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1.  Non-Hodgkin Lymphoma Risk and Insecticide, Fungicide and Fumigant Use in the Agricultural Health Study 
PLoS ONE  2014;9(10):e109332.
Farming and pesticide use have previously been linked to non-Hodgkin lymphoma (NHL), chronic lymphocytic leukemia (CLL) and multiple myeloma (MM). We evaluated agricultural use of specific insecticides, fungicides, and fumigants and risk of NHL and NHL-subtypes (including CLL and MM) in a U.S.-based prospective cohort of farmers and commercial pesticide applicators. A total of 523 cases occurred among 54,306 pesticide applicators from enrollment (1993–97) through December 31, 2011 in Iowa, and December 31, 2010 in North Carolina. Information on pesticide use, other agricultural exposures and other factors was obtained from questionnaires at enrollment and at follow-up approximately five years later (1999–2005). Information from questionnaires, monitoring, and the literature were used to create lifetime-days and intensity-weighted lifetime days of pesticide use, taking into account exposure-modifying factors. Poisson and polytomous models were used to calculate relative risks (RR) and 95% confidence intervals (CI) to evaluate associations between 26 pesticides and NHL and five NHL-subtypes, while adjusting for potential confounding factors. For total NHL, statistically significant positive exposure-response trends were seen with lindane and DDT. Terbufos was associated with total NHL in ever/never comparisons only. In subtype analyses, terbufos and DDT were associated with small cell lymphoma/chronic lymphocytic leukemia/marginal cell lymphoma, lindane and diazinon with follicular lymphoma, and permethrin with MM. However, tests of homogeneity did not show significant differences in exposure-response among NHL-subtypes for any pesticide. Because 26 pesticides were evaluated for their association with NHL and its subtypes, some chance finding could have occurred. Our results showed pesticides from different chemical and functional classes were associated with an excess risk of NHL and NHL subtypes, but not all members of any single class of pesticides were associated with an elevated risk of NHL or NHL subtypes. These findings are among the first to suggest links between DDT, lindane, permethrin, diazinon and terbufos with NHL subtypes.
doi:10.1371/journal.pone.0109332
PMCID: PMC4206281  PMID: 25337994
2.  A mixed-effects model approach for estimating the distribution of usual intake of nutrients: The NCI method 
Statistics in medicine  2010;29(27):10.1002/sim.4063.
It is of interest to estimate the distribution of usual nutrient intake for a population from repeat 24-h dietary recall assessments. A mixed effects model and quantile estimation procedure, developed at the National Cancer Institute (NCI), may be used for this purpose. The model incorporates a Box–Cox parameter and covariates to estimate usual daily intake of nutrients; model parameters are estimated via quasi-Newton optimization of a likelihood approximated by the adaptive Gaussian quadrature. The parameter estimates are used in a Monte Carlo approach to generate empirical quantiles; standard errors are estimated by bootstrap. The NCI method is illustrated and compared with current estimation methods, including the individual mean and the semi-parametric method developed at the Iowa State University (ISU), using data from a random sample and computer simulations. Both the NCI and ISU methods for nutrients are superior to the distribution of individual means. For simple (no covariate) models, quantile estimates are similar between the NCI and ISU methods. The bootstrap approach used by the NCI method to estimate standard errors of quantiles appears preferable to Taylor linearization. One major advantage of the NCI method is its ability to provide estimates for subpopulations through the incorporation of covariates into the model. The NCI method may be used for estimating the distribution of usual nutrient intake for populations and subpopulations as part of a unified framework of estimation of usual intake of dietary constituents.
doi:10.1002/sim.4063
PMCID: PMC3865776  PMID: 20862656
statistical distributions; diet surveys; nutrition assessment; mixed-effects model; nutrients; percentiles
3.  SYSTEMS STRATEGIES TO SUPPORT CANCER SCREENING IN U.S. PRIMARY CARE PRACTICE 
Background
Although systems strategies are effective in improving health care delivery, little is known about their use for cancer screening in U.S. primary care practice.
Methods
We assessed primary care physicians’ (n=2475) use of systems strategies for breast, cervical and colorectal cancer (CRC) screening in a national survey conducted in 2007. Systems strategies included patient and physician screening reminders, performance reports of screening rates, electronic medical records, implementation of in-practice guidelines, and use of nurse practitioners/physician assistants. We evaluated use of both patient and physician screening reminders with other strategies in separate models by screening type, adjusted for the effects of physician and practice characteristics with multivariate logistic regression.
Results
Fewer than 10% of physicians used a comprehensive set of systems strategies to support cancer screening; use was greater for mammography and Pap testing than for CRC screening. In adjusted analyses, performance reports of cancer screening rates, medical record type, and in-practice guidelines were associated with use of both patient and physician screening reminders for mammography, Pap testing, and CRC screening (p<0.05).
Conclusion
Despite evidence supporting use of systems strategies in primary care, few physicians report using a comprehensive set of strategies to support cancer screening.
