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Biomedical subjects

Robert C Lee

Publications and source records attributed to Robert C Lee.

14 recordsLinked to original sources
PubMed2006

Risk analysis in radiation treatment: application of a new taxonomic structure.

BACKGROUND AND PURPOSE: Radiation treatment (RT) for cancer is susceptible to clinical incidents resulting from human errors and equipment failures. A systematic approach to collecting and processing incidents is required to manage patient risks. We describe the application of a new taxonomic structure for RT that supports risk analysis and organizational learning. MATERIALS AND METHODS: A systematic analysis of the RT process identified five process domains. Within each domain we defined incident type groups. We then constructed a database reflecting this taxonomic structure and populated it with incidents from publicly available sources. Querying this database provides insights into the nature and relative frequency of incidents in RT. RESULTS: There are relatively few reports of incidents in the Prescription domain compared with the Preparation and Treatment domains. There are also fewer reports of systematic and infrastructure incidents in comparison to sporadic and process incidents. Infrastructure incidents are mainly systematic in nature, while process incidents are more likely to be sporadic. CONCLUSIONS: The lack of a standard, systems-oriented framework for incident reporting makes it difficult to learn from existing incident report sources. A clear understanding of the potential consequences and relationships between different incident types will guide incident reporting, resource allocation, and risk management efforts.

Documentation↗
PubMed2005

Describing the longitudinal course of major depression using Markov models: data integration across three national surveys.

BACKGROUND: Most epidemiological studies of major depression report period prevalence estimates. These are of limited utility in characterizing the longitudinal epidemiology of this condition. Markov models provide a methodological framework for increasing the utility of epidemiological data. Markov models relating incidence and recovery to major depression prevalence have been described in a series of prior papers. In this paper, the models are extended to describe the longitudinal course of the disorder. METHODS: Data from three national surveys conducted by the Canadian national statistical agency (Statistics Canada) were used in this analysis. These data were integrated using a Markov model. Incidence, recurrence and recovery were represented as weekly transition probabilities. Model parameters were calibrated to the survey estimates. RESULTS: The population was divided into three categories: low, moderate and high recurrence groups. The size of each category was approximated using lifetime data from a study using the WHO Mental Health Composite International Diagnostic Interview (WMH-CIDI). Consistent with previous work, transition probabilities reflecting recovery were high in the initial weeks of the episodes, and declined by a fixed proportion with each passing week. CONCLUSION: Markov models provide a framework for integrating psychiatric epidemiological data. Previous studies have illustrated the utility of Markov models for decomposing prevalence into its various determinants: incidence, recovery and mortality. This study extends the Markov approach by distinguishing several recurrence categories.

Journal Article↗
PubMed2005

Risk assessment for inherited susceptibility to cancer: a review of the psychosocial and ethical dimensions.

The objective of this study was to conduct a broad-based systematic review of social, ethical, and legal considerations associated with genetic cancer risk assessment technologies (CaRATs). This paper focuses on psychosocial and ethical issues. Search results were limited to papers published in English, French, or German from January, 1990, to May, 2003. A quality assessment tool was developed and applied to retrieved papers. Application of the quality assessment tool resulted in 77 of 247 qualitative and quantitative primary research papers being reviewed and synthesized. A broad range of issues were addressed and grouped into content areas. Despite a large literature addressing psychosocial and ethical issues associated with CaRATs, many existing studies are not adequate to inform decision-makers and stakeholders. Careful policy analysis, as in some of the economic analyses reviewed here, is important to bridge this gap.

Bioethics↗
PubMed2004

Epidemiological theory, decision theory and mental health services research.

BACKGROUND: Mathematical models describing the epidemiology of major depression are potentially useful for epidemiological analyses, as decision support tools and in economic analyses. The objective of this project was to develop a Markov model based on epidemiological theory that may be useful for decision analysis and health services research. METHODS: Longitudinal data from a Canadian national survey, the National Population Health Survey (NPHS), were used. The NPHS has collected longitudinal data on a cohort of 17,262 subjects since 1994. The analysis employed a Markov tunnel in order to model the dependence of recovery probabilities on episode duration. RESULTS: Episode incidence ranged between 6.2 % per year in women under 35 to 0.26 % in men over the age of 65.A greater proportion of subjects over 35 years old reported episodes lasting more than 26 weeks. The probability of recovery declined with increasing episode duration, independently of sex. Under steady-state assumptions, a Markov model integrating these parameters predicted a point prevalence of approximately 2% in women and 1% in men under the age of 55. In older age groups, the predicted point prevalence declined in both sexes. CONCLUSIONS: These models support the hypothesis that sex differences in major depression prevalence are due primarily to differences in incidence rather than episode length. These results also indicate that there is no meaningful "central tendency" describing the distribution of episode length in major depression episode. Estimates of mean episode duration represent an intermixing of frequent brief episodes with infrequent protracted episodes. This finding may have important policy implications.

