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Articles 31 - 43 of 43
Full-Text Articles in Medicine and Health Sciences
Nicotine-Replacement Therapy: A Proven Treatment For Smoking Cessation: Cpd, Noorzurani Robson Associate Prof. Dr.
Nicotine-Replacement Therapy: A Proven Treatment For Smoking Cessation: Cpd, Noorzurani Robson Associate Prof. Dr.
Associate Prof. Dr. Noorzurani Robson
Smoking is a major cause of cardiovascular diseases, respiratory diseases and cancer. Despite the high prevalence of smokers worldwide, smokers are often neglected and not offered effective assistance with quitting their habits. In order to overcome this public health burden, effective treatment is needed to help smokers stop smoking. Among the pharmacological treatments available, nicotine-replacement therapy (NRT), when prescribed in combination with behavioural support, has been proven to be effective in helping a wide range of smokers to quit. NRT helps smokers during the withdrawal process by replacing a proportion of the nicotine formerly obtained from cigarettes. NRT is available …
Alcohol Use And Psychosocial Correlates Among Aborigines In Central Penisular Malaysia, R. Abd Rashid, W.A. Irnee, M.M.A. Zahari, A.S.A. Nordin, Noorzurani Robson Associate Prof. Dr., A.H. Sulaiman, R.A. Kadir, D. A. A. Rahim, H. Peters, M. A. Said, H. Habil
Alcohol Use And Psychosocial Correlates Among Aborigines In Central Penisular Malaysia, R. Abd Rashid, W.A. Irnee, M.M.A. Zahari, A.S.A. Nordin, Noorzurani Robson Associate Prof. Dr., A.H. Sulaiman, R.A. Kadir, D. A. A. Rahim, H. Peters, M. A. Said, H. Habil
Associate Prof. Dr. Noorzurani Robson
To determine the prevalence of alcohol abuse/dependence, psychiatric morbidity and psychosocial correlates among Malaysian aborigines.
Identification Of Ovarian Cancer Symptoms In Health Insurance Claims Data., Paula Diehr, Sean Devlin
Identification Of Ovarian Cancer Symptoms In Health Insurance Claims Data., Paula Diehr, Sean Devlin
Paula Diehr
Background: Women with ovarian cancer have reported abdominal=pelvic pain, bloating, difficulty eating or feeling full quickly, and urinary frequency=urgency prior to diagnosis. We explored these findings in a general population using a dataset of insured women aged 40–64 and investigated the potential effectiveness of a routine review of claims data as a prescreen to identify women at high risk for ovarian cancer. Methods: Data from a large Washington State health insurer were merged with the Seattle-Puget Sound Surveillance, Epidemiology and End Results (SEER) cancer registry for 2000–2004. We estimated the prevalence of symptoms in the 36 months prior to diagnosis …
Paraoxonase 1 Activity As A Predictor Of Cardiovascular Disease In Type 2 Diabetes, Rozaida @ Poh Yuen Ying
Paraoxonase 1 Activity As A Predictor Of Cardiovascular Disease In Type 2 Diabetes, Rozaida @ Poh Yuen Ying
Rozaida @ Poh Yuen Ying
The role of paraoxonase 1 in cardiovascular disease complications in type 2 diabetes mellitus is not fully understood. We studied paraoxonase activity towards paraoxon in 188 non-diabetic and 140 diabetic subjects using general linear models and univariate analysis. Adjusting for age revealed a reduction in activity towards paraoxon was associated with a significant increase in risk (p=0.023) for cardiovascular disease complications in diabetic patients. Multivariate analysis of two plasma measures of paraoxonase activity using paraoxon and diazoxon also showed reduced paraoxonase activity towards paraoxon was associated with a significant increase in risk (p=0.045) for cardiovascular disease complications in diabetic patients. …
Targeted Maximum Likelihood Estimation Of The Parameter Of A Marginal Structural Model, Michael Rosenblum, Mark J. Van Der Laan
Targeted Maximum Likelihood Estimation Of The Parameter Of A Marginal Structural Model, Michael Rosenblum, Mark J. Van Der Laan
Michael Rosenblum
Targeted maximum likelihood estimation is a versatile tool for estimating parameters in semiparametric and nonparametric models. We work through an example applying targeted maximum likelihood methodology to estimate the parameter of a marginal structural model. In the case we consider, we show how this can be easily done by clever use of standard statistical software. We point out differences between targeted maximum likelihood estimation and other approaches (including estimating function based methods). The application we consider is to estimate the effect of adherence to antiretroviral medications on virologic failure in HIV positive individuals.
Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh
Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh
Debashis Ghosh
In high-throughput studies involving genetic data such as from gene expression mi- croarrays, dierential expression analysis between two or more experimental conditions has been a very common analytical task. Much of the resulting literature on multiple comparisons has paid relatively little attention to the choice of test statistic. In this article, we focus on the issue of choice of test statistic based on a special pattern of dierential expression. The approach here is based on recasting multiple comparisons procedures for assessing outlying expression values. A major complication is that the resulting p-values are discrete; some theoretical properties of sequential testing …
Detecting Outlier Genes From High-Dimensional Data: A Fuzzy Approach, Debashis Ghosh
Detecting Outlier Genes From High-Dimensional Data: A Fuzzy Approach, Debashis Ghosh
Debashis Ghosh
A recent nding in cancer research has been the characterization of previously undis- covered chromosomal abnormalities in several types of solid tumors. This was found based on analyses of high-throughput data from gene expression microarrays and motivated the development of so-called `outlier' tests for dierential expression. One statistical issue was the potential discreteness of the test statistics. Using ideas from fuzzy set theory, we develop fuzzy outlier detection algorithms that have links to ideas in multiple comparisons. Two- and K-sample extensions are considered. The methodology is illustrated by application to two microarray studies.
Links Between Analysis Of Surrogate Endpoints And Endogeneity, Debashis Ghosh, Jeremy M. Taylor, Michael R. Elliott
Links Between Analysis Of Surrogate Endpoints And Endogeneity, Debashis Ghosh, Jeremy M. Taylor, Michael R. Elliott
Debashis Ghosh
There has been substantive interest in the assessment of surrogate endpoints in medical research. These are measures which could potentially replace \true" endpoints in clinical trials and lead to studies that require less follow-up. Recent research in the area has focused on assessments using causal inference frameworks. Beginning with a simple model for associating the surrogate and true endpoints in the population, we approach the problem as one of endogenous covariates. An instrumental variables estimator and general two-stage algorithm is proposed. Existing surrogacy frameworks are then evaluated in the context of the model. A numerical example is used to illustrate …
Meta-Analysis For Surrogacy: Accelerated Failure Time Models And Semicompeting Risks Modelling, Debashis Ghosh, Jeremy M. Taylor, Daniel J. Sargent
Meta-Analysis For Surrogacy: Accelerated Failure Time Models And Semicompeting Risks Modelling, Debashis Ghosh, Jeremy M. Taylor, Daniel J. Sargent
Debashis Ghosh
There has been great recent interest in the medical and statistical literature in the assessment and validation of surrogate endpoints as proxies for clinical endpoints in medical studies. More recently, authors have focused on using meta-analytical methods for quanti cation of surrogacy. In this article, we extend existing procedures for analysis based on the accelerated failure time model to this setting. An advantage of this approach relative to proportional hazards model is that it allows for analysis in the semi-competing risks setting, where we constrain the surrogate endpoint to occur before the true endpoint. A novel principal components procedure is …
Spline-Based Models For Predictiveness Curves, Debashis Ghosh, Michael Sabel
Spline-Based Models For Predictiveness Curves, Debashis Ghosh, Michael Sabel
Debashis Ghosh
A biomarker is dened to be a biological characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. The use of biomarkers in cancer has been advocated for a variety of purposes, which include use as surrogate endpoints, early detection of disease, proxies for environmental exposure and risk prediction. We deal with the latter issue in this paper. Several authors have proposed use of the predictiveness curve for assessing the capacity of a biomarker for risk prediction. For most situations, it is reasonable to assume monotonicity of …
Combining Multiple Models With Survival Data: The Phase Algorithm, Debashis Ghosh, Zheng Yuan
Combining Multiple Models With Survival Data: The Phase Algorithm, Debashis Ghosh, Zheng Yuan
Debashis Ghosh
In many scientic studies, one common goal is to develop good prediction rules based on a set of available measurements. This paper proposes a model averaging methodology using proportional hazards regression models to construct new estimators of predicted survival probabilities. A screening step based on an adaptive searching algorithm is used to handle large numbers of covariates. The nite-sample properties of the proposed methodology is assessed using simulation studies. Application of the method to a cancer biomarker study is also given.
Farm Focus - Spring 2010, Brian K. Whitlock, Matt Welborn, Maria Prado, Amy Plummer
Farm Focus - Spring 2010, Brian K. Whitlock, Matt Welborn, Maria Prado, Amy Plummer
Brian K Whitlock, PhD, DVM, DACT
No abstract provided.
The Biology Of Reality Testing - Implications For Cognitive Education, Neil Greenberg
The Biology Of Reality Testing - Implications For Cognitive Education, Neil Greenberg
Neil Greenberg
• This report explores the proposition that teaching effectiveness can be enhanced by accommodating the key differences between two complementary and deeply engrained modes of reality testing, each predominantly centered in different hemispheres of the brain. • (1) Correspondence involves “reality-testing” of a percept, the cerebral representation of an experience in the world. • (2) Coherence involves “textualizing”, that is, reality-testing of a percept by how easily it relates to previous and ongoing parallel and collateral experiences. • Confidence in the validity of any percept throughout development is related to the interplay of these key processes. • As organisms develop, …