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Open Access Publications from the University of California

Scholarly Works (62 results)

  • Article
  • Peer Reviewed
UC Irvine Previously Published Works (2010)
    Cover page: Chemoprevention, Risk Reduction, Therapeutic Prevention, or Preventive Therapy?Creative Commons 'BY' version 4.0 license
    • Article
    • Peer Reviewed
    UC Irvine Previously Published Works (2011)
    View the pubcast on this paper at http://www.scivee.tv/node/29174
      Cover page: Melanoma: is hair the root of the problem?Creative Commons 'BY' version 4.0 license
      • Thesis
      • Peer Reviewed
      UC Irvine Electronic Theses and Dissertations (2018)

      Background: Diabetes mellitus is associated with increased cardiovascular prevalence and mortality. However, this relationship is different between type 1 and type 2 diabetes mellitus. While classical and diabetes-related cardiovascular risk factors are associated with cardiovascular events in both diabetes type, it is unclear how diabetes type plays a role in the prevalence of these cardiovascular risk factors.

      Objective: The objective of this study was to compare cardiovascular risk factors between type 1 and type 2 diabetes mellitus, in adults, performing a novel method for diabetes type classification.

      Methods: This is a cross-sectional analysis of participants aged 20 years or older in the National Health and Nutrition Examination Survey (NHANES) 1999-2016 that completed the medical examinations, laboratory tests, and the diabetes questionnaire.

      Results: A total of 5347 adult participants (age ≥ 20) with diagnosed diabetes were included. Our algorithm classified 230 as type 1 diabetes and 4677 as type 2 diabetes mellitus cases (remaining 440 were excluded). Higher age, triglycerides level, Body Mass Index, and being from races other than White were indicative of type 2 diabetes mellitus, while longer diabetes duration, higher HbA1c rate, more prevalent of chronic kidney disease and having higher education were more indicative of type 1 diabetes mellitus. Lipid panel disturbances, Chronic Kidney Disease, and insulin resistance appeared more prevalent in type 1 diabetes mellitus cohort as previously described.

      Conclusion: The prevalence of cardiovascular risk factors differs by diabetes type and have also attested temporal trends. Diabetes type should be considered in cardiovascular disease risk assessments and preventions.

        Cover page: Comparison of Cardiovascular Risk Factors between Type 1 and Type 2 Diabetes MellitusCreative Commons 'BY-NC-ND' version 4.0 license
        • Article
        • Peer Reviewed
        UC Irvine Previously Published Works (2014)
        Clinical treatment decisions rely on prognostic evaluation of a patient's future health outcomes. Thus, predictive models under different treatment options are key factors for making good decisions. While many criteria exist for judging the statistical quality of a prediction model, few are available to measure its clinical utility. As a consequence, we may find that the addition of a clinical covariate or biomarker improves the statistical quality of the model, but has little effect on its clinical usefulness. We focus on the setting where a treatment decision may reduce a patient's risk of a poor outcome, but also comes at a cost; this may be monetary, inconvenience, or the potential side effects. This setting is exemplified by cancer chemoprevention, or the use of statins to reduce the risk of cardiovascular disease. We propose a novel approach to assessing a prediction model using a formal decision analytic framework. We combine the predictive model's ability to discriminate good from poor outcome with the net benefit afforded by treatment. In this framework, reduced risk is balanced against the cost of treatment. The relative cost-benefit of treatment provides a useful index to assist patient decisions. This index also identifies the relevant clinical risk regions where predictive improvement is needed. Our approach is illustrated using data from a colorectal adenoma chemoprevention trial.
          Cover page: Combined Benefit of Prediction and Treatment: A Criterion for Evaluating Clinical Prediction Models
          • Article
          • Peer Reviewed
          UC Irvine Previously Published Works (2013)
          Gallbladder cancer is a rare malignancy, which often goes undiagnosed until advanced stages of disease and is associated with poor prognosis. The only potentially curative treatment is surgical resection. This retrospective study aims to investigate the validity of the revised 7th edition American Joint Committee on Cancer staging criteria and determine prognostic factors. Forty-two patients with confirmed gallbladder cancer who underwent attempted curative resection from 1999 to 2012 at the University of California, Irvine Medical Center were reviewed. Survival probability was determined using the Kaplan-Meier method. Ten patients underwent laparoscopy, were deemed unresectable, and no further surgical intervention was performed. R0 surgical resection, which included radical portal lymphadenectomy, liver segment IVb/V resection, with or without bile duct resection, was performed in the remaining 32 patients. N2 nodes were resected if positive on frozen section. Overall survival probability for Stage I to II patients was 100 per cent. Overall survival probability for Stage III patients was 80 per cent (95% confidence interval [CI], 61 to 99%) and 39.3 per cent (95% CI, 28 to 78%) for Stage IV patients. This study demonstrates that 7th edition clinical stage, T stage, and liver involvement are statistically significant predictors of prognosis. These data also demonstrate a benefit to extended resection in patients even with Stage III and IV disease.
            Cover page: Validation of Revised American Joint Committee on Cancer Staging for Gallbladder Cancer Based on a Single Institution Experience
            • Article
            • Peer Reviewed
            UC Irvine Previously Published Works (2008)

