Application of Local Rank Tests for Nonparametric Regression

Let Y_i = f(x_i) + E_i\ (1\le i\le n) with given covariates x_1\lt x_2\lt \cdots\lt x_n , an unknown regression function f and independent random errors E_i with median zero. It is shown how to apply several linear rank test statistics simultaneously in order to test monotonicity of f in various regions and to identify its local extrema.

Detecting outlying studies in meta-regression models using a forward search algorithm.

When considering data from many trials, it is likely that some of them present a markedly different intervention effect or exert an undue influence on the summary results. We develop a forward search algorithm for identifying outlying and influential studies in meta-analysis models. The forward search algorithm starts by fitting the hypothesized model to a small subset of likely outlier-free studies and proceeds by adding studies into the set one-by-one that are determined to be closest to the fitted model of the existing set. As each study is added to the set, plots of estimated parameters and measures of fit are monitored to identify outliers by sharp changes in the forward plots. We apply the proposed outlier detection method to two real data sets; a meta-analysis of 26 studies that examines the effect of writing-to-learn interventions on academic achievement adjusting for three possible effect modifiers, and a meta-analysis of 70 studies that compares a fluoride toothpaste treatment to placebo for preventing dental caries in children. A simple simulated example is used to illustrate the steps of the proposed methodology, and a small-scale simulation study is conducted to evaluate the performance of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.

Masked hypertension and cardiac remodeling in middle-aged endurance athletes

OBJECTIVES: Extensive endurance training and arterial hypertension are established risk factors for atrial fibrillation. We aimed to assess the proportion of masked hypertension in endurance athletes and the impact on cardiac remodeling, mechanics, and supraventricular tachycardias (SVT). METHODS: Male participants of a 10-mile race were recruited and included if office blood pressure was normal (<140/90 mmHg). Athletes were stratified into a masked hypertension and normotension group by ambulatory blood pressure. Primary endpoint was diastolic function, expressed as peak early diastolic mitral annulus velocity (E'). Left ventricular global strain, left ventricular mass/volume ratio, left atrial volume index, signal-averaged P-wave duration (SAPWD), and SVT during 24-h Holter monitoring were recorded. RESULTS: From 108 runners recruited, 87 were included in the final analysis. Thirty-three (38%) had masked hypertension. The mean age was 42 +/- 8 years. Groups did not differ with respect to age, body composition, cumulative training hours, and 10-mile race time. Athletes with masked hypertension had a lower E' and a higher left ventricular mass/volume ratio. Left ventricular global strain, left atrial volume index, SAPWD, and SVT showed no significant differences between the groups. In multiple linear regression analysis, masked hypertension was independently associated with E' (beta = -0.270, P = 0.004) and left ventricular mass/volume ratio (beta = 0.206, P = 0.049). Cumulative training hours was the only independent predictor for left atrial volume index (beta = 0.474, P < 0.001) and SAPWD (beta = 0.481, P < 0.001). CONCLUSION: In our study, a relevant proportion of middle-aged athletes had masked hypertension, associated with a lower diastolic function and a higher left ventricular mass/volume ratio, but unrelated to left ventricular systolic function, atrial remodeling, or SVT.

Regression of coronary atherosclerosis: Current evidence and future perspectives

Coronary atherosclerosis has been considered a chronic disease characterized by ongoing progression in response to systemic risk factors and local pro-atherogenic stimuli. As our understanding of the pathobiological mechanisms implicated in atherogenesis and plaque progression is evolving, effective treatment strategies have been developed that led to substantial reduction of the clinical manifestations and acute complications of coronary atherosclerotic disease. More recently, intracoronary imaging modalities have enabled detailed in vivo quantification and characterization of coronary atherosclerotic plaque, serial evaluation of atherosclerotic changes over time, and assessment of vascular responses to effective anti-atherosclerotic medications. The use of intracoronary imaging modalities has demonstrated that intensive lipid lowering can halt plaque progression and may even result in regression of coronary atheroma when the highest doses of the most potent statins are used. While current evidence indicates the feasibility of atheroma regression and of reversal of presumed high-risk plaque characteristics in response to intensive anti-atherosclerotic therapies, these changes of plaque size and composition are modest and their clinical implications remain largely elusive. Growing interest has focused on achieving more pronounced regression of coronary plaque using novel anti-atherosclerotic medications, and more importantly on elucidating ways toward clinical translation of favorable changes of plaque anatomy into more favorable clinical outcomes for our patients.