Impact
Current health policy initiatives underscore the importance of increased implementation of systems strategies in primary care to improve the use and quality of cancer screening in the U.S.
doi:10.1158/1055-9965.EPI-11-0783
PMCID: PMC3237756  PMID: 21976292
4.  Are Physicians’ Recommendations For Colorectal Cancer Screening Guideline-Consistent? 
ABSTRACT
BACKGROUND
Many older adults in the U.S. do not receive appropriate colorectal cancer (CRC) screening. Although primary care physicians’ recommendations to their patients are central to the screening process, little information is available about their recommendations in relation to guidelines for the menu of CRC screening modalities, including fecal occult blood testing (FOBT), flexible sigmoidoscopy (FS), colonoscopy, and double contrast barium enema (DCBE). The objective of this study was to explore potentially modifiable physician and practice factors associated with guideline-consistent recommendations for the menu of CRC screening modalities.
METHODS
We examined data from a nationally representative sample of 1266 physicians in the U.S. surveyed in 2007. The survey included questions about physician and practice characteristics, perceptions about screening, and recommendations for age of initiation and screening interval for FOBT, FS, colonoscopy and DCBE in average risk adults. Physicians’ screening recommendations were classified as guideline consistent for all, some, or none of the CRC screening modalities recommended. Analyses used descriptive statistics and polytomous logit regression models.
RESULTS
Few (19.1%; 95% CI:16.9%, 21.5%) physicians made guideline-consistent recommendations across all CRC screening modalities that they recommended. In multivariate analysis, younger physician age, board certification, north central geographic region, single specialty or multi-specialty practice type, fewer patients per week, higher number of recommended modalities, use of electronic medical records, greater influence of patient preferences for screening, and published clinical evidence were associated with guideline-consistent screening recommendations (p < 0.05).
CONCLUSIONS
Physicians’ CRC screening recommendations reflect both overuse and underuse, and few made guideline-consistent CRC screening recommendations across all modalities they recommended. Interventions that focus on potentially modifiable physician and practice factors that influence overuse and underuse and address the menu of recommended screening modalities will be important for improving screening practice.
doi:10.1007/s11606-010-1516-5
PMCID: PMC3019313  PMID: 20949328
guidelines mass screening; colorectal neoplasms/prevention & control; fecal occult blood test; flexible sigmoidoscopy; colonoscopy
5.  Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components 
There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.
We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole grains. We demonstrate numerically that our methods lead to increased speed of computation, converge to reasonable solutions, and have the flexibility to be used in either a frequentist or a Bayesian manner.
doi:10.2202/1557-4679.1267
PMCID: PMC3406506  PMID: 22848190
Bayesian approach; latent variables; measurement error; mixed effects models; nutritional epidemiology; zero-inflated data
6.  A NEW MULTIVARIATE MEASUREMENT ERROR MODEL WITH ZERO-INFLATED DIETARY DATA, AND ITS APPLICATION TO DIETARY ASSESSMENT 
The annals of applied statistics  2011;5(2B):1456-1487.
In the United States the preferred method of obtaining dietary intake data is the 24-hour dietary recall, yet the measure of most interest is usual or long-term average daily intake, which is impossible to measure. Thus, usual dietary intake is assessed with considerable measurement error. Also, diet represents numerous foods, nutrients and other components, each of which have distinctive attributes. Sometimes, it is useful to examine intake of these components separately, but increasingly nutritionists are interested in exploring them collectively to capture overall dietary patterns. Consumption of these components varies widely: some are consumed daily by almost everyone on every day, while others are episodically consumed so that 24-hour recall data are zero-inflated. In addition, they are often correlated with each other. Finally, it is often preferable to analyze the amount of a dietary component relative to the amount of energy (calories) in a diet because dietary recommendations often vary with energy level. The quest to understand overall dietary patterns of usual intake has to this point reached a standstill. There are no statistical methods or models available to model such complex multivariate data with its measurement error and zero inflation. This paper proposes the first such model, and it proposes the first workable solution to fit such a model. After describing the model, we use survey-weighted MCMC computations to fit the model, with uncertainty estimation coming from balanced repeated replication.
The methodology is illustrated through an application to estimating the population distribution of the Healthy Eating Index-2005 (HEI-2005), a multi-component dietary quality index involving ratios of interrelated dietary components to energy, among children aged 2-8 in the United States. We pose a number of interesting questions about the HEI-2005 and provide answers that were not previously within the realm of possibility, and we indicate ways that our approach can be used to answer other questions of importance to nutritional science and public health.
doi:10.1214/10-AOAS446
PMCID: PMC3145332  PMID: 21804910
Bayesian methods; Dietary assessment; Latent variables; Measurement error; Mixed models; Nutritional epidemiology; Nutritional surveillance; Zero-Inflated Data
7.  Performance of Common Genetic Variants in Breast-Cancer Risk Models 
The New England journal of medicine  2010;362(11):986-993.
