Practical investigation of the performance of robust logistic regression to predict the genetic risk of hypertension

Logistic regression is usually applied to investigate the association between inherited genetic variants and a binary disease phenotype. A limitation of standard methods used to estimate the parameters of logistic regression models is their strong dependence on a few observations deviating from the majority of the data. We used data from the Genetic Analysis Workshop 18 to explore the possible benefit of robust logistic regression to estimate the genetic risk of hypertension. The comparison between standard and robust methods relied on the influence of departing hypertension profiles (outliers) on the estimated odds ratios, areas under the receiver operating characteristic curves, and clinical net benefit. Our results confirmed that single outliers may substantially affect the estimated genotype relative risks. The ranking of variants by probability values was different in standard and in robust logistic regression. For cutoff probabilities between 0.2 and 0.6, the clinical net benefit estimated by leave-one-out cross-validation in the investigated sample was slightly larger under robust regression, but the overall area under the receiver operating characteristic curve was larger for standard logistic regression. The potential advantage of robust statistics in the context of genetic association studies should be investigated in future analyses based on real and simulated data

Using next-generation DNA sequence data for genetic association tests based on allele counts with and without consideration of zero inflation

The relationship between genetic variability and individual phenotypes is usually investigated by testing for association relying on called genotypes. Allele counts obtained from next-generation sequence data could be used for this purpose too. Genetic association can be examined by treating alternative allele counts (AACs) as the response variable in negative binomial regression. AACs from sequence data often contain an excess of zeros, thus motivating the use of Hurdle and zero-inflated models. Here we examine rough type I error rates and the ability to pick out variants with small probability values for 7 different testing approaches that incorporate AACs as an explanatory or as a response variable. Model comparisons relied on chromosome 3 DNA sequence data from 407 Hispanic participants in the Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) project 1 with complete information on diastolic blood pressure and related medication. Our results suggest that in the investigation of the relationship between AAC as response variable and individual phenotypes as explanatory variable, Hurdle-negative binomial regression has some advantages. This model showed a good ability to discriminate strongly associated variants and controlled overall type I error rates. However, probability values from Hurdle-negative binomial regression were not obtained for approximately 25 % of the investigated variants because of convergence problems, and the mass of the probability value distribution was concentrated around 1

Health-related Quality of Life in the Phase III LUME-Colon 1 Study: Comparison and Interpretation of Results From EORTC QLQ-C30 Analyses

INTRODUCTION: We used European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) data from the LUME-Colon 1 study to illustrate different methods of statistical analysis for health-related quality of life (HRQoL), and compared the results. PATIENTS AND METHODS: Patients were randomized 1:1 to receive nintedanib 200 mg twice daily plus best supportive care (n = 386) or matched placebo plus best supportive care (n = 382). Five methods (mean treatment difference averaged over time, using a mixed-effects growth curve model; mixed-effects models for repeated measurements (MMRM); time-to-deterioration (TTD); status change; and responder analysis) were used to analyze EORTC QLQ-C30 global health status (GHS)/QoL and scores from functional scales. RESULTS: Overall, GHS/QoL and physical functioning deteriorated over time. Mean treatment difference slightly favored nintedanib over placebo for physical functioning (adjusted mean, 2.66; 95% confidence interval [CI], 0.97-4.34) and social functioning (adjusted mean, 2.62; 95% CI, 0.66-4.47). GHS/QoL was numerically better with nintedanib versus placebo (adjusted mean, 1.61; 95% CI, -0.004 to 3.27). MMRM analysis had similar results, with better physical functioning in the nintedanib group at all timepoints. There was no significant delay in GHS/QoL deterioration (10%) and physical functioning (16%) with nintedanib versus placebo (TTD analysis). Status change analysis showed a higher proportion of patients with markedly improved GHS/QoL and physical functioning in the nintedanib versus placebo groups. Responder analysis showed a similar, less pronounced pattern. CONCLUSION: Analyses of EORTC QLQ-C30 data showed that HRQoL was not impaired by treatment with nintedanib versus placebo. Analysis and interpretation of HRQoL endpoints should consider symptom type and severity and course of disease. ispartof: CLINICAL COLORECTAL CANCER vol:18 issue:4 pages:269-+ ispartof: location:United States status: publishe

Empagliflozin, Health Status, and Quality of Life in Patients With Heart Failure and Preserved Ejection Fraction: The EMPEROR-Preserved Trial

