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Brian W Whitcomb

Publications and source records attributed to Brian W Whitcomb.

9 recordsLinked to original sources
PubMed2006

The limitations due to exposure detection limits for regression models.

Biomarker use in exposure assessment is increasingly common, and consideration of related issues is of growing importance. Exposure quantification may be compromised when measurement is subject to a lower threshold. Statistical modeling of such data requires a decision regarding the handling of such readings. Various authors have considered this problem. In the context of linear regression analysis, Richardson and Ciampi (Am J Epidemiol 2003;157:355-63) proposed replacement of data below a threshold by a constant equal to the expectation for such data to yield unbiased estimates. Use of such an imputation has some limitations; distributional assumptions are required, and bias reduction in estimation of regression parameters is asymptotic, thereby presenting concerns about small studies. In this paper, the authors propose distribution-free methods for managing values below detection limits and evaluate the biases that may result when exposure measurement is constrained by a lower threshold. The authors utilize an analytical approach and a simulation study to assess the effects of the proposed replacement method on estimates. These results may inform decisions regarding analytical plans for future studies and provide a possible explanation for some amount of the discordance seen in extant literature.

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PubMed2005

Impact of admission hyperglycemia on hospital mortality in various intensive care unit populations.

OBJECTIVE: Hyperglycemia in intensive care unit patients has been associated with an increased mortality rate, and institutions have already begun tight glucose control programs based on a limited number of clinical trials in restricted populations. This study aimed to assess the generalizability of the association between hyperglycemia and in-hospital mortality in different intensive care unit types adjusting for illness severity and diabetic history. DESIGN: Retrospective cohort study. SETTING: The medical, cardiothoracic surgery, cardiac, general surgical, and neurosurgical intensive care units of the University of Maryland Medical Center. PATIENTS: Patients admitted between July 1996 and January 1998 with length of stay > or = 24 hrs (n = 2713). INTERVENTIONS: On intensive care unit admission, blood glucose and other physiologic variables were evaluated. Regular measurements were taken for calculation of Acute Physiology and Chronic Health Evaluation III scoring. Patients were followed through hospital discharge. Admission blood glucose was used to classify patients as hyperglycemic (> 200 mg/dL) or normoglycemic (60-200 mg/dL). The contribution of hyperglycemia to in-hospital mortality stratified by intensive care unit type and diabetes history while controlling for illness severity was estimated by logistic regression. MEASUREMENTS AND MAIN RESULTS: The adjusted odds ratios for death comparing all patients with hyperglycemia to those without were 0.81 (95% confidence interval, 0.37, 1.77) and 1.76 (95% confidence interval, 1.23, 2.53) for those with and without diabetic history, respectively. Higher mortality was seen in hyperglycemic patients without diabetic history in the cardiothoracic, (adjusted odds ratio, 2.84 [1.21, 6.63]), cardiac (adjusted odds ratio, 2.64 [1.14, 6.10]), and neurosurgical units (adjusted odds ratio, 2.96 [1.51, 5.77]) but not the medical or surgical intensive care units or in patients with diabetic history. CONCLUSIONS: The association between hyperglycemia on intensive care unit admission and in-hospital mortality was not uniform in the study population; hyperglycemia was an independent risk factor only in patients without diabetic history in the cardiac, cardiothoracic, and neurosurgical intensive care units.

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PubMed2005

Lipid adjustment in the analysis of environmental contaminants and human health risks.

The literature on exposure to lipophilic agents such as polychlorinated biphenyls (PCBs) is conflicting, posing challenges for the interpretation of potential human health risks. Laboratory variation in quantifying PCBs may account for some of the conflicting study results. For example, for quantification purposes, blood is often used as a proxy for adipose tissue, which makes it necessary to model serum lipids when assessing health risks of PCBs. Using a simulation study, we evaluated four statistical models (unadjusted, standardized, adjusted, and two-stage) for the analysis of PCB exposure, serum lipids, and health outcome risk (breast cancer). We applied eight candidate true causal scenarios, depicted by directed acyclic graphs, to illustrate the ramifications of misspecification of underlying assumptions when interpreting results. Statistical models that deviated from underlying causal assumptions generated biased results. Lipid standardization, or the division of serum concentrations by serum lipids, was observed to be highly prone to bias. We conclude that investigators must consider biology, biologic medium (e.g., nonfasting blood samples), laboratory measurement, and other underlying modeling assumptions when devising a statistical plan for assessing health outcomes in relation to environmental exposures.

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PubMed2004

Coronary age as a risk factor in the modified Framingham risk score.

