Cox s proportional hazards model

Using regression analysis based on Cox s proportional hazards model, Ott and Zober (1996) found evidence of association between 2,3,7,8-TCDD exposure and digestive cancer (conditional risk ratio of 1.46 95% 0=1.13-1.89) the primary tumor sites were the liver, stomach, and pancreas. 

Data from a 7-year follow-up study in another Cd-polluted area (Nagasaki) showed that, in both men and women, serum p2-microglobulin and creatinine, as well as urinary total protein and p2-microglobulin were significantly related to mortality independent of age as assessed by the Cox s proportional hazards model [111]. In advanced cases, the excess mortality of subjects with Cd-induced renal tubular dysfunction might, to some extent, be ascribed to a reduction in GFR. 

Although we do not cover them in detail, there ate parametric methods to analyze time to event data of this type, the most notable of which is Cox s proportional hazards model. 

Ford I, Norrie J, Ahmadi S (199 5) Model inconsistency, illustrated by the Cox proportional hazards model. Statistics in Medicine 14 735-746. 

The predictive probabilities used to stop the trial for futility or for predicted success are calculated using a combination of the current posterior probability, each individual patient s data (follow-up time and whether they ve experienced an event), and simulated data from the current point forward along with the Cox proportional hazard model. 

Details of statistical analyses for potential toxicities that should be explicitly considered for all products and AEs of special interest Aiialyses for these events will in general be more comprehensive than for standard safety parameters. These analyses may include subject-year adjusted rates, Cox proportional hazards analysis of time to first event, and Kaplan-Meier curves. Detailed descriptions of the models would typically be provided. For example, if Cox proportional hazards analysis is specified, a detailed description of the model(s) that will be used should be provided. This would generally include study as a stratification factor, covariates, and model selection techniques. More advanced methods, such as multiple events models or competing risk analyses, should be described if used (as appropriate). It is recommended that graphical methods also be employed, for example, forest plot and risk-over-time plot (Xia et al., 2011). 

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