Robust effect sizes and their confidence intervals for group difference between trajectories in hierarchical linear growth model

Hierarchical linear growth model (HLGM), as a flexible and powerful analytic method, has played an increased important role in psychology, public health and medical sciences in recent decades. Mostly, researchers who conduct HLGM are interested in the treatment effect on individual trajectories, which can be indicated by the cross-level interaction effects. However, the statistical hypothesis test for the effect of cross-level interaction in HLGM only show us whether there is a significant group difference in the average rate of change, rate of acceleration or higher polynomial effect; it fails to convey information about the magnitude of the difference between the group trajectories at specific time point. Thus, reporting and interpreting effect sizes have been increased emphases in HLGM in recent years, due to the limitations and increased criticisms for statistical hypothesis testing. However, most researchers fail to report these model-implied effect sizes for group trajectories comparison and their corresponding confidence intervals in HLGM analysis, since lack of appropriate and standard functions to estimate effect sizes associated with the model-implied difference between grouping trajectories in HLGM, and also lack of computing packages in the popular statistical software to automatically calculate them. ^ The present project is the first to establish the appropriate computing functions to assess the standard difference between grouping trajectories in HLGM. We proposed the two functions to estimate effect sizes on model-based grouping trajectories difference at specific time, we also suggested the robust effect sizes to reduce the bias of estimated effect sizes. Then, we applied the proposed functions to estimate the population effect sizes (d ) and robust effect sizes (du) on the cross-level interaction in HLGM by using the three simulated datasets, and also we compared the three methods of constructing confidence intervals around d and du recommended the best one for application. At the end, we constructed 95% confidence intervals with the suitable method for the effect sizes what we obtained with the three simulated datasets. ^ The effect sizes between grouping trajectories for the three simulated longitudinal datasets indicated that even though the statistical hypothesis test shows no significant difference between grouping trajectories, effect sizes between these grouping trajectories can still be large at some time points. Therefore, effect sizes between grouping trajectories in HLGM analysis provide us additional and meaningful information to assess group effect on individual trajectories. In addition, we also compared the three methods to construct 95% confident intervals around corresponding effect sizes in this project, which handled with the uncertainty of effect sizes to population parameter. We suggested the noncentral t-distribution based method when the assumptions held, and the bootstrap bias-corrected and accelerated method when the assumptions are not met.^

DISTRIBUTION FUNCTIONS, MEAN SQUARED ERRORS, AND CONFIDENCE LIMITS FOR RIDGE REGRESSION ESTIMATORS

A large number of ridge regression estimators have been proposed and used with little knowledge of their true distributions. Because of this lack of knowledge, these estimators cannot be used to test hypotheses or to form confidence intervals.^ This paper presents a basic technique for deriving the exact distribution functions for a class of generalized ridge estimators. The technique is applied to five prominent generalized ridge estimators. Graphs of the resulting distribution functions are presented. The actual behavior of these estimators is found to be considerably different than the behavior which is generally assumed for ridge estimators.^ This paper also uses the derived distributions to examine the mean squared error properties of the estimators. A technique for developing confidence intervals based on the generalized ridge estimators is also presented. ^

GSTM1 and GSTT1 null polymorphisms and risk of salivary gland carcinoma.

