Prophylactic mastectomy and oophorectomy for women at risk of breast and ovarian cancer: Incorporating preferences in a decision analysis

The discoveries of the BRCA1 and BRCA2 genes have made it possible for women of families with hereditary breast/ovarian cancer to determine if they carry cancer-predisposing genetic mutations. Women with germline mutations have significantly higher probabilities of developing both cancers than the general population. Since the presence of a BRCA1 or BRCA2 mutation does not guarantee future cancer development, the appropriate course of action remains uncertain for these women. Prophylactic mastectomy and oophorectomy remain controversial since the underlying premise for surgical intervention is based more upon reduction in the estimated risk of cancer than on actual evidence of clinical benefit. Issues that are incorporated in a woman's decision making process include quality of life without breasts, ovaries, attitudes toward possible surgical morbidity as well as a remaining risk of future development of breast/ovarian cancer despite prophylactic surgery. The incorporation of patient preferences into decision analysis models can determine the quality-adjusted survival of different prophylactic approaches to breast/ovarian cancer prevention. Monte Carlo simulation was conducted on 4 separate decision models representing prophylactic oophorectomy, prophylactic mastectomy, prophylactic oophorectomy/mastectomy and screening. The use of 3 separate preference assessment methods across different populations of women allows researchers to determine how quality adjusted survival varies according to clinical strategy, method of preference assessment and the population from which preferences are assessed. ^

A study of nurses' judgement of and participation in decision-making for nursing home placement for the elderly

This study investigated the effects of patient variables (physical and cognitive disability, significant others' preference and social support) on nurses' nursing home placement decision-making and explored nurses' participation in the decision-making process.^ The study was conducted in a hospital in Texas. A sample of registered nurses on units that refer patients for nursing home placement were asked to review a series of vignettes describing elderly patients that differed in terms of the study variables and indicate the extent to which they agreed with nursing home placement on a five-point Likert scale. The vignettes were judged to have good content validity by a group of five colleagues (expert consultants) and test-retest reliability based on the Pearson correlation coefficient was satisfactory (average of.75) across all vignettes.^ The study tested the following hypotheses: Nurses have more of a propensity to recommend placement when (1) patients have severe physical disabilities; (2) patients have severe cognitive disabilities; (3) it is the significant others' preference; and (4) patients have no social support nor alternative services. Other hypotheses were that (5) a nurse's characteristics and extent of participation will not have a significant effect on their placement decision; and (6) a patient's social support is the most important, single factor, and the combination of factors of severe physical and cognitive disability, significant others' preference, and no social support nor alternative services will be the most important set of predictors of a nurse's placement decision.^ Analysis of Variance (ANOVA) was used to analyze the relationships implied in the hypothesis. A series of one-way ANOVA (bivariate analyses) of the main effects supported hypotheses one-five.^ Overall, the n-way ANOVA (multivariate analyses) of the main effects confirmed that social support was the most important single factor controlling for other variables. The 4-way interaction model confirmed that the most predictive combination of patient characteristics were severe physical and cognitive disability, no social support and the significant others did not desire placement. These analyses provided an understanding of the importance of the influence of specific patient variables on nurses' recommendations regarding placement. ^

Design and implementation of a multicriteria medical decision support system for diagnosis and treatment

Health care providers face the problem of trying to make decisions with inadequate information and also with an overload of (often contradictory) information. Physicians often choose treatment long before they know which disease is present. Indeed, uncertainty is intrinsic to the practice of medicine. Decision analysis can help physicians structure and work through a medical decision problem, and can provide reassurance that decisions are rational and consistent with the beliefs and preferences of other physicians and patients. ^ The primary purpose of this research project is to develop the theory, methods, techniques and tools necessary for designing and implementing a system to support solving medical decision problems. A case study involving “abdominal pain” serves as a prototype for implementing the system. The research, however, focuses on a generic class of problems and aims at covering theoretical as well as practical aspects of the system developed. ^ The main contributions of this research are: (1) bridging the gap between the statistical approach and the knowledge-based (expert) approach to medical decision making; (2) linking a collection of methods, techniques and tools together to allow for the design of a medical decision support system, based on a framework that involves the Analytic Network Process (ANP), the generalization of the Analytic Hierarchy Process (AHP) to dependence and feedback, for problems involving diagnosis and treatment; (3) enhancing the representation and manipulation of uncertainty in the ANP framework by incorporating group consensus weights; and (4) developing a computer program to assist in the implementation of the system. ^

A space-time analysis of reported shigellosis and salmonellosis cases in Texas from 2000 to 2004