Adolescent↗
PubMed2004

Pathogenicity of Stagonospora nodorum requires malate synthase.

A gene encoding malate synthase, a key enzyme of the glyoxylate cycle, has been cloned and characterized in the necrotrophic wheat pathogen Stagonospora nodorum. Expression studies of Mls1 showed high levels of transcript in ungerminated spores whereas malate synthase enzyme activities were low. Expression studies in planta found that Mls1 transcript levels decreased approximately 10-fold upon germination before slowly increasing throughout the remainder of the infection. To characterize Mls1 further, the gene was disrupted in S. nodorum by homologous recombination. In the absence of any supplied carbon source, the mls1 spores were unable to germinate and consequently the mutants were non-pathogenic. Germination and pathogenicity could be restored by the addition of either glucose or sucrose, implying that S. nodorum is reliant upon the catabolism of lipids for infection. Furthermore, analysis of lipid bodies in the mutant strain indicated that lipid mobilization and, consequently, peroxisomal beta-oxidation of fatty acids is delayed or inhibited by the disruption of the glyoxylate cycle. This study has demonstrated for the first time in a fungal phytopathogen the requirement of malate synthase for pathogenicity, suggesting that gluconeogenesis is both dependent on the glyoxylate cycle and required for infection.

Ascomycota↗
PubMed2003

Health technology assessment, research, and implementation within a health region in Alberta, Canada.

OBJECTIVES: To determine the need for and implement health technology assessment (HTA) to inform decision making and policy within a regional health care system in Calgary (Alberta, Canada). METHODS: Published literature and organizational materials for the Calgary Health Region (CHR) and HTA units worldwide were reviewed. Key individuals within the provincial health ministry (Alberta Health and Wellness), CHR, the University of Calgary (U of C), funding agencies, and HTA organizations were consulted in a structured fashion. A structure for a regional HTA program was developed, taking into account relationships between these organizations. RESULTS: A locally focused HTA and implementation unit was deemed desirable. The Calgary Health Technology Implementation Unit (CaHTIU) was established. The CaHTIU was designed to efficiently integrate with CHR planning as well as undertake independent research activities. HTA activities focus primarily on CHR needs and are managed by a Health Technology Advisory Committee (HTAC) that consists of CHR management and other key individuals. Working groups contribute to and coordinate HTAs and implementation under the leadership of the unit Director, and include content as well as management individuals. The unit cooperates where appropriate with extant Canadian HTA organizations. CONCLUSIONS: The Calgary HTA unit is unique in Canada, because it functions within a regional health care system as well as a research institution. Advantages include a local focus in terms of applied HTAs, a systematic process for implementation of recommendations, and a collaborative atmosphere for research within the U of C.

Alberta↗
PubMed2003

Why reinvent risk?

Explore the source record for details and available documents.

Decision Making↗
PubMed2003

The need for evolution in healthcare decision modeling.

STATEMENT OF PROBLEM: Many healthcare decisions are difficult because they are complex and have important consequences such as the impact on survival or quality-of-life of individuals and on allocation of limited resources. The present state-of-the-art in healthcare decision modeling is often inadequate to properly assess these decisions. METHODS: Based on a literature search and the experience of the authors, typical methodologies used in healthcare decision analysis modeling are explored and compared with methods used in other practices. An example of hormonal therapy decisions is used. RESULTS: Useful methods that have been developed in other fields are presented. These include methods targeted toward appropriate assessment and representation of the complexity of decisions, assessment of uncertainty, use of nonexpected value decision analysis, and use of multi-attribute decision criteria. CONCLUSION: The state-of-the-art in healthcare decision modeling can be improved through learning from other practices.

Decision Making↗
PubMed2002

Bifunctional family 3 glycoside hydrolases from barley with alpha -L-arabinofuranosidase and beta -D-xylosidase activity. Characterization, primary structures, and COOH-terminal processing.