Glutathione S-transferase (GST) genes detoxify and metabolize carcinogens, including oxygen free radicals which may contribute to salivary gland carcinogenesis. This cancer center-based case-control association study included 166 patients with incident salivary gland carcinoma (SGC) and 511 cancer-free controls. We performed multiplex polymerase chain reaction-based polymorphism genotyping assays for GSTM1 and GSTT1 null genotypes. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with multivariable logistic regression analyses adjusted for age, sex, ethnicity, tobacco use, family history of cancer, alcohol use and radiation exposure. In our results, 27.7% of the SGC cases and 20.6% of the controls were null for the GSTT1 (P = 0.054), and 53.0% of the SGC cases and 50.9% of the controls were null for the GSTM1 (P = 0.633). The results of the adjusted multivariale regression analysis suggested that having GSTT1 null genotype was associated with a significantly increased risk for SGC (odds ratio 1.5, 95% confidence interval 1.0-2.3). Additionally, 13.9% of the SGC cases but only 8.4% of the controls were null for both genes and the results of the adjusted multivariable regression analysis suggested that having both null genotypes was significantly associated with an approximately 2-fold increased risk for SGC (odds ratio 1.9, 95% confidence interval 1.0-3.5). The presence of GSTT1 null genotype and the simultaneous presence of GSTM1 and GSTT1 null genotypes appear associated with significantly increased SGC risk. These findings warrant further study with larger sample sizes.

Screening for obstructive sleep apnea on the internet: randomized trial.

BACKGROUND: Obstructive sleep apnea is underdiagnosed. We conducted a pilot randomized controlled trial of an online intervention to promote obstructive sleep apnea screening among members of an Internet weight-loss community. METHODS: Members of an Internet weight-loss community who have never been diagnosed with obstructive sleep apnea or discussed the condition with their healthcare provider were randomized to intervention (online risk assessment+feedback) or control. The primary outcome was discussing obstructive sleep apnea with a healthcare provider at 12 weeks. RESULTS: Of 4700 members who were sent e-mail study announcements, 168 (97% were female, age 39.5 years [standard deviation 11.7], body mass index 30.3 [standard deviation 7.8]) were randomized to intervention (n=84) or control (n=84). Of 82 intervention subjects who completed the risk assessment, 50 (61%) were low risk and 32 (39%) were high risk for obstructive sleep apnea. Intervention subjects were more likely than control subjects to discuss obstructive sleep apnea with their healthcare provider within 12 weeks (11% [9/84] vs 2% [2/84]; P=.02; relative risk=4.50; 95% confidence interval, 1.002-20.21). The number needed to treat was 12. High-risk intervention subjects were more likely than control subjects to discuss obstructive sleep apnea with their healthcare provider (19% [6/32] vs 2% [2/84]; P=.004; relative risk=7.88; 95% confidence interval, 1.68-37.02). One high-risk intervention subject started treatment for obstructive sleep apnea. CONCLUSION: An online screening intervention is feasible and likely effective in encouraging members of an Internet weight-loss community to discuss obstructive sleep apnea with their healthcare provider.

HIV-related malignancies: A community-based study using a linkage of cancer registry and HIV registry data

Background. Increased incidence of cancer is documented in immunosuppressed transplant patients. Likewise, as survival increases for persons infected with the Human Immunodeficiency Virus (HIV), we expect their incidence of cancer to increase. The objective of this study was to examine the current gender specific spectrum of cancer in an HIV infected cohort (especially malignancies not currently associated with Acquired Immunodeficiency Syndrome (AIDS)) in relation to the general population.^ Methods. Cancer incidence data was collected for residents of Harris County, Texas who were diagnosed with a malignancy between 1975 and 1994. This data was linked to HIV/AIDS registry data to identify malignancies in an HIV infected cohort of 14,986 persons. A standardized incidence ratio (SIR) analysis was used to compare incidence of cancer in this cohort to that in the general population. Risk factors such as mode of HIV infection, age, race and gender, were evaluated for contribution to the development of cancer within the HIV cohort, using Cox regression techniques.^ Findings. Of those in the HIV infected cohort, 2289 persons (15%) were identified as having one or more malignancies. The linkage identified 29.5% of these malignancies (males 28.7% females 60.9%). HIV infected men and women had incidences of cancer that were 16.7 (16.1, 17.3) and 2.9 (2.3, 3.7) times that expected for the general population of Harris County, Texas, adjusting for age. Significant SIR's were observed for the AIDS-defining malignancies of Kaposi's sarcoma, non-Hodgkin's lymphoma, primary lymphoma of the brain and cancer of the cervix. Additionally, significant SIR's for non-melanotic skin cancer in males, 6.9 (4.8, 9.5) and colon cancer in females, 4.0 (1.1, 10.2) were detected. Among the HIV infected cohort, race/ethnicity of White (relative risk 2.4 with 95% confidence intervals 2.0, 2.8) or Spanish Surname, 2.2 (1.9, 2.7) and an infection route of male to male sex, with, 3.0 (1.9, 4.9) or without, 3.4 (2.1, 5.5) intravenous drug use, increased the risk of having a diagnosis of an incident cancer.^ Interpretation. There appears to be an increased risk of developing cancer if infected with the HIV. In addition to the malignancies routinely associated with HIV infection, there appears to be an increased risk of being diagnosed with non-melanotic skin cancer in males and colon cancer in females. ^

