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Published studies report inconsistent associations of polyunsaturated fatty acid (PUFA) intake with non-Hodgkin lymphoma (NHL) risk. We conducted a nested case-control study in Nurses' Health Study and Health Professionals Follow-Up Study participants to evaluate a hypothesis of inverse association of pre-diagnosis red blood cell (RBC) membrane PUFA levels with risk of NHL endpoints. We confirmed 583 NHL cases and matched 583 controls by cohort/sex, age, race and blood draw date/time. We estimated odds ratios (OR) and 95% confidence intervals (CI) for risk of NHL endpoints using logistic regression. RBC PUFA levels were not associated with all NHL risk; cis 20:2n-6 was associated with follicular lymphoma risk (OR [95% CI] per one standard deviation increase: 1.35 [1.03–1.77]), and the omega-6/omega-3 PUFA ratio was associated with diffuse large B-cell lymphoma risk (2.33 [1.23–4.43]). Overall, PUFA did not demonstrate a role in NHL etiology; the two unexpected positive associations lack clear biologic explanations. [ABSTRACT FROM AUTHOR]

Adiposity has been associated with several health conditions as well as timing of menopause. Prior epidemiologic studies on the association of adiposity and anti-Müllerian hormone (AMH) have been inconsistent. We evaluated the relations of anthropometric measures with AMH at two time periods in a subset of premenopausal participants in the Nurses' Health Study II. This prospective study included 795 women who provided a premenopausal sample in 1996–1999 and in 2010–2012. Current weight and height, and weight at age 18 were assessed in 1989 and weight again in 1996–1999. Waist and hip circumference were measured and reported in 1993. In linear regression models adjusted for smoking, reproductive events, and other factors, AMH was inversely related to BMI at age 18 (P =.03) and in 1996–1999 (P <.0001). Higher waist circumference was related to lower AMH levels in 1996–1999 (p =.0009). BMI in 1996–1999 was inversely associated with AMH levels in 2010–2012 (P =.005). Weight gain between age 18 and 1996–1999 was strongly inversely associated with AMH levels in 1996–1999 (P <.0001) and in 2010–2012 (P <.0001). Our results indicate that adiposity and weight gain are associated with lower AMH levels, suggesting an adverse impact on ovarian function. [ABSTRACT FROM AUTHOR]

To demonstrate methods for receiver-operating characteristic (ROC) analysis of correlated eye data. We applied the Obuchowski's nonparametric approach and cluster bootstrap for estimating and comparing the area under ROC curve (AUC) between different sets of predictors to three datasets with varying inter-eye correlation. In an optic neuritis (ON) study of 152 eyes (80 patients), the AUC of optical coherence tomography retinal nerve fiber layer thickness for diagnosing ON (inter-eye kappa = 0.13) was 0.71 [95% confidence interval (95% CI): 0.622, 0.792] from the naïve approach without accounting for inter-eye correlation was narrower than from nonparametric (95% CI: 0.613, 0.801) or cluster bootstrap (95% CI: 0.614, 0.797) approaches. In an analysis of 198 eyes (135 patients), the baseline Age-related Eye disease Study scale predicted 5-year incidence of advanced age-related macular degeneration (inter-eye kappa = 0.23) with AUC of 0.72. The 95% CI from the naïve approach was slightly narrower (0.645, 0.794) than from the nonparametric (0.641, 0.797) or cluster bootstrap (0.641, 0.793) approaches. In an analysis of 1542 eyes (771 infants), birthweight and gestational age predicted treatment-requiring retinopathy of prematurity (inter-eye kappa = 0.98) with AUC of 0.80. Furthermore, the 95% CI from the naïve approach was narrower (0.769, 0.835) than from the nonparametric (0.755, 0.848) or cluster bootstrap (0.755, 0.845) approaches. 95% CIs for AUC differences between different models were narrower in the naïve approach than the nonparametric or cluster bootstrap approaches. In ROC analysis of correlated eye data, ignoring inter-eye correlation leads to narrower 95% CI with underestimation dependent on magnitude of inter-eye correlation. Nonparametric and cluster bootstrap approaches properly account for inter-eye correlation. [ABSTRACT FROM AUTHOR]