An alpha-l-arabinofuranosidase and a beta-d-xylosidase, designated ARA-I and XYL, respectively, have been purified about 1,000-fold from extracts of 5-day-old barley (Hordeum vulgare L.) seedlings using ammonium sulfate fractional precipitation, ion exchange chromatography, chromatofocusing, and size-exclusion chromatography. The ARA-I has an apparent molecular mass of 67 kDa and an isoelectric point of 5.5, and its catalytic efficiency during hydrolysis of 4'-nitrophenyl alpha-l-arabinofuranoside is only slightly higher than during hydrolysis of 4'-nitrophenyl beta-d-xyloside. Thus, the enzyme is actually a bifunctional alpha-l-arabinofuranosidase/beta-d-xylosidase. In contrast, the XYL enzyme, which also has an apparent molecular mass of 67 kDa and an isoelectric point of 6.7, preferentially hydrolyzes 4'-nitrophenyl beta-d-xyloside, with a catalytic efficiency approximately 30-fold higher than with 4'-nitrophenyl alpha-l-arabinofuranoside. The enzymes hydrolyze wheat flour arabinoxylan slowly but rapidly hydrolyze oligosaccharide products released from this polysaccharide by (1 --> 4)-beta-d-xylan endohydrolase. Both enzymes hydrolyze (1 --> 4)-beta-d-xylopentaose, and ARA-I can also degrade (1 --> 5)-alpha-l-arabinofuranohexaose. ARA-I and XYL cDNAs encode mature proteins of 748 amino acid residues which have calculated molecular masses of 79.2 and 80.5 kDa, respectively. Both are family 3 glycoside hydrolases. The discrepancies between the apparent molecular masses obtained for the purified enzymes and those predicted from the cDNAs are attributable to COOH-terminal processing, through which about 130 amino acid residues are removed from the primary translation product. The genes encoding the ARA-I and XYL have been mapped to chromosomes 2H and 6H, respectively. ARA-I transcripts are most abundant in young roots, young leaves, and developing grain, whereas XYL mRNA is detected in most barley tissues.

Amino Acid Sequence↗
PubMedDate not supplied

Towards a dynamic description of major depression epidemiology.

AIMS: The substantial impact of major depression on population health is widely acknowledged. To date, health system responses to this condition have been largely shaped by observational findings. In the future, health policy decisions will benefit from an increasingly integrated and dynamic understanding of the epidemiology of this condition. Policy decisions can also be supported by the development of decision-support tools that can simulate the impact of alternative policy decisions on population health. Markov models are useful both in epidemiological modelling and in decision analysis. METHODS: In this project, a Markov model describing major depression epidemiology was developed. The model employed a Markov Tunnel in order to depict the dependence of recovery probabilities on episode duration. Transition probabilities, including incidence, recovery and mortality were estimated from Canadian national survey data. RESULTS: Episode incidence was approximately 3% per year. Recovery rates declined exponentially over time. The model predicted point prevalence at slightly less than 1%, agreeing closely with observed prevalence data. CONCLUSIONS: Epidemiological models describing the dynamic relationships between major depression incidence, prevalence, recovery and mortality can help to integrate available epidemiological data. Such models offer an attractive option for support of health policy decisions.

Adolescent↗
PubMedDate not supplied

Refining estimates of major depression incidence and episode duration in Canada using a Monte Carlo Markov model.

BACKGROUND: Serial period prevalence estimates for recurrent diseases such as major depression are available more frequently than fully detailed longitudinal data, but it is difficult to estimate incidence and episode duration from such data. Incidence and episode duration are critical decision modeling parameters for recurrent diseases. OBJECTIVES: To reduce bias that would otherwise occur in national incidence and duration-of-episode estimates for major depressive episodes deriving from studies using serial period prevalence data and to illustrate a methodological approach for the estimation of incidence from such studies. METHODS: Monte Carlo simulation was applied to a Markov process describing incidence and recovery from major depressive episodes. RESULTS: The annual incidence and episode duration were found to be 3.1% and 17.1 weeks, respectively. These estimates are expected to be less subject to bias than those generated without modeling. CONCLUSIONS: These results highlight the usefulness of Markov models for analysis of longitudinal data. The methods described here may be useful for decision modeling and may be generalizable to other chronic diseases.

Canada↗
PubMedDate not supplied

Implications of cancer staging uncertainties in radiation therapy decisions.

INTRODUCTION: Radiation therapy (RT) for cancer is a critical medical procedure that occurs in a complex environment involving numerous health professionals, hardware, software, and equipment. Uncertainties and potential incidents can lead to inappropriate administration of radiation to patients, with sometimes catastrophic consequences such as premature death or appreciably impaired quality of life. The authors evaluate the impact of incorrectly staging (i.e., estimation of extent of cancer) breast cancer patients and resulting inappropriate treatment decisions. METHODS: The authors employ analytic and simulation methods in an influence-diagram framework to estimate the probability of incorrect staging and treatment decisions. As inputs, they use a combination of literature information on the accuracy and precision of pathology and tests as well as expert judgment. Sensitivity and value-of-information analyses are conducted to identify important uncertainties. RESULTS AND CONCLUSIONS: The authors find a small but nontrivial probability that breast cancer patients will be incorrectly staged and thus may be subjected to inappropriate treatment. Results are sensitive to a number of variables, and some routinely used tests for metastasis have very limited information value. This work has implications for the methods used in cancer staging, and the methods are generalizable for quantitative risk assessment of treatment errors.

Breast Neoplasms↗