N-of-1 (single-patient) trials for statin-related myalgia.

BACKGROUND: Statin-related myalgia is difficult to distinguish from other conditions causing myalgia and may often lead to statin discontinuation. OBJECTIVE: To compare the effect of statin rechallenge with placebo in patients with prior statin-related myalgia and to determine whether patients resumed statin therapy after evaluating the results. DESIGN: N-of-1 trial with 3 double-blind, crossover comparisons separated by 3-week washout periods. (Clinicaltrials.gov: NCT01259791) SETTING: Tertiary care lipid clinic. PATIENTS: Patients with prior statin-related myalgia with or without mild elevation of creatine kinase levels. INTERVENTION: Rechallenge with the statin that was previously associated with myalgia within 3 weeks of open-label use versus matching placebo. MEASUREMENTS: Weekly visual analogue scale (VAS) scores for myalgia and specific symptoms (VAS myalgia score and symptom-specific VAS score, respectively), pain interference scores, and pain severity scores were recorded during the 3-week periods when patients were receiving placebo or statin. The primary outcome was the VAS myalgia score (range, 0 to 100 mm). RESULTS: Eight patients (mean age, 66 years [SD, 8 years]; 88% women, all with high 10-year Framingham cardiovascular risk) participated in n-of-1 trials. Seven patients completed 3 treatment pairs, and 1 completed 2 treatment pairs. For each n-of-1 trial, no statistically significant differences were seen between statin and placebo in the VAS myalgia score, symptom-specific VAS score, pain interference score, and pain severity score. Five patients resumed open-label statin treatment, with a median posttrial follow-up of 10 months. LIMITATION: Results are limited by the small sample size and cannot be extended to patients with longer onset of myalgia after statin initiation. CONCLUSION: In selected patients with a history of statin-related myalgia whose symptoms are difficult to evaluate, n-of-1 trials may be a useful method for determining statin tolerability. PRIMARY FUNDING SOURCE: Western University, London, Ontario, Canada.

Simultaneous confidence intervals of risk differences in stratified paired designs.

In stratified matched-pair studies, risk difference between two proportions is one of the most frequently used indices in comparing efficiency between two treatments or diagnostic tests. This article presents five simultaneous confidence intervals and two bootstrap simultaneous confidence intervals for risk differences in stratified matched-pair designs. The proposed confidence intervals are evaluated with respect to their coverage probabilities, expected widths, and ratios of the mesial noncoverage to noncoverage probability. Empirical results show that (1) hybrid simultaneous confidence intervals outperform nonhybrid simultaneous confidence intervals; (2) hybrid simultaneous confidence intervals based on median estimator outperform those based on maximum likelihood estimator; and (3) hybrid simultaneous confidence intervals incorporated with Wilson score and Agresti coull intervals and the bootstrap t-percentile simultaneous interval based on median unbiased estimators behave satisfactorily for small to large sample sizes in the sense that their empirical coverage probabilities are close to the prespecified nominal confidence level, and their ratios of the mesial noncoverage to noncoverage probabilities lie in [0.4,0.6] and are hence recommended. Real examples from clinical studies are used to illustrate the proposed methodologies.

A polygenic basis for four classical Fredrickson hyperlipoproteinemia phenotypes that are characterized by hypertriglyceridemia.

