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Summary.  The interaction between the vulnerable atherosclerotic plaque prone to disruption and thrombus formation is the cornerstone of acute coronary syndrome (ACS). Although distinct from one another, the atherosclerotic and thrombotic processes appear to be interdependent, hence the term atherothrombosis. Inflammation is a crucial common pathophysiological mechanism. Overall, the association of plaque vulnerability and ACS has been well documented. Given the multifactorial origin of atherothrombosis the best preventive approach should be aggressive management of all the risk factors. New interventions should be directed toward decreasing vulnerability of the lesions thereby decreasing the risk of ACS.  相似文献   
105.

Purpose

To analyze trends in second primary cancer (SPC) incidence by using a case-mix approach to standardize on first cancer site distribution.

Methods

Cases registered by 13 French cancer registries between 1989 and 2010 and followed-up until June 2013 were included. The person-year approach was used to compute standardized incidence ratios (SIRs) of metachronous SPC. Usual SIRs and cancer site–specific weighted SIRs called “case-mix SIRs” (cmSIRs) were estimated by sex and calendar period of first cancer diagnosis. Calendar trends in SIRs and cmSIRs were compared.

Results

More than 2.9 million person-years at risk were included. Among males, SIRs dropped from 1.49 to 1.23 between 1989–1994 and 2005–2010, while cmSIRs decreased from 1.40 to 1.27. This difference seems mainly related to a stronger representation of prostate cancers (at lower risk of SPC) and a weaker contribution of bladder and head and neck cancers (at higher risk of SPC) in recent periods of diagnosis. Among females, both SIRs and cmSIRs have remained stable at around 1.22 and 1.21, respectively.

Conclusions

The cmSIR is an indicator that is not influenced by changes in first cancer site distribution. Its use should be encouraged to assess second cancer incidence control.  相似文献   
106.
The health concentration curve is the standard graphical tool to depict socioeconomic health inequality in the literature on health inequality. This paper shows that testing for the absence of socioeconomic health inequality is equivalent to testing if the conditional expectation of health on income is a constant function that is equal to average health status. In consequence, any test for parametric specification of a regression function can be used to test for the absence of socioeconomic health inequality (subject to regularity conditions). Furthermore, this paper illustrates how to test for this equality using a test for parametric regression functional form and applies it to health‐related behaviors from the National Health Survey 2014.  相似文献   
107.

Objectives

Treatment landscape in prostate cancer has changed dramatically with the emergence of new medicines in the past few years. The traditional survival partition model (SPM) cannot accurately predict long-term clinical outcomes because it is limited by its ability to capture the key consequences associated with this changing treatment paradigm. The objective of this study was to introduce and validate a discrete-event simulation (DES) model for prostate cancer.

Methods

A DES model was developed to simulate overall survival (OS) and other clinical outcomes based on patient characteristics, treatment received, and disease progression history. We tested and validated this model with clinical trial data from the abiraterone acetate phase III trial (COU-AA-302). The model was constructed with interim data (55% death) and validated with the final data (96% death). Predicted OS values were also compared with those from the SPM.

Results

The DES model’s predicted time to chemotherapy and OS are highly consistent with the final observed data. The model accurately predicts the OS hazard ratio from the final data cut (predicted: 0.74; 95% confidence interval [CI] 0.64–0.85 and final actual: 0.74; 95% CI 0.6–0.88). The log-rank test to compare the observed and predicted OS curves indicated no statistically significant difference between observed and predicted curves. However, the predictions from the SPM based on interim data deviated significantly from the final data.

Conclusions

Our study showed that a DES model with properly developed risk equations presents considerable improvements to the more traditional SPM in flexibility and predictive accuracy of long-term outcomes.  相似文献   
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110.

Background

The under-5 mortality rate (U5MR) is an important metric of child health and survival. Country-level estimates of U5MR are readily available, but efforts to estimate U5MR subnationally have been limited, in part, due to spatial misalignment of available data sources (e.g., use of different administrative levels, or as a result of historical boundary changes).

Methods

We analyzed all available complete and summary birth history data in surveys and censuses in six countries (Bangladesh, Cameroon, Chad, Mozambique, Uganda, and Zambia) at the finest geographic level available in each data source. We then developed small area estimation models capable of incorporating spatially misaligned data. These small area estimation models were applied to the birth history data in order to estimate trends in U5MR from 1980 to 2015 at the second administrative level in Cameroon, Chad, Mozambique, Uganda, and Zambia and at the third administrative level in Bangladesh.

Results

We found substantial variation in U5MR in all six countries: there was more than a two-fold difference in U5MR between the area with the highest rate and the area with the lowest rate in every country. All areas in all countries experienced declines in U5MR between 1980 and 2015, but the degree varied both within and between countries. In Cameroon, Chad, Mozambique, and Zambia we found areas with U5MRs in 2015 that were higher than in other parts of the same country in 1980. Comparing subnational U5MR to country-level targets for the Millennium Development Goals (MDG), we find that 12.8% of areas in Bangladesh did not meet the country-level target, although the country as whole did. A minority of areas in Chad, Mozambique, Uganda, and Zambia met the country-level MDG targets while these countries as a whole did not.

Conclusions

Subnational estimates of U5MR reveal significant within-country variation. These estimates could be used for identifying high-need areas and positive deviants, tracking trends in geographic inequalities, and evaluating progress towards international development targets such as the Sustainable Development Goals.
  相似文献   
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