What can be learnt from models of incidence rates?

Models of breast cancer incidence have evolved from the observation by Armitage and Doll in the 1950s that the pattern of incidence by age differs for reproductive cancers from those of other major malignancies. Both two-stage and multistage models have been applied to breast cancer incidence. Consistent across modeling approaches, risk accumulation or the rate of increase in breast cancer incidence is most rapid from menarche to first birth. Models that account for the change in risk after menopause and the temporal sequence of reproductive events summarize risk efficiently and give added insights to potentially important mechanistic features. First pregnancy has an adverse impact on progesterone receptor negative tumors, while increasing parity reduces the risk of estrogen/progesterone receptor positive tumors but not estrogen/progesterone receptor negative tumors. Integrated prediction models that incorporate prediction of carrier status for highly penetrant genes and also account for lifestyle factors, mammographic density, and endogenous hormone levels remain to be efficiently implemented. Models that both inform and reflect the emerging understanding of the molecular and cell biology of carcinogenesis are still a long way off

NRQCD and Static Systems -- A General Variational Approach

We present initial results from Monte Carlo simulations of NRQCD-light, static-light, and NRQCD-NRQCD mesons, using a variational technique (MOST), as part of our ongoing calculation of the $f_{B}$ decay constant. The basis states for the variational calculation are quark-antiquark operators separated by all possible relative distances not equivalent under the cubic group (for example, for a $20^{3}$ lattice there are 286 operators). The efficacy of the method is demonstrated by the good plateaus obtained for the ground state and the clean extraction of the wave functions of the ground and first radially excited state.Comment: Contribution to the Lattice '94 conference, 3 pages, uuencoded-compressed PostScript fil

Rare and Common Genetic Variants, Smoking, and Body Mass Index: Progression and Earlier Age of Developing Advanced Age-Related Macular Degeneration

Purpose: To determine behavioral and genetic factors associated with incidence and age of progression to advanced age-related macular degeneration (AMD), geographic atrophy (GA), and neovascular disease (NV), and to quantify these effects. Methods: Longitudinal analyses were conducted among 5421 eyes with nonadvanced AMD at baseline in 2976 participants in the Age-Related Eye Disease Study (mean age of 68.8 (+/-5.0), 56.1% female). Progression was confirmed based on two consecutive visits on the AMD severity scale. Separate analyses for progression and age of progression were performed. All analyses adjusted for correlation between eyes, demographic and behavioral covariates, baseline severity scale, and genetic variants. Results: A higher genetic risk score (GRS) including eight genetic variants was associated with a higher rate of progression to advanced AMD within each baseline severity scale, especially for the highest risk intermediate level AMD category, and smoking further increased this risk. When assessing age when progression to advanced disease occurred, smoking reduced age of onset by 3.9 years (P \u3c 0.001), and higher body mass index (BMI) led to earlier onset by 1.7 years (P = 0.003), with similar results for GA and NV. Genetic variants associated with earlier age of progression were CFH R1201C (4.3 years), C3 K155Q (2.15 years), and ARMS2/HTRA1 (0.8 years per allele). Conclusions: Rare variants in the complement pathway and a common risk allele in ARMS2/HTRA1, smoking, and higher BMI can lead to as much as 11.5 additional years of disease and treatment burden. Closer adherence to healthy lifestyles could reduce years of visual impairment

Design issues in crossover trials involving patients with Parkinson’s disease

Background and objectivesCrossover designs are frequently used to assess treatments for patients with Parkinson’s disease. Typically, two-period two-treatment trials include a washout period between the 2 periods and assume that the washout period is sufficiently long to eliminate carryover effects. A complementary strategy might be to jointly model carryover and treatment effects, though this has rarely been done in Parkinson’s disease crossover studies. The primary objective of this research is to demonstrate a modeling approach that assesses treatment and carryover effects in one unified mixed model analysis and to examine how it performs in a simulation study and a real data analysis example, as compared to other data analytic approaches used in Parkinson’s disease crossover studies.MethodsWe examined how three different methods of analysis (standard crossover t-test, mixed model with a carryover term included in model statement, and mixed model with no carryover term) performed in a simulation study and illustrated the methods in a real data example in Parkinson’s disease.ResultsThe simulation study based on the presence of a carryover effect indicated that mixed models with a carryover term and an unstructured correlation matrix provided unbiased estimates of treatment effect and appropriate type I error. The methods are illustrated in a real data example involving Parkinson’s disease. Our literature review revealed that a majority of crossover studies included a washout period but did not assess whether the washout was sufficiently long to eliminate the possibility of carryover.DiscussionWe recommend using a mixed model with a carryover term and an unstructured correlation matrix to obtain unbiased estimates of treatment effect

Three New Genetic Loci (R1210C in CFH, Variants in COL8A1 and RAD51B) Are Independently Related to Progression to Advanced Macular Degeneration

