Benefits of adding coronary calcium score scan to stress myocardial perfusion positron emission tomography imaging

There have been little and conflicting data regarding the relationship between coronary artery calcification score (CACS) and myocardial ischemia on positron emission tomography myocardial perfusion imaging (PET MPI). The aims of this study were to investigate the relationship between myocardial ischemia on PET MPI and CACS, the frequency and severity of CACS in patients with normal PET MPI, and to determine the optimal CACS cutoff point for abnormal PET. This retrospective study included 363 patients who underwent same-setting stress PET perfusion imaging and CACS scan because of clinically suspected coronary artery disease (CAD). Fifty-five (55%) of the 363 patients had abnormal PET perfusion. There was an association between sex, diabetes mellitus (DM), smoking, and CACS and PET perfusion abnormities with P = 0.003, 0.05, 0.005, and 0.001, respectively. However, there was no association between PET perfusion abnormalities with age, body mass index, hypertension, and hypercholesterolemia. There was association between CACS and age, sex, and DM with P = 0.000, 0.014, and 0.052, respectively, and stepwise increase in the frequency of myocardial ischemia and CACS groups. Receiver-operating characteristic analysis showed that a CACS ≥304 is the optimal cutoff for predicting perfusion abnormalities with sensitivity of 64% and specificity of 69%. In conclusion, the frequency of CAC in patients with normal PET MPI is 49%, it is highly recommended to combine CACS with PET MPI in patients without a history of CAD. PET MPI identifies myocardial ischemia and defines the need for coronary revascularization, but CAC reflects the anatomic burden of coronary atherosclerosis. Combining CACS to PET MPI allows better risk stratification and identifies high-risk patients with PET, and it may change future follow-up recommendations. CACS scan is readily available and easily acquired with modern PET-computed tomography (CT) and single-photon emission CT (SPECT)-CT with modest radiation exposure.

Reduced rate of human papillomavirus infection and genetic overtransmission of TP53 72C polymorphic variant lower cervical cancer incidence

BACKGROUND

Cervical cancer is a predominantly human papillomavirus (HPV)‐driven disease worldwide. However, its incidence is unexplainably low in western Asia, including Saudi Arabia. Using this paradigm, we investigated the role of HPV infection rate and host genetic predisposition in TP53 G72C single nucleotide polymorphism (SNP) presumed to affect cancer incidence.

METHODS

Patients treated between 1990 and 2012 were reviewed, and a series of 232 invasive cervical cancer cases were studied and compared with 313 matched controls without cancer. SNP was genotyped by way of direct sequencing. HPV linear array analysis was used to detect and genotype HPV in tumor samples.

RESULTS

The incidence of cervical cancer revealed bimodal peaks at 42.5 years, with a slighter rebound at 60.8 years. Among all cases, 77% were HPV‐positive and 16 HPV genotypes were detected—mostly genotypes 16 (75%) and 18 (9%)—with no difference by age, histology, or geographical region. Although the TP53 G72C genotype was not associated with overall cervical cancer risk, it was significantly associated with HPV positivity (odds ratio, 0.57; 95% confidence interval, 0.36‐0.90; P = .016). Furthermore, the variant C allele was significantly overtransmitted in the population (P < .0003).

CONCLUSION

Cervical cancer incidence displays bimodal curve peaking at a young age with secondary rebound at older age. The combination of relative low HPV infection and variant TP53 72C allele overtransmission provide a plausible explanation for the low incidence of cervical cancer in our population. Therefore, HPV screening and host SNP genotyping may provide more relevant biomarkers to gauge the risk of developing cervical cancer. Cancer 2017;123:2459–66. © 2017 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Cervical cancer incidence shows bimodal peaks at 43 years and relative rebound at 61 years of age. A reduced rate of human papillomavirus infection and overtransmission of the TP53 72C variant lower cancer incidence.

Thromboembolic events in patients with inflammatory bowel disease

BACKGROUND/AIMS

Inflammatory bowel disease (ulcerative colitis and Crohn's disease) is characterized by a chronic inflammatory condition, and is accompanied by abnormalities in coagulation and a hyper-coagulable state. This study was conducted to examine the risk factors for developing Thromboembolic Events in Inflammatory Bowel Disease (IBD) in a population with prevalent consanguinity.

PATIENTS AND METHODS

Patients with a definitive diagnosis of IBD who were seen in the gastroenterology clinic of King Khalid University Hospital (Riyadh, Saudi Arabia) from 2010- to 2012, were asked to participate in this prospective cohort study, and were followed for one 1 year. Data was collected using specifically designed case report forms (CRF) by trained research personnel.

RESULTS

A total of 100 Saudi patients with IBD were studied. There were 51 (51%) women and the mean ± standard deviation (SD) age of the group was 31.24 ± 10.78 years. Those with Crohn's disease constituted 72% of the patients, and 28% had ulcerative colitis. Eight patients (8%) had at least one Thrombotic Event ([six deep venous thrombosis (DVT), and two pulmonary embolism (PE)]. Family history of deep venous thrombosis was present in 5%, and family history of pulmonary embolism (PE) in 4% of the patients. After adjusting for age and gender, a family history of Thrombotic event was identified as to be the only statistically significant predictor of thrombosis in IBD patients (RR = 9.22, 95% CI: 2.10--40.43).

CONCLUSION

In a population with high consanguinity, Thromboembolic events (DVT and PE) had a prevalence of 8% among IBD patients, positive family history of pulmonary embolism was a predictor of thrombosis. Further studies are needed to explore the role of genetic factors in this population.

Adjusted inference procedures for the interobserver agreement in twin studies

We propose adjusted inference procedures for evaluating the agreement/disagreement of two raters in a clustered setting involving twins or paired body parts. These procedures include the construction of a confidence interval for the kappa statistic, a related test of statistical significance and a formula that facilitates sample size estimation. The results of a simulation study suggest that a simple adjustment using an estimated design effect will provide valid inferences. The methods proposed are illustrated using an example from the literature.