Quantifying uncertainty in cost effectiveness analyses

This study compared four alternative approaches (Taylor, Fieller, percentile bootstrap, and bias-corrected bootstrap methods) to estimating confidence intervals (CIs) around cost-effectiveness (CE) ratio. The study consisted of two components: (1) Monte Carlo simulation was conducted to identify characteristics of hypothetical cost-effectiveness data sets which might lead one CI estimation technique to outperform another. These results were matched to the characteristics of an (2) extant data set derived from the National AIDS Demonstration Research (NADR) project. The methods were used to calculate (CIs) for data set. These results were then compared. The main performance criterion in the simulation study was the percentage of times the estimated (CIs) contained the “true” CE. A secondary criterion was the average width of the confidence intervals. For the bootstrap methods, bias was estimated. ^ Simulation results for Taylor and Fieller methods indicated that the CIs estimated using the Taylor series method contained the true CE more often than did those obtained using the Fieller method, but the opposite was true when the correlation was positive and the CV of effectiveness was high for each value of CV of costs. Similarly, the CIs obtained by applying the Taylor series method to the NADR data set were wider than those obtained using the Fieller method for positive correlation values and for values for which the CV of effectiveness were not equal to 30% for each value of the CV of costs. ^ The general trend for the bootstrap methods was that the percentage of times the true CE ratio was contained in CIs was higher for the percentile method for higher values of the CV of effectiveness, given the correlation between average costs and effects and the CV of effectiveness. The results for the data set indicated that the bias corrected CIs were wider than the percentile method CIs. This result was in accordance with the prediction derived from the simulation experiment. ^ Generally, the bootstrap methods are more favorable for parameter specifications investigated in this study. However, the Taylor method is preferred for low CV of effect, and the percentile method is more favorable for higher CV of effect. ^

Physical activity and survival after a first myocardial infarction: The Corpus Christi Heart Project

