THE RELATIONSHIP BETWEEN SERUM CHOLESTEROL AND CANCER INCIDENCE IN THE POPULATION OF THE HYPERTENSION DETECTION AND FOLLOW-UP PROGRAM

The relationship between serum cholesterol and cancer incidence was investigated in the population of the Hypertension Detection and Follow-up Program (HDFP). The HDFP was a multi-center trial designed to test the effectiveness of a stepped program of medication in reducing mortality associated with hypertension. Over 10,000 participants, ages 30-69, were followed with clinic and home visits for a minimum of five years. Cancer incidence was ascertained from existing study documents, which included hospitalization records, autopsy reports and death certificates. During the five years of follow-up, 286 new cancer cases were documented. The distribution of sites and total number of cases were similar to those predicted using rates from the Third National Cancer Survey. A non-fasting baseline serum cholesterol level was available for most participants. Age, sex, and race specific five-year cancer incidence rates were computed for each cholesterol quartile. Rates were also computed by smoking status, education status, and percent ideal weight quartiles. In addition, these and other factors were investigated with the use of the multiple logistic model.^ For all cancers combined, a significant inverse relationship existed between baseline serum cholesterol levels and cancer incidence. Previously documented associations between smoking, education and cancer were also demonstrated but did not account for the relationship between serum cholesterol and cancer. The relationship was more evident in males than females but this was felt to represent the different distribution of occurrence of specific cancer sites in the two sexes. The inverse relationship existed for all specific sites investigated (except breast) although a level of statistical significance was reached only for prostate carcinoma. Analyses after exclusion of cases diagnosed during the first two years of follow-up still yielded an inverse relationship. Life table analysis indicated that competing risks during the period of follow-up did not account for the existence of an inverse relationship. It is concluded that a weak inverse relationship does exist between serum cholesterol for many but not all cancer sites. This relationship is not due to confounding by other known cancer risk factors, competing risks or persons entering the study with undiagnosed cancer. Not enough information is available at the present time to determine whether this relationship is causal and further research is suggested. ^

THE RELATIONSHIP BETWEEN DEGREE OF BLOOD PRESSURE REDUCTION AND MORTALITY AMONG HYPERTENSIVES IN THE HYPERTENSION DETECTION AND FOLLOW-UP PROGRAM

The relationship between degree of diastolic blood pressure (DBP) reduction and mortality was examined among hypertensives, ages 30-69, in the Hypertension Detection and Follow-up Program (HDFP). The HDFP was a multi-center community-based trial, which followed 10,940 hypertensive participants for five years. One-year survival was required for inclusion in this investigation since the one-year annual visit was the first occasion where change in blood pressure could be measured on all participants. During the subsequent four years of follow-up on 10,052 participants, 568 deaths occurred. For levels of change in DBP and for categories of variables related to mortality, the crude mortality rate was calculated. Time-dependent life tables were also calculated so as to utilize available blood pressure data over time. In addition, the Cox life table regression model, extended to take into account both time-constant and time-dependent covariates, was used to examine the relationship change in blood pressure over time and mortality.^ The results of the time-dependent life table and time-dependent Cox life table regression analyses supported the existence of a quadratic function which modeled the relationship between DBP reduction and mortality, even after adjusting for other risk factors. The minimum mortality hazard ratio, based on a particular model, occurred at a DBP reduction of 22.6 mm Hg (standard error = 10.6) in the whole population and 8.5 mm Hg (standard error = 4.6) in the baseline DBP stratum 90-104. After this reduction, there was a small increase in the risk of death. There was not evidence of the quadratic function after fitting the same model using systolic blood pressure. Methodologic issues involved in studying a particular degree of blood pressure reduction were considered. The confidence interval around the change corresponding to the minimum hazard ratio was wide and the obtained blood pressure level should not be interpreted as a goal for treatment. Blood pressure reduction was attributed, not only to pharmacologic therapy, but also to regression to the mean, and to other unknown factors unrelated to treatment. Therefore, the surprising results of this study do not provide direct implications for treatment, but strongly suggest replication in other populations. ^