Background. The purpose of this study was to describe the risk factors and demographics of persons with salmonellosis and shigellosis and to investigate both seasonal and spatial variations in the occurrence of these infections in Texas from 2000 to 2004, utilizing time series analyses and the geographic information system digital mapping methods. ^ Methods. Spatial Analysis: MapInfo software was used to map the distribution of age-adjusted rates of reported shigellosis and salmonellosis in Texas from 2000–2004 by zip codes. Census data on above or below poverty level, household income, highest level of educational attainment, race, ethnicity, and urban/rural community status was obtained from the 2000 Decennial Census for each zip code. The zip codes with the upper 10% and lower 10% were compared using t-tests and logistic regression to determine whether there were any potential risk factors. ^ Temporal analysis. Seasonal patterns in the prevalence of infections in Texas from 2000 to 2003 were determined by performing time-series analysis on the numbers of cases of salmonellosis and shigellosis. A linear regression was also performed to assess for trends in the incidence of each disease, along with auto-correlation and multi-component cosinor analysis. ^ Results. Spatial analysis: Analysis by general linear model showed a significant association between infection rates and age, with young children aged less than 5 and those aged 5–9 years having increased risk of infection for both disease conditions. The data demonstrated that those populations with high percentages of people who attained a higher than high school education were less likely to be represented in zip codes with high rates of shigellosis. However, for salmonellosis, logistic regression models indicated that when compared to populations with high percentages of non-high school graduates, having a high school diploma or equivalent increased the odds of having a high rate of infection. ^ Temporal analysis. For shigellosis, multi-component cosinor analyses were used to determine the approximated cosine curve which represented a statistically significant representation of the time series data for all age groups by sex. The shigellosis results show 2 peaks, with a major peak occurring in June and a secondary peak appearing around October. Salmonellosis results showed a single peak and trough in all age groups with the peak occurring in August and the trough occurring in February. ^ Conclusion. The results from this study can be used by public health agencies to determine the timing of public health awareness programs and interventions in order to prevent salmonellosis and shigellosis from occurring. Because young children depend on adults for their meals, it is important to increase the awareness of day-care workers and new parents about modes of transmission and hygienic methods of food preparation and storage. ^

Cost-effectiveness of universal prophylaxis in pregnancy with prior group B streptococci colonization.

OBJECTIVE: To estimate the costs and outcomes of rescreening for group B streptococci (GBS) compared to universal treatment of term women with history of GBS colonization in a previous pregnancy. STUDY DESIGN: A decision analysis model was used to compare costs and outcomes. Total cost included the costs of screening, intrapartum antibiotic prophylaxis (IAP), treatment for maternal anaphylaxis and death, evaluation of well infants whose mothers received IAP, and total costs for treatment of term neonatal early onset GBS sepsis. RESULTS: When compared to screening and treating, universal treatment results in more women treated per GBS case prevented (155 versus 67) and prevents more cases of early onset GBS (1732 versus 1700) and neonatal deaths (52 versus 51) at a lower cost per case prevented ($8,805 versus $12,710). CONCLUSION: Universal treatment of term pregnancies with a history of previous GBS colonization is more cost-effective than the strategy of screening and treating based on positive culture results.

Effective interventions for lowering HbA1C in African Americans with type 2 diabetes: A review

This synthesis of the literature provides descriptive analysis and outlines current self-management interventions for African Americans with type 2 diabetes. Specifically, this study describes and explores the design of those studies whose interventions have been shown to lower HbA1C levels in this population by at least 0.5% points, an improvement that provides approximately 10% reduction in long term complications from this disease.^ Results. In total, 37 articles were reviewed and 17 articles met inclusion criteria for analysis. Analysis of each study's methodology and results was performed and selected studies with interventions that resulted in improvements in HbA1C outcomes equal to 0.5% or greater for both group 1 and 2 were summarized by intervention type in table format. Descriptive analysis, outlining the number and characteristics of proximal and distal mediating components addressed in Group 1 studies, was performed in order to determine whether mediating components may have had some relation to effectiveness of intervention on outcome HbA1C. Descriptive analysis revealed that no particular design is substantially more effective than another among Behavioral studies although, there may be an advantage in using culturally sensitive, group interventions that address greater numbers of distal mediating components. Among Process studies, structured approaches (i.e. algorithm care and scheduled follow up), as well as utilization of specialty and group care are represented as effective for African American populations. ^ Conclusions. It may be summarized that by targeting behavior and addressing provider delivery (i.e. algorithm use, group care, home care, and provider follow up) in this population, a greater yield in outcome improvements may be accomplished. However, many gaps exist in a review process that stratifies results and focuses on identifying group specific intervention successes and failures. Further research in different populations will aid researchers and practitioners in discovering the best evidence, and identifying models that could be utilized in practice to achieve the best diabetes management for at risk groups.^

