Describing the association between socioeconomic inequalities and cancer survival: methodological guidelines and illustration with population-based data
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B. Rachet | G. Launoy | A. Guizard | O. Dejardin | L. Remontet | S. Bara | N. Bossard | L. Roche | A. Belot | H. Charvat
[1] Charli Spier. Deprivation. , 2019, Health visitor.
[2] Georg Heinze,et al. Variable selection – A review and recommendations for the practicing statistician , 2018, Biometrical journal. Biometrische Zeitschrift.
[3] D. Niederwieser,et al. Socio-economic disparities in long-term cancer survival—10 year follow-up with individual patient data , 2017, Supportive Care in Cancer.
[4] O. Lantieri,et al. Assessment of the ecological bias of seven aggregate social deprivation indices , 2017, BMC Public Health.
[5] B. Rachet,et al. Analysing population-based cancer survival – settling the controversies , 2016, BMC Cancer.
[6] Juan Merlo,et al. The median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysis , 2016, Statistics in medicine.
[7] Bernard Rachet,et al. A multilevel excess hazard model to estimate net survival on hierarchical data allowing for non‐linear and non‐proportional effects of covariates , 2016, Statistics in medicine.
[8] B. Rachet,et al. No inequalities in survival from colorectal cancer by education and socioeconomic deprivation - a population-based study in the North Region of Portugal, 2000-2002 , 2016, BMC Cancer.
[9] G. Molenberghs,et al. Quantifying intraclass correlations for count and time‐to‐event data , 2016, Biometrical journal. Biometrische Zeitschrift.
[10] F. Bray,et al. Regional variations in cancer survival: Impact of tumour stage, socioeconomic status, comorbidity and type of treatment in Norway , 2016, International journal of cancer.
[11] P. Baade,et al. Cancer survival in New South Wales, Australia: socioeconomic disparities remain despite overall improvements , 2016, BMC Cancer.
[12] R. De Angelis,et al. 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). , 2015, The Lancet. Haematology.
[13] L. Guittet,et al. Correction of misclassification bias induced by the residential mobility in studies examining the link between socioeconomic environment and cancer incidence. , 2015, Cancer epidemiology.
[14] P. Arveux,et al. Age-related socio-economic and geographic disparities in breast cancer stage at diagnosis: a population-based study. , 2015, European journal of public health.
[15] Helena Carreira,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) , 2015, The Lancet.
[16] S. Altekruse,et al. Racial and ethnic disparities in cancer survival by neighborhood socioeconomic status in Surveillance, Epidemiology, and End Results (SEER) Registries. , 2014, Journal of the National Cancer Institute. Monographs.
[17] Steven Woloshin,et al. Cancer survival: an overview of measures, uses, and interpretation. , 2014, Journal of the National Cancer Institute. Monographs.
[18] T. Nakaya,et al. Socioeconomic inequalities in cancer survival: A population-based study of adult patients diagnosed in Osaka, Japan, during the period 1993–2004 , 2014, Acta oncologica.
[19] Willy Wynant,et al. Impact of the model‐building strategy on inference about nonlinear and time‐dependent covariate effects in survival analysis , 2014, Statistics in medicine.
[20] W. Maier,et al. Socioeconomic deprivation and cancer survival in Germany: An ecological analysis in 200 districts in Germany , 2014, International journal of cancer.
[21] Kenneth R Hess,et al. Getting More Out of Survival Data by Using the Hazard Function , 2014, Clinical Cancer Research.
[22] Coraline Danieli,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 , 2013, International journal of cancer.
[23] Cyrille Delpierre,et al. Construction of an adaptable European transnational ecological deprivation index: the French version , 2012, Journal of Epidemiology & Community Health.
[24] Laurent Remontet,et al. Estimating net survival: the importance of allowing for informative censoring , 2012, Statistics in medicine.
[25] Janez Stare,et al. On Estimation in Relative Survival , 2012, Biometrics.
[26] C. Preudhomme,et al. Changes in the dynamics of the excess mortality rate in chronic phase-chronic myeloid leukemia over 1990-2007: a population study. , 2011, Blood.
