Preladenant as an Adjunctive Therapy With Levodopa in Parkinson Disease

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Effect of ertugliflozin on glucose control, body weight, blood pressure and bone density in type 2 diabetes mellitus inadequately controlled on metformin monotherapy (VERTIS MET)

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Prediction of remission and low disease activity in disease-modifying anti-rheumatic drug-refractory patients with rheumatoid arthritis treated with golimumab

OBJECTIVE: To create a tool to predict probability of remission and low disease activity (LDA) in patients with RA being considered for anti-TNF treatment in clinical practice. METHODS: We analysed data from GO-MORE, an open-label, multinational, prospective study in biologic-naïve patients with active RA (DAS28-ESR ⩾3.2) despite DMARD therapy. Patients received 50 mg s.c. golimumab (GLM) once monthly for 6 months. In secondary analyses, regression models were used to determine the best set of baseline factors to predict remission (DAS28-ESR <2.6) at month 6 and LDA (DAS28-ESR ⩽3.2) at month 1. RESULTS: In 3280 efficacy-evaluable patients, of 12 factors included in initial regression models predicting remission or LDA, six were retained in final multivariable models. Greater likelihood of LDA and remission was associated with being male; younger age; lower HAQ, ESR (or CRP) and tender joint count (or swollen joint count) scores; and absence of comorbidities. In models predicting 1-, 3- and 6-month LDA or remission, area under the receiver operating curve was 0.648-0.809 (R(2) = 0.0397-0.1078). The models also predicted 6-month HAQ and EuroQoL-5-dimension scores. A series of matrices were developed to easily show predicted rates of remission and LDA. CONCLUSION: A matrix tool was developed to show predicted GLM treatment outcomes in patients with RA, based on a combination of six baseline characteristics. The tool could help provide practical guidance in selection of candidates for anti-TNF therapy

Design and baseline characteristics of the eValuation of ERTugliflozin effIcacy and Safety CardioVascular outcomes trial (VERTIS-CV)

Background Ertugliflozin is an inhibitor of sodium-glucose co-transporter-2 (SGLT2), approved in the United States and European Union to improve glycemic control in adults with type 2 diabetes mellitus (T2DM). The VERTIS cardiovascular (CV) outcomes trial (NCT01986881) has a primary objective to demonstrate non-inferiority of ertugliflozin versus placebo on major adverse CV events: time to the first event of CV death, nonfatal myocardial infarction, or nonfatal stroke. Secondary objectives are to demonstrate superiority of ertugliflozin versus placebo on time to: 1) the composite outcome of CV death or hospitalization for heart failure (HF); 2) CV death; and 3) the composite outcome of renal death, dialysis/transplant, or doubling of serum creatinine from baseline. Methods Patients ≥40 years old with T2DM (HbA1c 7.0–10.5%) and established atherosclerotic cardiovascular disease (ASCVD) of the coronary, cerebral, and/or peripheral arterial systems, were randomized 1:1:1 to once daily double-blind placebo, ertugliflozin 5 mg or 15 mg added to existing therapy. Results 8246 patients were randomized and 8238 received at least 1 dose of investigational product. Mean age was 64.4 years, 11.0% were ≥75 years old, and mean diabetes duration was 12.9 years with screening HbA1c of 8.3%. At entry, coronary artery disease, cerebrovascular disease, and peripheral arterial disease were present in 76.3%, 23.1%, and 18.8% of patients, respectively. HF was present in 23.1%, and Stage 3 kidney disease in 21.6% of patients. Conclusion The results from the VERTIS-CV trial will define the CV and renal safety and efficacy of ertugliflozin in patients with T2DM and ASCVD. (Am Heart J 2018;206:11-23.

Modeling times of maximum biomarker excretion:

Analysis of biomarkers to detect levels of chemical exposure in humans is an important risk evaluation tool. For example, urine biomarkers such as 1-aminopyrene can be used to assess exposure levels to diesel exhaust (DE), an important public health concern. Toxic chemicals contained in DE and DE particles have demonstrated genotoxic and carcinogenic properties in experimental animals. A recent experiment evaluating the urine concentration of DE biomarkers was the impetus for this dissertation. One goal of the experiment, and the focus of this dissertation, was to characterize the excretion time course of the biomarker 1-aminopyrene. The times of maximum concentration in plasma or maximum excretion in urine have been typically summarized using non-parametric or asymptotic techniques based on individual subject-level values; however, there is limited information addressing confidence interval generation when sparse subject-level samples requiring population-modeling approaches are present. Therefore, there was a need to generate and evaluate an appropriate confidence interval approach when sparse sampling is present. Pharmacokinetic (PK) modeling was used to fit a standard one-compartment urine excretion model to the data for estimation of the time of maximum excretion. Several variations of the PK model were explored and a model based on cumulative excretion rates was selected. Several statistical techniques for modeling PK data and calculating confidence intervals for the time of maximum excretion were compared including confidence intervals based on the first and second order delta methods, derived for this dissertation. A comparison of confidence interval methods showed that when using: (1) within-subject Tmax values, coverages obtained using the non-parametric method were highest and often provide coverages close to the nominal 95% level; and (2) population-average Tmax values, confidence intervals generated using the first-order delta method provided the highest coverages, at approximately 93% when numerical approximation estimation methods were used. Subject response profiles for the 1-aminopyrene biomarker data were varied and led to a hypothesis that a mixture of more than one distribution of profiles may be present. Future exploration with data collected for more than 24-hours would be needed to further explore this hypothesis fully.D.P.H.Includes bibliographical references (p. 169-173)by Susan Huyc

Colectomy incidence rates in five-year data from the observational postmarketing ulcerative colitis study of originator infliximab

Background: This analysis of the Observational Postmarketing Ulcerative Colitis Study examined incidence rates of colectomy in patients with ulcerative colitis who received originator infliximab (IFX) or conventional therapies (ConvRx) as per their treating physician. Methods: Cox proportional hazards models compared time to colectomy for both treatment groups. A secondary analysis examined colectomy incidence rates based on IFX exposure timing (defined by a 90-day window after the last IFX dose date). Results: Of 2239 patients with data, 1059 enrolled in IFX and 1180 enrolled in ConvRx (including 296 patients who switched to IFX). Patients in the IFX group had more severe disease at baseline vs the ConvRx group (percentage with baseline partial Mayo score 7-9: 46.0% vs 30.5%, respectively). During 5 years of follow-up, 271 patients (12.1% of enrolled patients) had colectomy. Enrollment in the IFX group was associated with a higher risk of colectomy (hazard ratio = 3.12; 95% confidence interval, 2.25-4.34; P < 0.001) compared with enrollment in the ConvRx group. A total of 174 colectomies occurred in the IFX group, but 97 of these colectomies occurred ≥90 days after the last IFX dose date. Conclusions: Colectomy was reported at a higher rate in the IFX group than in the ConvRx group, although patients in the IFX group had more severe disease at baseline and most of the colectomies occurred after patients had been off of IFX for ≥90 days

Randomized trial of preladenant, given as monotherapy, in patients with early Parkinson disease

To evaluate the adenosine 2a receptor antagonist preladenant as a nondopaminergic drug for the treatment of Parkinson disease (PD) when given as monotherapy