Sample size requirements for the design of reliability study: review and new results

The reliability of continuous or binary outcome measures is usually assessed by estimation of the intraclass correlation coefficient (ICC). A crucial step for this purpose is the determination of the required sample size. In this review, we discuss the contributions made in this regard and derive the optimal allocation for the number of subjects k and the number of repeated measurements n that minimize the variance of the estimated ICC. Cost constraints are discussed for both normally and non-normally distributed responses, with emphasis on the case of dichotomous assessments. Tables showing optimal choices of k and n are given along with the guidelines for the efficient design of reliability studies.

Systematic Analysis of AU-Rich Element Expression in Cancer Reveals Common Functional Clusters Regulated by Key RNA-Binding Proteins

Defects in AU-rich elements (ARE)-mediated posttranscriptional control can lead to several abnormal processes that underlie carcinogenesis. Here, we performed a systematic analysis of ARE-mRNA expression across multiple cancer types. First, the ARE database (ARED) was intersected with The Cancer Genome Atlas databases and others. A large set of ARE-mRNAs was over-represented in cancer and, unlike non-ARE-mRNAs, correlated with the reversed balance in the expression of the RNA-binding proteins tristetraprolin (TTP, ZFP36) and HuR (ELAVL1). Serial statistical and functional enrichment clustering identified a cluster of 11 overexpressed ARE-mRNAs (CDC6, KIF11, PRC1, NEK2, NCAPG, CENPA, NUF2, KIF18A, CENPE, PBK, TOP2A) that negatively correlated with TTP/HuR mRNA ratios and was involved in the mitotic cell cycle. This cluster was upregulated in a number of solid cancers. Experimentally, we demonstrated that the ARE-mRNA cluster is upregulated in a number of tumor breast cell lines when compared with noninvasive and normal-like breast cancer cells. RNA-IP demonstrated the association of the ARE-mRNAs with TTP and HuR. Experimental modulation of TTP or HuR expression led to changes in the mitosis ARE-mRNAs. Posttranscriptional reporter assays confirmed the functionality of AREs. Moreover, TTP augmented mitotic cell-cycle arrest as demonstrated by flow cytometry and histone H3 phosphorylation. We found that poor breast cancer patient survival was significantly associated with low TTP/HuR mRNA ratios and correlated with high levels of the mitotic ARE-mRNA signature. These results significantly broaden the role of AREs and their binding proteins in cancer, and demonstrate that TTP induces an antimitotic pathway that is diminished in cancer. Cancer Res; 76(14); 4068-80. ©2016 AACR.

Regional variation in organ donation in Saudi Arabia

INTRODUCTION

There is marked regional variation in organ donation among the different regions of Saudi Arabia. Our aim was to study the dominating factors for these variations to improve organ donation in low-donation areas.

MATERIALS AND METHODS

This study was a retrospective review of the Saudi Center for Organ Transplantation data for cadaveric organ donation from 2006 to 2012, with the number of cases reported, documented, consented, and harvested in various regions (northern, southern, eastern, western, and central). The region, number, and size of contributing intensive care units (ICUs), overall donation rate, and transplanted rate (potential donor and those harvested, respectively) were also reviewed.

RESULTS

Between 2006 and 2012, a total of 512 cases were procured and analyzed from Saudi Arabia. From the central region, 393 were acquired, representing 76.7% of the total consented cases. These 393 cases came from 30 of 97 contributing ICUs (31%). The eastern region was ranked second, followed by the western region. The conversion rate for all regions followed a similar trend.

CONCLUSIONS

There is marked variation with regard to organ donation in different regions throughout Saudi Arabia, from 1.9% in the southern region to 76.7% in the central region. This finding is related to the presence of a Mobile Action Donor Team in the central region. The number of potential donors and the contributing ICUs were strong predictors of the number of actual donors. We suggest that having a mobile donor team in each region will increase the number of donors by at least 3 times within the next 3 to 5 years.

Patterns of folic acid use in pregnant Saudi women and prevalence of neural tube defects - Results from a nested case-control study

BACKGROUND

Although the role of folic acid (FA) in preventing neural tube defects (NTDs) is well documented, its optimal intake in pregnant women is still low in many countries. Here, we prospectively studied the prevalence of NTDs in the newborns and the patterns of FA intake in pregnant Saudi mothers.

METHODS

This case-control study was nested within a 3-year project (July 2010 to June 2013) to study the patterns of birth defects in the offspring of Saudi women who received their antenatal care and delivered at Prince Sultan Military Medical City, Riyadh-Saudi Arabia. Enrolled mothers were divided into 4 groups: group 1 (FA taken before pregnancy and continued regularly after conception), group 2 (FA taken post-conception), group 3 (no FA intake), and group 4 (did not remember or were unsure of taking FA). Control mothers were randomly selected from those with normal first obstetrical ultrasound scan at 18-22 weeks of gestation.

RESULTS

The cohort included 30,531 mothers giving birth to 28,646 infants. We studied 1179 mothers of babies with birth defects (BDs) and 1262 control mothers. There were 237 (9.7%) mothers in-group 1; 2001 (82%) in-group 2; 154 (6.3%) in-group 3; and 49 (2%) in-group 4. There were 49 babies with NTDs, a prevalence of 1.7/1000 total births. Among the studied mothers 2274 (93%) took FA either full or partial course.

CONCLUSION

The high prevalence of NTDs and the low optimal FA intake highlight the need for a strict implementation of staple food fortification and health education program for Saudi women.

High dose intravenous colistin methanesulfonate therapy is associated with high rates of nephrotoxicity; a prospective cohort study from Saudi Arabia

Background

Nephrotoxicity is an important adverse effect of colistin methanesulfonate (CMS) therapy. No data exist on rates and risk factors for colistin-related nephrotoxicity in Saudi Arabia (SA). We conducted a prospective cohort study to identify rates and risk factors for CMS nephrotoxicity in our patient population.

Methods

We prospectively included adult patients who received ≥48 hours of intravenous CMS therapy. Pregnant patients and those on renal replacement were excluded. Patients received 9 million units (mU) loading dose followed by 3 mU 8 hourly. In renal impairment, CMS dosing was adjusted according to calculated creatinine clearance (CrCl). Nephrotoxicity was defined as per RIFLE criteria (Risk, Injury, Failure, Loss and End-stage renal disease). Statistical analysis was performed using SPSS version 20.0 (IBM, Armonk, New York, USA). The study was approved by the institution’s Research Ethics Committee.

