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.

Use of beta blockers is associated with hearing loss.

OBJECTIVE: This study was conducted to investigate the hypothesis that patients using ß-blockers will develop hearing loss. DESIGN: A cross-sectional study. STUDY SAMPLE: A total of 125 patients completed the study. A total of 63 patients were on ß-blockers and 62 were not on ß-blockers. RESULTS: Carvedilol was significantly associated with hearing loss. Other beta-blockers including metoprolol and atenolol showed no association with hearing loss. Linear multiple regression analysis was run including variables of gender, age, ischaemic heart disease, cardiac failure/dilated cardiomyopathy, frusemide and carvedilol use as predictors for total hearing loss severity at all frequencies. Age and gender, as well as carvedilol, were found to be the only statistically significant predictors for hearing loss severity. CONCLUSION: Chronic use of carvedilol was associated with significant hearing loss. This may need to be taken into account when prescribing the drug. Further randomised controlled studies with baseline audiometric hearing tests before starting treatment, and periodic follow-up tests, would provide a better assessment of the effect of carvedilol on hearing.

Genetic Predisposition to Cervical Cancer and the Association With XRCC1 and TGFB1 Polymorphisms.

OBJECTIVE: Cervical carcinoma (CC), a multifactorial cancer, is assumed to have a host genetic predisposition component that modulates its susceptibility in various populations. We investigated the association between CC risk in Saudi women and 6 single-nucleotide polymorphisms (SNPs) in hypothesis-driven candidate genes. METHODS: A total of 545 females were included, comprising 232 CC patients and 313 age-/sex-matched control subjects. Six SNPs (CDKN1A C31A, ATM G1853A, HDM2 T309G, TGFB1 T10C, XRCC1 G399A, and XRCC3 C241T) were genotyped by direct sequencing. RESULTS: Of the 6 SNPs studied, TGFB1 T10C (odds ratio, 0.74; 95% confidence interval, 0.57-0.94) and XRCC1 G399A (odds ratio, 1.45; 95% confidence interval, 1.11-1.90) displayed different frequencies in cancer patients and control subjects and showed statistically significant association in univariate (P = 0.017, P = 0.005, respectively) analysis. The Cochran-Armitage trend test had confirmed the results (P = 0.027 and P = 0.006, respectively), indicating an ordering in the effect of the risk alleles in CC patients. The 2 SNPs, TGFB1 T10C and XRCC1 G399A, showed also degrees of deviation from Hardy-Weinberg equilibrium in cancer patients (P = 0.001 and P = 0.083, respectively) but not in the control subjects. Furthermore, correction for multiple testing using multivariate logistic regression to assess the joint effect of all SNPs has sustained significant statistical association (P = 0.025 and P = 0.009, respectively). CONCLUSIONS: TGFB1 T10C and XRCC1 G399A SNPs were associated with CC risk in univariate and multivariate analysis and displayed allele-dosage effects and coselection in cancer patients. Patients harboring the majority allele TGFB1 T10 (Leu) or the variant allele XRCC1 399A (Gln) have approximately 1.5-fold increased risk to develop CC. Host SNPs genotyping may provide relevant biomarkers for CC risk assessment in personalized preventive medicine.

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 American Cancer Society.

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.

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.

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.

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.

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.

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.

Human papillomaviruses in cervical specimens of women residing in Riyadh, Saudi Arabia: a hospital-based study.

INTRODUCTION: Certain genotypes of human papillomavirus (HPV) are linked to cervical abnormalities. HPV DNA and genotype prevalence among women residing in Riyadh, Saudi Arabia is investigated in this hospital-based study. METHODOLOGY: Cervical specimens were taken from 519 subjects along with consent and demographic data. DNA was extracted and PCR was performed on all specimens using general primers. Low- and high-risk HPV genotypes were determined by reverse blot hybridization assay using specific probes. SPSS version 17 was used for the data analysis. RESULTS: Of 519 cervical specimens, 164 (31.6%) were positive for HPV DNA. There was a significant association between HPV positivity and abnormal cytology (p < 0.00001). Even though the HPV positivity was relatively high, the squamous intraepithelial lesions were minimal, with one low grade and one high grade case among those HPV DNA-positive specimens. Regardless of single or multiple infections per specimen, HPV-16 was found in 87.8%, followed by HPV-18 in 86%, and HPV-11 in 78.3%. CONCLUSIONS: Amplification technology showed that HPV is common among women in Riyadh, Saudi Arabia, with a strong association between HPV infection and cytological changes. HPV-16 was the most frequent genotype but had a low prevalence of cervical cancer.

Covariate-adjusted confidence interval for the intraclass correlation coefficient.

