Fasting blood glucose and 8-year mortality in the hypertension detection follow-up program population

This study analyzed the relationship between fasting blood glucose (FBG) and 8-year mortality in the Hypertension Detection Follow-up Program (HDFP) population. Fasting blood glucose (FBG) was examined both as a continuous variable and by specified FBG strata: Normal (FBG 60–100 mg/dL), Impaired (FBG ≥100 and ≤125 mg/dL), and Diabetic (FBG>125 mg/dL or pre-existing diabetes) subgroups. The relationship between type 2 diabetes was examined with all-cause mortality. This thesis described and compared the characteristics of fasting blood glucose strata by recognized glucose cut-points; described the mortality rates in the various fasting blood glucose strata using Kaplan-Meier mortality curves, and compared the mortality risk of various strata using Cox Regression analysis. Overall, mortality was significantly greater among Referred Care (RC) participants compared to Stepped Care (SC) {HR = 1.17; 95% CI (1.052,1.309); p-value = 0.004}, as reported by the HDFP investigators in 1979. Compared with SC participants, the RC mortality rate was significantly higher for the Normal FBG group {HR = 1.18; 95% CI (1.029,1.363); p-value = 0.019} and the Impaired FBG group, {HR = 1.34; 95% CI (1.036,1.734); p-value = 0.026,}. However, for the diabetic group, 8-year mortality did not differ significantly between the RC and SC groups after adjusting for race, gender, age, smoking status among Diabetic individuals {HR = 1.03; 95% CI (0.816,1.303); p-value = 0.798}. This latter finding is possibly due to a lack of a treatment difference of hypertension among Diabetic participants in both RC and SC groups. The largest difference in mortality between RC and SC was in the Impaired subgroup, suggesting that hypertensive patients with FBG between 100 and 125 mg/dL would benefit from aggressive antihypertensive therapy.^

Application of the general linear model to assess the effect of missing data on bone marrow mononuclear cell therapy with infusion timing and follow-up MRI

With most clinical trials, missing data presents a statistical problem in evaluating a treatment's efficacy. There are many methods commonly used to assess missing data; however, these methods leave room for bias to enter the study. This thesis was a secondary analysis on data taken from TIME, a phase 2 randomized clinical trial conducted to evaluate the safety and effect of the administration timing of bone marrow mononuclear cells (BMMNC) for subjects with acute myocardial infarction (AMI).^ We evaluated the effect of missing data by comparing the variance inflation factor (VIF) of the effect of therapy between all subjects and only subjects with complete data. Through the general linear model, an unbiased solution was made for the VIF of the treatment's efficacy using the weighted least squares method to incorporate missing data. Two groups were identified from the TIME data: 1) all subjects and 2) subjects with complete data (baseline and follow-up measurements). After the general solution was found for the VIF, it was migrated Excel 2010 to evaluate data from TIME. The resulting numerical value from the two groups was compared to assess the effect of missing data.^ The VIF values from the TIME study were considerably less in the group with missing data. By design, we varied the correlation factor in order to evaluate the VIFs of both groups. As the correlation factor increased, the VIF values increased at a faster rate in the group with only complete data. Furthermore, while varying the correlation factor, the number of subjects with missing data was also varied to see how missing data affects the VIF. When subjects with only baseline data was increased, we saw a significant rate increase in VIF values in the group with only complete data while the group with missing data saw a steady and consistent increase in the VIF. The same was seen when we varied the group with follow-up only data. This essentially showed that the VIFs steadily increased when missing data is not ignored. When missing data is ignored as with our comparison group, the VIF values sharply increase as correlation increases.^