Purpose: To describe and demonstrate methods for analyzing longitudinal correlated eye data with a continuous outcome measure. Methods: We described fixed effects, mixed effects and generalized estimating equations (GEE) models, applied them to data from the Complications of Age-Related Macular Degeneration Prevention Trial (CAPT) and the Age-Related Eye Disease Study (AREDS). In CAPT (N = 1052), we assessed the effect of eye-specific laser treatment on change in visual acuity (VA). In the AREDS study, we evaluated effects of systemic supplement treatment among 1463 participants with AMD category 3. Results: In CAPT, the inter-eye correlations (0.33 to 0.53) and longitudinal correlations (0.31 to 0.88) varied. There was a small treatment effect on VA change (approximately one letter) at 24 months for all three models (p =.009 to 0.02). Model fit was better with the mixed effects model than the fixed effects model (p <.001). In AREDS, there was no significant treatment effect in all models (p >.55). Current smokers had a significantly greater VA decline than non-current smokers in the fixed effects model (p =.04) and the mixed effects model with random intercept (p =.0003), but marginally significant in the mixed effects model with random intercept and slope (p =.08), and GEE models (p =.054 to 0.07). The model fit was better with the fixed effects model than the mixed effects model (p <.0001). Conclusion: Longitudinal models using the eye as the unit of analysis can be implemented using available statistical software to account for both inter-eye and longitudinal correlations. Goodness-of-fit statistics may guide the selection of the most appropriate model. [ABSTRACT FROM AUTHOR]

Purpose: To describe and demonstrate methods for analyzing correlated binary eye data. Methods: We describe non-model based (McNemar’s test, Cochran-Mantel-Haenszel test) and model-based methods (generalized linear mixed effects model, marginal model) for analyses involving both eyes. These methods were applied to: (1) CAPT (Complications of Age-related Macular Degeneration Prevention Trial) where one eye was treated and the other observed (paired design); (2) ETROP (Early Treatment for Retinopathy of Prematurity) where bilaterally affected infants had one eye treated conventionally and the other treated early and unilaterally affected infants had treatment assigned randomly; and (3) AREDS (Age-Related Eye Disease Study) where treatment was systemic and outcome was eye-specific (both eyes in the same treatment group). Results: In the CAPT (n= 80), treatment group (30% vision loss in treated vs. 44% in observed eyes) was not statistically significant (p= 0.07) when inter-eye correlation was ignored, but was significant (p= 0.01) with McNemar’s test and the marginal model. Using standard logistic regression for unfavorable vision in ETROP, standard errors andp-values were larger for person-level covariates and were smaller for ocular covariates than using models accounting for inter-eye correlation. For risk factors of geographic atrophy in AREDS, two-eye analyses accounting for inter-eye correlation yielded more power than one-eye analyses and provided larger standard errors andp-values than invalid two-eye analyses ignoring inter-eye correlation. Conclusion: Ignoring inter-eye correlation can lead to largerp-values for paired designs and smallerp-values when both eyes are in the same group. Marginal models or mixed effects models using the eye as the unit of analysis provide valid inference. [ABSTRACT FROM PUBLISHER]

Purpose: To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. Methods: We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. Results: When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI −0.03 to 0.32D,p= 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D,p= 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smallerp-values, while analysis of the worse eye provided largerp-values than mixed effects models and marginal models. Conclusion: In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision. [ABSTRACT FROM AUTHOR]

We characterized recently identified event clusters in systemic mastocytosis (SM) by calculating the coefficient of variation (CV, %) of CD117 and side scatter (SSC), based on the mean fluorescence intensity of mast cells using flow cytometry. Seventy-five samples were from patients with SM and 124 samples from patients negative for SM (non-SM). Discrete cluster formation seen in 50 cases correlated with significantly lower CV for SSC (46.1% vs. 61.0%, p < 0.0001) and CD117 (64.5% vs. 80.5%, p < 0.0001) for SM vs. non-SM samples. A combined CVCD117 + SSC of < 125 showed a sensitivity of 80% and specificity of 80% for SM with PPV of 67% and NPV of 80%. Probability scores of having SM, generated based on CVs for SSC and CD117, were significantly higher in patients with SM than non-SM (0.55 vs. 0.17, respectively; p < 0.001). Flow cytometric-based quantitative analysis of event clustering is a useful approach for diagnosing and monitoring patients with SM. [ABSTRACT FROM AUTHOR]

