While in chronic diseases, such as diabetes, mortalityrates slowly increases with age, in oncological seriesmortality usually changes dramatically during thefollow-up, often in an unpredictable pattern. Forinstance, i...While in chronic diseases, such as diabetes, mortalityrates slowly increases with age, in oncological seriesmortality usually changes dramatically during thefollow-up, often in an unpredictable pattern. Forinstance, in gastric cancer mortality peaks in thefirst two years of follow-up and declines thereafter.Also several risk factors, such as TNM stage, largelyaffect mortality in the first years after surgery, whileafterward their effect tends to fade. Temporal trendsin mortality were compared between a gastric cancerseries and a cohort of type 2 diabetic patients. Forthis purpose, 937 patients, undergoing curativegastrectomy with D1/D2/D3 lymphadenectomy forgastric cancer in three GIRCG （Gruppo Italiano RicercaCancro Gastrico = Italian Research Group for GastricCancer） centers, were compared with 7148 type 2diabetic patients from the Verona Diabetes Study. Inthe early/advanced gastric cancer series, mortality fromrecurrence peaked to 200 deaths per 1000 personyears1 year after gastrectomy and then declined,becoming lower than 40 deaths per 1000 person-yearsafter 5 years and lower than 20 deaths after 8 years.Mortality peak occurred earlier in more advanced Tand N tiers. At variance, in the Verona diabetic cohort overall mortality slowly increased during a 10-yearfollow-up, with ageing of the type 2 diabetic patients.Seasonal oscillations were also recorded, mortalitybeing higher during winter than during summer. Alsothe most important prognostic factors presented adifferent temporal pattern in the two diseases： whilethe prognostic significance of T and N stage markedlydecrease over time, differences in survival amongpatients treated with diet, oral hypoglycemic drugsor insulin were consistent throughout the follow-up.Time variations in prognostic significance of main riskfactors, their impact on survival analysis and possiblesolutions were evaluated in another GIRCG series of568 patients with advanced gastric cancer, undergoingcurative gastrectomy with D2/D3 lymphadenectomy.Survival curves in the two different histotypes （intestinaland mixed/diffuse） were superimposed in the first threeyears of follow-up and diverged thereafter. Likewise,survival curves as a function of site （fundus vs body/antrum） started to diverge after the first year. On thecontrary, survival curves differed among age classesfrom the very beginning, due to different post-operativemortality, which increased from 0.5% in patients aged65-74 years to 9.9% in patients aged 75-91 years;this discrepancy later disappeared. Accordingly, theproportional hazards assumption of the Cox modelwas violated, as regards age, site and histology. Tocope with this problem, multivariable survival analysiswas performed by separately considering either thefirst two years of follow-up or subsequent years.Histology and site were significant predictors only aftertwo years, while T and N, although significant bothin the short-term and in the long-term, became lessimportant in the second part of follow-up. Increasingage was associated with higher mortality in the firsttwo years, but not thereafter. Splitting survival timewhen performing survival analysis allows to distinguishbetween short-term and long-term risk factors.Alternative statistical solutions could be to excludepost-operative mortality, to introduce in the modeltime-dependent covariates or to stratify on variablesviolating proportionality assumption.展开更多
This work studies a proportional hazards model for survival data with ＂long-term survivors＂, in which covariates are subject to linear measurement error. It is well known that the naive estimators from both partial ...This work studies a proportional hazards model for survival data with ＂long-term survivors＂, in which covariates are subject to linear measurement error. It is well known that the naive estimators from both partial and full likelihood methods are inconsistent under this measurement error model. For measurement error models, methods of unbiased estimating function and corrected likelihood have been proposed in the literature. In this paper, we apply the corrected partial and full likelihood approaches to estimate the model and obtain statistical inference from survival data with long-term survivors. The asymptotic properties of the estimators are established. Simulation results illustrate that the proposed approaches provide useful tools for the models considered.展开更多
文摘While in chronic diseases, such as diabetes, mortalityrates slowly increases with age, in oncological seriesmortality usually changes dramatically during thefollow-up, often in an unpredictable pattern. Forinstance, in gastric cancer mortality peaks in thefirst two years of follow-up and declines thereafter.Also several risk factors, such as TNM stage, largelyaffect mortality in the first years after surgery, whileafterward their effect tends to fade. Temporal trendsin mortality were compared between a gastric cancerseries and a cohort of type 2 diabetic patients. Forthis purpose, 937 patients, undergoing curativegastrectomy with D1/D2/D3 lymphadenectomy forgastric cancer in three GIRCG （Gruppo Italiano RicercaCancro Gastrico = Italian Research Group for GastricCancer） centers, were compared with 7148 type 2diabetic patients from the Verona Diabetes Study. Inthe early/advanced gastric cancer series, mortality fromrecurrence peaked to 200 deaths per 1000 personyears1 year after gastrectomy and then declined,becoming lower than 40 deaths per 1000 person-yearsafter 5 years and lower than 20 deaths after 8 years.Mortality peak occurred earlier in more advanced Tand N tiers. At variance, in the Verona diabetic cohort overall mortality slowly increased during a 10-yearfollow-up, with ageing of the type 2 diabetic patients.Seasonal oscillations were also recorded, mortalitybeing higher during winter than during summer. Alsothe most important prognostic factors presented adifferent temporal pattern in the two diseases： whilethe prognostic significance of T and N stage markedlydecrease over time, differences in survival amongpatients treated with diet, oral hypoglycemic drugsor insulin were consistent throughout the follow-up.Time variations in prognostic significance of main riskfactors, their impact on survival analysis and possiblesolutions were evaluated in another GIRCG series of568 patients with advanced gastric cancer, undergoingcurative gastrectomy with D2/D3 lymphadenectomy.Survival curves in the two different histotypes （intestinaland mixed/diffuse） were superimposed in the first threeyears of follow-up and diverged thereafter. Likewise,survival curves as a function of site （fundus vs body/antrum） started to diverge after the first year. On thecontrary, survival curves differed among age classesfrom the very beginning, due to different post-operativemortality, which increased from 0.5% in patients aged65-74 years to 9.9% in patients aged 75-91 years;this discrepancy later disappeared. Accordingly, theproportional hazards assumption of the Cox modelwas violated, as regards age, site and histology. Tocope with this problem, multivariable survival analysiswas performed by separately considering either thefirst two years of follow-up or subsequent years.Histology and site were significant predictors only aftertwo years, while T and N, although significant bothin the short-term and in the long-term, became lessimportant in the second part of follow-up. Increasingage was associated with higher mortality in the firsttwo years, but not thereafter. Splitting survival timewhen performing survival analysis allows to distinguishbetween short-term and long-term risk factors.Alternative statistical solutions could be to excludepost-operative mortality, to introduce in the modeltime-dependent covariates or to stratify on variablesviolating proportionality assumption.
基金supported by the National Nature Science Foundation of China under Grant No.10871084Macquarie University Safety Net grant
文摘This work studies a proportional hazards model for survival data with ＂long-term survivors＂, in which covariates are subject to linear measurement error. It is well known that the naive estimators from both partial and full likelihood methods are inconsistent under this measurement error model. For measurement error models, methods of unbiased estimating function and corrected likelihood have been proposed in the literature. In this paper, we apply the corrected partial and full likelihood approaches to estimate the model and obtain statistical inference from survival data with long-term survivors. The asymptotic properties of the estimators are established. Simulation results illustrate that the proposed approaches provide useful tools for the models considered.
