Describing the association between socioeconomic inequalities and cancer survival: methodological guidelines and illustration with population-based data

References

• KogevinasMPortaMSocioeconomic differences in cancer survival: a review of the evidenceKogevinasMPearceNSusserMBoffettaPSocial Inequalities and CancerIARC Scientific Publications No. 138LyonInternational Agency for Research on Cancer1997177206
   Google Scholar
• ColemanMPRachetBWoodsLMTrends and socioeconomic inequalities in cancer survival in England and Wales up to 2001Br J Cancer20049071367137315054456
   PubMed Web of Science ®Google Scholar
• WoodsLMRachetBColemanMPOrigins of socio-economic inequalities in cancer survival: a reviewAnn Oncol200617151916143594
   PubMed Web of Science ®Google Scholar
• ItoYNakayaTNakayamaTSocioeconomic inequalities in cancer survival: a population-based study of adult patients diagnosed in Osaka, Japan, during the period 1993–2004Acta Oncol201453101423143324865119
   PubMed Web of Science ®Google Scholar
• JansenLEberleAEmrichKGEKID Cancer Survival Working GroupSocioeconomic deprivation and cancer survival in Germany: an ecological analysis in 200 districts in GermanyInt J Cancer2014134122951296024259308
   PubMed Web of Science ®Google Scholar
• StanburyJFBaadePDYuYYuXQCancer survival in New South Wales, Australia: socioeconomic disparities remain despite overall improvementsBMC Cancer2016164826832359
   PubMed Web of Science ®Google Scholar
• SubramanianSVThe relevance of multilevel statistical methods for identifying causal neighborhood effectsSoc Sci Med200458101961196715020011
   PubMed Web of Science ®Google Scholar
• DuchateauLJanssenPThe Frailty ModelNew York, NYSpringer2008
   Google Scholar
• WienkeAFrailty Models in Survival AnalysisBoca Raton, FLCRC Press2011
   Google Scholar
• AntunesLMendoncaDBentoMJRachetBNo inequalities in survival from colorectal cancer by education and socioeconomic deprivation – a population-based study in the North Region of Portugal, 2000–2002BMC Cancer20161660827495309
   PubMed Web of Science ®Google Scholar
• KishJKYuMPercy-LaurryAAltekruseSFRacial and ethnic disparities in cancer survival by neighborhood socioeconomic status in Surveillance, Epidemiology, and End Results (SEER) RegistriesJ Natl Cancer Inst Monogr201420144923624325417237
   PubMedGoogle Scholar
• DiallaPOArveuxPOuedraogoSAge-related socio-economic and geographic disparities in breast cancer stage at diagnosis: a population-based studyEur J Public Health201525696697225829506
   PubMed Web of Science ®Google Scholar
• TownsendPPhillimorePBeattieAHealth and Deprivation: Inequality and the NorthLondonCroom Helm1988
   Google Scholar
• CarstairsVMorrisRDeprivation: explaining differences in mortality between Scotland and England and WalesBMJ198929967048868892510878
   PubMed Web of Science ®Google Scholar
• WoodsLMRachetBColemanMPChoice of geographic unit influences socioeconomic inequalities in breast cancer survivalBr J Cancer20059271279128215798765
   PubMed Web of Science ®Google Scholar
• Diez RouxAVInvestigating neighborhood and area effects on healthAm J Public Health200191111783178911684601
   PubMed Web of Science ®Google Scholar
• Diez RouxAVA glossary for multilevel analysisJ Epidemiol Community Health200256858859412118049
   PubMed Web of Science ®Google Scholar
• PornetCDelpierreCDejardinOConstruction of an adaptable European transnational ecological deprivation index: the French versionJ Epidemiol Community Health2012661198298922544918
   PubMed Web of Science ®Google Scholar
• TownsendPDeprivationJ Soc Policy1987162125146
   Web of Science ®Google Scholar
• GuillaumeEPornetCDejardinODevelopment of a cross-cultural deprivation index in five European countriesJ Epidemiol Community Health201670549349926659762