A crucial step in designing a new study is to estimate the required sample size. For a design involving cluster sampling, the appropriate sample size depends on the so-called design effect, which is a function of the average cluster size and the intracluster correlation coefficient (ICC). It is well-known that under the framework of hierarchical and generalized linear models, a reduction in residual error may be achieved by including risk factors as covariates. In this paper we show that the covariate design, indicating whether the covariates are measured at the cluster level or at the within-cluster subject level affects the estimation of the ICC, and hence the design effect. Therefore, the distinction between these two types of covariates should be made at the design stage. In this paper we use the nested-bootstrap method to assess the accuracy of the estimated ICC for continuous and binary response variables under different covariate structures. The codes of two SAS macros are made available by the authors for interested readers to facilitate the construction of confidence intervals for the ICC. Moreover, using Monte Carlo simulations we evaluate the relative efficiency of the estimators and evaluate the accuracy of the coverage probabilities of a 95% confidence interval on the population ICC. The methodology is illustrated using a published data set of blood pressure measurements taken on family members.

Measures of family resemblance for binary traits: likelihood based inference.

Detection and estimation of measures of familial aggregation is considered the first step to establish whether a certain disease has genetic component. Such measures are usually estimated from observational studies on siblings, parent-offspring, extended pedigrees or twins. When the trait of interest is quantitative (e.g. Blood pressures, body mass index, blood glucose levels, etc.) efficient likelihood estimation of such measures is feasible under the assumption of multivariate normality of the distributions of the traits. In this case the intra-class and inter-class correlations are used to assess the similarities among family members. When the trail is measured on the binary scale, we establish a full likelihood inference on such measures among siblings, parents, and parent-offspring. We illustrate the methodology on nuclear family data where the trait is the presence or absence of hypertension.

Likelihood inference on the relative risk in split-cluster designs.

BACKGROUND: Split-cluster experiments are being used by investigators in health sciences when naturally occurring aggregate of individuals with nested sub-groups may be assigned to different treatments. Cited examples include the split-mouth trials, in which a subject's mouth is divided into two segments that are randomly assigned to different treatment groups. In other situation, randomization to treatment conditions may be possible at the person level within the cluster. In this case, when the treatment conditions are available within each cluster, the design is referred to as a multisite or split-cluster design (SCD). The major attractiveness of this design is that it removes a large portion of the inter-subject variation from the estimates of the treatment effect; hence, it has the potential to require lesser number of measurements than a parallel arm design with the same power. When the response variable of interest is binary, statistical methods developed to evaluate the effect of interventions depended on nonparametric methods. Though these methods are simple to apply, they are known to be less efficient. METHODS: Taking the relative risk (RR) as an effect measure, we construct a bivariate-correlated model under which a score test is applied to test H(0): RR = 1.0. Moreover, we construct Wald- and Fieller-based confidence intervals on RR. Since the efficiency of SCD increases when the interclass correlation coefficient (ρ12) is high, we present a goodness-of-fit procedure for testing H(0):ρ12 = 0, which may be helpful in choosing a design for a future study. RESULTS: For illustrating the proposed methodology, we consider two application data from the published literature; the first from a split-mouth trial on 23 patients evaluating the effect of chlorhexidine in the treatment of gingivitis, and second from study of mental health (depression and anxiety) as outcome measure obtained on 173 patients evaluated by two screening instruments. Moreover, we discussed the efficiency gained using our approach in these design settings. LIMITATIONS: The likelihood approach makes more assumptions as compared to previous approaches that have been described. CONCLUSIONS: We have developed a bivariate beta-binomial model, from which we can conduct a full likelihood statistical inference. Based on this model, we may construct Wald's confidence intervals and score tests, which are known to possess optimal statistical properties. For the purpose of comparison with nonparametric methods, we constructed the Fieller's confidence interval.

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.

Estimation of modified concordance ratio in sib-pairs: effect of consanguinity on the risk of congenital heart diseases.

Family studies are widely used for research into genetic and environmental influences on human traits. In this paper, we establish statistical methodology for the estimation of a new measure of sib similarity with respect to dichotomous traits measured on each member of within family sib-pair. We call this parameter "excess risk." For inference problems involving a single sample, we construct a large sample confidence interval on the concerned parameter. It has long been suspected that consanguinity is a risk factor for many genetic defects. Therefore, we establish a procedure to test the significance of the difference between excess risk parameters in a sample of consanguineous marriages and another sample of non-consanguineous marriages. We apply the methodology to data from a hospital-based congenital heart defects registry in Saudi Arabia, a population in which consanguinity is quite common.

Bivariate modeling of interobserver agreement coefficients.

Many studies of interobserver agreement yield outcome measures on more than one binary trait. For example, Becker et al. (Int. J. Psychiatry Med. 2002; 32(3):271-283) reported on a study of depression and anxiety as two outcome measures obtained on 173 patients evaluated by two screening instruments, the first using a Patient Health Questionnaire and the second employing a Structured Clinical Interview. In this case, although inferences on each trait separately are usually of main interest, a question that also arises is whether or not the level of interobserver agreement can be regarded as stable across the two traits. In this paper, we develop the required methodology and provide an illustrative example.

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.

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.