Results

A total of 67 patients were included in the study. Mean (±standard deviation) age was 57.5 (±24.0) years, Charlson Co-morbidity Score 2.88 (±2.39), CrCl 133.60 (±92.54) mL/min and serum albumin 28.65 (±4.45) g/L. Mean CMS dose was 0.11 (±0.04) mU/kg/day and mean total CMS dose received was 101.21 (±47.37) mU. Fifty-one (76.1%) patients developed RIFLE-defined nephrotoxicity. Mean total CMS dose and duration of therapy before onset of nephrotoxicity were 66.71 (±43.45) mU and 8.70 (±6.70) days, respectively. In bivariate analysis, patients with nephrotoxicity were significantly older (P 0.013) and had lower baseline serum albumin (P 0.008). Multivariate logistic regression identified serum albumin [odds ratio (OR) 0.72; 95% confidence interval (CI) 0.57–0.93; P 0.010] and intensive care admission (OR 16.38; 95% CI 1.37–195.55; P 0.027) as independent risk factors for CMS nephrotoxicity.

Conclusions

High dose intravenous CMS therapy is associated with high rates of nephrotoxicity in SA. Independent risk factors for colistin nephrotoxicity were baseline hypoalbuminemia and intensive care admission.

Effect of consanguinity on birth defects in Saudi women: results from a nested case-control study

BACKGROUND

The role of consanguinity in the etiology of structural birth defects outside of chromosomal and inherited disorders has always been debated. We studied the independent role of consanguinity on birth defects in Saudi women with a high prevalence of consanguineous marriages.

METHODS

This case and control study was nested within a 3-year prospective cohort study to examine patterns of fetal and neonatal malformations in Saudi women at Prince Sultan Military Medical City (PSMMC), Riyadh -Saudi Arabia. Consanguineous marriages were defined as marriages with first or second cousins (related); unions beyond second cousins (distant relatives) were considered unrelated for this study.

RESULTS

During the 3-year study (July 2010 through June 2013), there were 28,646 total births; of these, we included 1,179 babies with major birth defects, and 1,262 babies as their controls. The consanguinity prevalence for all included women was 49.6%. The consanguinity among babies with major Birth Defects (BDs) was 54.5% and 45.2% for controls (P < 0.0002). The prevalence of major birth defects was 41.1 per 1000 total births. Univariate analysis showed that consanguinity had a statistically significant contribution in babies born with genetic syndromes, isolated renal defects, and isolated other defects (P < 0.05). Multivariate logistic regression analyses showed that consanguinity was an independent risk factor for this high prevalence of birth defects in the study population (P < 0.0002).

CONCLUSION

The prevalence of major birth defects in the study population is higher than what is reported from European countries. Consanguinity is a significant independent risk factor for the high prevalence of birth defects.

Integrative and comparative genomics analysis of early hepatocellular carcinoma differentiated from liver regeneration in young and old

BACKGROUND

Hepatocellular carcinoma (HCC) is the third-leading cause of cancer-related deaths worldwide. It is often diagnosed at an advanced stage, and hence typically has a poor prognosis. To identify distinct molecular mechanisms for early HCC we developed a rat model of liver regeneration post-hepatectomy, as well as liver cells undergoing malignant transformation and compared them to normal liver using a microarray approach. Subsequently, we performed cross-species comparative analysis coupled with copy number alterations (CNA) of independent early human HCC microarray studies to facilitate the identification of critical regulatory modules conserved across species.

RESULTS

We identified 35 signature genes conserved across species, and shared among different types of early human HCCs. Over 70% of signature genes were cancer-related, and more than 50% of the conserved genes were mapped to human genomic CNA regions. Functional annotation revealed genes already implicated in HCC, as well as novel genes which were not previously reported in liver tumors. A subset of differentially expressed genes was validated using quantitative RT-PCR. Concordance was also confirmed for a significant number of genes and pathways in five independent validation microarray datasets. Our results indicated alterations in a number of cancer related pathways, including p53, p38 MAPK, ERK/MAPK, PI3K/AKT, and TGF-beta signaling pathways, and potential critical regulatory role of MYC, ERBB2, HNF4A, and SMAD3 for early HCC transformation.

CONCLUSIONS

The integrative analysis of transcriptional deregulation, genomic CNA and comparative cross species analysis brings new insights into the molecular profile of early hepatoma formation. This approach may lead to robust biomarkers for the detection of early human HCC.

Comparison of two dependent within subject coefficients of variation to evaluate the reproducibility of measurement devices

BACKGROUND

The within-subject coefficient of variation and intra-class correlation coefficient are commonly used to assess the reliability or reproducibility of interval-scale measurements. Comparison of reproducibility or reliability of measurement devices or methods on the same set of subjects comes down to comparison of dependent reliability or reproducibility parameters.

METHODS

In this paper, we develop several procedures for testing the equality of two dependent within-subject coefficients of variation computed from the same sample of subjects, which is, to the best of our knowledge, has not yet been dealt with in the statistical literature. The Wald test, the likelihood ratio, and the score tests are developed. A simple regression procedure based on results due to Pitman and Morgan is constructed. Furthermore we evaluate the statistical properties of these methods via extensive Monte Carlo simulations. The methodologies are illustrated on two data sets; the first are the microarray gene expressions measured by two plat- forms; the Affymetrix and the Amersham. Because microarray experiments produce expressions for a large number of genes, one would expect that the statistical tests to be asymptotically equivalent. To explore the behaviour of the tests in small or moderate sample sizes, we illustrated the methodologies on data from computer-aided tomographic scans of 50 patients.

RESULTS

It is shown that the relatively simple Wald's test (WT) is as powerful as the likelihood ratio test (LRT) and that both have consistently greater power than the score test. The regression test holds its empirical levels, and in some occasions is as powerful as the WT and the LRT.