Numerous single nucleotide polymorphisms (SNPs) have been found in recent genome wide association studies (GWAS) to be associated with subtle plasma triglyceride (TG) variation in normolipidemic subjects. However, since these GWAS did not specifically evaluate patients with rare disorders of lipoprotein metabolism--'hyperlipoproteinemia' (HLP)--it remains largely unresolved whether any of these SNP determinants of modest physiological changes in TG are necessarily also determinants of most HLP phenotypes. To address this question, we evaluated 28 TG-associated SNPs from GWAS in 386 unrelated adult patients with one of five Fredrickson phenotypes (HLP types 2A, 2B, 3, 4 and 5) and 242 matched normolipidemic controls. We found that several SNPs associated with TG in normolipidemic samples, including APOA5 p.S19W and -1131T>C, TRIB1 rs17321515, TBL2 rs17145738, GCKR rs780094, GALNT2 rs4846914 and ANGPTL3 rs12130333, were significantly associated with HLP types 2B, 3, 4 and 5. The findings indicate that: (i) the TG-associated Fredrickson HLP types 2B, 3, 4 and 5 are polygenic traits; (ii) these Fredrickson HLP types share numerous genetic determinants among themselves; and (iii) genetic determinants of modest TG variation in normolipidemic population samples also underlie--to an apparently even greater degree--susceptibility to these rare HLP phenotypes. Thus, the TG-associated Fredrickson HLP types 2B, 3, 4 and 5, although historically considered to be distinct are actually complex traits sharing among them several common genetic determinants seen in GWAS of normolipidemic population samples.

STrengthening the REporting of Genetic Association Studies (STREGA)--an extension of the STROBE statement.

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Polygenic determinants of severe hypertriglyceridemia.

Recent genome-wide association (GWA) studies have identified new genetic determinants of complex quantitative traits, including plasma triglyceride (TG). We hypothesized that common variants associated with mild TG variation identified in GWA studies would also be associated with severe hypertriglyceridemia (HTG). We studied 132 patients of European ancestry with severe HTG (fasting plasma TG > 10 mmol/l), who had no mutations found by resequencing of candidate genes, and 351 matched normolipidemic controls. We determined genotypes for: GALNT2 rs4846914, TBL2/MLXIPL rs17145738, TRIB1 rs17321515, ANGPTL3 rs12130333, GCKR rs780094, APOA5 rs3135506 (S19W), APOA5 rs662799 (-1131T > C), APOE (isoforms) and LPL rs328 (S447X). We found that: (i) genotypes, including those of APOA5 S19W, APOA5 -1131T > C, APOE, GCKR, TRIB1 and TBL2/MLXIPL, were significantly associated with severe HTG; (ii) odds ratios for these genetic variables were significant in both univariate and multivariate regression analyses, irrespective of the presence or absence of diabetes or obesity; (iii) a significant fraction-about one-quarter-of the explained variation in disease status was associated with these genotypes. Therefore, common SNPs (single nucleotide polymorphisms) that are associated with mild TG variation in GWA studies of normolipidemic subjects are also associated with severe HTG. Our findings are consistent with the emerging model of a complex genetic trait. At the extremes of a quantitative trait, such as severe HTG, are found the cumulative contributions of both multiple rare alleles with large genetic effects and common alleles with small effects.

STrengthening the REporting of Genetic Association studies (STREGA): an extension of the STROBE Statement.

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information into the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and issues of data volume that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association Studies (STREGA): an extension of the STROBE statement.

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE Statement.

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

STrengthening the REporting of Genetic Association studies (STREGA)--an extension of the STROBE statement.

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the STrengthening the Reporting of OBservational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct or analysis.

Strengthening the reporting of genetic association studies (STREGA): an extension of the STROBE statement.

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.

On the estimation of additive interaction by use of the four-by-two table and beyond.

A four-by-two table with its four rows representing the presence and absence of gene and environmental factors has been suggested as the fundamental unit in the assessment of gene-environment interaction. For such a table to be more meaningful from a public health perspective, it is important to estimate additive interaction. A confidence interval procedure proposed by Hosmer and Lemeshow has become widespread. This article first reveals that the Hosmer-Lemeshow procedure makes an assumption that confidence intervals for risk ratios are symmetric and then presents an alternative that uses the conventional asymmetric intervals for risk ratios to set confidence limits for measures of additive interaction. For the four-by-two table, the calculation involved requires no statistical programs but only elementary calculations. Simulation results demonstrate that this new approach can perform almost as well as the bootstrap. Corresponding calculations in more complicated situations can be simplified by use of routine output from multiple regression programs. The approach is illustrated with three examples. A Microsoft Excel spreadsheet and SAS codes for the calculations are available from the author and the Journal's website, respectively.

