3 resultados para temporal compressive sensing ratio design
Resumo:
Background: Most mortality atlases show static maps from count data aggregated over time. This procedure has several methodological problems and serious limitations for decision making in Public Health. The evaluation of health outcomes, including mortality, should be approached from a dynamic time perspective that is specific for each gender and age group. At the moment, researches in Spain do not provide a dynamic image of the population’s mortality status from a spatio-temporal point of view. The aim of this paper is to describe the spatial distribution of mortality from all causes in small areas of Andalusia (Southern Spain) and evolution over time from 1981 to 2006. Methods: A small-area ecological study was devised using the municipality as the unit for analysis. Two spatiotemporal hierarchical Bayesian models were estimated for each age group and gender. One of these was used to estimate the specific mortality rate, together with its time trends, and the other to estimate the specific rate ratio for each municipality compared with Spain as a whole. Results: More than 97% of the municipalities showed a diminishing or flat mortality trend in all gender and age groups. In 2006, over 95% of municipalities showed male and female mortality specific rates similar or significantly lower than Spanish rates for all age groups below 65. Systematically, municipalities in Western Andalusia showed significant male and female mortality excess from 1981 to 2006 only in age groups over 65. Conclusions: The study shows a dynamic geographical distribution of mortality, with a different pattern for each year, gender and age group. This information will contribute towards a reflection on the past, present and future of mortality in Andalusia.
Resumo:
BACKGROUND: To improve the efficacy of first-line therapy for advanced non-small cell lung cancer (NSCLC), additional maintenance chemotherapy may be given after initial induction chemotherapy in patients who did not progress during the initial treatment, rather than waiting for disease progression to administer second-line treatment. Maintenance therapy may consist of an agent that either was or was not present in the induction regimen. The antifolate pemetrexed is efficacious in combination with cisplatin for first-line treatment of advanced NSCLC and has shown efficacy as a maintenance agent in studies in which it was not included in the induction regimen. We designed a phase III study to determine if pemetrexed maintenance therapy improves progression-free survival (PFS) and overall survival (OS) after cisplatin/pemetrexed induction therapy in patients with advanced nonsquamous NSCLC. Furthermore, since evidence suggests expression levels of thymidylate synthase, the primary target of pemetrexed, may be associated with responsiveness to pemetrexed, translational research will address whether thymidylate synthase expression correlates with efficacy outcomes of pemetrexed. METHODS/DESIGN: Approximately 900 patients will receive four cycles of induction chemotherapy consisting of pemetrexed (500 mg/m2) and cisplatin (75 mg/m2) on day 1 of a 21-day cycle. Patients with an Eastern Cooperative Oncology Group performance status of 0 or 1 who have not progressed during induction therapy will randomly receive (in a 2:1 ratio) one of two double-blind maintenance regimens: pemetrexed (500 mg/m2 on day 1 of a 21-day cycle) plus best supportive care (BSC) or placebo plus BSC. The primary objective is to compare PFS between treatment arms. Secondary objectives include a fully powered analysis of OS, objective tumor response rate, patient-reported outcomes, resource utilization, and toxicity. Tumor specimens for translational research will be obtained from consenting patients before induction treatment, with a second biopsy performed in eligible patients following the induction phase. DISCUSSION: Although using a drug as maintenance therapy that was not used in the induction regimen exposes patients to an agent with a different mechanism of action, evidence suggests that continued use of an agent present in the induction regimen as maintenance therapy enables the identification of patients most likely to benefit from maintenance treatment.
Resumo:
In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.