Objectives: To assess the independent impact of new genetic variants on conversion to advanced stages of AMD, controlling for established risk factors, and to determine the contribution of genes in predictive models. Methods: In this prospective longitudinal study of 2765 individuals, 777 subjects progressed to neovascular disease (NV) or geographic atrophy (GA) in either eye over 12 years. Recently reported genetic loci were assessed for their independent effects on incident advanced AMD after controlling for 6 established loci in 5 genes, and demographic, behavioral, and macular characteristics. New variants which remained significantly related to progression were then added to a final multivariate model to assess their independent effects. The contribution of genes to risk models was assessed using reclassification tables by determining risk within cross-classified quintiles for alternative models. Results: Three new genetic variants were significantly related to progression: rare variant R1210C in CFH (hazard ratio (HR) 2.5, 95% confidence interval [CI] 1.2–5.3, P = 0.01), and common variants in genes COL8A1 (HR 2.0, 95% CI 1.1–3.5, P = 0.02) and RAD51B (HR 0.8, 95% CI 0.60–0.97, P = 0.03). The area under the curve statistic (AUC) was significantly higher for the 9 gene model (.884) vs the 0 gene model (.873), P = .01. AUC’s for the 9 vs 6 gene models were not significantly different, but reclassification analyses indicated significant added information for more genes, with adjusted odds ratios (OR) for progression within 5 years per one quintile increase in risk score of 2.7, P<0.001 for the 9 vs 6 loci model, and OR 3.5, P<0.001 for the 9 vs. 0 gene model. Similar results were seen for NV and GA. Conclusions: Rare variant CFH R1210C and common variants in COL8A1 and RAD51B plus six genes in previous models contribute additional predictive information for advanced AMD beyond macular and behavioral phenotypes

Semileptonic Decays: an Update Down Under

Heavy-meson semileptonic decays calculations on the lattice are reviewed. The focus is upon obtaining reliable matrix elements. Errors that depend upon the lattice spacing, $a$, are an important source of systematic error. Full $O(a)$ improvement of matrix elements for arbitrary-mass four-component quarks is discussed. With improvement, bottom-quark matrix elements can be calculated directly using current lattices. Momentum dependent errors for $O(a)$-improved quarks and statistical noise limit momenta to around 1 GeV/c with current lattices. Hence, maximum recoil momenta can be reached for $D$ decays while only a fraction of the maximum recoil momentum can be reliably studied for the light-meson decay modes of the $B$. Differential decay rates and partial widths are phenomenologically important quantities in $B$ decays that can be reliably determined with present lattices.Comment: 14 pages, 9 postscript figures, requires espcrc2.st

Analytical method for detecting outlier evaluators

Epidemiologic and medical studies often rely on evaluators to obtain measurements of exposures or outcomes for study participants, and valid estimates of associations depends on the quality of data. Even though statistical methods have been proposed to adjust for measurement errors, they often rely on unverifiable assumptions and could lead to biased estimates if those assumptions are violated. Therefore, methods for detecting potential `outlier' evaluators are needed to improve data quality during data collection stage. In this paper, we propose a two-stage algorithm to detect `outlier' evaluators whose evaluation results tend to be higher or lower than their counterparts. In the first stage, evaluators' effects are obtained by fitting a regression model. In the second stage, hypothesis tests are performed to detect `outlier' evaluators, where we consider both the power of each hypothesis test and the false discovery rate (FDR) among all tests. We conduct an extensive simulation study to evaluate the proposed method, and illustrate the method by detecting potential `outlier' audiologists in the data collection stage for the Audiology Assessment Arm of the Conservation of Hearing Study, an epidemiologic study for examining risk factors of hearing loss in the Nurses' Health Study II. Our simulation study shows that our method not only can detect true `outlier' evaluators, but also is less likely to falsely reject true `normal' evaluators. Our two-stage `outlier' detection algorithm is a flexible approach that can effectively detect `outlier' evaluators, and thus data quality can be improved during data collection stage

Association Between Perifoveal Drusen Burden Determined by OCT and Genetic Risk in Early and Intermediate Age-Related Macular Degeneration

Purpose: The purpose of this study was to determine associations between macular drusen parameters derived from an automatic optical coherence tomography (OCT) algorithm, nonadvanced age-related macular degeneration (AMD) stage, and genetic variants. Methods: Eyes classified as early or intermediate AMD with OCT imaging and genetic data were selected (n = 239 eyes). Drusen area and volume measurements were estimated using the Zeiss Cirrus advanced retinal pigment epithelium analysis algorithm in a perifoveal zone centered on the fovea. Associations between drusen measurements and common genetic variants in the complement and high-density lipoprotein (HDL) lipid pathways and the ARMS2/HTRA1 variant were calculated using generalized estimating equations and linear mixed models adjusting for age, sex, smoking, body mass index, and education. Results: Drusen area \u3e /= the median was independently associated with a higher number of risk alleles for CFH risk score and risk variants in C3 and ARMS2/HTRA1 compared with eyes with no measurable drusen. Similar results were obtained for drusen volume. When all genes were analyzed in the same model, only CFH score and ARMS2/HTRA1 were associated with drusen measurements. HDL pathway genes were not significantly related to drusen parameters. Nonadvanced AMD stages were associated with OCT-derived drusen area and volume. Conclusions: Variants in CFH and ARMS2/HTRA1, commonly associated with advanced AMD, were independently associated with an increase in drusen burden determined by OCT in an allele dose dependent manner, in eyes with early and intermediate AMD. Biomarkers such as a quantitative classification of nonadvanced AMD and other OCT-derived subphenotypes could provide earlier anatomic endpoints for clinical trials and facilitate the development of new therapies for AMD