Purpose: The eye is often the unit of measurement for outcomes, and frequently also for covariates, in vision research, and measurements in the two eyes of the same person are often strongly but far from perfectly correlated. Advances have occurred in the development and accessibility of analytic approaches to evaluate determinants of eye-specific outcomes including information from both eyes of some subjects. Methods: We illustrate available regression approaches to analyze correlated outcomes from both eyes in datasets with both eye- and subject-specific exposures and potential confounding variables. We consider cross-sectional and longitudinal study designs, and discrete, continuous, and time-to-event outcomes. Results: Across a range of study designs and measurement scales for the outcome variable, we show the under-estimation of P-values and widths of confidence intervals that occurs when the correlation between paired eyes in a person is ignored, and the reduced precision that occurs in separate analyses of right or left eyes, or in analyses of persons rather than eyes. By comparison, regression models with the eye as the unit of analysis and appropriate consideration of the correlation between paired outcomes generally offer maximal use of available data, enhanced interpretability of covariate-outcome associations, and efficient use of information from subjects who contribute only one eye to analyses. Conclusions: For many studies in vision research, the now widely available regression models that appropriately treat the eye as the unit of analysis offer the best analytic approach. [ABSTRACT FROM AUTHOR]

Research on diet in breast cancer survival has been focused on single nutrients or foods, particularly dietary fat, fruits, vegetables, fiber, and alcohol. We hypothesized that diet quality indices decrease the risk of total and non-breast-cancer-related deaths in women diagnosed with breast cancer. We evaluated 4 dietary quality scores: Alternate Healthy Eating Index (AHEI), Diet Quality Index-Revised (DQIR), Recommended Food Score (RFS), and the alternate Mediterranean Diet Score (aMED), among 2,729 women from the Nurses' Health Study with invasive Stage 1-3 breast cancer diagnosed between 1978 and 1998 with follow-up through 2004. In multivariate adjusted analyses, no association was found between diet quality indices and either total or non-breast-cancer-related deaths. However, a higher aMED score was associated with a lower risk of non-breast-cancer death in women with low physical activity; the RR comparing the highest to lowest tertile was 0.39 (95% CI, 0.20-0.75, P trend = 0.0004). Our results suggest that a higher-quality diet after breast cancer diagnosis does not considerably change the risk of death from breast cancer. However, healthy dietary choices may be important because women are at risk of death from non-breast-cancer-related causes affected by diet. [ABSTRACT FROM AUTHOR]

Purpose: In prospective studies of incident cataract, a person may have developed two or all three of cortical, nuclear sclerotic and posterior subscapsular cataract at the time when clinically significant cataract is apparent. One can compare the impact of risk factors on different types of cataract with methods of competing risk survival analysis that account for tied events. Methods: We studied risk factors for incident cataract among 20,599 participants in the Physicians' Health Study; 1,923 of whom developed cataract that reduced visual acuity over a median follow-up of 13.0 years. Among incident cases, 45% had two types of cataract and an additional 12% had all three. Proportional hazards models, adjusted for tied failures through use of generalized estimating equations, provided comparisons across different cataract types. Stratified analyses by type with age as the time scale were used to accommodate the strong but different relationships of age with occurrence of different cataract types. Results: Analyses found different relationships of diabetes and body mass index, but similar relationships of smoking, family history of coronary disease and multivitamin use, across different cataract types. A simplified model provided common estimates for relative risks associated with those characteristics with similar effects across cataract types. Conclusions: Whereas polytomous logistic regression has proven useful for comparisons of risks across cataract types in retrospective and cross-sectional studies, this approach based on methods of survival analysis has greater flexibility in prospective studies with variable follow-up and frequently tied event times for different cataract types. [ABSTRACT FROM AUTHOR]

The article presents a study that investigated the importance of cost and awareness of health- or disease-promoting properties of foods and meals for choices by customers of a cafeteria in the Harvard School of Public Health. Results show an increase in the consumption of healthy foods. Eating habits apparently result from individual choices, behavior and social environment. Effect of pricing structure on food choices is also discussed.