Previous studies have demonstrated that habitual physical activity is associated with a reduced risk of incident coronary heart disease (CHD). However, the role of physical activity in lowering the risk of all-cause mortality, CHD mortality, reinfarction, or receipt of a revascularization procedure after a first myocardial infarction (MI) remains unresolved, particularly in minority populations. To investigate the associations between physical activity and risk of all-cause mortality, CHD mortality, reinfarction, and receipt of a revascularization procedure, this study was conducted among Mexican-American and non-Hispanic white women and men who survived a first MI. The Corpus Christi Heart Project, a population-based cardiovascular surveillance study, provide data which included vital status, survival time, medical history, CHD risk factor information, including level of physical activity among Mexican-American and non-Hispanic white adults who had experienced a first MI between May, 1988 and April, 1990. MI patients were interviewed at baseline and annually thereafter until their death or through May, 1995. A categorical variable was created to reflect change in level of physical activity following the first MI; categories included (1) sedentary with no change, (2) decreased activity, (3) increased activity, and (4) moderate activity with no change (the referent group). Proportional hazards regression analyses were used to assess the relationship of level of physical activity and risk of death, reinfarction, or receipt of a revascularization procedure adjusting for age, sex, ethnicity, severity of MI, and CHD risk factor status. Over a 7-year follow-up period, the relative risk (95% confidence intervals) of all-cause mortality was 4.67 (2.27, 9.60) for the sedentary-no change group, 2.33 (0.96, 5.67) for the decreased activity group, and 0.52 (0.11, 2.41) for the increased activity group. The relative risk of CHD mortality was 6.92 (2.05, 23.34) for the sedentary-no change group, 2.40 (0.55, 10.51) for the decreased activity group, and 1.58 (0.26, 9.65) for the increased activity group. The relative risk for reinfarction was 2.50 (1.52, 4.10) for the sedentary-no change group, 2.26 (1.24, 4.12) for the decreased activity group, and 0.52 (0.21, 1.32) for the increased activity group. Finally, the relative risk for receipt of a revascularization procedure was 0.65 (0.39, 1.07) for the sedentary-no change group, 0.45 (0.22, 0.92) for the decreased activity group, and 1.01 (0.51, 2.02) for the increased activity group. No interactions were observed for ethnicity or severity of first MI. These results are consistent with the hypothesis that moderate physical activity is independently associated with a lower risk of all-cause mortality, CHD mortality, and reinfarction, but not revascularization, among Mexican-American and non-Hispanic white, female and male, first MI patients. These results also support the current recommendation that physical activity plays an important role in the secondary prevention of CHD. ^

Descriptive epidemiology of cancer in three regions of Kazakhstan

The current study investigated data quality and estimated cancer incidence and mortality rates using data provided by Pavlodar, Semipalatinsk and Ust-Kamenogorsk Regional Cancer Registries of Kazakhstan during the period of 1996–1998. Assessment of data quality was performed using standard quality indicators including internal database checks, proportion of cases verified from death certificates only, mortality:incidence ratio, data patterns, proportion of cases with unknown primary site, proportion of cases with unknown age. Crude and age-adjusted incidence and mortality rates and 95% confidence intervals were calculated, by gender, for all cancers combined and for 28 specific cancer sites for each year of the study period. The five most frequent cancers were identified and described for every population. The results of the study provide the first simultaneous assessment of data quality and standardized incidence and mortality rates for Kazakh cancer registries. ^

Evaluation of Mycobacterium avium complex lung disease in women

Mycobacterium avium complex (MAC) is a ubiquitous organism responsible for most pulmonary and disseminated disease caused by non-tuberculosis (NTM) mycobacteria. Though MAC lung disease without predisposing factors is uncommon, in recent years it has been increasingly described in middle-aged and elderly women. Recognition and correct diagnosis, is often delayed due to the indolent nature of the disease. It is unclear if these women have significant clinical disease as or if their airways are simply colonized by the bacterium. This study describes the clinical presentation, identifies risk factors, and describes the clinical significance of MAC lung disease in HIV-negative women aged 50 or greater. ^ A hybrid study design utilizing both cross-sectional and case-control methodologies was used. A comparison population was selected from previously identified tuberculosis suspects found throughout Harris County. The study population had at least one acid fast bacillus pulmonary culture performed between 1/1/1998 and 12/31/2000 from a pulmonary source. Clinical presentation and symptoms were analyzed using a cross-sectional design. Past medical history and other risk factors were evaluated using a traditional case-control study design. Differences in categorical variables were estimated with the Chi Square or Fisher's Exact test as appropriate. Odds ratios and 95% confidence intervals were utilized to evaluate associations. Multivariate logistic regression was used to identify predictive factors for MAC. All statistical tests were two-sided and P-values <0.05 were considered statistically significant. ^ Culture confirmed MAC pulmonary cases were more likely to be white, have bronchiectasis, scoliosis, evidence of cavitation and pleural changes on chest radiography and granulomas on histopathologic examination than women whose pulmonary cultures were AFB negative. After controlling for selected risk factors, white race continued to be significantly associated with MAC lung disease (OR = 4.6, 95% CI = 2.3, 9.2). In addition, asthma history, smoking history and alcohol use were less likely to be evident among MAC cases in a multivariate analysis. Right upper and right middle lobe disease was further noted among clinically significant cases. Based on population data, MAC lung disease appears to represent a significant clinical syndrome in HIV-negative women thus supporting the theory of the Lady Windermere Syndrome. ^

