A qualitative and quantitative assessment of cancer patients' perceptions of barriers to treatment

This study examined barriers that cancer patients experience in obtaining treatment. The principal aim of the study was to conduct a comprehensive quantitative and qualitative assessment of barriers to cancer treatment for Texas cancer patients. The three specific aims of the study were to: (1) conduct a review and critique of published and unpublished research on barriers to cancer treatment; (2) conduct focus groups for the qualitative assessment of cancer patients' perceived barriers to cancer treatment; and (3) survey a representative sample of cancer patients regarding perceived barriers to treatment. The study was guided by the Aday and Andersen access framework of predisposing, enabling, and need determinants of care-seeking.^ To address the first specific aim, a total of 732 abstracts were examined, from which 154 articles were selected for review. Of these 154 articles, 57 that related directly to research on barriers to cancer treatment were chosen for subsequent analysis. Criteria were applied to each article to evaluate the strength of the study design, sampling and measurement procedures. The major barriers that were consistently documented to influence whether or not cancer patients sought or continued required treatment included problems with communication between the patient and provider, lack of information on side effects, the cost of treatment and associated difficulties in obtaining and maintaining insurance coverage, and the absence of formal and informal networks of social support. Access barriers were generally greater for older, minority women, and patients of lower socioeconomic status.^ To address the second specific aim, a total of eight focus groups (n = 44) were conducted across the State of Texas with cancer patients identified by the Texas Community Oncology Network, American Cancer Society, and community health centers. One important finding was that cost is the greatest hurdle that patients face. Another finding was that with the health care/insurance crisis, an increasing number of physicians are working with their patients to develop individually-tailored payment plans. For people in rural areas, travel to treatment sites is a major barrier due to the travel costs as well as work time forfeited by patients and their family members. A third major finding was the patients' family and church play important roles in providing social and emotional support for cancer patients.^ To address the third aim, a total of 910 cancer patients were surveyed during October and November, 1993. Approximately 65% of the cancer patients responded to the survey. The findings showed that the major barriers to treatment included costs of medications and diagnostic tests, transportation, lack of social support, problems understanding the written information regarding their disease as well as losing coverage or having higher premiums or copayments once they were diagnosed (particularly among blacks).^ Significant differences in reported barriers were found between racial groups. The minority respondents (i.e., blacks and Hispanics) tended to experience more barriers to treatment compared to the white respondents. More specifically, Hispanics were more likely to report transportation as a barrier to treatment than both white and blacks. Future research is needed to better understand the problems that minority cancer patients experience in receiving treatment. (Abstract shortened by UMI.) ^

A qualitative assessment of the impact of Texas policy changes on nutrition in child care centers in Travis County, Texas

Background. Over half of children in the United States under age five spend 32 hours a week in child care, facilities, where they consume approximately 33-50% of their food intake. ^ Objectives. The aim of this research was to identify the effects of state nutrition policies on provision of food in child care centers. ^ Subjects. Eleven directors or their designee from ten randomly selected licensed child care centers in Travis County, Texas were interviewed. Centers included both nonprofit and for-profit centers, with enrollments ranging from 19 to 82. ^ Methods. Centers were selected using a web-based list of licensed child care providers in the Austin area. One-on-one interviews were conducted in person with center directors using a standard set of questions developed from previous pilot work. Interview items included demographic data, questions about state policies regarding provision of foods in centers, effects of policies on child care center budgets and foods offered, and changes in the provision of food. All interviews were audiotaped and transcribed, and themes were identified using standard qualitative techniques. ^ Results. Four of the centers provided both meals and snacks, four provided snacks only, and two did not provide any food. Directors of centers that provided food were more likely to report adherence to the Minimum Standards than directors of centers that did not. In general, center directors reported that the regulations were loosely enforced. In contrast, center directors were more concerned about a local city-county regulation that required food permits and new standards for kitchens. Most of these local regulations were cost prohibitive and, as a result, centers had changed the types of foods provided, which included providing less fresh produce and more prepackaged items. Although implementation of local regulations had reduced provision of fruits and vegetables to children, no adjustments were reported for allocation of resources, tuition costs or care of the children. ^ Conclusions. Qualitative data from a small sample of child care directors indicate that the implementation and accountability of food- and nutrition-related guidelines for centers is sporadic, uncoordinated, and can have unforeseen effects on the provision of food. A quantitative survey and dietary assessment methods should be conducted to verify these findings in a larger and more representative sample.^

Quantitative comparison of late effects following photon versus proton external-beam radiation therapies: Toward an evidence-based approach to selecting a treatment modality

Radiation therapy has been used as an effective treatment for malignancies in pediatric patients. However, in many cases, the side effects of radiation diminish these patients’ quality of life. In order to develop strategies to minimize radiogenic complications, one must first quantitatively estimate pediatric patients’ relative risk for radiogenic late effects, which has not become feasible till recently because of the calculational complexity. The goals of this work were to calculate the dose delivered to tissues and organs in pediatric patients during contemporary photon and proton radiotherapies; to estimate the corresponding risk of radiogenic second cancer and cardiac toxicity based on the calculated doses and on dose-risk models from the literature; to test for the statistical significance of the difference between predicted risks after photon versus proton radiotherapies; and to provide a prototype of an evidence-based approach to selecting treatment modalities for pediatric patients, taking second cancer and cardiac toxicity into account. The results showed that proton therapy confers a lower predicted risk of radiogenic second cancer, and lower risks of radiogenic cardiac toxicities, compared to photon therapy. An uncertainty analysis revealed that the qualitative findings of this study are insensitive to changes in a wide variety of host and treatment related factors.

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.