Follow-up of SARS-CoV-2 positive subgroup from the Asymptomatic novel CORonavirus iNFection study.

A nested longitudinal study within theAsymptomatic novel CORonavirus iNFfection study followed participants with positive nasopharyngeal swab to query for development of symptoms and assess duration of positive reverse transcription-polymerase chain reaction (RT-PCR) test results. Of the 91 participants initially testing positive, 86 participated in follow-up approximately 14 days after study enrollment; of those 86 participants, 19 (22.1%) developed at least one symptom at any time after the initial positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) test result. The median number of days to symptom development after their initial positive test result was 6 (range 1-29 days). No participants reported a SARS-CoV-2-related hospitalization. The most frequently reported symptoms were fatigue or muscle aches (10.5%), headache (9.3%), fever (5.8%), and shortness of breath (5.8%). Of the 78 participants who submitted a nasopharyngeal swab for repeat RT-PCR testing, 17 (21.8%) remained positive at Day 14, 4 of which continued to test positive at Day 28. These findings reinforce the probable role of silent SARS-CoV-2 infections in community transmission, and that reliance on symptom development will miss a large proportion of infections. Broad testing programs not limited to individuals presenting with symptoms are critical for identifying persons with SARS-CoV-2 infection and ultimately slowing transmission.

A cross-sectional community-based observational study of asymptomatic SARS-CoV-2 prevalence in the greater Indianapolis area.

The Asymptomatic novel CORonavirus iNfection (ACORN) study was designed to investigate the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the asymptomatic adult population of the Indianapolis metropolitan area, to follow individuals testing positive for the development of symptoms, and to understand duration of positive test results. ACORN is a cross-sectional community-based observational study of adult residents presenting asymptomatic for COVID-like illness, defined as the self-reported absence of the following three symptoms in the last 7 days: fever (≥100°F), new-onset or worsening cough, and new-onset or worsening shortness of breath. SARS-CoV-2 infection was determined by real-time reverse transcription-polymerase chain reaction in nasopharyngeal swab samples. SARS-CoV-2 infection prevalence was expressed as a point estimate with 95% confidence interval (CI). Test results are reported for 2953 participants who enrolled and underwent nasopharyngeal swab testing between 7 April 2020 and 16 May 2020. Among tested participants, 91 (3.1%; 95% CI: 2.5%-3.7%) were positive for SARS-CoV-2. Overall, baseline characteristics, medical history, and infection risk factors were comparable between SARS-CoV-2 positive and negative participants. Within the ongoing 14-day follow-up period for positive participants, 58 (71.6%) of 81 assessed participants remained asymptomatic while others (n = 23, 28.4%) reported one or more symptoms. Indiana had "Stay-at-Home" orders in place during nearly the entire test period reported here, yet 3.1% of asymptomatic participants tested positive for SARS-CoV-2. These results indicate screening questions had limited predictive utility for testing in an asymptomatic population and suggest broader testing strategies are needed. Importantly, these findings underscore that more research is needed to understand the viral transmission and the role asymptomatic and presymptomatic individuals play in this global pandemic.

Restricted mean survival time for the analysis of cardiovascular outcome trials assessing non-inferiority: Case studies from antihyperglycemic drug development.

Cardiovascular outcome trials (CVOTs) have been employed in multiple therapeutic areas to explore whether a noncardiovascular drug increases the risk for cardiovascular events. These studies are now a central part of drug development programs for antihyperglycemic drugs. These programs are expected to demonstrate that new antihyperglycemic drugs for patients with Type 2 diabetes do not have unacceptable cardiovascular risk. The hazard ratio, which is usually provided as evidence that patients receiving the investigational treatment are not at statistically significantly greater cardiovascular risk than patients on the control treatment, can be difficult to interpret for various reasons. Therefore, an alternative approach known as the Restricted Mean Survival Time (RMST) or τ-year mean survival time is presented, and its ability to overcome interpretation challenges with the hazard ratio discussed. The RMST approach is applied to five completed CVOTs and is compared with the corresponding hazard ratios. Additionally, detailed considerations are given on how to design a non-inferiority CVOT using the RMST approach. The RMST methodology is shown to be a practical alternative to the hazard ratio methodology for designing a non-inferiority CVOT.

Perspectives on Some Controversies in Cardiovascular Disease Risk Assessment in the Pharmaceutical Development of Glucose-Lowering Medications.

