Predictions of Systemic, Intracellular, and Lung Concentrations of Azithromycin With Different Dosing Regimens Used in COVID-19 Clinical Trials.

Azithromycin (AZ), a broad-spectrum macrolide antibiotic, is being investigated in patients with coronavirus disease 2019 (COVID-19). A population pharmacokinetic model was implemented to predict lung, intracellular poly/mononuclear cell (peripheral blood monocyte (PBM)/polymorphonuclear leukocyte (PML)), and alveolar macrophage (AM) concentrations using published data and compared against preclinical effective concentration 90% (EC90 ) for severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). The final model described the data reported in eight publications adequately. Consistent with its known properties, concentrations were higher in AM and PBM/PML, followed by lung tissue, and lowest systemically. Simulated PBM/PML concentrations exceeded EC90 following the first dose and for ~ 14 days following 500 mg q.d. for 3 days or 500 mg q.d. for 1 day/250 mg q.d. on days 2-5, 10 days following a single 1,000 mg dose, and for > 20 days with 500 mg q.d. for 10 days. AM concentrations exceeded the 90% inhibitory concentration for > 20 days for all regimens. These data will better inform optimization of dosing regimens for AZ clinical trials.

An appraisal of meta-analysis guidelines: how do they relate to safety outcomes?

Although well developed to assess efficacy questions, meta-analyses and, more generally, systematic reviews, have received less attention in application to safety-related questions. As a result, many open questions remain on how best to apply meta-analyses in the safety setting. This appraisal attempts to: (i) summarize the current guidelines for assessing individual studies, systematic reviews, and network meta-analyses; (ii) describe several publications on safety meta-analytic approaches; and (iii) present some of the questions and issues that arise with safety data. A number of gaps in the current quality guidelines are identified along with issues to consider when performing a safety meta-analysis. While some work is ongoing to provide guidance to improve the quality of safety meta-analyses, this review emphasizes the critical need for better reporting and increased transparency regarding safety data in the systematic review guidelines. Copyright © 2016 John Wiley & Sons, Ltd.

Systematic review and meta-analysis of serious infections with tofacitinib and biologic disease-modifying antirheumatic drug treatment in rheumatoid arthritis clinical trials.

BACKGROUND: Tofacitinib is an oral Janus kinase inhibitor for the treatment of rheumatoid arthritis (RA). Tofacitinib modulates the signaling of cytokines that are integral to lymphocyte activation, proliferation, and function. Thus, tofacitinib therapy may result in suppression of multiple elements of the immune response. Serious infections have been reported in tofacitinib RA trials. However, limited head-to-head comparator data were available within the tofacitinib RA development program to directly compare rates of serious infections with tofacitinib relative to biologic agents, and specifically adalimumab (employed as an active control agent in two randomized controlled trials of tofacitinib). METHODS: A systematic literature search of data from interventional randomized controlled trials and long-term extension studies with biologics in RA was carried out. Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) consensus was followed for reporting results of the review and meta-analysis. Incidence rates (unique patients with events/100 patient-years) for each therapy were estimated based on data from randomized controlled trials and long-term extension studies using a random-effects model. Relative and absolute risk comparisons versus placebo used Mantel-Haenszel methods. RESULTS: The search produced 657 hits. In total, 66 randomized controlled trials and 22 long-term extension studies met the selection criteria. Estimated incidence rates (95% confidence intervals [CIs]) for abatacept, rituximab, tocilizumab, and tumor necrosis factor inhibitors were 3.04 (2.49, 3.72), 3.72 (2.99, 4.62), 5.45 (4.26, 6.96), and 4.90 (4.41, 5.44), respectively. Incidence rates (95% CIs) for tofacitinib 5 and 10 mg twice daily (BID) in phase 3 trials were 3.02 (2.25, 4.05) and 3.00 (2.24, 4.02), respectively. Corresponding incidence rates in long-term extension studies were 2.50 (2.05, 3.04) and 3.19 (2.74, 3.72). The risk ratios (95% CIs) versus placebo for tofacitinib 5 and 10 mg BID were 2.21 (0.60, 8.14) and 2.02 (0.56, 7.28), respectively. Risk differences (95% CIs) versus placebo for tofacitinib 5 and 10 mg BID were 0.38% (-0.24%, 0.99%) and 0.40% (-0.22%, 1.02%), respectively. CONCLUSIONS: In interventional studies, the risk of serious infections with tofacitinib is comparable to published rates for biologic disease-modifying antirheumatic drugs in patients with moderate to severely active RA.

Disease progression meta-analysis model in Alzheimer's disease.

BACKGROUND: Various authors have evaluated disease progression in Alzheimer's disease (AD), using patient data from individual clinical studies or pooled data across various trials. We conducted a systematic review of public data sources from 1990 to 2008 for all available AChE inhibitor studies, as well as clinical studies that evaluated the rate of deterioration in AD patients. Unique to this analysis, we developed a model based on literature data to describe the longitudinal response in the Alzheimer's Disease Assessment Scale-Cognitive (ADAS-cog) (change from baseline) in mild to moderate severity AD patients. The model was used to estimate disease progression for both placebo-treated patients and acetylcholinesterase (AChE)-inhibitor treated patients, and factors that affected disease progression. METHODS: We collected 576 mean ADAS-cog changes from baseline data points of 52 trials, representing data from approximately 19,972 patients and more than 84,000 individual observations. The model described the rate of disease progression, the evident placebo effect, and the symptomatic effect of AChE-inhibitors. Baseline ADAS-cog, Mini-Mental State Examination score, age, and year of publication were tested as covariates. RESULTS: The disease progression in mild to moderate AD patients across all available and relevant literature sources was estimated as 5.5 points per year. An Emax-type model best described the symptomatic drug effect of AChE inhibitors. The rate of disease progression (underlying disease progression) was no different between placebo and AChE-inhibitors groups. Baseline ADAS-cog is a significant covariate in disease progression. Baseline age was also tested as a covariate in the rate of disease progression, but the model was unable to describe any effects of age, likely because of the narrow distribution of mean age (literature-level analysis). There was no significant impact of publication year in the model. CONCLUSIONS: Baseline ADAS-cog is a significant covariate affecting the rate of disease progression, and it describes or at least explains the different rates of deterioration evident in early or late stages of the disease. There was no significant impact of publication year in the model, suggesting that disease progression has not slowed in more recent trials.