CONCLUSION

A comparison between the reproducibility of two measuring instruments using the same set of subjects leads naturally to a comparison of two correlated indices. The presented methodology overcomes the difficulty noted by data analysts that dependence between datasets would confound any inferences one could make about the differences in measures of reliability and reproducibility. The statistical tests presented in this paper have good properties in terms of statistical power.

Copula based prediction models: an application to an aortic regurgitation study

BACKGROUND

An important issue in prediction modeling of multivariate data is the measure of dependence structure. The use of Pearson's correlation as a dependence measure has several pitfalls and hence application of regression prediction models based on this correlation may not be an appropriate methodology. As an alternative, a copula based methodology for prediction modeling and an algorithm to simulate data are proposed.

METHODS

The method consists of introducing copulas as an alternative to the correlation coefficient commonly used as a measure of dependence. An algorithm based on the marginal distributions of random variables is applied to construct the Archimedean copulas. Monte Carlo simulations are carried out to replicate datasets, estimate prediction model parameters and validate them using Lin's concordance measure.

RESULTS

We have carried out a correlation-based regression analysis on data from 20 patients aged 17-82 years on pre-operative and post-operative ejection fractions after surgery and estimated the prediction model: Post-operative ejection fraction = - 0.0658 + 0.8403 (Pre-operative ejection fraction); p = 0.0008; 95% confidence interval of the slope coefficient (0.3998, 1.2808). From the exploratory data analysis, it is noted that both the pre-operative and post-operative ejection fractions measurements have slight departures from symmetry and are skewed to the left. It is also noted that the measurements tend to be widely spread and have shorter tails compared to normal distribution. Therefore predictions made from the correlation-based model corresponding to the pre-operative ejection fraction measurements in the lower range may not be accurate. Further it is found that the best approximated marginal distributions of pre-operative and post-operative ejection fractions (using q-q plots) are gamma distributions. The copula based prediction model is estimated as: Post -operative ejection fraction = - 0.0933 + 0.8907 x (Pre-operative ejection fraction); p = 0.00008 ; 95% confidence interval for slope coefficient (0.4810, 1.3003). For both models differences in the predicted post-operative ejection fractions in the lower range of pre-operative ejection measurements are considerably different and prediction errors due to copula model are smaller. To validate the copula methodology we have re-sampled with replacement fifty independent bootstrap samples and have estimated concordance statistics 0.7722 (p = 0.0224) for the copula model and 0.7237 (p = 0.0604) for the correlation model. The predicted and observed measurements are concordant for both models. The estimates of accuracy components are 0.9233 and 0.8654 for copula and correlation models respectively.

CONCLUSION

Copula-based prediction modeling is demonstrated to be an appropriate alternative to the conventional correlation-based prediction modeling since the correlation-based prediction models are not appropriate to model the dependence in populations with asymmetrical tails. Proposed copula-based prediction model has been validated using the independent bootstrap samples.

Bivariate models for co-aggregation of dichotomous traits in twins

The study of twins is widely used for research into genetic and environmental influences on human traits. Study designs in which independent samples of monozygotic and dizygotic twins are compared with respect to their similarity have focused on single binary trait. However, the risk of co-occurrence of more than one disease in twins is a parameter of interest to genetic epidemiologists and other investigators. For example, they may be interested in assessing the genetic and environmental etiologies of reading deficits (RD) and attention deficit hyperactivity disorder (ADHD) and their co-morbidity. In this paper, we present statistical methodology for the estimation of twin similarity with respect to two dichotomous traits measured on each member of the twin pair. For two sample problems, several test procedures that account for the correlation between twins and the correlation between traits are presented. An example based on the Australian population-based twin registry published data is given to illustrate the methodology.

Interval estimation and optimal design for the within-subject coefficient of variation for continuous and binary variables

BACKGROUND

In this paper we propose the use of the within-subject coefficient of variation as an index of a measurement's reliability. For continuous variables and based on its maximum likelihood estimation we derive a variance-stabilizing transformation and discuss confidence interval construction within the framework of a one-way random effects model. We investigate sample size requirements for the within-subject coefficient of variation for continuous and binary variables.

METHODS

We investigate the validity of the approximate normal confidence interval by Monte Carlo simulations. In designing a reliability study, a crucial issue is the balance between the number of subjects to be recruited and the number of repeated measurements per subject. We discuss efficiency of estimation and cost considerations for the optimal allocation of the sample resources. The approach is illustrated by an example on Magnetic Resonance Imaging (MRI). We also discuss the issue of sample size estimation for dichotomous responses with two examples.

RESULTS

For the continuous variable we found that the variance stabilizing transformation improves the asymptotic coverage probabilities on the within-subject coefficient of variation for the continuous variable. The maximum like estimation and sample size estimation based on pre-specified width of confidence interval are novel contribution to the literature for the binary variable.

CONCLUSION

Using the sample size formulas, we hope to help clinical epidemiologists and practicing statisticians to efficiently design reliability studies using the within-subject coefficient of variation, whether the variable of interest is continuous or binary.

Segmentation of cDNA microarray spots using markov random field modeling

MOTIVATION

Spot segmentation is a critical step in microarray gene expression data analysis. Therefore, the performance of segmentation may substantially affect the results of subsequent stages of the analysis, such as the detection of differentially expressed genes. Several methods have been developed to segment microarray spots from the surrounding background. In this study, we have proposed a new approach based on Markov random field (MRF) modeling and tested its performance on simulated and real microarray images against a widely used segmentation method based on Mann-Whitney test adopted by QuantArray software (Boston, MA). Spot addressing was performed using QuantArray. We have also devised a simulation method to generate microarray images with realistic features. Such images can be used as gold standards for the purposes of testing and comparing different segmentation methods, and optimizing segmentation parameters.

RESULTS

Experiments on simulated and 14 actual microarray image sets show that the proposed MRF-based segmentation method can detect spot areas and estimate spot intensities with higher accuracy.