   PubMed Web of Science ®Google Scholar
• Moreno-BetancurMSadaouiHPiffarettiCReyGSurvival analysis with multiple causes of death: extending the competing risks modelEpidemiology2017281121927362647
   PubMed Web of Science ®Google Scholar
• RemontetLBossardNBelotAEstèveJFrench network of cancer registries FRANCIMAn overall strategy based on regression models to estimate relative survival and model the effects of prognostic factors in cancer survival studiesStat Med200726102214222816900570
   PubMed Web of Science ®Google Scholar
• EstèveJBenhamouECroasdaleMRaymondLRelative survival and the estimation of net survival: elements for further discussionStat Med1990955295382349404
   PubMed Web of Science ®Google Scholar
• PoharMPStareJEstèveJOn estimation in relative survivalBiometrics201268111312021689081
   PubMed Web of Science ®Google Scholar
• DanieliCRemontetLBossardNRocheLBelotAEstimating net survival: the importance of allowing for informative censoringStat Med201231877578622281942
   PubMed Web of Science ®Google Scholar
• RocheLDanieliCBelotACancer net survival on registry data: use of the new unbiased Pohar-Perme estimator and magnitude of the bias with the classical methodsInt J Cancer2013132102359236922961565
   PubMed Web of Science ®Google Scholar
• BossardNVeltenMRemontetLSurvival of cancer patients in France: a population-based study from the Association of French Cancer Registries (FRANCIM)Eur J Cancer200743114916017084622
   PubMed Web of Science ®Google Scholar
• MariottoABNooneAMHowladerNCancer survival: an overview of measures, uses, and interpretationJ Natl Cancer Inst Monogr201420144914518625417231
   PubMedGoogle Scholar
• De AngelisRSantMColemanMPCancer survival in Europe 1999–2007 by country and age: results of EUROCARE-5 – a population-based studyLancet Oncol2014151233424314615
   PubMed Web of Science ®Google Scholar
• AllemaniCWeirHKCarreiraHCONCORD Working GroupGlobal 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)Lancet20153859972977101025467588
   PubMed Web of Science ®Google Scholar
• Pohar PermeMEsteveJRachetBAnalysing population-based cancer survival – settling the controversiesBMC Cancer201616193327912732
   PubMed Web of Science ®Google Scholar
• QuantinCAbrahamowiczMMoreauTVariation over time of the effects of prognostic factors in a population-based study of colon cancer: comparison of statistical modelsAm J Epidemiol1999150111188120010588079
   PubMed Web of Science ®Google Scholar
• MollerHSandinFRobinsonDColorectal cancer survival in socioeconomic groups in England: variation is mainly in the short term after diagnosisEur J Cancer2012481465321676610
   PubMed Web of Science ®Google Scholar
• CharvatHRemontetLBossardNCENSUR Working Survival GroupA multilevel excess hazard model to estimate net survival on hierarchical data allowing for non-linear and non-proportional effects of covariatesStat Med201635183066308426924122
   PubMed Web of Science ®Google Scholar
• AustinPCWagnerPMerloJThe median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysisStat Med201736692893827885709
   PubMed Web of Science ®Google Scholar
• WynantWAbrahamowiczMImpact of the model-building strategy on inference about nonlinear and time-dependent covariate effects in survival analysisStat Med201433193318333724757068
   PubMed Web of Science ®Google Scholar
• CorazziariIQuinnMCapocacciaRStandard cancer patient population for age standardising survival ratiosEur J Cancer200440152307231615454257
   PubMed Web of Science ®Google Scholar
• Commission EWhy Socio-Economic Inequalities Increase? Facts and Policy Responses in Europe1st edLuxembourgPublications Office of the European Union2010
   Google Scholar
• BryereJPornetCDejardinOLaunayLGuittetLLaunoyGCorrection of misclassification bias induced by the residential mobility in studies examining the link between socioeconomic environment and cancer incidenceCancer Epidemiol201539225626425579981