Systematic analysis of factors associated with progression and regression of ulcerative colitis in 918 patients.

BACKGROUND Studies that systematically assess change in ulcerative colitis (UC) extent over time in adult patients are scarce. AIM To assess changes in disease extent over time and to evaluate clinical parameters associated with this change. METHODS Data from the Swiss IBD cohort study were analysed. We used logistic regression modelling to identify factors associated with a change in disease extent. RESULTS A total of 918 UC patients (45.3% females) were included. At diagnosis, UC patients presented with the following disease extent: proctitis [199 patients (21.7%)], left-sided colitis [338 patients (36.8%)] and extensive colitis/pancolitis [381 (41.5%)]. During a median disease duration of 9 [4-16] years, progression and regression was documented in 145 patients (15.8%) and 149 patients (16.2%) respectively. In addition, 624 patients (68.0%) had a stable disease extent. The following factors were identified to be associated with disease progression: treatment with systemic glucocorticoids [odds ratio (OR) 1.704, P = 0.025] and calcineurin inhibitors (OR: 2.716, P = 0.005). No specific factors were found to be associated with disease regression. CONCLUSIONS Over a median disease duration of 9 [4-16] years, about two-thirds of UC patients maintained the initial disease extent; the remaining one-third had experienced either progression or regression of the disease extent.

Diabetes, use of antidiabetic drugs, and the risk of glioma

BACKGROUND Prior epidemiologic studies suggest inverse relations between diabetes and glioma risk, but the underlying mechanisms, including use of antidiabetic drugs, are unknown. METHODS We therefore performed a matched case-control analysis using the Clinical Practice Research Datalink (CPRD). We identified incident glioma cases diagnosed between 1995 and 2012 and matched each case with 10 controls on age, gender, calendar time, general practice, and years of active history in the CPRD. We performed conditional logistic regression to estimate odds ratios (ORs) with 95% CIs, adjusted for body mass index and smoking. RESULTS We identified 2005 cases and 20 050 controls. Diabetes was associated with decreased risk of glioma (OR = 0.74; 95% CI = 0.60-0.93), particularly glioblastoma (OR = 0.69; 95% CI = 0.51-0.94). Glioblastoma risk reduction was markedly pronounced among diabetic men (OR = 0.60; 95% CI = 0.40-0.90), most apparently for those with diabetes of long-term duration (OR for >5 vs 0 y = 0.46; 95% CI = 0.26-0.82) or poor glycemic control (OR for HbA1c ≥8 vs <6.5% = 0.20; 95% CI = 0.06-0.70). In contrast, the effect of diabetes on glioblastoma risk was absent among women (OR = 0.85; 95% CI = 0.53-1.36). No significant associations with glioma were found for use of metformin (OR for ≥30 vs 0 prescriptions = 0.72; 95% CI = 0.38-1.39), sulfonylureas (OR = 0.71; 95% CI = 0.39-1.30), or insulin (OR = 0.79; 95% CI = 0.37-1.69). CONCLUSIONS Antidiabetic treatment appears to be unrelated to glioma, but long-term diabetes duration and increased HbA1c both show decreased glioma risk. Stronger findings in men than women suggest low androgen levels concurrent with diabetes as a biologic mechanism.