A temporal-spatial analysis of bovine spongiform encephalopathy in Irish cattle herds, from 1996 to 2000

This study investigated the distribution of bovine spongiform encephalopathy (BSE) in herds of cattle in Ireland over the years 1996 through 2000, prior to the introduction of widespread active surveillance. Mappings of index herds, herd density, and standardized morbidity ratios, by county, were employed to help visualize areas of potential clustering of BSE. The hypothesis of spatial clustering was tested using a spatial scan statistic applied to the location of the herd where exposure likely occurred. Both Bernoulli and Poisson spatial models indicated marked clustering of BSE herds centred on Monaghan county, with secondary clusters detected by Bernoulli approaches and some Poisson models in Wexford and Cork. The number of cases increased with time, but clear temporal-spatial clusters were rarely detected, except in the case of a cluster in Wexford. The focussed spatial scan analyses using the location of large-scale feed suppliers provided support for the hypothesis that clustering of BSE may be associated with feed source. The results of our analyses provided strong evidence in support of the hypothesis that herds, in which animals were most likely to have been exposed to the BSE agent, cluster geographically.

Assessment of reliability of microarray data and estimation of signal thresholds using mixture modeling

DNA microarray is an important tool for the study of gene activities but the resultant data consisting of thousands of points are error-prone. A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks. In this study, we describe an approach based on normal mixture modeling for determining optimal signal intensity thresholds to identify reliable measurements of the microarray elements and subsequently eliminate false expression ratios. We used univariate and bivariate mixture modeling to segregate the microarray data into two classes, low signal intensity and reliable signal intensity populations, and applied Bayesian decision theory to find the optimal signal thresholds. The bivariate analysis approach was found to be more accurate than the univariate approach; both approaches were superior to a conventional method when validated against a reference set of biological data that consisted of true and false gene expression data. Elimination of unreliable signal intensities in microarray data should contribute to the quality of microarray data including reproducibility and reliability of gene expression ratios.

Issues of Cost and Efficiency in the Design of Reliability Studies

Reliability of continuous and dichotomous responses is usually assessed by means of the intraclass correlation coefficient (ICC). We derive the optimal allocation of the number of subjects k and the number of repeated measurements n that minimize the variance of the estimated ICC. Cost constraints are discussed for the case of normally distributed responses. Tables showing optimal choices of k and n are given, along with guidelines for the design of reliability studies in light of our results and those reported by others.

Air emissions from sour-gas processing plants and dairy-cattle reproduction in Alberta, Canada

The dispersion of air pollutants from all 231 licensed sour-gas processing plants in Alberta, Canada, was modeled on a monthly basis over a 10-year period (1985-1994). Exposure estimates for sulfur dioxide (SO(2)-used as a surrogate for exposure to combusted emissions) then were assigned to 1382 provincial dairy farms using a geographical-information system. Individual average and peak exposure for periods prior to each of 15 months of age and conception (four exposure-averaging periods for each of two dispersion models) were estimated for 163,988 primiparous female dairy-cattle between 1986 and 1994. Monthly or annual average farm-site exposure estimates likewise were assigned to associated herd-level data sets for the biologically relevant period of interest for each of three additional reproductive outcomes: monthly herd-average calving interval, stillbirth risk, and twinning risk. In one of the main-effects models, the maximum (i.e., peak) monthly sour-gas exposure experienced by individual-animals from birth to conception was associated with an increased time to first-calving in the very-highest exposure category (hazard ratio=0.86, 95% CI=0.80, 0.92). This equates to a decreased hazard (lambda) of calving (in each month subsequent to 22 months of age) for the highest-exposure animals (lambda=0.170) versus the zero-exposure animals (lambda=0.198) in a model with referent values for agro-ecological region and season of birth. The dose-response was not consistent across the full range of exposure categories. There was significant (P=0.003) interaction of emissions with agro-ecological region. After accounting for the interaction, a more-consistent dose-response was evident for some (but not all) agro-ecological regions. This suggests that any effect of emissions on dairy-heifer reproduction is subject to modification by features of soil type, vegetative cover, and/or climate. The increase in monthly herd-average calving interval on farms exposed to the very-highest levels of emissions appeared quite small and of limited practical importance within the range of expected exposures. There was no association between exposure and the risk for twinning. Herds exposed to higher emissions exhibited a slight decrease in risk for stillbirth.

Associations between air emissions from sour gas processing plants and indices of cow retainment and survival in dairy herds in Alberta

This paper describes the results of an investigation into the effects of air emissions from sour gas processing plants on indices of retainment or survival of adult female dairy cattle on farms in Alberta; namely, the productive lifespan of individual animals, and annual herd-level risks for culling and mortality. Using a geographical information system, 2 dispersion models--1 simple and 1 complex--were used to assess historical exposures to sour gas emissions at 1382 dairy farm sites from 1985 through to 1994. Multivariable survival models, adjusting for the dependence of survival responses within a herd over time, as well as potential confounding variables, were utilized to determine associations between sour gas exposure estimates and the time from the first calving date to either death or culling of 150210 dairy cows. Generalized linear models were used to model the relationship between herd-level risks for culling and mortality and levels of sour gas exposure. No significant (P < 0.05) associations were found with the time to culling (n = 70052). However, both dispersion model exposure estimates were significantly associated (P < 0.05) with a decreased hazard for mortality; that is, in cases where cattle had died on-farm (n = 8743). There were no significant associations (P > 0.05) between herd culling risks and the 2 dispersion model exposure estimates. There was no measurable impact of plant emissions on the annual herd risk of mortality.

Efficiency considerations in the analysis of inter-observer agreement

The reliability of binary assessments is often measured by the proportion of agreement above chance, as estimated by the kappa statistic. In this paper, we develop a model to estimate inter-rater and intra-rater reliability when each of the two observers has the opportunity to obtain a pair of replicate measurements on each subject. The model is analogous to the nested beta-binomial model proposed by Rosner (1989, 1992). We show that the gain in precision obtained from increasing the number of measurements per rater from one to two may allow fewer subjects to be included in the study with no net loss in efficiency for estimating the inter-rater reliability.