BACKGROUND
Genomewide association studies have identified multiple genetic variants associated with breast cancer. The extent to which these variants add to existing risk-assessment models is unknown.
METHODS
We used information on traditional risk factors and 10 common genetic variants associated with breast cancer in 5590 case subjects and 5998 control subjects, 50 to 79 years of age, from four U.S. cohort studies and one case–control study from Poland to fit models of the absolute risk of breast cancer. With the use of receiveroperating- characteristic curve analysis, we calculated the area under the curve (AUC) as a measure of discrimination. By definition, random classification of case and control subjects provides an AUC of 50%; perfect classification provides an AUC of 100%. We calculated the fraction of case subjects in quintiles of estimated absolute risk after the addition of genetic variants to the traditional risk model.
RESULTS
The AUC for a risk model with age, study and entry year, and four traditional risk factors was 58.0%; with the addition of 10 genetic variants, the AUC was 61.8%. About half the case subjects (47.2%) were in the same quintile of risk as in a model without genetic variants; 32.5% were in a higher quintile, and 20.4% were in a lower quintile.
CONCLUSIONS
The inclusion of newly discovered genetic factors modestly improved the performance of risk models for breast cancer. The level of predicted breast-cancer risk among most women changed little after the addition of currently available genetic information.
doi:10.1056/NEJMoa0907727
PMCID: PMC2921181  PMID: 20237344
8.  Modeling Data with Excess Zeros and Measurement Error: Application to Evaluating Relationships between Episodically Consumed Foods and Health Outcomes 
Biometrics  2009;65(4):1003-1010.
Summary
Dietary assessment of episodically consumed foods gives rise to nonnegative data that have excess zeros and measurement error. Tooze et al. (2006, Journal of the American Dietetic Association 106, 1575–1587) describe a general statistical approach (National Cancer Institute method) for modeling such food intakes reported on two or more 24-hour recalls (24HRs) and demonstrate its use to estimate the distribution of the food’s usual intake in the general population. In this article, we propose an extension of this method to predict individual usual intake of such foods and to evaluate the relationships of usual intakes with health outcomes. Following the regression calibration approach for measurement error correction, individual usual intake is generally predicted as the conditional mean intake given 24HR-reported intake and other covariates in the health model. One feature of the proposed method is that additional covariates potentially related to usual intake may be used to increase the precision of estimates of usual intake and of diet-health outcome associations. Applying the method to data from the Eating at America’s Table Study, we quantify the increased precision obtained from including reported frequency of intake on a food frequency questionnaire (FFQ) as a covariate in the calibration model. We then demonstrate the method in evaluating the linear relationship between log blood mercury levels and fish intake in women by using data from the National Health and Nutrition Examination Survey, and show increased precision when including the FFQ information. Finally, we present simulation results evaluating the performance of the proposed method in this context.
doi:10.1111/j.1541-0420.2009.01223.x
PMCID: PMC2881223  PMID: 19302405
Dietary measurement error; Dietary survey; Episodically consumed foods; Excess zero models; Food frequency questionnaire; Fish; Individual usual intake; Mercury; Nonlinear mixed models; Regression calibration; 24-hour recall
9.  The Influence of Loop Electrosurgical Excision Procedure on the Subsequent Acquisition of New Human Papillomavirus Infections 
The Journal of infectious diseases  2009;199(11):1612-1620.
Background
The impact of loop electrosurgical excision procedure (LEEP) treatment for cervical precancerous lesions on subsequent acquisition of new human papillomavirus (HPV) infections is not well described.
Methods
Cumulative incidence rate ratios (IRR) for treated versus untreated women at 6- and 24-months of follow-up with 95% confidence intervals (95%CI) were calculated for infection by individual HPV genotypes, any HPV genotype, any carcinogenic HPV genotype, any non-carcinogenic HPV genotypes, and phylogenetic groups of HPV genotypes were compared between HPV-positive women who underwent colposcopy and were treated by LEEP (n = 195) and were untreated (n = 1,625) at entry into a two-year study.
Results
Treated women were 29% less likely than untreated women to acquire carcinogenic HPV genotypes at the 6-month follow-up (IRR = 0.71; 95%CI = 0.50–1.00) and 18% less likely at the 24-month follow-up (IRR = 0.82, 95%CI = 0.68–1.01). Treated women were, respectively, 56% and 40% less likely to acquire HPV genotypes of the α9 phylogenetic species (which includes HPV16) at 6-months (IRR = 0.44, 95%CI = 0.23–0.85) and 24-months (IRR = 0.60, 95%CI = 0.42–0.85).
Conclusion
LEEP may reduce the acquisition of certain carcinogenic HPV genotypes related to HPV16.
doi:10.1086/598981
PMCID: PMC2790913  PMID: 19405865
human papillomavirus (HPV); loop electrosurgical excision procedure (LEEP); cervical intraepithelial neoplasia (CIN); cervical cancer; atypical squamous cell of undetermined significance (ASCUS); low-grade squamous intraepithelial lesion (LSIL)

Results 1-9 (9)