            Objectives

            The objectives of this study were to: 1) determine if a genetic algorithm in combination with morphing software can be used to evolve more attractive faces; and 2) evaluate whether this approach can be used as a tool to define or identify the attributes of the ideal attractive face.

            Study design

            Basic research study incorporating focus group evaluations.

            Methods

            Digital images were acquired of 250 female volunteers (18-25 y). Randomly selected images were used to produce a parent generation (P) of 30 synthetic faces using morphing software. Then, a focus group of 17 trained volunteers (18-25 y) scored each face on an attractiveness scale ranging from 1 (unattractive) to 10 (attractive). A genetic algorithm was used to select 30 new pairs from the parent generation, and these were morphed using software to produce a new first generation (F1) of faces. The F1 faces were scored by the focus group, and the process was repeated for a total of four iterations of the algorithm. The algorithm mimics natural selection by using the attractiveness score as the selection pressure; the more attractive faces are more likely to morph. All five generations (P-F4) were then scored by three focus groups: a) surgeons (n = 12), b) cos-metology students (n = 44), and c) undergraduate students (n = 44). Morphometric measurements were made of 33 specific features on each of the 150 synthetic faces, and correlated with attractiveness scores using univariate and multivariate analysis.

            Results

            The average facial attractiveness scores increased with each generation and were 3.66 (+0.60), 4.59 (+/-0.73), 5.50 (+/-0.62), 6.23 (+/-0.31), and 6.39 (+/-0.24) for P and F1-F4 generations, respectively. Histograms of attractiveness score distributions show a significant shift in the skew of each curve toward more attractive faces with each generation. Univariate analysis identified nasal width, eyebrow arch height, and lip thickness as being significantly correlated with attractiveness scores. Multivariate analysis identified a similar collection of morphometric measures. No correlation with more commonly accepted measures such as the length facial thirds or fifths were identified. When images are examined as a montage (by generation), clear distinct trends are identified: oval shaped faces, distinct arched eyebrows, and full lips predominate. Faces evolve to approximate the guidelines suggested by classical canons. F3 and F4 generation faces look profoundly similar. The statistical and qualitative analysis indicates that the algorithm and methodology succeeds in generating successively more attractive faces.

            Conclusions

            The use of genetic algorithms in combination with a morphing software and traditional focus-group derived attractiveness scores can be used to evolve attractive synthetic faces. We have demonstrated that the evolution of attractive faces can be mimicked in software. Genetic algorithms and morphing provide a robust alternative to traditional approaches rooted in comparing attractiveness scores with a series of morphometric measurements in human subjects.
              Cover page: Evolving Attractive Faces Using Morphing Technology and a Genetic Algorithm: A New Approach to Determining Ideal Facial AestheticsCreative Commons 'BY' version 4.0 license
              • Article
              • Peer Reviewed
              UC Irvine Previously Published Works (2012)

              Chemoprevention with the polyamine-inhibitory regimen difluoromethylornithine (DFMO) + sulindac markedly reduces risk of recurrent adenoma in colorectal adenoma patients. Obesity is associated with risk of colorectal adenoma and colorectal cancer. This study investigates how obesity influences risk of recurrent adenoma after prolonged treatment with DFMO + sulindac versus placebo.

              Our analysis included subjects enrolled in the phase III colorectal adenoma prevention clinical trial investigating DFMO + sulindac versus placebo. Patients were classified by obesity (body mass index, BMI ≥ 30 kg/m(2)) status at baseline. Pearson χ(2) statistic and Mann-Whitney U test were used to compare baseline characteristics, including rectal tissue polyamine levels. Log-binomial regression analysis was used to determine the risk ratio (RR) of recurrent adenomas, adjusted for covariates and an interaction term for obesity and treatment.

              The final analytic cohort was comprised of 267 patients. In separate regression models, the risk of adenoma recurrence after treatment compared to placebo was similar for obese (RR = 0.32, 95 % CI 15-71) and non-obese patients (RR = 0.27, 95 % CI 15-49). No significant interaction was detected between obesity, treatment, and risk of colorectal adenoma in the full regression model (p (interaction) = 0.91).

              Obesity does not substantially modify the colorectal adenoma risk reduction ascribed to DFMO + sulindac versus placebo.