REGRESSION ANALYSIS FOR STANDARDIZED MORTALITY RATIOS WITH APPLICATION TO OCCUPATIONAL FOLLOW-UP STUDIES

Traditional comparison of standardized mortality ratios (SMRs) can be misleading if the age-specific mortality ratios are not homogeneous. For this reason, a regression model has been developed which incorporates the mortality ratio as a function of age. This model is then applied to mortality data from an occupational cohort study. The nature of the occupational data necessitates the investigation of mortality ratios which increase with age. These occupational data are used primarily to illustrate and develop the statistical methodology.^ The age-specific mortality ratio (MR) for the covariates of interest can be written as MR(,ij...m) = ((mu)(,ij...m)/(theta)(,ij...m)) = r(.)exp (Z('')(,ij...m)(beta)) where (mu)(,ij...m) and (theta)(,ij...m) denote the force of mortality in the study and chosen standard populations in the ij...m('th) stratum, respectively, r is the intercept, Z(,ij...m) is the vector of covariables associated with the i('th) age interval, and (beta) is a vector of regression coefficients associated with these covariables. A Newton-Raphson iterative procedure has been used for determining the maximum likelihood estimates of the regression coefficients.^ This model provides a statistical method for a logical and easily interpretable explanation of an occupational cohort mortality experience. Since it gives a reasonable fit to the mortality data, it can also be concluded that the model is fairly realistic. The traditional statistical method for the analysis of occupational cohort mortality data is to present a summary index such as the SMR under the assumption of constant (homogeneous) age-specific mortality ratios. Since the mortality ratios for occupational groups usually increase with age, the homogeneity assumption of the age-specific mortality ratios is often untenable. The traditional method of comparing SMRs under the homogeneity assumption is a special case of this model, without age as a covariate.^ This model also provides a statistical technique to evaluate the relative risk between two SMRs or a dose-response relationship among several SMRs. The model presented has application in the medical, demographic and epidemiologic areas. The methods developed in this thesis are suitable for future analyses of mortality or morbidity data when the age-specific mortality/morbidity experience is a function of age or when there is an interaction effect between confounding variables needs to be evaluated. ^

Sacred vocation program follow up evaluation at the Baylor healthcare system

Background: The Sacred Vocation Program (SVP) (Amick B, Karff S., 2003) helps workers find meaning, spirituality, and see their job as a sacred vocation. The SVP is based on Participatory Action Research (PAR) (Minkler & Wallerstein, 1997; Parker & Wall, 1998). This study aims to evaluate the SVP implemented at the Baylor Healthcare System, Dallas-Fort Worth. ^ Methods: The study design is a qualitative design. We used data from study participants who have participated in focus groups. During these focus groups specific questions and probes regarding the effectiveness of the SVP have been asked. We analyzed the focus groups and derived themes. ^ Results: Results of this study demonstrate SVP helps graduates feel valued and important. The SVP has improved meaningful work for employees and improved a sense of belonging for participants. The program has also increased participant spirituality. The coping techniques developed during a SVP class helps participants deal with stressful situations. The SVP faces challenges of implementation fidelity, poor communication, program viability in tough economic times and implementation of phase II. Another sustainability challenge for SVP is the perception of the program being a religious one versus a spiritual program. ^ Conclusion: Several aspects of the SVP work. The phase I of SVP is successful in improving meaningful work and a sense of belonging for participants. The coping techniques help participants deal with difficult work situations. The SVP can increase effectiveness through improvements in implementation fidelity, communication and leadership commitment. ^

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.^

In-utero exposure to chemotherapy: What are the long term effects?

There is not a large body of evidence on in-utero exposure to chemotherapy for pregnancy-associated cancers to help determine the long term effects on offspring. This study is a systematic review of long term follow-up to find evidence for adverse outcomes in exposed offspring. In order for studies to be eligible for this systematic review, they had to have a median follow up of at least 24 months with the resulting child. PubMed, Medline, and Scopus were the databases used, and we included all eligible articles, regardless of the date of publication. The search resulted in six articles meeting the eligibility requirements. The review of findings of these studies suggested that there is not enough evidence to make a determination of the risk of chemotherapy for the offspring. Exposed children in the sample of reviewed papers did have some medical conditions, but the rate and type did not differ from the non-exposed population. However, a limitation of this literature review is the very small sample size of publications on this important topic. This finding of few studies on this topic is an important result of this systematic review. More research and long term follow-up studies must be conducted to address this issue.^

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.^

TALISMAN+: Intelligent System for Follow-Up and Promotion of Personal Autonomy

The TALISMAN+ project, financed by the Spanish Ministry of Science and Innovation, aims to research and demonstrate innovative solutions transferable to society which offer services and products based on information and communication technologies in order to promote personal autonomy in prevention and monitoring scenarios. It will solve critical interoperability problems among systems and emerging technologies in a context where heterogeneity brings about accessibility barriers not yet overcome and demanded by the scientific, technological or social-health settings.

A telematics solution for the remote follow-up of malnourished children in underserved areas

The identification of malnourished children living under extreme poverty conditions in isolated areas is crucial to trigger urgent interventions like supplementary or therapeutic feeding. This work aims to strengthen the task of following-up malnourished maternal-child population in rural areas of developing countries like Nicaragua. The solution facilitates low-cost health nutritional remote monitoring to support rural communities at the point of care. Thus, the system allows medical staff to communicate with brigades, who transmit anthropometric measurements, such as weight and height of the children, from communities which are sited about 12 km. far away. A hybrid WiMAX/WiFi architecture was deployed to provide affordable communications between the isolated communities and the health center. Furthermore, a free PBX software and an open information system, installed at the health center, support WiFi based mobile communications and information management to support the care needs of maternal-child population at risk.