Developing the follow-up schedules for women with breast cancer

Background: The follow-up care for women with breast cancer requires an understanding of disease recurrence patterns and the follow-up visit schedule should be determined according to the times when the recurrence are most likely to occur, so that preventive measure can be taken to avoid or minimize the recurrence. Objective: To model breast cancer recurrence through stochastic process with an aim to generate a hazard function for determining a follow-up schedule. Methods: We modeled the process of disease progression as the time transformed Weiner process and the first-hitting-time was used as an approximation of the true failure time. The women's "recurrence-free survival time" or a "not having the recurrence event" is modeled by the time it takes Weiner process to cross a threshold value which represents a woman experiences breast cancer recurrence event. We explored threshold regression model which takes account of covariates that contributed to the prognosis of breast cancer following development of the first-hitting time model. Using real data from SEER-Medicare, we proposed models of follow-up visits schedule on the basis of constant probability of disease recurrence between consecutive visits. Results: We demonstrated that the threshold regression based on first-hitting-time modeling approach can provide useful predictive information about breast cancer recurrence. Our results suggest the surveillance and follow-up schedule can be determined for women based on their prognostic factors such as tumor stage and others. Women with early stage of disease may be seen less frequently for follow-up visits than those women with locally advanced stages. Our results from SEER-Medicare data support the idea of risk-controlled follow-up strategies for groups of women. Conclusion: The methodology we proposed in this study allows one to determine individual follow-up scheduling based on a parametric hazard function that incorporates known prognostic factors.^

Federally regulated institutional review boards: The aspects of a "model" IRB---Is the current system in need of a tune up or complete overhaul?

Institutional Review Boards (IRBs) are the primary gatekeepers for the protection of ethical standards of federally regulated research on human subjects in this country. This paper focuses on what general, broad measures that may be instituted or enhanced to exemplify a "model IRB". This is done by examining the current regulatory standards of federally regulated IRBs, not private or commercial boards, and how many of those standards have been found either inadequate or not generally understood or followed. The analysis includes suggestions on how to bring about changes in order to make the IRB process more efficient, less subject to litigation, and create standardized educational protocols for members. The paper also considers how to include better oversight for multi-center research, increased centralization of IRBs, utilization of Data Safety Monitoring Boards when necessary, payment for research protocol review, voluntary accreditation, and the institution of evaluation/quality assurance programs. ^ This is a policy study utilizing secondary analysis of publicly available data. Therefore, the research for this paper focuses on scholarly medical/legal journals, web information from the Department of Health and Human Services, Federal Drug Administration, and the Office of the Inspector General, Accreditation Programs, law review articles, and current regulations applicable to the relevant portions of the paper. ^ Two issues are found to be consistently cited by the literature as major concerns. One is a need for basic, standardized educational requirements across all IRBs and its members, and secondly, much stricter and more informed management of continuing research. There is no federally regulated formal education system currently in place for IRB members, except for certain NIH-based trials. Also, IRBs are not keeping up with research once a study has begun, and although regulated to do so, it does not appear to be a great priority. This is the area most in danger of increased litigation. Other issues such as voluntary accreditation and outcomes evaluation are slowing gaining steam as the processes are becoming more available and more sought after, such as JCAHO accrediting of hospitals. ^ Adopting the principles discussed in this paper should promote better use of a local IRBs time, money, and expertise for protecting the vulnerable population in their care. Without further improvements to the system, there is concern that private and commercial IRBs will attempt to create a monopoly on much of the clinical research in the future as they are not as heavily regulated and can therefore offer companies quicker and more convenient reviews. IRBs need to consider the advantages of charging for their unique and important services as a cost of doing business. More importantly, there must be a minimum standard of education for all IRB members in the area of the ethical standards of human research and a greater emphasis placed on the follow-up of ongoing research as this is the most critical time for study participants and may soon lead to the largest area for litigation. Additionally, there should be a centralized IRB for multi-site trials or a study website with important information affecting the trial in real time. There needs to be development of standards and metrics to assess the performance of the IRBs for quality assurance and outcome evaluations. The boards should not be content to run the business of human subjects' research without determining how well that function is actually being carried out. It is important that federally regulated IRBs provide excellence in human research and promote those values most important to the public at large.^