Survival Extrapolation In The Presence Of Cause Specific Hazards.

Health economic evaluations require estimates of expected survival from patients receiving different interventions, often over a lifetime. However, data on the patients of interest are typically only available for a much shorter follow-up time, from randomised trials or cohorts. Previous work showed how to use general population mortality to improve extrapolations of the short-term data, assuming a constant additive or multiplicative effect on the hazards for all-cause mortality for study patients relative to the general population. A more plausible assumption may be a constant effect on the hazard for the specific cause of death targeted by the treatments. To address this problem, we use independent parametric survival models for cause-specific mortality among the general population. Because causes of death are unobserved for the patients of interest, a polyhazard model is used to express their all-cause mortality as a sum of latent cause-specific hazards. Assuming proportional cause-specific hazards between the general and study populations then allows us to extrapolate mortality of the patients of interest to the long term. A Bayesian framework is used to jointly model all sources of data. By simulation, we show that ignoring cause-specific hazards leads to biased estimates of mean survival when the proportion of deaths due to the cause of interest changes through time. The methods are applied to an evaluation of implantable cardioverter defibrillators for the prevention of sudden cardiac death among patients with cardiac arrhythmia. After accounting for cause-specific mortality, substantial differences are seen in estimates of life years gained from implantable cardioverter defibrillators.

Projeto de caixa de madeira para manga (Mangifera Indica L.)

Losses of horticulture product in Brazil are significant and among the main causes are the use of inappropriate boxes and the absence of a cold chain. A project for boxes is proposed, based on computer simulations, optimization and experimental validation, trying to minimize the amount of wood associated with structural and ergonomic aspects and the effective area of the openings. Three box prototypes were designed and built using straight laths with different configurations and areas of openings (54% and 36%). The cooling efficiency of Tommy Atkins mango (Mangifera Indica L.) was evaluated by determining the cooling time for fruit packed in the wood models and packed in the commercially used cardboard boxes, submitted to cooling in a forced-air system, at a temperature of 6ºC and average relative humidity of 85.4±2.1%. The Finite Element Method was applied, for the dimensioning and structural optimization of the model with the best behavior in relation to cooling. All wooden boxes with fruit underwent vibration testing for two hours (20 Hz). There was no significant difference in average cooling time in the wooden boxes (36.08±1.44 min); however, the difference was significant in comparison to the cardboard boxes (82.63±29.64 min). In the model chosen for structural optimization (36% effective area of openings and two side laths), the reduction in total volume of material was 60% and 83% in the cross section of the columns. There was no indication of mechanical damage in the fruit after undergoing the vibration test. Computer simulations and structural study may be used as a support tool for developing projects for boxes, with geometric, ergonomic and thermal criteria.