. et al. Cancer survival in Europe 1999–2007 by country and age: results of EUROCARE-5—a population-based study. Lancet Oncol 2014; 15: 23-34.De AngelisRSantMColemanMPFrancisciSBailiPPierannunzioDCancer survival in Europe 1999–2007 by country and age: results of EUROCARE-5—a population-based study201415233410.1016/S1470-2045(13)70546-1Search in Google Scholar
OECD. Health at a glance 2011: OECD indicators. Paris: OECD Publishing, 2011.OECDParisOECD Publishing2011Search in Google Scholar
OECD. Health at a glance: Europe 2014. Paris: OECD Publishing, 2014.OECDParisOECD Publishing2014Search in Google Scholar
Howlader N, Noone A, Krapcho M, Grashell J, Neyman N, Altekruse S. et al. SEER cancer statistics review, 1975-2010. Bethseda MD: National Cancer Instiutte, 2013.HowladerNNooneAKrapchoMGrashellJNeymanNAltekruseSBethseda MDNational Cancer Instiutte2013Search in Google Scholar
Engholm G, Ferlay J, Christensen N, Bray F, Gjerstorff ML, Klint A. et al. NORDCAN--a Nordic tool for cancer information, planning, quality control and research. Acta Oncol 2010; 49: 725–36.EngholmGFerlayJChristensenNBrayFGjerstorffMLKlintANORDCAN--a Nordic tool for cancer information, planning, quality control and research2010497253610.3109/0284186100378201720491528Search in Google Scholar
Zadnik V, Primic Žakelj M. SLORA. Ljubljana: Onkološki inštitut Ljubljana, 2010. Available April 25, 2015 from: www.slora.si/en.ZadnikVPrimic ŽakeljMLjubljanaOnkološki inštitut Ljubljana2010Available April 25, 2015 fromwww.slora.si/enSearch in Google Scholar
Pokhrel A, Hakulinen T. How to interpret the relative survival ratios of cancer patients. Eur J Cancer. 2008; 44(17): 2661–7.PokhrelAHakulinenTHow to interpret the relative survival ratios of cancer patients200844172661710.1016/j.ejca.2008.08.01618819791Search in Google Scholar
Roche L, Danieli C, Belot A, Grosclaude P, Bouvier AM, Velten M. et al. 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 2013; 132: 2359–69.RocheLDanieliCBelotAGrosclaudePBouvierAMVeltenMCancer net survival on registry data: use of the new unbiased Pohar-Perme estimator and magnitude of the bias with the classical methods201313223596910.1002/ijc.2783022961565Search in Google Scholar
Kaplan E, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc 1958; 53: 457–81.KaplanEMeierPNonparametric estimation from incomplete observations1958534578110.1007/978-1-4612-4380-9_25Search in Google Scholar
Sarfati D, Blakely T, Pearce N. Measuring cancer survival in populations: relative survival vs cancer-specific survival. Int J Epidemiol 2010; 39: 598–610.SarfatiDBlakelyTPearceNMeasuring cancer survival in populations: relative survival vs cancer-specific survival20103959861010.1093/ije/dyp39220142331Search in Google Scholar
Percy C, Stanek E 3rd, Gloeckler L. Accuracy of cancer death certificates and its effect on cancer mortality statistics. Am J Public Health 1981; 71: 242–50.PercyCStanekE3rdGloecklerLAccuracy of cancer death certificates and its effect on cancer mortality statistics1981712425010.2105/AJPH.71.3.242Search in Google Scholar
Primic Zakelj M, Pompe-Kirn V, Šelb-Šemrl J. Can we rely on cancer mortality data? Checking the validity of cervical cancer mortality data for Slovenia. Radiol Oncol 2001; 35: 243–7.Primic ZakeljMPompe-KirnVŠelb-ŠemrlJCan we rely on cancer mortality data? Checking the validity of cervical cancer mortality data for Slovenia2001352437Search in Google Scholar
Huang B, Guo J, Charnigo R. Statistical methods for population-based cancer survival in registry data. J Biomet Biostat 2014; 5: e129.HuangBGuoJCharnigoRStatistical methods for population-based cancer survival in registry data20145e12910.4172/2155-6180.1000e129Search in Google Scholar