Background: Patients with heart failure with preserved ejection fraction have significant impairment in health-related quality of life. In the EMPEROR-Preserved trial (Empagliflozin Outcome Trial in Patients With Chronic Heart Failure With Preserved Ejection Fraction), we evaluated the efficacy of empagliflozin on health-related quality of life in patients with heart failure with preserved ejection fraction and whether the clinical benefit observed with empagliflozin varies according to baseline health status. Methods: Health-related quality of life was measured with the Kansas City Cardiomyopathy Questionnaire (KCCQ) at baseline and 12, 32, and 52 weeks. Patients were divided by baseline KCCQ Clinical Summary Score (CSS) tertiles, and the effect of empagliflozin on outcomes was examined. The effect of empagliflozin on KCCQ-CSS, Total Symptom Score, and Overall Summary Score was evaluated. Responder analyses were performed to compare the odds of improvement and deterioration in KCCQ related to treatment with empagliflozin. Results: The effect of empagliflozin on reducing the risk of time to cardiovascular death or heart failure hospitalization was consistent across baseline KCCQ-CSS tertiles (hazard ratio, 0.83 [95% CI, 0.69–1.00], 0.70 [95% CI, 0.55–0.88], and 0.82 [95% CI, 0.62–1.08] for scores <62.5, 62.5–83.3, and ≥83.3, respectively; P trend=0.77). Similar results were seen for total heart failure hospitalizations. Patients treated with empagliflozin had significant improvement in KCCQ-CSS versus placebo (+1.03, +1.24, and +1.50 at 12, 32, and 52 weeks, respectively; P<0.01); similar results were seen for Total Symptom Score and Overall Summary Score. At 12 weeks, patients on empagliflozin had higher odds of improvement ≥5 points (odds ratio, 1.23 [95% CI, 1.10–1.37]), ≥10 points (odds ratio, 1.15 [95% CI, 1.03–1.27]), and ≥15 points (odds ratio, 1.13 [95% CI, 1.02–1.26]) and lower odds of deterioration ≥5 points in KCCQ-CSS (odds ratio, 0.85 [95% CI, 0.75–0.97]). A similar pattern was seen at 32 and 52 weeks, and results were consistent for Total Symptom Score and Overall Summary Score. Conclusions: In patients with heart failure with preserved ejection fraction, empagliflozin reduced the risk for major heart failure outcomes across the range of baseline KCCQ scores. Empagliflozin improved health-related quality of life, an effect that appeared early and was sustained for at least 1 year

Atlas of the clinical genetics of human dilated cardiomyopathy

[Abstract] Aim. Numerous genes are known to cause dilated cardiomyopathy (DCM). However, until now technological limitations have hindered elucidation of the contribution of all clinically relevant disease genes to DCM phenotypes in larger cohorts. We now utilized next-generation sequencing to overcome these limitations and screened all DCM disease genes in a large cohort. Methods and results. In this multi-centre, multi-national study, we have enrolled 639 patients with sporadic or familial DCM. To all samples, we applied a standardized protocol for ultra-high coverage next-generation sequencing of 84 genes, leading to 99.1% coverage of the target region with at least 50-fold and a mean read depth of 2415. In this well characterized cohort, we find the highest number of known cardiomyopathy mutations in plakophilin-2, myosin-binding protein C-3, and desmoplakin. When we include yet unknown but predicted disease variants, we find titin, plakophilin-2, myosin-binding protein-C 3, desmoplakin, ryanodine receptor 2, desmocollin-2, desmoglein-2, and SCN5A variants among the most commonly mutated genes. The overlap between DCM, hypertrophic cardiomyopathy (HCM), and channelopathy causing mutations is considerably high. Of note, we find that >38% of patients have compound or combined mutations and 12.8% have three or even more mutations. When comparing patients recruited in the eight participating European countries we find remarkably little differences in mutation frequencies and affected genes. Conclusion. This is to our knowledge, the first study that comprehensively investigated the genetics of DCM in a large-scale cohort and across a broad gene panel of the known DCM genes. Our results underline the high analytical quality and feasibility of Next-Generation Sequencing in clinical genetic diagnostics and provide a sound database of the genetic causes of DCM.Hôpitaux de Paris; PHRC AOM0414

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Tailored Selection of Study Individuals to be Sequenced in Order to Improve the Accuracy of Genotype Imputation [Source Code]

The addition of sequence data from own‐study individuals to genotypes from external data repositories, for example, the HapMap, has been shown to improve the accuracy of imputed genotypes. Early approaches for reference panel selection favored individuals who best reflect recombination patterns in the study population. By contrast, a maximization of genetic diversity in the reference panel has been recently proposed. We investigate here a novel strategy to select individuals for sequencing that relies on the characterization of the ancestral kernel of the study population. The simulated study scenarios consisted of several combinations of subpopulations from HapMap. HapMap individuals who did not belong to the study population constituted an external reference panel which was complemented with the sequences of study individuals selected according to different strategies. In addition to a random choice, individuals with the largest statistical depth according to the first genetic principal components were selected. In all simulated scenarios the integration of sequences from own‐study individuals increased imputation accuracy. The selection of individuals based on the statistical depth resulted in the highest imputation accuracy for European and Asian study scenarios, whereas random selection performed best for an African‐study scenario. Present findings indicate that there is no universal ‘best strategy’ to select individuals for sequencing. We propose to use the methodology described in the manuscript to assess the advantage of focusing on the ancestral kernel under own study characteristics (study size, genetic diversity, availability and properties of external reference panels, frequency of imputed variants…)

Health-related Quality of Life in the Phase III LUME-Colon 1 Study: Comparison and Interpretation of Results From EORTC QLQ-C30 Analyses