   PubMed Web of Science ®Google Scholar
• BinquetCAbrahamowiczMAstrucKFaivreJBonithon-KoppCQuantinCFlexible statistical models provided new insights into the role of quantitative prognostic factors for mortality in gastric cancerJ Clin Epidemiol200962323224019070464
   PubMed Web of Science ®Google Scholar
• CormSRocheLMicolJBChanges in the dynamics of the excess mortality rate in chronic phase-chronic myeloid leukemia over 1990–2007: a population studyBlood2011118164331433721849485
   PubMed Web of Science ®Google Scholar
• HessKRLevinVAGetting more out of survival data by using the hazard functionClin Cancer Res20142061404140924501392
   PubMed Web of Science ®Google Scholar
• MounierMBossardNRemontetLEUROCARE-5 Working GroupCENSUR Working Survival GroupChanges 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 Haematol2015211e481e49126686258
   PubMed Web of Science ®Google Scholar
• VaupelJWYashinAIHeterogeneity’s ruses: some surprising effects of selection on population dynamicsAm Stat198539317618512267300
   PubMed Web of Science ®Google Scholar
• SauerbreiWRoystonPLookMA new proposal for multivariable modelling of time-varying effects in survival data based on fractional polynomial time-transformationBiom J200749345347317623349
   PubMed Web of Science ®Google Scholar
• VittinghoffEMcCullochCERelaxing the rule of ten events per variable in logistic and Cox regressionAm J Epidemiol2007165671071817182981
   PubMed Web of Science ®Google Scholar
• HeinzeGWallischCDunklerDVariable selection – a review and recommendations for the practicing statisticianBiom J Epub201812
   Web of Science ®Google Scholar
• Com-RuelleLDourgnonPJusotFLengagnePLes problèmes d’alcool en France: quelles sont les populations à risque? [The problems of alcohol in France: what are at-risk populations?]Institut De Recherche Et Documentation En Economie De La Santé200812916 French
   Google Scholar
• GuignardRBeckFRichardJBLermenierAWilquinJLNguyen-ThanhVLa consommation de tabac en France en 2014: caractéristiques et évolutions récentes [The use of tobacco in France in 2014: characteristics and recent developments]Évolutions20153116 French
   Google Scholar
• DuportNSerraDGoulardHBlochJWhich factors influence screening practices for female cancer in France?Rev Epidemiol Sante Publique2008565303313 French18951740
   PubMed Web of Science ®Google Scholar
• OliveiraIRMolenberghsGDemetrioCGDiasCTGioloSRAndradeMCQuantifying intraclass correlations for count and time-to-event dataBiom J201658485286726899931
   PubMed Web of Science ®Google Scholar
• GoldsteinHBrowneWRasbashJPartitioning variation in multilevel modelsUnderstand Stat200214223231
   Google Scholar
• BryereJPornetCCopinNAssessment of the ecological bias of seven aggregate social deprivation indicesBMC Public Health20171718628095815
   PubMed Web of Science ®Google Scholar
• Diez-RouxAVMultilevel analysis in public health researchAnnu Rev Public Health20002117119210884951
   PubMed Web of Science ®Google Scholar
• SloggettAYoungHGrundyEThe association of cancer survival with four socioeconomic indicators: a longitudinal study of the older population of England and Wales 1981–2000BMC Cancer200772017254357
   PubMed Web of Science ®Google Scholar
• SingerSBartelsMBriestSSocio-economic disparities in long-term cancer survival-10 year follow-up with individual patient dataSupport Care Cancer20172551391139927942934
   PubMed Web of Science ®Google Scholar
• SkyrudKDBrayFEriksenMTNilssenYMollerBRegional variations in cancer survival: impact of tumour stage, socioeconomic status, comorbidity and type of treatment in NorwayInt J Cancer201613892190220026679150
   PubMed Web of Science ®Google Scholar