Prediction of preterm birth in symptomatic women using decision tree modeling for biomarkers.

OBJECTIVE: The objective of the study was to use recursive partitioning (RP) to identify gestational age-specific and threshold values for infectious and endocrine biomarkers of imminent delivery. STUDY DESIGN: RP was developed using a previously collected data set and then applied to a prospectively collected cohort of women in threatened preterm labor. Predictors of preterm birth were considered, including white blood cell count (WBC), corticotrophin-releasing hormone (CRH), cortisol, and maternal age. RESULTS: At 22-27 weeks' gestation, WBC of greater than 12,000/mL was the most accurate predictor of delivery within 48 hours; at 28-31 weeks' gestation, CRH of greater than 684 pg/mL was the most accurate predictor; and at 32-26 weeks' gestation, CRH and maternal age were the most important variables. CONCLUSIONS: These results indicate that maternal WBC greater than 12,000/mL prior to 28 weeks' gestation and CRH beyond 28 weeks are the most accurate biomarkers in predicting preterm birth within 48 hours. RP assists in establishing clinically relevant and gestational age-specific threshold levels for these variables.

Assessing severity of epilepsy in children: preliminary evidence of validity and reliability of a single-item scale.

The development and initial validity and reliability testing of a single-item, 7-point global rating scale designed for neurologists to assess the overall severity of epilepsy in children, the Global Assessment of Severity of Epilepsy (GASE) Scale, is described. The GASE Scale was quick and easy to use. Median epilepsy severity in the development sample was 3 (moderately severe), with a range from 1 ("not severe at all") in 36 patients (26.9%) to 7 ("extremely severe") in 7 patients (5.2%). Preliminary evidence of construct validity was found in support for our a priori predictions of associations between GASE scores and neurologists' ratings of seven individual clinical aspects of epilepsy and in a cumulative R(2) for the GASE score of 81% using ratings of the clinical aspects of epilepsy. Weighted kappa was 0.85 (95% CI: 0.79, 0.90) for inter-rater reliability and 0.90 (95% CI: 0.82, 0.98) and 0.95 (95% CI: 0.91, 0.98) for test-retest reliability for each of two raters. These promising initial results support continuation of the multistage process of testing the validity and reliability of the GASE Scale within various clinical contexts.

Omega-3 free fatty acids for the maintenance of remission in Crohn disease: the EPIC Randomized Controlled Trials.

CONTEXT: Maintenance therapy for Crohn disease features the use of immunosuppressive drugs, which are associated with an increased risk of infection. Identification of safe and effective maintenance strategies is a priority. OBJECTIVE: To determine whether the oral administration of omega-3 free fatty acids is more effective than placebo for prevention of relapse of Crohn disease. DESIGN, SETTING, AND PATIENTS: Two randomized, double-blind, placebo-controlled studies (Epanova Program in Crohn's Study 1 [EPIC-1] and EPIC-2) conducted between January 2003 and February 2007 at 98 centers in Canada, Europe, Israel, and the United States. Data from 363 and 375 patients with quiescent Crohn disease were evaluated in EPIC-1 and EPIC-2, respectively. INTERVENTIONS: Patients with a Crohn's Disease Activity Index (CDAI) score of less than 150 were randomly assigned to receive either 4 g/d of omega-3 free fatty acids or placebo for up to 58 weeks. No other treatments for Crohn disease were permitted. MAIN OUTCOME MEASURE: Clinical relapse, as defined by a CDAI score of 150 points or greater and an increase of more than 70 points from the baseline value, or initiation of treatment for active Crohn disease. RESULTS: For EPIC-1, 188 patients were assigned to receive omega-3 free fatty acids and 186 patients to receive placebo. Corresponding numbers for EPIC-2 were 189 and 190 patients, respectively. The rate of relapse at 1 year in EPIC-1 was 31.6% in patients who received omega-3 free fatty acids and 35.7% in those who received placebo (hazard ratio, 0.82; 95% confidence interval, 0.51-1.19; P = .30). Corresponding values for EPIC-2 were 47.8% and 48.8% (hazard ratio, 0.90; 95% confidence interval, 0.67-1.21; P = .48). Serious adverse events were uncommon and mostly related to Crohn disease. CONCLUSION: In these trials, treatment with omega-3 free fatty acids was not effective for the prevention of relapse in Crohn disease. TRIAL REGISTRATION: clinicaltrials.gov Identifiers: EPIC-1: NCT00613197, EPIC-2: NCT00074542.