BACKGROUND: Clinical guidelines emphasize risk assessment as vital to patient selection for medical primary intervention. However, risk assessment methods are restricted in their ability to predict further coronary events. The most widely accepted tool in the United States is the Framingham risk score. In these equations age is a powerful risk factor. Although the extent of coronary atherosclerosis increases with age, there is large inter-individual variability in the rate of development and progression of this disease. This fact limits the utility of Framingham scoring when applied to individuals. Electron beam tomography (EBT), which measures coronary calcium, provides a non-invasive method for assessing coronary plaque burden, thus offering the possibility of providing a more accurate estimate of an individual's "arterial age" than from chronological age alone. METHODS: In this paper we discuss a new and simple method for incorporating the coronary calcium score (CCS) to modify the Framingham Risk Assessment (FRA). Using this method, a coronary artery calcium (CAC) age equivalent is generated that replaces chronological age in Framingham scoring. RESULTS AND DISCUSSION: Using a percentile table of CCS scores by age group and sex, individuals are matched to the age group whose calcium score most closely approximates their own individual score. The original 10-year absolute risk score of a 65-year old man with a CCS of 6 based on chronological age is 10%, whereas the modified absolute risk score based on CAC age equivalents is 2%. CONCLUSION: Our approach of replacing chronological age with CAC age equivalents in the Framingham equations possesses simplicity of application combined with precision. Physicians can easily derive adjusted Framingham risk scores and prescribe intervention methods based on patients' ten-year risks. The adjusted ten-year risks are likely to be more accurate than unadjusted risks since they are based on coronary calcium score information. The modified FRA approach not only may increase the predicted risk for some patients, but also may decrease the predicted risk for others, making it a more precise adjustment than other methods.

Journal Article↗
PubMed2004

Use of the Social Security Administration Death Master File for ascertainment of mortality status.

OBJECTIVES: Internet sources that use the Social Security Administration's (SSA) Death Master File have demonstrated high sensitivity among males for detection of mortality status in comparisons to the National Death Index, but the sensitivity has not been investigated for other demographic groups. METHODS: The authors used the SSA Death Master File to determine the mortality status of 374 decedents from the ongoing Patient Outcomes Study at Cedars-Sinai Medical Center whose deaths were confirmed by physicians using hospital records. RESULTS: Decedents identified by the SSA Death Master File were significantly older than those not identified. Foreign-born decedents were significantly less likely to be identified as dead than American-born decedents. Gender and marital status were not significant factors for identification by the SSA Death Master File. CONCLUSION: The results of this study suggest that Internet sources may be used as an inexpensive and effective tool for determination of mortality status. However, among certain populations use of these databases alone may provide incomplete information.

Journal Article↗
PubMed2002

The association of hormone replacement therapy and coronary calcium as determined by electron beam tomography.

BACKGROUND: Observational studies have shown that hormone replacement therapy (HRT) is associated with lower coronary heart disease (CHD), and animal studies demonstrate potent antiatherosclerotic estrogen effects. Paradoxically, recent clinical trials have not demonstrated a protective effect. This paradox may be explained by a healthy woman effect bias. Women using HRT have improved health outcomes unrelated to underlying atherosclerotic burden. Examination of the association between coronary calcium (CC), a marker of atherosclerotic plaque burden, and the use of HRT in postmenopausal women may help address this paradox. METHODS: The study population comprised 641 asymptomatic postmenopausal women, 425 (66%) of whom were taking HRT. Data obtained from a self-administered questionnaire and blood samples were analyzed. Electron beam tomography (EBT) for CC was performed on each subject. Analysis of variance (ANOVA) was used to evaluate adjusted means. RESULTS: Independent t tests found that age, low-density lipoproteins (LDL), high-density lipoproteins (HDL), body mass index (BMI), vitamin use, coronary calcium score (CCS), coronary calcified volume (CCV), and the number of coronary calcium lesions (CCL) were significantly different between the HRT group and the non-HRT group. However, after controlling for potential confounders, no significant differences were observed in CCS, CCV, or the number of CCL between the HRT and non-HRT groups. Stratifying by BMI shows that obese/overweight women taking HRT have lower adjusted CCS and fewer CCL than the obese/overweight women not taking HRT. CONCLUSIONS: These findings demonstrate no association between HRT use and CCS, CCV, and CCL after adjusting for measurable confounders in postmenopausal women. Our failure to demonstrate an independent association between HRT use and a marker of atherosclerotic plaque burden suggests that a healthy woman effect may explain the beneficial association between HRT use and CHD in observational studies.

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