Purpose: To extend the Wilcoxon rank sum test to the analysis of clustered observational data with a binary exposure variable where not all cluster members (or subunits) have the same exposure status, as in ophthalmologic data where fellow eyes may differ in exposure status. Methods: The Wilcoxon rank sum test statistic (Wc) is defined as the sum of ranks of all exposed subunits over all clusters. The large sample distribution of Wc is derived based on a two-stage permutation distribution approach which maintains the clustering structure of the exposure distribution in the original data. The procedure is applied to data from the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) for assessing differences in retinopathy grade between eyes with high vs. low intraocular pressure (IOP). Results: Data analyses based on the WESDR data indicate significant positive associations between IOP and retinopathy grade as assessed by the clustered Wilcoxon test (p = 0.019), but non-significant effects with mixed model procedures based on raw scores (p = 0.30). Conclusions: The clustered Wilcoxon procedure is an effective approach for analyzing clustered non-normal outcome data with a binary eye-specific exposure which may vary in 2 eyes of an individual. [ABSTRACT FROM AUTHOR]

Purpose: Alcohol intake reduces intraocular pressure, a risk factor for primary open-angle glaucoma (POAG). We investigated whether alcohol consumption is associated with a reduced risk of POAG. Methods: We followed female nurses from 1980 and male health professionals from 1986 to 2002. Eligible participants were 40+ years old, did not have POAG, and reported receiving eye examinations during follow-up. Information on alcohol consumption, potential confounders and POAG diagnoses were updated by using biennial questionnaires. We identified 856 self-reported POAG cases that were confirmed with medical record review. Cohort-specific and pooled analyses across cohorts were conducted to calculate multivariable rate ratios (RR) of POAG. Results: Alcohol consumption < 30 g/day did not influence POAG risk: compared with non-drinkers, the pooled RRs were 0.99 (95% Confidence Interval [CI]: 0.83-1.19) for drinking < 10 g/day, 0.96 (95% CI: 0.76-1.22) for 10-19 g/day, and 0.95 (95% CI: 0.68-1.33) for 20-29 g/day. Although there were suggestive inverse associations with drinking > 30 g/day (RR = 0.71), this was not significant (95% CI: 0.49-1.04), and no significant linear associations were detected. Risks of POAG did not differ by type of alcoholic beverage consumed. To evaluate the potential for detection bias, we controlled for additional factors, such as frequency of eye exams, but results were similar. Conclusion: In this large prospective study of men and women, alcohol consumption did not influence the risk of POAG. [ABSTRACT FROM AUTHOR]

PURPOSE Women are at higher risk for age-related cataract than men, and it has been hypothesized that this difference is due in part to gender-related hormonal differences. METHODS We investigated the association between postmenopausal hormone use and lens opacities in a population of 480 postmenopausal women from the Nurses' Health Study for whom we had prospectively collected exposure data. Participants received standardized eye exams; the Lens Opacity Classification System III (LOCS III) was used to measure the degree of opacification. RESULTS A total of 342 women had some opacity in one or both eyes. Overall, we did not observe a significant association between current hormone use and presence of any type of opacity (compared to never users, multivariate relative risk: 0.85; 95% confidence interval (CI): 0.54-1.34). In ordinal logistic regression compared to never users, current hormone users had multivariate relative risks of cortical opacities of 0.80 (95% CI: 0.54-1.19) and for past users the relative risk was 0.76 (95% CI: 0.48-1.22). For nuclear opacities, the comparable relative risk for current use of hormones was 0.77 (95% CI: 0.52-1.13), and for past use the relative risk was 1.48 (95% CI: 0.92-2.34). Current use of estrogen-only preparations was associated with a 49% decreased risk of nuclear opacities compared to never use (multivariate relative risk 0.51, 95% CI: 0.29-0.89). CONCLUSIONS While the overall findings are null, they do not exclude the possibility of a protective effect, particularly among current estrogen users. [ABSTRACT FROM AUTHOR]