Caffeine metabolism in premature infants

Caffeine has been used frequently in the treatment and prevention of apnea of prematurity. The metabolism of caffeine depends on the activities of the hepatic enzymes that vary from one infant to another. The objective of this study was to determine the influence of postnatal age (PNA), birth weight (BW), study weight (SW), gestational age (GA), postconceptual age (PCA), and gender on the maturation of caffeine metabolism in premature infants. The caffeine base was administered orally as a loading dose of 10 mg/kg, followed by a maintenance dose of 2 mg/kg every 24 hours. The steady-state concentration of caffeine and metabolites was measured in plasma taken on the 5th-day postloading dose. The molar concentration ratios for the N3 (N3-), N7 (N7-), N1 (N1-), and all methyl (Nall-) demethylation processes; clearance (CL); and the percentage of molar concentration of caffeine found in plasma to that of the total caffeine and metabolites (%CAF) were calculated from samples collected from 80 neonatal infants. The 48 male and 32 female premature infants had median (range) BW (g), GA (weeks), SW (g), PCA (weeks), and PNA (days) of 1300 (650-2260), 30 (24-34), 1630 (980-2670), 34 (29-40), and 28 (5-60), respectively. The median (range) of the ratios for the %CAF, CL, and the N3-, N7-, N1-, and Nall- were 86.9 (52.9-99.0), 0.127 (0.046-0.503) ml.kg-1.min-1, 0.032 (0-0.438), 0.070 (0.007-0.471), 0.026 (0-0.283), and 0.0463 (0.003-0.303), respectively. When the patients were stratified into four PNA age groups, each older group showed a consistently higher level of caffeine metabolic activity for the N3-, N7-, and Nall- pathways with a corresponding decrease in the %CAF, whereas no significant differences were seen for the N1-pathway or for CL. No pattern of significant differences between the demethylation process ratios, %CAF, or CL was seen between groups of infants when they were stratified according to BW, SW, PCA, or GA. The female infants were found to have significantly higher rates of caffeine metabolism as shown by %CAF, N1-, N3-, and Nall- processes but not the N7-. Multivariate linear regression analysis by two methods demonstrated that PNA is significantly related to %CAF and Nall-, whereas the female patients had higher levels of metabolic activity for the %CAF and N1- process. The authors conclude that the N7-demethy-lation process is the predominate caffeine metabolic process in premature infants. Furthermore, the maturation of the caffeine metabolism in premature infants with a PNA of less than 60 days increases with postnatal age, regardless of birth weight, gestational age, postconceptual age, and study weight. The female neonatal patients demonstrated a higher rate of caffeine metabolism than the males.

Testing the equality of two dependent kappa statistics

Procedures are developed and compared for testing the equality of two dependent kappa statistics in the case of two raters and a dichotomous outcome variable. Such problems may arise when each of a sample of subjects are rated under two distinct settings, and it is of interest to compare the observed levels of inter-observer and intra-observer agreement. The procedures compared are extensions of previously developed procedures for comparing kappa statistics computed from independent samples. The results of a Monte Carlo simulation show that adjusting for the dependency between samples tends to be worthwhile only if the between-setting correlation is comparable in magnitude to the within-setting correlations. In this case, a goodness-of-fit procedure that takes into account the dependency between samples is recommended.

An epidemiologic study of disease in 32 registered Holstein dairy herds in British Columbia

Data recorded in a herd health management system were obtained from 32 registered Holstein dairy herds from British Columbia. Frequencies of disease were described, and the effect of herd, age, year, season, and the interrelationships between diseases within a lactation on the occurrence of disease were evaluated. Lactational incidence rates were computed for diseases with a short period of risk (ie, udder edema, milk fever, retained placenta, metritis, displaced abomasum, and ketosis), whereas for diseases with a longer period of risk (ie, cystic ovaries, mastitis and stable footrot), incidence densities were calculated. Overall, the disease incidence was low and showed an increase in frequency by year, which we attributed to more observing and complete recording by the owner, rather than an actual increase in disease incidence. Most diseases occurred early in lactation and their frequency increased with lactation number; the exception was udder edema, which occurred mainly during the first 2 lactations. An informal path model of disease interrelationships was made conditional on herd. Based on the results we inferred 2 independent pathways: one started by udder edema, and the other by milk fever. Udder edema was directly associated with mastitis occurrence from 0 to 30 d in lactation, metritis, and cystic ovaries. Mastitis from 0-30 d in lactation increased the risk of both mastitis from 31-150 d in lactation and cystic ovaries. Both of these increased the risk of late lactation mastitis. Milk fever was directly related with displaced abomasum, which increased the risk of footrot. In general, diseases that occurred in early lactation tended to increase the risk of other diseases later in lactation.

Investigating potential risk factors for seasonal variation: an example using graphical and spectral analysis methods based on the production of milk components in dairy cattle

The objective of this study was to illustrate methods for investigating factors associated with seasonality, using milk-component production as an example. Milk-protein and fat percentages showed a seasonal pattern; percentages were lowest during June and July and highest in October and November. Graphical methods were used to compare herd calving patterns to seasonal production patterns and spectral analysis were used to compare seasonal production patterns between farm groups with different management practices. For the comparison of seasonality of production and herd calving patterns, data was obtained from archival records for all cows enrolled in Dairy Herd Improvement (DHI) milk recording in Ontario, Canada from 1990 to 1994. For comparisons of seasonality and management practices, monthly protein and fat percentages were obtained from the Dairy Farmers of Ontario from March 1985 to July 1994. Management information was obtained from responses to questionnaires completed by 364 dairy producers in Ontario. Graphical analyses provided a visualization of the relationship between herd calving patterns and seasonality of production-however, graphical methods alone did not allow statistical inferences to be made. Spectral analyses provided a formal statistical test of the null hypothesis of no association between an independent variable (farm management type) and seasonal production pattern in the data over time, provided that the outcome followed the same seasonal pattern regardless of covariate levels under the null hypothesis.