The U.S. Food and Drug Administration (FDA) issued guidance on requirements to assess cardiovascular disease (CVD) risk with drugs being developed for approval for clinical use. The guidance was triggered by a meta-analysis published by Nissen and Wolski that suggested an increased risk for myocardial infarction with the use of rosiglitazone. This article discusses controversies around CVD trials in diabetes beginning with the University Group Diabetes Program. This is followed by a brief description of the FDA guidance for evaluating CVD risk with glucose-lowering medications. Limitations of meta-analyses of data from phase 2 and 3 (phase 2/3) trials to inform CVD risk are highlighted. These include the differences between patient characteristics in phase 2/3 trials and those in cardiovascular outcome trials (CVOTs) and the relatively short exposure time in phase 2/3 trials. The differences may partly explain the observed disparity between phase 2/3 meta-analyses and the results of completed CVOTs. Approaches to understanding CVD risk with a new medication should get to the answer about risk as efficiently as possible to minimize any potential harm to patients. In that context, we discuss options for clinical trial design and an alternative approach for statistical analyses.

A clinical utility index for selecting an optimal insulin dosing algorithm for LY2605541 in patients with type 2 diabetes pretreated with basal insulin.

BACKGROUND: Because insulin dosing requires optimization of glycemic control, it is important to use a single metric of benefit and risk to determine best insulin dosing practices. We retrospectively applied a multiplicative clinical utility index (CUI) to a study of LY2605541 (Eli Lilly and Company, Indianapolis, IN), a novel, long-acting basal insulin. MATERIALS AND METHODS: A CUI was developed to transform the multidimensional problem of assessing benefit/risk of multiple dosing algorithms into a single decision-making metric to evaluate two LY2605541 dosing algorithms relative to the insulin glargine (GL) dosing algorithm. The CUI was applied to data in a 12-week, open-label, Phase 2 trial in patients with type 2 diabetes mellitus who were randomized to one of two dosing algorithms for LY2605541 (LY1 or LY2) or GL (algorithm similar to LY1). The CUI was created (via expert input) by weighing the relative benefit/risk of four components (glycosylated hemoglobin [HbA1c], percentage of patients with HbA1c ≤ 7%, hypoglycemia rate, and time to steady-state dose); individual utility values were multiplied to compute CUI values for LY1 and LY2 relative to GL, and bootstrap samples were used to determine variability. RESULTS: The mean CUI was 0.82 for LY1 and 1.35 for LY2. Based on 3,000 bootstrap samples, there was a 48% probability of LY2 performing better than LY1 and a 28% probability of LY1 performing better than LY2. CONCLUSIONS: CUI methodology, and in particular this CUI, is a useful tool for comparing dosing algorithms. Based on this CUI, LY2 is likely to be a better dosing algorithm than LY1.

Bayesian methods for design and analysis of safety trials.

Safety assessment is essential throughout medical product development. There has been increased awareness of the importance of safety trials recently, in part due to recent US Food and Drug Administration guidance related to thorough assessment of cardiovascular risk in the treatment of type 2 diabetes. Bayesian methods provide great promise for improving the conduct of safety trials. In this paper, the safety subteam of the Drug Information Association Bayesian Scientific Working Group evaluates challenges associated with current methods for designing and analyzing safety trials and provides an overview of several suggested Bayesian opportunities that may increase efficiency of safety trials along with relevant case examples.

Optimizing Drug Development Programs: Type 2 Diabetes Case Study.

Recently, consideration was given to the impact of dose selection strategies in phase IIb on the overall success of drug development programs. A natural next step is to simultaneously optimize design aspects of both phase IIB and phase III. We used type 2 diabetes as an example, including realistic regulatory and commercial scenarios for this indication. The expected net present value (eNPV) has been selected as the primary outcome because it naturally accommodates optimization, providing an explicit trade-off between the probability of success (PoS) and time delays and trial costs. Our findings are that larger studies and/or implementation of an adaptive design over a fixed design in phase IIb provide more precise dose selection and reduce the bias of treatment effects and uncertainty in the estimated eNPV within the range of sample sizes that we examined. Developers also have to ensure that dose selection criteria are consistent with development strategy and objectives.

Bayesian adaptive dose-finding studies with delayed responses.