In epidemiological studies, continuous covariates often are measured with error and categorical covariates often are misclassified. Using the logistic regression model to represent the relationship between the binary outcome and the perfectly measured and classified covariates, the model for the observed main study data is derived. This derivation relies on the assumption that the error in the continuous covariates is multivariate normally distributed and uses a chain of logistic regression models to describe the misclassification processes. These model assumptions are empirically verified in the validation study, where the misclassified and mismeasured covariates are validated using perfectly measured and classified data. The full data likelihood, including contributions from both the main study and the validation study, is maximized to obtain the maximum likelihood estimates for the parameters of the underlying logistic regression model and of the measurement error model and reclassification models simultaneously. Standard asymptotic theory is applied. An example of this methodology is presented from the Nurses' Health Study investigating the relationship between cumulative incidence of breast cancer and saturated fat, total energy, and alcohol intake. A detailed simulation study was conducted to investigate the small-sample properties of these likelihood-based estimates and inferential quantities. No single estimation/inference option performed satisfactorily when the main study/validation study size was representative of that typically encountered in practice. When the validation size was twice or larger than from the usual one, features of asymptotic optimality were more apparent. By example and through simulation, the procedures appeared to be robust to misspecification of the order of the chain of conditional measurement error/reclassification models. [ABSTRACT FROM AUTHOR]

Develops a model for the distribution of number of batters faced and number of runs scored against starting pitchers in Major League Baseball games based on data from the year 1990. Details of the model; Estimation.

Clustered data occur frequently in statistical practice. In some areas of application, such as ophthalmology, clustered data are the rule rather than the exception. In this setting, standard multivariate methods such as logistic regression are invalid, because of the lack of independence among outcomes for individual sample points within a cluster. In Rosner (1984), a polychotomous logistic regression model was presented to control for the effect of both cluster and individual-specific covariates while accounting for the correlation among units within a cluster. This model reduces to a beta-binomial model in the absence of covariates, and to an ordinary logistic model for clusters of size 1 and for larger clusters when no correlation is present. A 1 level of nesting correlation structure is assumed, as is typically found in ophthalmology, where the person is the cluster and the individual eyes are the units within a cluster. In this article, this model is generalized to a 2 level of nesting structure. This model is motivated by an ophthalmologic application, where data are collected in family units and one wishes to model simultaneously the correlation at the first level of nesting among persons within a family, and at the second level of nesting between eyes within a person. In the absence of covariates, the model is characterized by a compound beta-binomial distribution that generalizes the betabinomial distribution to more than one level of nesting. The compound beta-binomial distribution is then augmented in a regression setting, to allow for the presence of family-, person-, and eye-specific covariates while controlling for correlation at each level of nesting. Extensions to more than two levels of nesting are also considered. [ABSTRACT FROM AUTHOR]

A generalized (extreme Studentized deviate) ESD many-outlier procedure is given for detecting from i to k outliers in a data set. This procedure has an advantage over the original ESD many-outlier procedure (Rosner 1975) in that it controls the type I error both under the hypothesis of no outliers and under the alternative hypotheses of 1, 2, …, k-1 outliers. A method is given for approximating percentiles for this procedure based on the t distribution. This method is shown to be adequately accurate using Monte Carlo simulation, for detecting up to 10 outliers in samples as small as 25. Tables are given for implementing this method for n = 25(1)50(10)100(50)500; k = 10, α = .05, .01, .005. [ABSTRACT FROM AUTHOR]

This article is concerned with estimating percentage points for the RST (R-statistic) many outlier procedure. This procedure has been introduced in [5] and a brief discussion is given in Section 1. The algorithm used to estimate the percentage points is given in Section 2. Percentage points are given for α = .10, .05, .01, N = 10(5) 20(10) 50(25) 100, k = 2; N = 20(10) 50(25) 100, k = 3; N = 20(10) 50(25) 100, k = 4. Two examples illustrating the use of the procedure are given in Section 3. Finally some potential weaknesses of the method are discussed in Section 4: namely, when the actual number of outliers in a sample is larger than the maximum number of outliers assumed by the procedure. Alternatives are proposed for possibly modifying the procedure to allow for this contingency. [ABSTRACT FROM AUTHOR]

This article is concerned with "many outlier" procedures i.e., procedures that can detect more than one outlier in a simple. Several many outlier procedures are proposed in Section 2 and via power comparisons in Section 3 are found to be much superior to one outlier procedures in detecting many outliers. We then compare several different many outlier procedures in Section 4 and find that the procedure based on the extreme studentized deviate (ESD) is slightly the best. Finally, 5%, 1% .5% points are given for the ESD procedure for various sample sizes in Section 5. [ABSTRACT FROM AUTHOR]

Examines the influence of cigarette smoking and age on bone loss in men. Conduction of hand X-ray for the investigation of bone loss; Estimation of bone density at midshaft of the second metacarpal of the hand; Occurrence of decrease in percent cortical area with age.