Similar outcome of upfront-unrelated and matched sibling stem cell transplantation in idiopathic paediatric aplastic anaemia. A study on behalf of the UK Paediatric BMT Working Party, Paediatric Diseases Working Party and Severe Aplastic Anaemia Working Party of EBMT

Abstract We explored the feasibility of unrelated donor haematopoietic stem cell transplant (HSCT) upfront without prior immunosuppressive therapy (IST) in paediatric idiopathic severe aplastic anaemia (SAA). This cohort was then compared to matched historical controls who had undergone first-line therapy with a matched sibling/family donor (MSD) HSCT (n = 87) or IST with horse antithymocyte globulin and ciclosporin (n = 58) or second-line therapy with unrelated donor HSCT post-failed IST (n = 24). The 2-year overall survival in the upfront cohort was 96 ± 4% compared to 91 ± 3% in the MSD controls (P = 0·30) and 94 ± 3% in the IST controls (P = 0·68) and 74 ± 9% in the unrelated donor HSCT post-IST failure controls (P = 0·02).The 2-year event-free survival in the upfront cohort was 92 ± 5% compared to 87 ± 4% in MSD controls (P = 0·37), 40 ± 7% in IST controls (P = 0·0001) and 74 ± 9% in the unrelated donor HSCT post-IST failure controls (n = 24) (P = 0·02). Outcomes for upfront-unrelated donor HSCT in paediatric idiopathic SAA were similar to MSD HSCT and superior to IST and unrelated donor HSCT post-IST failure. Front-line therapy with matched unrelated donor HSCT is a novel treatment approach and could be considered as first-line therapy in selected paediatric patients who lack a MSD. © 2015 John Wiley & Sons Ltd.

Diagnostik von Regressionsschätzungen bei kleinen Stichproben (mit einem Exkurs zu logistischer Regression)

Wie alle anderen statistischen Verfahren konzentriert sich auch die Methode der Regression nur auf die Analyse ausgewählter Aspekte vorliegenden Datenmaterials. Entsprechend sind zu gegebenen Regressionsergebnissen ganz unterschiedliche Datenkonstellationen denkbar, wovon aber für die Interpretation der Ergebnisse nicht alle unproblematisch sind. So besteht besonders bei kleinen Stichproben die Gefahr, dass die Regressionsschätzung entscheidend von einzelnen Extremwerten abhängt, was die Verlässlichkeit der daraus abgeleiteten Schlussfolgerungen beeinträchtigt. In diesem Beitrag werden deshalb anhand von Beispielen einige einfache grafische und formale Instrumente zur Diagnose einflussreicher Datenpunkte in der linearen und logistischen Regression vorgestellt, die im Prozess der Datenanalyse standardmäßig angewendet werden sollten. Weiterhin werden nach Identifikation „atypischer“ Datenpunkte zu verfolgende Analysestrategien diskutiert.

From regression estimates to document tables: output formatting using -estout-

Postestimation processing and formatting of regression estimates for input into document tables are tasks that many of us have to do. However, processing results by hand can be laborious, and is vulnerable to error. There are therefore many benefits to automation of these tasks while at the same time retaining user flexibility in terms of output format. The estout package meets these needs. estout assembles a table of coefficients, "significance stars", summary statistics, standard errors, t/z statistics, p-values, confidence intervals, and other statistics calculated for up to twenty models previously fitted and stored by estimates store. It then writes the table to the Stata log and/or to a text file. The estimates are formatted optionally in several styles: html, LaTeX, or tab-delimited (for input into MS Excel or Word). There are a large number of options regarding which output is formatted and how. This talk will take users through a range of examples, from relatively basic simple applications to complex ones.

LOGITCPRPLOT: Stata module to graph component-plus-residual plot for logistic regression

logitcprplot can be used after logistic regression for graphing a component-plus-residual plot (a.k.a. partial residual plot) for a given predictor, including a lowess, local polynomial, restricted cubic spline, fractional polynomial, penalized spline, regression spline, running line, or adaptive variable span running line smooth

RRLOGIT: Stata module to estimate logistic regression for randomized response data

rrlogit fits a maximum-likelihood logistic regression for randomized response data.

WGTTEST: Stata module to test the impact of sampling weights in regression analysis

wgttest performs a test proposed by DuMouchel and Duncan (1983) to evaluate whether the weighted and unweighted estimates of a regression model are significantly different.