INTRODUCTION: We used European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) data from the LUME-Colon 1 study to illustrate different methods of statistical analysis for health-related quality of life (HRQoL), and compared the results. PATIENTS AND METHODS: Patients were randomized 1:1 to receive nintedanib 200 mg twice daily plus best supportive care (n = 386) or matched placebo plus best supportive care (n = 382). Five methods (mean treatment difference averaged over time, using a mixed-effects growth curve model; mixed-effects models for repeated measurements (MMRM); time-to-deterioration (TTD); status change; and responder analysis) were used to analyze EORTC QLQ-C30 global health status (GHS)/QoL and scores from functional scales. RESULTS: Overall, GHS/QoL and physical functioning deteriorated over time. Mean treatment difference slightly favored nintedanib over placebo for physical functioning (adjusted mean, 2.66; 95% confidence interval [CI], 0.97-4.34) and social functioning (adjusted mean, 2.62; 95% CI, 0.66-4.47). GHS/QoL was numerically better with nintedanib versus placebo (adjusted mean, 1.61; 95% CI, -0.004 to 3.27). MMRM analysis had similar results, with better physical functioning in the nintedanib group at all timepoints. There was no significant delay in GHS/QoL deterioration (10%) and physical functioning (16%) with nintedanib versus placebo (TTD analysis). Status change analysis showed a higher proportion of patients with markedly improved GHS/QoL and physical functioning in the nintedanib versus placebo groups. Responder analysis showed a similar, less pronounced pattern. CONCLUSION: Analyses of EORTC QLQ-C30 data showed that HRQoL was not impaired by treatment with nintedanib versus placebo. Analysis and interpretation of HRQoL endpoints should consider symptom type and severity and course of disease.status: publishe

Health-related Quality of Life in the Phase III LUME-Colon 1 Study: Comparison and Interpretation of Results From EORTC QLQ-C30 Analyses

Introduction: We used European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) data from the LUME-Colon 1 study to illustrate different methods of statistical analysis for health-related quality of life (HRQoL), and compared the results. Patients and Methods: Patients were randomized 1:1 to receive nintedanib 200 mg twice daily plus best supportive care (n = 386) or matched placebo plus best supportive care (n = 382). Five methods (mean treatment difference averaged over time, using a mixed-effects growth curve model; mixed-effects models for repeated measurements (MMRM); time-to-deterioration (TTD); status change; and responder analysis) were used to analyze EORTC QLQ-C30 global health status (GHS)/QoL and scores from functional scales. Results: Overall, GHS/QoL and physical functioning deteriorated over time. Mean treatment difference slightly favored nintedanib over placebo for physical functioning (adjusted mean, 2.66; 95% confidence interval [CI], 0.97-4.34) and social functioning (adjusted mean, 2.62; 95% CI, 0.66-4.47). GHS/QoL was numerically better with nintedanib versus placebo (adjusted mean, 1.61; 95% CI, −0.004 to 3.27). MMRM analysis had similar results, with better physical functioning in the nintedanib group at all timepoints. There was no significant delay in GHS/QoL deterioration (10%) and physical functioning (16%) with nintedanib versus placebo (TTD analysis). Status change analysis showed a higher proportion of patients with markedly improved GHS/QoL and physical functioning in the nintedanib versus placebo groups. Responder analysis showed a similar, less pronounced pattern. Conclusion: Analyses of EORTC QLQ-C30 data showed that HRQoL was not impaired by treatment with nintedanib versus placebo. Analysis and interpretation of HRQoL endpoints should consider symptom type and severity and course of disease

Weight Change and Clinical Outcomes in Heart Failure with Reduced Ejection Fraction: Insights from EMPEROR-Reduced.

AIMS: Baseline body mass index (BMI) and weight loss promoted by sodium-glucose co-transporter 2 inhibitors may impact outcomes in patients with heart failure with reduced ejection fraction (HFrEF). We assessed in the EMPEROR-Reduced population treated with empagliflozin vs placebo the relationship between baseline BMI, weight loss and effects on the primary (time to first hospitalization for heart failure [HHF] or cardiovascular death) and key secondary outcomes. METHODS AND RESULTS: We categorized patients according to their baseline BMI: <20 kg/m2 , (n = 180); 20-<25 kg/m2 (n = 1038); 25-<30 kg/m2 (n = 1345); 30-<35 kg/m2 (n = 774) and ≥35 kg/m2 (n = 393). The treatment effect of empagliflozin on the primary outcome was consistent across all BMI categories (HRs in subgroups 0.66 to 0.88, interaction trend p = 0.32), as was the effect on total (first plus recurrent) HHF (interaction trend p = 0.31). Empagliflozin reduced the rate of eGFR decline consistently across the BMI categories (interaction trend p = 0.67). Overall, incidence rates of any or serious adverse events were comparable between the treatment groups across all BMI categories. Three-hundred-and thirteen (17.4%) of patients treated with empagliflozin experienced a weight loss of more than 5% at week 52 vs. 230 (12.8%) in placebo. When analyzed separately within each treatment group, presence of weight loss was similarly associated with an increased risk of all-cause mortality. CONCLUSION: The benefits of empagliflozin versus placebo were consistently present across all BMI categories in HFrEF patients. Weight loss was associated with higher risk of all-cause mortality, regardless of treatment group