Implementation of the Canadian Neurological Scale on an acute care neuroscience unit: a program evaluation.

The Canadian Neurological Scale (CNS), a validated stroke assessment tool, was implemented for the neurological assessment of patients with stroke. The purpose of this study was to explore nurses' values and perceptions of best-practice guidelines (BPGs) and the CNS assessment, to evaluate the effect of a workshop and implementation process on nurses' self-efficacy for CNS use, to determine whether the workshop and implementation process met the needs of the nurses, and to evaluate the accuracy and appropriateness of CNS assessment documentation. Nurses reported moderate-to-strong awareness and use of BPGs and expressed the belief that BPGs were valuable; however, they had some difficulty accessing BPGs. At 3 months after the workshop, nurses reported using the CNS assessment in practice but said that it was not easy to use and that it was not useful as a patient status communication tool or for documenting neurological changes. Nurses were moderately confident while performing the CNS assessment before the workshop. Confidence increased immediately afterward (p < .0001), and then decreased slightly at 3 months. The majority of nurses said the workshop met their learning needs. A chart audit demonstrated that only 69% of patients appropriate for the CNS assessment were assessed with this tool. Although nurses are aware of BPGs, translating these changes into practice takes time and may require BPG modification to best fit the needs of the areas in which they will be used. When choosing a validated stroke assessment tool, clinicians must consider how often the tool will be used for assessments, particularly in the acute phase.

Toward using confidence intervals to compare correlations.

Confidence intervals are widely accepted as a preferred way to present study results. They encompass significance tests and provide an estimate of the magnitude of the effect. However, comparisons of correlations still rely heavily on significance testing. The persistence of this practice is caused primarily by the lack of simple yet accurate procedures that can maintain coverage at the nominal level in a nonlopsided manner. The purpose of this article is to present a general approach to constructing approximate confidence intervals for differences between (a) 2 independent correlations, (b) 2 overlapping correlations, (c) 2 nonoverlapping correlations, and (d) 2 independent R2s. The distinctive feature of this approach is its acknowledgment of the asymmetry of sampling distributions for single correlations. This approach requires only the availability of confidence limits for the separate correlations and, for correlated correlations, a method for taking into account the dependency between correlations. These closed-form procedures are shown by simulation studies to provide very satisfactory results in small to moderate sample sizes. The proposed approach is illustrated with worked examples.

Comparison of regression models for the analysis of fall risk factors in older veterans.

PURPOSE: To compare the performance of eight regression models for analyzing risk of falling, focusing on the effect of physical inactivity in older veterans. METHODS: This study uses data from a fall risk factor screening and modification trial in community-dwelling Canadian male veterans of World War II or the Korean War, with falls ascertained prospectively using calendars and physical activity (PA) measured at baseline with a single global question. The effect of PA on falling was assessed using eight different multivariable regression models, with three models treating falling as a non-recurrent event whereas the other five models regard falls as recurrent events. RESULTS: Recurrent event models showed that male veterans who reported being less active than their peers were 1.42 (1.02-1.97) to 2.46 (1.18-5.14) times more likely to fall than those who reported being about as or more active than their peers (n = 270; mean age +/- SD = 81.1 +/- 4.0 years). None of the non-recurrent event models detected a statistically significant association between PA and falls. CONCLUSIONS: Risk of falling may be better analyzed using regression models for recurrent events. These results have important implications for the collection and analysis of fall outcome data.

Strengthening the reporting of genetic association studies (STREGA): an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) statement.

Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.