Repeatability of the Petrifilm HEC test and agreement with a hydrophobic grid membrane filtration method for the enumeration of Escherichia coli O157:H7 on beef carcasses

The Petrifilm HEC test (3M Canada Inc., London, Ontario), a quantitative microbiological test for Escherichia coli O157:H7, was evaluated for its performance as a beef-carcass monitoring test. Test repeatability and agreement and agreement with an E. coli O157:H7 detection method using a hydrophobic grid membrane filter (HGMF) overlaid onto cefixime-tellurite-sorbitol MacConkey agar (CT-SMAC) followed by a latex agglutination test for the O157 antigen were determined by using pure cultures of E. coli O157:H7, beef samples experimentally contaminated with bovine feces containing E. coli O157:H7, and naturally contaminated beef carcasses of unknown E. coli O157:H7 status from a local abattoir. The Petrifilm HEC test showed excellent repeatability and excellent agreement with the HGMF-CT-SMAC method when test samples were obtained from pure cultures and experimentally contaminated meat. All 125 naturally contaminated beef carcasses surveyed were negative for E. coli O157:H7 with both microbial methods. The Petrifilm HEC test, however, demonstrated a significantly lower proportion of cross-reactive organisms (false-positive reactions) than the HGMF-CT-SMAC method. Given the performance of this test coupled with its ease of use and compact size, it shows considerable promise for carcass testing where abattoir laboratory facilities are limited and as a substitute for more complex laboratory testing methods used in established laboratories.

A comparison of different models for assessing variations in the sero-prevalence of infectious bovine rhinotracheitis by farm, area and district in Kenya

The relative variability of the sero-prevalence of antibodies to infectious bovine rhinotracheitis (IBR) due to cow, farm, and agroecological area levels were investigated for three contrasting districts in Kenya: Samburu, an arid and pastoral area; Kiambu, a tropical highland area; and Kilifi, a typical tropical coastal area. Cattle were selected by two-stage cluster sampling and visited once between August 1991 and 1992. Data on animal, farm, and area factors were analyzed using Schall's algorithm and MLn (multi-level, n-level), two generalized mixed-model programs suitable for multi-level analysis. Most variation in IBR sero-prevalence was from farm-to-farm. This was reflected by the many farm-level fixed effects (farm size, disease control measures and type of breeding) significant in models both ignoring and accounting for single variance components (clustering) at farm, area, and district levels. Area-to-area and district-to-district variations were noted but the area and district variance components were one-third and one-fifth the size of the farm variance components for both methods. As farm-to-farm variation differed markedly by farm size and district, models in MLn were extended to allow for multiple farm-level variance components by these categories. For each, sero-prevalence of IBR increased with age and was significantly decreased on small-sized zero-grazing farms. These models, particularly the model with different farm variance components by districts, fit the data better and highlighted well that there was considerable farm-to-farm variation--differing by district--and that the available farm-level fixed effects did not predict IBR sero-prevalence well.

Statistical analysis of intraclass correlations from multiple samples with applications to arterial blood pressure data

We consider inference procedures on intraclass correlations for unbalanced data from several multivariate normal populations. We derive several tests, including ones based on Fisher's variance stabilizing transformation and Neyman's score functions, to test the homogeneity of intraclass correlations. We illustrate the methodology with an example that uses arterial blood pressure data collected by Miall and Oldham and we compare the procedures in terms of their empirical levels and powers with a Monte Carlo simulation study. We recommend the use of Neyman's C(alpha) test and a test based on the ANOVA estimators of the intraclass correlations as they hold their significance levels and give consistently higher powers.

The association between the bovine tuberculosis status of herds in the East Offaly Project Area, and the distance to badger setts, 1988-1993

The proximity of farms to badger setts was compared between farms that had experienced a tuberculosis breakdown and those that had not, over the 6 year period from 1988 to 1993. The data were derived from a badger removal study conducted in East Offaly County in the Republic of Ireland. Badger removal began in 1989 and continued through 1993; by the end of 1990, approximately 80% of all badgers caught in the 6 year period had been removed. All badgers were examined, grossly, for evidence of tuberculosis. Tuberculosis status of the approximately 900 study herds was based on the results of the single intradermal comparative skin test and/or lesions of bovine tuberculosis. All herds were tested at least once annually. The number of herds experiencing bovine tuberculosis declined over the period, particularly in the years 1992 and 1993. The data on farm and badger sett location were stored and analysed, initially, in a geographical information system. Owing to the badger removal programme, the distance between the barn yard of a typical farm and the nearest occupied badger sett increased, by about 300 m year-1, and by about 600 m year-1 to the closest infected sett. In bivariate analyses, in the years 1988 and 1989, the risk of tuberculosis declined with increasing distance to a badger sett containing one or more tuberculous badgers. In multivariable logistic regression analyses, year and the average number of cattle tested per farm per year were controlled. A second identical analysis was conducted to control for the repeated observations on the same herds using generalised estimating equations. In both analyses, the risk of a multiple reactor tuberculosis breakdown decreased for herds at least 1000 m away from an infected badger sett, and increased as the number of infected badgers per infected sett increased. Despite the significantly reduced risk of a breakdown with increasing distance to infected badger setts, the relationship was not strong (sensitivity and specificity of the model in the low 70% range) and explained only 9-19% of tuberculosis breakdowns.

Calf health in cow-calf herds in Switzerland

In 1993, an observational study was initiated to provide general information on animal health in extensive beef farms, to estimate disease frequency and the economic impact of calf diseases and to identify risk factors related to health and weight gain. The longitudinal study was conducted from fall 1993 until winter 94/95 and included 100 farms in western Switzerland. The basic concept was to follow one generation of calves on these farms and record all events concerning animal health from birth to weaning. The study population included 1270 calves (most were Angus crossbreds). Farm-management data were collected with a questionnaire conducted on the farm. Birth and weaning weights were obtained from the beef cattle breeding association. Clinical diagnoses and treatment costs were provided by the farm veterinarians. Two thirds of the dead calves were submitted to a complete postmortem examination. Fifty-three percent of the farms in the study were primary type income farms while 47% were secondary type income farms. Thirty-eight percent of the farms were situated in the lower areas of Switzerland, 14% in the prealpine foothills, the remaining 48% were located in mountain areas. Preweaning calf mortality was 5%. The main causes of calf deaths were respiratory diseases and digestive disorders. Twenty-two percent of the calves were treated at least once by a veterinarian; 36% of the treatments administered by the veterinarian were applied because of diarrhea, 27% because of respiratory diseases. Disease incidence was highest during the months of November, December and January. The association of disease and potential farm-level risk factors was analysed using chi 2-statistics and multivariable regression methods including generalized estimating equations to adjusted for herd effects. Specific risk factors for disease were not identified. Treatment for disease was not associated with 250-day standardized weight gain.