                Cover page: Role of obesity in a randomized placebo-controlled trial of difluoromethylornithine (DFMO) + sulindac for the prevention of sporadic colorectal adenomas.
                • Article
                • Peer Reviewed
                UC Irvine Previously Published Works (2020)
                In epidemiology studies, identification of diabetes type (type 1 vs. type 2) among study participants with diabetes is important; however, conventional diabetes type identification approaches that include age at diabetes diagnosis as an initial criterion introduces biases. Using data from the National Health and Nutrition Examination Survey, we have developed a novel algorithm which does not include age at diagnosis to identify participants with self-reported diagnosed diabetes as having type 1 vs. type 2 diabetes.

                Methods

                A total of 5457 National Health and Nutrition Examination Survey participants between cycles 1999-2000 and 2015-2016 reported that a health professional had diagnosed them as having diabetes at a time other than during pregnancy and had complete information on diabetes-related questions. After developing an algorithm based on information regarding the treatment(s) they received, we classified these participants as having type 1 or type 2 diabetes.

                Results

                The treatment-based algorithm yielded a 6-94% split for type 1 and type 2 diabetes, which is consistent with reports from the Centers for Disease Control and other resources. Moreover, the demographics and clinical characteristics of the assigned type 1 and type 2 cases were consistent with contemporary epidemiologic findings.

                Conclusion

                Applying diabetes treatment information from the National Health and Nutrition Examination Survey, as formulated in our treatment-based algorithm, may better identify type 1 and type 2 diabetes cases and thus prevent the specific biases imposed by conventional approaches which include the age of diabetes diagnosis as an initial criterion for diabetes type classification.
                  Cover page: A treatment-based algorithm for identification of diabetes type in the National Health and Nutrition Examination Survey.
                  • Article
                  • Peer Reviewed
                  UC Irvine Previously Published Works (2018)
                  Haemochromatosis is defined as systemic iron overload of genetic origin, caused by a reduction in the concentration of the iron regulatory hormone hepcidin, or a reduction in hepcidin-ferroportin binding. Hepcidin regulates the activity of ferroportin, which is the only identified cellular iron exporter. The most common form of haemochromatosis is due to homozygous mutations (specifically, the C282Y mutation) in HFE, which encodes hereditary haemochromatosis protein. Non-HFE forms of haemochromatosis due to mutations in HAMP, HJV or TFR2 are much rarer. Mutations in SLC40A1 (also known as FPN1; encoding ferroportin) that prevent hepcidin-ferroportin binding also cause haemochromatosis. Cellular iron excess in HFE and non-HFE forms of haemochromatosis is caused by increased concentrations of plasma iron, which can lead to the accumulation of iron in parenchymal cells, particularly hepatocytes, pancreatic cells and cardiomyocytes. Diagnosis is noninvasive and includes clinical examination, assessment of plasma iron parameters, imaging and genetic testing. The mainstay therapy is phlebotomy, although iron chelation can be used in some patients. Hepcidin supplementation might be an innovative future approach.
                    Cover page: Haemochromatosis
                    • Article
                    • Peer Reviewed
                    UC Irvine Previously Published Works (2009)

                    Nonsteroidal anti-inflammatory drugs (NSAID) have been associated with adverse cardiovascular (CV) outcomes in cancer prevention and other clinical trials. A recent meta-analysis suggested that baseline CV risk is associated with NSAID-associated adverse CV events. We evaluated the effect of baseline CV risk on adverse CV events in a phase III trial of difluoromethylornithine (DFMO) plus the NSAID sulindac versus placebo in preventing colorectal adenomas. Trial data were analyzed to determine baseline CV risk. CV toxicity outcomes were then assessed overall and excluding high CV-risk patients. Baseline CV risk scores were evenly distributed within our overall trial population of 184 placebo (low risk, 27%; moderate risk, 34%; high risk, 39%) and 191 DFMO/sulindac (low risk, 30%; moderate risk, 29%; high risk, 41%) patients. In patients with a high baseline CV risk, the number of adverse CV events was greater among DFMO/sulindac (n = 9) than among placebo (n = 3) patients. Excluding patients with a high baseline CV risk, the numbers of adverse CV events were similar in the DFMO/sulindac (n = 7) and placebo (n = 6) arms. A high CV risk score at baseline may confer an increased risk of CV events associated with treatment with DFMO/sulindac, and a low baseline score may not increase this risk. These results have implications for future NSAID-based cancer prevention clinical trials.

                      Cover page: Risk of cardiovascular events in a randomized placebo-controlled, double-blind trial of difluoromethylornithine plus sulindac for the prevention of sporadic colorectal adenomas.
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