Are functional and genetic components of platelets linked to coronary artery disease: A case-control study

Coronary artery disease (CAD) is a multifactorial disease process involving behavioral, inflammatory, clinical, thrombotic, and genetic components. Previous epidemiologic studies focused on identifying behavioral and demographic risk factors of CAD, but none focused on platelets. Current platelet literature lacks the known effects of platelet function and platelet receptor polymorphisms on CAD. This case-control analysis addressed these issues by analyzing data collected for a previous study. Cases were individuals who had undergone CABG and thus had been diagnosed with CAD, while the controls were volunteers presumed to be CAD free. The platelet function variables analyzed included fibrinogen Von Willebrand Factor activity (VWF), shear-induced platelet aggregation (SIPA), sCD40L, and mean platelet volume; and the platelet polymorphisms studied included PIA, α2 807, Ko, Kozak, and VNTR. Univariate analysis found fibrinogen, VWF, SIPA, and PIA to be independent risk factors of CAD. Logistic regression was used to build a predictive model for CAD using the platelet function and platelet polymorphism data adjusted for age, sex, race, and current smoking status. A model containing only platelet polymorphisms and their respective receptor densities, found polymorphisms within GPIbα to be associated with CAD, yielding an 86% (95% C.I. 0.97–3.55) increased risk with the presence of at least 1 polymorphism in Ko, Kozak, or VNTR. Another model included both platelet function and platelet polymorphism data. Fibrinogen, the receptor density of GPIbα, and the polymorphism in GPIa-IIa (α2 807) were all associated with CAD with odds ratios of 1.10, 1.04, and 2.30 for fibrinogen (10mg/dl increase), GPIbα receptors (1 MFI increase), and GPIa-IIa, respectively. In addition, risk estimates and 99% confidence intervals adjusted for race were calculated to determine if the presence of a platelet receptor polymorphism was associated with CAD. The results were as follows: PIA (1.64, 0.74–3.65); α2 807 (1.35, 0.77–2.37); Ko (1.71, 0.70–4.16); Kozak (1.17, 0.54–2.52); and VNTR (1.24, 0.52–2.91). Although not statistically significant, all platelet polymorphisms were associated with an increased risk for CAD. These exploratory findings indicate that platelets do appear to have a role in atherosclerosis and that anti-platelet drugs targeting GPI-IIa and GPIbα may be better treatment candidates for individuals with CAD. ^

Preclinical modeling of multi-drug cancer therapies

Anticancer drugs typically are administered in the clinic in the form of mixtures, sometimes called combinations. Only in rare cases, however, are mixtures approved as drugs. Rather, research on mixtures tends to occur after single drugs have been approved. The goal of this research project was to develop modeling approaches that would encourage rational preclinical mixture design. To this end, a series of models were developed. First, several QSAR classification models were constructed to predict the cytotoxicity, oral clearance, and acute systemic toxicity of drugs. The QSAR models were applied to a set of over 115,000 natural compounds in order to identify promising ones for testing in mixtures. Second, an improved method was developed to assess synergistic, antagonistic, and additive effects between drugs in a mixture. This method, dubbed the MixLow method, is similar to the Median-Effect method, the de facto standard for assessing drug interactions. The primary difference between the two is that the MixLow method uses a nonlinear mixed-effects model to estimate parameters of concentration-effect curves, rather than an ordinary least squares procedure. Parameter estimators produced by the MixLow method were more precise than those produced by the Median-Effect Method, and coverage of Loewe index confidence intervals was superior. Third, a model was developed to predict drug interactions based on scores obtained from virtual docking experiments. This represents a novel approach for modeling drug mixtures and was more useful for the data modeled here than competing approaches. The model was applied to cytotoxicity data for 45 mixtures, each composed of up to 10 selected drugs. One drug, doxorubicin, was a standard chemotherapy agent and the others were well-known natural compounds including curcumin, EGCG, quercetin, and rhein. Predictions of synergism/antagonism were made for all possible fixed-ratio mixtures, cytotoxicities of the 10 best-scoring mixtures were tested, and drug interactions were assessed. Predicted and observed responses were highly correlated (r2 = 0.83). Results suggested that some mixtures allowed up to an 11-fold reduction of doxorubicin concentrations without sacrificing efficacy. Taken together, the models developed in this project present a general approach to rational design of mixtures during preclinical drug development. ^

