18 resultados para Poisson regression analysis
Resumo:
The purpose of this study was to analyze the implementation of national family planning policy in the United States, which was embedded in four separate statutes during the period of study, Fiscal Years 1976-81. The design of the study utilized a modification of the Sabatier and Mazmanian framework for policy analysis, which defined implementation as the carrying out of statutory policy. The study was divided into two phases. The first part of the study compared the implementation of family planning policy by each of the pertinent statutes. The second part of the study identified factors that were associated with implementation of federal family planning policy within the context of block grants.^ Implemention was measured here by federal dollars spent for family planning, adjusted for the size of the respective state target populations. Expenditure data were collected from the Alan Guttmacher Institute and from each of the federal agencies having administrative authority for the four pertinent statutes, respectively. Data from the former were used for most of the analysis because they were more complete and more reliable.^ The first phase of the study tested the hypothesis that the coherence of a statute is directly related to effective implementation. Equity in the distribution of funds to the states was used to operationalize effective implementation. To a large extent, the results of the analysis supported the hypothesis. In addition to their theoretical significance, these findings were also significant for policymakers insofar they demonstrated the effectiveness of categorical legislation in implementing desired health policy.^ Given the current and historically intermittent emphasis on more state and less federal decision-making in health and human serives, the second phase of the study focused on state level factors that were associated with expenditures of social service block grant funds for family planning. Using the Sabatier-Mazmanian implementation model as a framework, many factors were tested. Those factors showing the strongest conceptual and statistical relationship to the dependent variable were used to construct a statistical model. Using multivariable regression analysis, this model was applied cross-sectionally to each of the years of the study. The most striking finding here was that the dominant determinants of the state spending varied for each year of the study (Fiscal Years 1976-1981). The significance of these results was that they provided empirical support of current implementation theory, showing that the dominant determinants of implementation vary greatly over time. ^
Resumo:
Invasive pneumococcal disease (IPD) causes significant health burden in the US, is responsible for the majority of bacterial meningitis, and causes more deaths than any other vaccine preventable bacterial disease in the US. The estimated National IPD rate is 14.3 cases per 100,000 population with a case-fatality rate of 1.5 cases per 100,000 population. Although cases of IPD are routinely reported to the local health department in Harris County Texas, the incidence (IR) and case-fatality (CFR) rates have not been reported. Additionally, it is important to know which serotypes of S. pneumoniae are circulating in Harris County Texas and to determine if ‘replacement disease’ is occurring. ^ This study reported incidence and case-fatality rates from 2003 to 2009, and described the trends in IPD, including the IPD serotypes circulating in Harris County Texas during the study period, particularly in 2008 and 2010. Annual incidence rates were calculated and reported for 2003 to 2009, using complete surveillance-year data. ^ Geographic information system (GIS) software was used to create a series of maps of the data reported during the study period. Cluster and outlier analysis and hot spot analysis were conducted using both case counts by census tract and disease rate by census tract. ^ IPD age- and race-adjusted IR for Harris County Texas and their 95% confidence intervals (CIs) were 1.40 (95% CI 1.0, 1.8), 1.71 (95% CI 1.24, 2.17), 3.13 (95% CI 2.48, 3.78), 3.08 (95% CI 2.43, 3.74), 5.61 (95% CI 4.79, 6.43), 8.11 (95% CI 7.11, 9.1), and 7.65 (95% CI 6.69, 8.61) for the years 2003 to 2009, respectively (rates were age- and race-adjusted to each year's midyear US population estimates). A Poisson regression model demonstrated a statistically significant increasing trend of about 32 percent per year in the IPD rates over the course of the study period. IPD age- and race-adjusted case-fatality rates (CFR) for Harris County Texas were also calculated and reported. A Poisson regression model demonstrated a statistically significant increasing trend of about 26 percent per year in the IPD case-fatality rates from 2003 through 2009. A logistic regression model associated the risk of dying from IPD to alcohol abuse (OR 4.69, 95% CI 2.57, 8.56) and to meningitis (OR 2.42, 95% CI 1.46, 4.03). ^ The prevalence of non-vaccine serotypes (NVT) among IPD cases with serotyped isolates was 98.2 percent. In 2008, the year with the sample more geographically representative of all areas of Harris County Texas, the prevalence was 96 percent. Given these findings, it is reasonable to conclude that ‘replacement disease’ is occurring in Harris County Texas, meaning that, the majority of IPD is caused by serotypes not included in the PCV7 vaccine. Also in conclusion, IPD rates increased during the study period in Harris County Texas.^
Resumo:
Background. Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among females, accounting for 23% (1.38 million) of the total new cancer cases and 14% (458,400) of the total cancer deaths in 2008. [1] Triple-negative breast cancer (TNBC) is an aggressive phenotype comprising 10–20% of all breast cancers (BCs). [2-4] TNBCs show absence of estrogen, progesterone and HER2/neu receptors on the tumor cells. Because of the absence of these receptors, TNBCs are not candidates for targeted therapies. Circulating tumor cells (CTCs) are observed in blood of breast cancer patients even at early stages (Stage I & II) of the disease. Immunological and molecular analysis can be used to detect the presence of tumor cells in the blood (Circulating tumor cells; CTCs) of many breast cancer patients. These cells may explain relapses in early stage breast cancer patients even after adequate local control. CTC detection may be useful in identifying patients at risk for disease progression, and therapies targeting CTCs may improve outcome in patients harboring them. Methods . In this study we evaluated 80 patients with TNBC who are enrolled in a larger prospective study conducted at M D Anderson Cancer Center in order to determine whether the presence of circulating tumor cells is a significant prognostic factor in relapse free and overall survival . Patients with metastatic disease at the time of presentation were excluded from the study. CTCs were assessed using CellSearch System™ (Veridex, Raritan, NJ). CTCs were defined as nucleated cells lacking the presence of CD45 but expressing cytokeratins 8, 18 or 19. The distribution of patient and tumor characteristics was analyzed using chi square test and Fisher's exact test. Log rank test and Cox regression analysis was applied to establish the association of circulating tumor cells with relapse free and overall survival. Results. The median age of the study participants was 53years. The median duration of follow-up was 40 months. Eighty-eight percent (88%) of patients were newly diagnosed (without a previous history of breast cancer), and (60%) of patients were chemo naïve (had not received chemotherapy at the time of their blood draw for CTC analysis). Tumor characteristics such as stage (P=0.40), tumor size (P=69), sentinel nodal involvement (P=0.87), axillary lymph node involvement (P=0.13), adjuvant therapy (P=0.83), and high histological grade of tumor (P=0.26) did not predict the presence of CTCs. However, CTCs predicted worse relapse free survival (1 or more CTCs log rank P value = 0.04, at 2 or more CTCs P = 0.02 and at 3 or more CTCs P < 0.0001) and overall survival (at 1 or more CTCs log rank P value = 0.08, at 2 or more CTCs P = 0.01 and at 3 or more CTCs P = 0.0001. Conclusions. The number of circulating tumor cells predicted worse relapse free survival and overall survival in TNBC patients.^