[27] M. Abrahamowicz,et al. Flexible statistical models provided new insights into the role of quantitative prognostic factors for mortality in gastric cancer. , 2009, Journal of clinical epidemiology.
[28] Paul Janssen,et al. Frailty Model , 2007, International Encyclopedia of Statistical Science.
[29] P. Royston,et al. A New Proposal for Multivariable Modelling of Time‐Varying Effects in Survival Data Based on Fractional Polynomial Time‐Transformation , 2007, Biometrical journal. Biometrische Zeitschrift.
[30] J. Estève,et al. An overall strategy based on regression models to estimate relative survival and model the effects of prognostic factors in cancer survival studies , 2007, Statistics in medicine.
[31] Charles E McCulloch,et al. Relaxing the rule of ten events per variable in logistic and Cox regression. , 2007, American journal of epidemiology.
[32] E. Grundy,et al. The association of cancer survival with four socioeconomic indicators: a longitudinal study of the older population of England and Wales 1981–2000 , 2007, BMC Cancer.
[33] M. Coleman,et al. Choice of geographic unit influences socioeconomic inequalities in breast cancer survival , 2005, British Journal of Cancer.
[34] Mike Quinn,et al. Standard cancer patient population for age standardising survival ratios. , 2004, European journal of cancer.
[35] S V Subramanian,et al. The relevance of multilevel statistical methods for identifying causal neighborhood effects. , 2004, Social science & medicine.
[36] B Rachet,et al. Trends and socioeconomic inequalities in cancer survival in England and Wales up to 2001 , 2004, British Journal of Cancer.
[37] Harvey Goldstein,et al. Partitioning variation in multilevel models , 2002 .
[38] A. Roux,et al. A glossary for multilevel analysis , 2002, Journal of epidemiology and community health.
[39] C Quantin,et al. Variation over time of the effects of prognostic factors in a population-based study of colon cancer: comparison of statistical models. , 1999, American journal of epidemiology.
[40] Johann Sölkner,et al. Frailty Models in Survival Analysis , 1996 .
[41] J. Estève,et al. Relative survival and the estimation of net survival: elements for further discussion. , 1990, Statistics in medicine.
[42] V. Carstairs,et al. Deprivation: explaining differences in mortality between Scotland and England and Wales. , 1989, BMJ.
[43] D. Black. HEALTH AND DEPRIVATION: Inequality and the north , 1988 .
[44] A. Yashin,et al. Heterogeneity's ruses: some surprising effects of selection on population dynamics. , 1985, The American statistician.
[45] G. Rey,et al. Survival Analysis with Multiple Causes of Death: Extending the Competing Risks Model. , 2017, Epidemiology.
[46] M. Coleman,et al. Cancer survival in Europe 1999-2007 by country and age: results of EUROCARE--5-a population-based study. , 2014, The Lancet. Oncology.
[47] L. Holmberg,et al. Colorectal cancer survival in socioeconomic groups in England: variation is mainly in the short term after diagnosis. , 2012, European journal of cancer.
[48] D. Perrons,et al. Why socio-economic inequalities increase? Facts and policy responses in Europe , 2010 .
[49] J. Bloch,et al. [Which factors influence screening practices for female cancer in France?]. , 2008, Revue d'epidemiologie et de sante publique.
[50] L. Com-ruelle,et al. Les problèmes d'alcool en France : quelles sont les populations à risque? , 2008 .
[51] G. Launoy,et al. Survival of cancer patients in France: a population-based study from The Association of the French Cancer Registries (FRANCIM). , 2007, European journal of cancer.
[52] B Rachet,et al. Origins of socio-economic inequalities in cancer survival: a review. , 2006, Annals of oncology : official journal of the European Society for Medical Oncology.
[53] A. D. Diez Roux,et al. Investigating neighborhood and area effects on health. , 2001, American journal of public health.
[54] A. Diez-Roux. Multilevel analysis in public health research. , 2000, Annual review of public health.
[55] M. Kogevinas,et al. Socioeconomic differences in cancer survival: a review of the evidence. , 1997, IARC scientific publications.