The effect of immigration status on racial differences in health insurance coverage, access to care, and utilization in the United States

Background. Lack of coverage, lack of access, and failure to utilize health care services have all been linked to dismal health outcomes in the US. Such consequences have been a longstanding challenge that US minorities are faced with, in the context of a health care system believed to be lacking efficiency and equity. National population surveys in the US suggest that the number of uninsured approaches 50 millions, while some concerns and suspicions are raised by opponents to the growing number of foreign born US residents, many of whom are Hispanic. Research shows that race is a significant predictor of lack of coverage, access, and utilization, while age, gender, education, and income are also linked to these outcomes. We investigated the potential effect of immigration status or duration in the US on the association between coverage, access, use, and race. Methods. Using National Health Interview Survey (NHIS) data of 2006, we selected 22, 667 individuals of Non-Hispanic Black, Hispanic, and Non-Hispanic White descent, at least 18 years of age, US-born and foreign-born who reported their duration of residence in the US. Through complex sample survey logistic regression analysis, we computed odds ratios, beta coefficients, and 95% confidence intervals using models which excluded then included immigration status. Results. Although a significant predictor of the outcomes, immigration status did not change the relationship between each of the dependent variables (coverage, access, utilization), and the factor race, while adjusting for age, gender, education, and income. Our results show that Hispanics were least likely to have coverage (OR=.58; 95% CI[.49, .68]), access (OR=.62; 95% CI[.50, .76]), and to utilize services (OR=.60; 95% CI[.46, .79]) followed by Non-Hispanic Blacks, and Non-Hispanic Whites. These results were not changed by stratification, or the inclusion of interaction terms to eliminate the potential effect of relationships between independent variables. Recent immigrants (<5 years in US) were 0.12 times less likely to be insured, but also 0.26 times less likely to utilize services (p<0.001), and in addition they represented only 7.3% of the uninsured and 1.9% of the US population in 2006. Furthermore, 12% of the Non-Hispanic White population in the US was not covered, and 65% of the uninsured individuals were US-Born Citizens. Other predictors of lack of coverage, access and use were age below 45, male gender, education at high school or below, and income of less than $20,000. Conclusion. This investigation shows that the high percentage of uninsured was not directly caused by Hispanics, and immigration status alone could not explain racial differences in coverage, access, and utilization. An immigration reform may not be the solution to the healthcare crisis, and more specifically, will not stop the increase in the number of uninsured in the US, nor reduce the cost of health care. As a better alternative, universal health insu rance coverage should be considered, when aiming to eliminate racial disparities, and to solve the health care crisis. ^ Keywords. health insurance, coverage, access, utilization, race, immigration, disparities.^

Association between glycemic index and glycemic load and the risk of incident coronary heart disease among whites and African Americans with and without type 2 diabetes: The Atherosclerosis Risk in Communities study