Variations in the prevalence of antibody to brucella infection in cattle by farm, area and district in Kenya

Variations in the sero-prevalence of antibody to brucella infection by cow, farm and area factors were investigated for three contrasting districts in Kenya: Samburu, an arid and pastoral area: Kiambu, a tropical highland area; and Kilifi, a typical tropical coastal area. Cattle were selected by a two-stage cluster sampling procedure and visited once between August 1991 and 1992. Schall's algorithm, a statistical model suitable for multi-level analysis was used. Using this model, older age, free grazing and large herd size (> or = 31) were associated with higher seroprevalence. Also, significant farm-to-farm, area-to-area and district-to-district variations were estimated. The patterns of high risk districts and areas seen were consistent with known animal husbandry and movement risk factors, but the larger than expected farm-to-farm variation within high risk areas and districts could not be explained. Thus, a multi-level method provided additional information beyond conventional analyses of sero-prevalence data.

Assessing infections at multiple levels of aggregation

The patterns of sero-prevalence of antibodies to four infectious diseases, representing a broad range of pathogens (bacteria: brucellosis; mycoplasma: contagious bovine pleuropneumonia; viruses: infectious bovine rhinotracheitis; protozoa: trypanosomosis) were investigated at three levels of organization (farm, area and district). Three contrasting districts in Kenya were compared: an arid and pastoral area (Samburu); a tropical highland area (Kiambu), and a tropical coastal area (Kilifi). Cattle in three districts were selected by two-stage cluster sampling between August 1991 and 1992. Schall's algorithm, a generalized linear mixed model suitable for multi-level analysis, was compared to ordinary logistic regression (OLR), which ignores clustering of responses; generalized estimating equations (GEE) or Jacknife, to account for clustering at the farm level; SAS VARCOMP, which provides normal-theory random-effects models. Schall's algorithm provided similar estimates to GEE (regression effects) and Jackknife (standard errors) for farm-level clustered data. Extending Schall's procedure for additional district and area-within-district random effects usually provided additional information. In general, models that included only a farm-level random effect consistently provided larger estimates of farms' variance components than did models with additional district and area random effects. The four type diseases exhibited various amounts of clustering. Brucellosis had moderate farm clustering plus some area and district clustering. Contagious bovine pleuropneumonia had only a small amount of clustering, mostly by area. Infectious bovine rhinotracheitis exhibited a large amount of clustering, primarily at the farm level. Trypanosomiasis antibody prevalence varied by district, area and farm. We believe that patterns of disease clustering identified by multi-level analysis can be used to better target high-risk units for disease control and guide research to understand disease transmission factors.

Maximum likelihood estimation of the kappa coefficient from bivariate logistic regression

We propose a maximum likelihood estimator (MLE) of the kappa coefficient from a 2 x 2 table when the binary ratings depend on patient and/or clinician effects. We achieve this by expressing the logit of the probability of positive rating as a linear function of the subject-specific and the rater-specific covariates. We investigate the bias and variance of the MLE in small and moderate size samples through Monte Carlo simulation and we provide the sample size calculation to detect departure from the null hypothesis H0: kappa = kappa 0 in the direction of H1: kappa > kappa 0.

Maximum likelihood estimation of the kappa coefficient from models of matched binary responses

We present an estimate of the kappa-coefficient of agreement between two methods of rating based on matched pairs of binary responses and show that the estimate depends on the common intraclass correlation coefficient between the pairs. Via Monte Carlo simulation, we investigate power of the test of significance on kappa, and the large sample bias and variance of its maximum likelihood estimator.

Parametric estimation in a genetic mixture model with application to nuclear family data

The apparent conflict between the biometrician and Mendelian genetics has been recently resolved by the introduction of a genetic mixed model to analyze continuous traits measured on human families and to elucidate the mechanism of underlying major genes. The mixed model formulated by Elston and Stewart (1971, Human Heredity 21, 523-542), extended by Morton and MacLean (1974, American Journal of Human Genetics 26, 489-503), and reviewed, with further extensions, by Boyle and Elston (1979, Biometrics 35, 55-68) has become an extremely useful tool of wide applicability in the field of genetic epidemiology. This model allows for segregation at a major locus, a polygenic effect, and a sibling environmental variation. The main concern of this paper is with estimating the model parameters by the method of maximum likelihood. The expectation-maximization (EM) algorithm is developed to derive the estimates iteratively. An approximation of the information matrix when using the EM algorithm is given. We illustrate the methodology by fitting the model to the arterial blood pressure data collected by Miall and Oldham (1955, Clinical Science 14, 459-487).

Statistical testing of genetic linkage under heterogeneity

Recent advances in human genetics have led to a renewed interest in statistical methods for the detection of linkage from family data--for example, between marker loci and disease traits. Statistical analysis of linkage between two loci is carried out almost exclusively by means of the lod (log-odds) score test, equivalent to a likelihood ratio test. The current practice is to declare genetic linkage between loci when the maximum lod score exceeds 3. As will be discussed here, the lod-score approach is not appropriate for the detection of linkage from heterogeneous data, e.g., when families consist of a mixture of linked and unlinked types. Heterogeneity may arise, for example, when rare mutations at different genetic loci are responsible for the same disease trait. As an alternative approach to account for possible heterogeneity in the detection of linkage, we propose the application of large-sample test statistics that are members of Neyman's class of C(alpha), or partial score tests. The convergence of the proposed test statistics to their asymptotic distributions is investigated via Monte Carlo simulation for typical study designs applicable in human genetics.

Estimating the number of clusters for the analysis of correlated binary response variables from unbalanced data

Dominating the literature on sample size determination are papers concerned with observations collected from independent responses. We discuss in this paper, under the common correlation model for binary responses, the issue of estimating the number of groups when the sampling units are clusters of variable sizes.