Assessing the relationship between obesity and type II diabetes among South Asian Indians in Houston A population based study

Objective: My study aimed at determining the association between obesity and diabetes prevalence in South Asian Indian immigrants in Houston, Texas. To also compare the prevalence odds of diabetes given obesity, using WHO-BMI criteria and recommended Asian ethnic-specific BMI criteria for obesity, as well as using WHO-standard waist circumference criteria and ethnic-specific criteria for abdominal obesity, across gender and age, in this population. ^ Methods: My study was a secondary data analysis based on a cross-sectional study carried out on adult South Asian Indians who attended a local community health fair in Houston, in 2007. They recruited 213 voluntary, eligible, South Asian Indian participants aged between 18 to 79 years. Self reported history of Diabetes was obtained and height, weight, waist and hip circumference were measured. I classified BMI based on WHO-standard and ethnic-specific criteria, according to gender and age groups of 18–35 years, 36–64 years and 65 years and over. Waist circumference was also classified based on WHO-standard NCEP criteria and currently recommended ethnic-specific IDF criteria and analysis was done stratifying by gender and age groups. ^ Results: The prevalence of diabetes in this population was 14.6%, significantly higher in older age groups (25.8%) and males (19.2%). The prevalence of DM was statistically similar in individuals who were overweight/obese compared to those not overweight/obese, however in overweight/obese individuals, there was a statistically significant difference in the prevalence of DM between WHO and ethnic-specific criteria for both BMI and waist circumference. In older adults and in males, ethnic-specific criteria identified significantly more as overweight/obese compared to WHO-standard criteria. ^ Conclusions: Ethnic-specific criteria for both BMI and waist circumference give a better estimate for obesity in this South Asian Indian population. Diabetes is highly prevalent in migrant South Asian Indians even at low BMI or waist circumference levels and significantly more in males and older age groups, hence adequate awareness should be created for early prevention and intervention.^

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

A review of economic analysis in the vaccination program; decision making and governance: Adivisory Committee on Immunization Practices (ACIP)

The Advisory Committee on Immunization Practices (ACIP) develops written recommendations for the routine administration of vaccines to children and adults in the U.S. civilian population. The ACIP is the only entity in the federal government that makes such recommendations. ACIP elaborates on selection of its members and rules out concerns regarding its integrity, but fails to provide information about the importance of economic analysis in vaccine selection. ACIP recommendations can have large health and economic consequences. Emphasis on economic evaluation in health is a likely response to severe pressures of the federal and state health budget. This study describes the economic aspects considered by the ACIP while sanctioning a vaccine, and reviews the economic evaluations (our economic data) provided for vaccine deliberations. A five year study period from 2004 to 2009 is adopted. Publicly available data from ACIP web database is used. Drummond et al. (2005) checklist serves as a guide to assess the quality of economic evaluations presented. Drummond et al.'s checklist is a comprehensive hence it is unrealistic to expect every ACIP deliberation to meet all of their criteria. For practical purposes we have selected seven criteria that we judge to be significant criteria provided by Drummond et al. Twenty-four data points were obtained in a five year period. Our results show that out of the total twenty-four data point‘s (economic evaluations) only five data points received a score of six; that is six items on the list of seven were met. None of the data points received a perfect score of seven. Seven of the twenty-four data points received a score of five. A minimum of a two score was received by only one of the economic analyses. The type of economic evaluation along with the model criteria and ICER/QALY criteria met at 0.875 (87.5%). These three criteria were met at the highest rate among the seven criteria studied. Our study findings demonstrate that the perspective criteria met at 0.583 (58.3%) followed by source and sensitivity analysis criteria both tied at 0.541 (54.1%). The discount factor was met at 0.250 (25.0%).^ Economic analysis is not a novel concept to the ACIP. It has been practiced and presented at these meetings on a regular basis for more than five years. ACIP‘s stated goal is to utilize good quality epidemiologic, clinical and economic analyses to help policy makers choose among alternatives presented and thus achieve a better informed decision. As seen in our study the economic analyses over the years are inconsistent. The large variability coupled with lack of a standardized format may compromise the utility of the economic information for decision-making. While making recommendations, the ACIP takes into account all available information about a vaccine. Thus it is vital that standardized high quality economic information is provided at the ACIP meetings. Our study may provide a call for the ACIP to further investigate deficiencies within the system and thereby to improve economic evaluation data presented. ^