Several studies have examined the association between high glycemic index (GI) and glycemic load (GL) diets and the risk for coronary heart disease (CHD). However, most of these studies were conducted primarily on white populations. The primary aim of this study was to examine whether high GI and GL diets are associated with increased risk for developing CHD in whites and African Americans, non-diabetics and diabetics, and within stratifications of body mass index (BMI) and hypertension (HTN). Baseline and 17-year follow-up data from ARIC (Atherosclerosis Risk in Communities) study was used. The study population (13,051) consisted of 74% whites, 26% African Americans, 89% non-diabetics, 11% diabetics, 43% male, 57% female aged 44 to 66 years at baseline. Data from the ARIC food frequency questionnaire at baseline were analyzed to provide GI and GL indices for each subject. Increases of 25 and 30 units for GI and GL respectively were used to describe relationships on incident CHD risk. Adjusted hazard ratios for propensity score with 95% confidence intervals (CI) were used to assess associations. During 17 years of follow-up (1987 to 2004), 1,683 cases of CHD was recorded. Glycemic index was associated with 2.12 fold (95% CI: 1.05, 4.30) increased incident CHD risk for all African Americans and GL was associated with 1.14 fold (95% CI: 1.04, 1.25) increased CHD risk for all whites. In addition, GL was also an important CHD risk factor for white non-diabetics (HR=1.59; 95% CI: 1.33, 1.90). Furthermore, within stratum of BMI 23.0 to 29.9 in non-diabetics, GI was associated with an increased hazard ratio of 11.99 (95% CI: 2.31, 62.18) for CHD in African Americans, and GL was associated with 1.23 fold (1.08, 1.39) increased CHD risk in whites. Body mass index modified the effect of GI and GL on CHD risk in all whites and white non-diabetics. For HTN, both systolic blood pressure and diastolic blood pressure modified the effect on GI and GL on CHD risk in all whites and African Americans, white and African American non-diabetics, and white diabetics. Further studies should examine other factors that could influence the effects of GI and GL on CHD risk, including dietary factors, physical activity, and diet-gene interactions. ^

Obesity and risk of multiple myeloma: A case-control study

Introduction. Several studies have reported a positive association of body mass index (BMI) with multiple myeloma; however, the period of adulthood where BMI is most important remains unclear. In addition, it is well known that body fat is associated with both sex-steroid hormone storage and with increasing insulin levels; therefore, it was hypothesized that the association between obesity and multiple myeloma may be attributed to increased aromatization of androgen in adipose tissue. Objective. The overall objective of this case-control study was to determine whether multiple myeloma cases had higher BMI and greater adult weight gain relative to healthy controls. In addition, we tested the hypothesis that hormone replacement therapy use among women will further increase the association between BMI and risk of multiple myeloma. This study used data from a pilot case-control study at M.D. Anderson Cancer Center (MDACC), entitled Etiology of multiple myeloma, directed by Dr. Sara Strom and Dr. Sergio Giralt. Methods. The pilot study recruited a total of 122 cases of histopathologically confirmed multiple myeloma from MDACC. Controls (n=183) were selected from a database of random digit dialing controls accrued in the Department of Epidemiology at MDACC and were frequency matched to the cases on age (±5 years), gender, and race/ethnicity. Demographic and risk factor information were obtained from all participants who completed a self-administered questionnaire. Items included in the questionnaire include demographic information, height and weight at age 25, 40 and current/diagnosis, medical history, family history of cancer, smoking and alcohol use. Statistical analysis. Initial descriptive analysis included Student's t-test and Pearson's chi-squared tests. Odds ratios and 95% confidence intervals were calculated to quantify the association between the variables of interest and multiple myeloma. A multivariable model will be developed using unconditional logistic regression. Results. MM cases were 1.79 times (95% CI=0.99-3.32) more likely to have been overweight or obese (BMI > 25 kg/m2) at age 25 relative to healthy controls after controlling for age, gender, race/ethnicty, education and family history of cancer. Being overweight or obese at age 40 was not significantly associated with mutliple myeloma risk (OR=1.42, 95% CI=0.86-2.34) nor was being overweight or obses at diagnosis (OR=1.43, 95% CI=0.78, 2.63). We observed a statistically significant 2-fold increased odds of multiple myeloma in individuals who gained more than 4.7 kg during between 25 and 40 years (OR=1.97, 95% CI=1.15-3.39). When assessing HRT as a modifier of the BMI and multiple myeloma association among women (N=123), no association between obesity and MM status was observed among women who have never used HRT (OR=0.60, 95% CI=0.23-1.61; n=73). Yet among women who have ever used HRT (n=50), being overweight or obese was associated with an increase in MM risk (OR=2. 93, 95% CI=0.81-10.6) after adjusting for age; however, the association was not statistically significant. Significance. This study provides further evidence that increased BMI increases the risk of multiple myeloma. Furthermore, among women, HRT use may modify risk of disease. ^