Ederer F, Axtell LM, Cutler SJ. The relative survival rate: a statistical methodology. Natl Cancer Inst Monogr 1961; 6: 101–21.EdererFAxtellLMCutlerSJThe relative survival rate: a statistical methodology1961610121Search in Google Scholar
Žagar T, Zadnik V, Pohar Perme M, Primic Zakelj M. Complete yearly life tables by sex for Slovenia, 1982-2004, and their use in public health. Radiol Oncol 2006; 40: 115–24.ŽagarTZadnikVPohar PermeMPrimic ZakeljMComplete yearly life tables by sex for Slovenia, 1982-2004, and their use in public health20064011524Search in Google Scholar
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; 40: 2494–501.BrennerHRachetBHybrid analysis for up-to-date long-term survival rates in cancer registries with delayed recording of incident cases200440249450110.1016/j.ejca.2004.07.02215519525Search in Google Scholar
Dickman PW, Lambert PC, Coviello E, Rutherford MJ. Estimating net survival in population-based cancer studies. Int J Cancer 2013; 133: 519–21.DickmanPWLambertPCCovielloERutherfordMJEstimating net survival in population-based cancer studies20131335192110.1002/ijc.2804123338817Search in Google Scholar
23. 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; 40: 326–35.BrennerHGefellerOHakulinenTPeriod analysis for “up-to-date” cancer survival data: theory, empirical evaluation, computational realisation and applications2004403263510.1016/j.ejca.2003.10.01314746849Search in Google Scholar
Ederer F, Heise H. Instructions to IBM 650 programmers in processing survival computations. Bethesda MD: Technical, and Results Evaluation Section, National Cancer Institut, 1959.EdererFHeiseHBethesda MDTechnical, and Results Evaluation Section, National Cancer Institut1959Search in Google Scholar
Perme MP, Stare J, Estève J. On estimation in relative survival. Biometrics 2012; 68: 113–20PermeMPStareJEstèveJOn estimation in relative survival2012681132010.1111/j.1541-0420.2011.01640.x21689081Search in Google Scholar
Dickman P, Coviello E, Hills M. Estimating and modelling relative survival. Available April 20, 2015 from: http://www.pauldickman.com/survival/strs.pdfDickmanPCovielloEHillsMEstimating and modelling relative survivalAvailableApril202015http://www.pauldickman.com/survival/strs.pdfSearch in Google Scholar
Surveillance Research Program. SEER*Stat software. National Cancer Institute, 2013. Available April 20 2015 from: seer.cancer.gov/seerstat.Surveillance Research ProgramSEER*Stat software2013AvailableApril202015seer.cancer.gov/seerstatSearch in Google Scholar
Rachet B, Woods LM, Mitry E, Riga M, Cooper N, Quinn MJ. et al. Cancer survival in England and Wales at the end of the 20th century. Br J Cancer 2008; 99(Suppl 1): S2–10.RachetBWoodsLMMitryERigaMCooperNQuinnMJCancer survival in England and Wales at the end of the 20th century200899Suppl 1S21010.1038/sj.bjc.6604571255754518813248Search in Google Scholar
Hakulinen T. Cancer survival corrected for heterogeneity in patient withdrawal. Biometrics 1982; 38: 933–42.HakulinenTCancer survival corrected for heterogeneity in patient withdrawal1982389334210.2307/2529873Search in Google Scholar
Rutherford MJ, Dickman PW, Lambert PC. Comparison of methods for calculating relative survival in population-based studies. Cancer Epidemiol 2012; 36: 16–21.RutherfordMJDickmanPWLambertPCComparison of methods for calculating relative survival in population-based studies201236162110.1016/j.canep.2011.05.01021840284Search in Google Scholar
Corazziari I, Quinn M, Capocaccia R. Standard cancer patient population for age standardising survival ratios. Eur J Cancer 2004; 40: 2307–16.CorazziariIQuinnMCapocacciaRStandard cancer patient population for age standardising survival ratios20044023071610.1016/j.ejca.2004.07.00215454257Search in Google Scholar