In recent years, Bayesian response-adaptive designs have been used to improve the efficiency of learning in dose-finding studies. Many current methods for analyzing the data at the time of the interim analysis only use the data from patients who have completed the study. Therefore, data collected at intermediate time points are not used for decision making in these studies. However, in some disease areas such as diabetes and obesity, patients may need to be studied for several weeks or months for a drug effect to emerge. Additionally, slow enrollment rates can limit the number of patients who complete the study in a given period of time. Consequently, at the time of an interim analysis, there may be only a small proportion (e.g., 20%) of patients who have completed the study. In this paper, we propose a new Bayesian prediction model to incorporate all the data (from patients who have completed the study and those who have not completed) to make decisions about the study at the interim analysis. Examples of decisions made at the interim analysis include adaptive treatment allocation, dropping nonefficacious dose arms, stopping the study for positive efficacy, and stopping the study for futility. The model is able to handle incomplete longitudinal data including missing data considered missing at random (MAR). A utility-function-based decision rule is also discussed. The benefit of our new method is demonstrated through trial simulations. Three scenarios are examined, and the simulation results demonstrate that this new method outperforms traditional design with the same sample size in each of these scenarios.

Upper basilar artery aneurysms: oculomotor outcomes in 163 cases.

OBJECT: The purpose of this study was to identify factors predictive of postoperative oculomotor nerve palsy among patients who undergo surgery for distal basilar artery (BA) aneurysms. The data can be used to estimate preoperative risk in this population. The natural history of oculomotor nerve palsy in patients with good outcomes is also defined. METHODS: The cases of 163 patients with distal BA aneurysms, who were treated surgically between 1996 and 2002, were retrospectively studied to identify factors contributing to oculomotor nerve palsy. After the data had been collected, stepwise logistic regression procedures were used to determine the predictive effects of each variable on the development of oculomotor nerve palsy and to create a scoring system. Factors that interfered with resolution of oculomotor dysfunction in patients with good outcomes were also studied. Postoperative oculomotor nerve palsy occurred in 86 patients (52.8%) with distal BA aneurysms. The following factors were associated with postoperative oculomotor dysfunction, as determined by a categorical data analysis: (1) younger patient age (p < 0.001); (2) poor admission Hunt and Hess grade (p < 0.001); (3) use of temporary arterial occlusion (p < 0.001); 4) poor Glasgow Outcome Scale score (p < 0.001); and (5) the presence of a BA apex aneurysm that projected posteriorly (p < 0.001). For patients with good outcomes, postoperative oculomotor nerve palsy resolved completely within 3 months in 31 patients (52%) and within 6 months in 47 patients (80%). The projection of the BA aneurysm was associated with incomplete oculomotor recovery at 6 months postoperatively (p = 0.019). CONCLUSIONS: The results of this study can help identify patients with a high risk for the development of oculomotor nerve palsy. This may help neurosurgeons in preoperative planning and discussions.

Vertebral artery-posteroinferior cerebellar artery aneurysms: clinical and lower cranial nerve outcomes in 52 patients.

OBJECTIVE: To identify factors predictive of postoperative lower cranial nerve palsy (LCNP) among patients undergoing surgery for vertebral artery (VA)- posteroinferior cerebellar artery (PICA) aneurysms. The natural history of this LCNP is defined, and its effect on postoperative patient course is analyzed. No similar study has been described in the literature. METHODS: Fifty-two patients with VA-PICA aneurysms, who were treated surgically between 1996 and 2002, were retrospectively studied to identify factors contributing to postoperative LCNP. The effect of LCNP on intensive care unit stay and development of nosocomial pneumonia also was analyzed. All analyses were performed with Fisher's exact test. RESULTS: Postoperative LCNP occurred in 25 patients (48.1%) with VA-PICA aneurysms. Of the factors investigated, the use of temporary or total occlusion was associated with increased incidence of postoperative LCNP (P <0.001). The average length of stay in the intensive care unit was 13.8 days for patients with LCNP defined as moderate to severe, compared with 7.92 days for patients with LCNP defined as none or mild (P=0.0014). Nosocomial pneumonia occurred only in patients with moderate to severe LCNP (P=0.022). Postoperative LCNP resolved completely within 3 months in 12 patients (48%) and within 6 months in 19 patients (76%) . CONCLUSION: The results of this study can help to identify the effect and natural history of LCNP after surgical clipping of VA-PICA aneurysms. This information may assist neurosurgeons in expediting treatment, decrease the cost and length of hospital stays, and result in improved outcomes.