Outcomes of tuberculosis positive non-injection drug users in Harris County from October 1995 through September 2004

Background. The population-based Houston Tuberculosis Initiative (HTI) study has enrolled and gathered demographic, social, behavioral, and disease related data on more than 80% of all reported Mycobacterium Tuberculosis (MTB) cases and 90% of all culture positive patients in Houston/Harris County over a 9 year period (from October 1995-September 2004). During this time period 33% (n=1210) of HTI MTB cases have reported a history of drug use. Of those MTB cases reporting a history of drug use, a majority of them (73.6%), are non-injection drug users (NIDUs). ^ Other than HIV, drug use is the single most important risk factor for progression from latent to infectious tuberculosis (TB). In addition, drug use is associated with increased transmission of active TB, as seen by the increased number of clonally related strains or clusters (see definition on page 30) found in this population. The deregulatory effects of drug use on immune function are well documented. Associations between drug use and increased morbidity have been reported since the late 1970's. However, limited research focused on the immunological consequence of non-injection drug use and its relation to tuberculosis infection among TB patients is available. ^ Methods. TB transmission patterns, symptoms, and prevalence of co-morbidities were a focus of this project. Smoking is known to suppress Nitric Oxide (NO) production and interfere with immune function. In order to limit any possible confounding due to smoking two separate analyses were done. Non-injection drug user smokers (NIDU-S) were compared to non-drug user smokers (NDU-S) and non-injection drug user non-smokers (NIDU-NS) were compared to non-drug user non-smokers (NDU-NS) individually. Specifically proportions, chi-square p-values, and (where appropriate) odds ratios with 95% confidence intervals were calculated to assess characteristics and potential associations of co-morbidities and symptoms of TB among NIDUs HTI TB cases. ^ Results. Significant differences in demographic characteristics and risk factors were found. In addition drug users were found to have a decreased risk for cancer, diabetes mellitus, and chronic pulmonary disease. They were at increased risk of having HIV/AIDS diagnosis, liver disease, and trauma related morbidities. Drug users were more likely to have pulmonary TB disease, and a significantly increased amount of clonally related strains of TB or "clusters" were seen in both smokers and non-smoker drug users when compared to their non-drug user counterparts. Drug users are more likely to belong to print groups (clonally related TB strains with matching spoligotypes) including print one and print three and the Beijing family group, s1. Drug users were found to be no more likely to experience drug resistance to TB therapy and were likely to be cured of disease upon completion of therapy. ^ Conclusion. Drug users demographic and behavioral risk factors put them at an increased risk contracting and spreading TB disease throughout the community. Their increased levels of clustering are evidence of recent transmission and the significance of certain print groups among this population indicate the transmission is from within the social family. For these reasons a focus on this "at risk population" is critical to the success of future public health interventions. Successful completion of directly observed therapy (DOT), the tracking of TB outbreaks and incidence through molecular characterization, and increased diagnostic strategies have led to the stabilization of TB incidence in Houston, Harris County over the past 9 years and proven that the Houston Tuberculosis Initiative has played a critical role in the control and prevention of TB transmission. ^