Effect of Neutralizing Monoclonal Antibody Treatment on Early Trajectories of Virologic and Immunologic Biomarkers in Patients Hospitalized With COVID-19

BACKGROUND

Neutralizing monoclonal antibodies (nmAbs) failed to show clear benefit for hospitalized patients with coronavirus disease 2019 (COVID-19). Dynamics of virologic and immunologic biomarkers remain poorly understood.

METHODS

Participants enrolled in the Therapeutics for Inpatients with COVID-19 trials were randomized to nmAb versus placebo. Longitudinal differences between treatment and placebo groups in levels of plasma nucleocapsid antigen (N-Ag), anti-nucleocapsid antibody, C-reactive protein, interleukin-6, and D-dimer at enrollment, day 1, 3, and 5 were estimated using linear mixed models. A 7-point pulmonary ordinal scale assessed at day 5 was compared using proportional odds models.

RESULTS

Analysis included 2149 participants enrolled between August 2020 and September 2021. Treatment resulted in 20% lower levels of plasma N-Ag compared with placebo (95% confidence interval, 12%-27%; P < .001), and a steeper rate of decline through the first 5 days (P < .001). The treatment difference did not vary between subgroups, and no difference was observed in trajectories of other biomarkers or the day 5 pulmonary ordinal scale.

CONCLUSIONS

Our study suggests that nmAb has an antiviral effect assessed by plasma N-Ag among hospitalized patients with COVID-19, with no blunting of the endogenous anti-nucleocapsid antibody response. No effect on systemic inflammation or day 5 clinical status was observed.

CLINICAL TRIALS REGISTRATION

NCT04501978.

Optimal timing for an accelerated interim futility analysis incorporating real world data

BACKGROUND

Randomized controlled trials include interim monitoring guidelines to stop early for safety, efficacy, or futility. Futility monitoring facilitates re-allocation of limited resources. However, conventional methods for interim futility monitoring require a trial to accrue nearly half of the outcome data to make a reliable early stopping decision, limiting its benefit. As early stopping for futility will not inflate type-I error, these analyses are an appealing venue for incorporating external data to improve efficiency.

METHODS

We propose a Bayesian approach to futility monitoring leveraging real world data using Semi-Supervised MIXture Multi-source Exchangeability Models, which accounts for both measured and unmeasured differences between data sources. We implement futility monitoring using predictive probabilities and investigate the optimal timing with respect to the expected sample size under the null hypothesis. Because we only incorporate external data during the interim futility analysis the proposed design is not limited by type-I error inflation.

RESULTS

When the external and trial data are exchangeable, the proposed method provides a roughly 70 person reduction in expected sample size under the null. Under scenarios where exchangeability does not hold, our approach still provides a 10-20 person reduction in expected sample size under the null with about 80% power.

CONCLUSIONS

External data borrowing in interim futility monitoring is a promising venue to improve trial efficiency without type-I error inflation. Approaches that are acceptable to regulatory authorities and leverage the complementary strengths of real world and trial data are vital to more efficiently allocate limited resources amongst clinical trials.

Network meta analysis to predict the efficacy of an approved treatment in a new indication

Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not widely used in practice. Instead, repurposing decisions are often based on subjective judgments from limited empirical evidence. In this article, we develop a novel Bayesian network meta-analysis (NMA) framework that can predict the efficacy of an approved treatment in a new indication and thereby identify candidate treatments for repurposing. We obtain predictions using two main steps: first, we use standard NMA modeling to estimate average relative effects from a network comprised of treatments studied in both indications in addition to one treatment studied in only one indication. Then, we model the correlation between relative effects using various strategies that differ in how they model treatments across indications and within the same drug class. We evaluate the predictive performance of each model using a simulation study and find that the model minimizing root mean squared error of the posterior median for the candidate treatment depends on the amount of available data, the level of correlation between indications, and whether treatment effects differ, on average, by drug class. We conclude by discussing an illustrative example in psoriasis and psoriatic arthritis and find that the candidate treatment has a high probability of success in a future trial.

Bayesian hierarchical models incorporating study-level covariates for multivariate meta-analysis of diagnostic tests without a gold standard with application to COVID-19

When evaluating a diagnostic test, it is common that a gold standard may not be available. One example is the diagnosis of SARS-CoV-2 infection using saliva sampling or nasopharyngeal swabs. Without a gold standard, a pragmatic approach is to postulate a "reference standard," defined as positive if either test is positive, or negative if both are negative. However, this pragmatic approach may overestimate sensitivities because subjects infected with SARS-CoV-2 may still have double-negative test results even when both tests exhibit perfect specificity. To address this limitation, we propose a Bayesian hierarchical model for simultaneously estimating sensitivity, specificity, and disease prevalence in the absence of a gold standard. The proposed model allows adjusting for study-level covariates. We evaluate the model performance using an example based on a recently published meta-analysis on the diagnosis of SARS-CoV-2 infection and extensive simulations. Compared with the pragmatic reference standard approach, we demonstrate that the proposed Bayesian method provides a more accurate evaluation of prevalence, specificity, and sensitivity in a meta-analytic framework.

Randomized controlled dose-escalation design to evaluate the safety of a novel pharmacological cardiopulmonary resuscitation strategy

BACKGROUND/AIMS

The motivating randomized controlled phase I trial evaluates three sodium nitroprusside doses in a novel sodium nitroprusside-enhanced cardiopulmonary resuscitation strategy for improved end-organ perfusion relative to local standard of care. Sodium nitroprusside is a vasodilator with an established safety profile in other indications, whereas the local standard of care uses vasoconstrictors, typically epinephrine. The purpose of the proposed trial is to identify the highest safe dose of sodium nitroprusside in this new context as excessive doses may cause severe hypotension with compromised end-organ perfusion.

METHODS

The proposed phase I trial design expands upon traditional dose-finding designs to include a randomized control arm, which is needed to assess safety through the relative increase in serum lactate on hospital admission. For guiding dose escalation, we propose and compare six Bayesian models which characterize expected serum lactate as a function of sodium nitroprusside dose and randomization group. Each model makes a different assumption about the expected change in serum lactate across control cohorts concurrently randomized with each dose. Model selection aims to minimize the expected number of times that a dose is incorrectly classified as safe or unsafe while sample size selection targets an expected number of incorrectly classified doses. Randomization is 1:1 for the initial cohort, and for subsequent cohorts is chosen to maximize the lower confidence bound.

RESULTS

The spike-and-slab model minimizes the expected number of times that a dose is incorrectly classified as safe or unsafe under the most scenarios in the motivating three-dose trial, but all six models exhibit relatively similar performance. A 2:1 randomization ratio for the second and third cohorts maximizes the lower confidence bound when using the spike-and-slab model. With the optimal design, on average, 70 individuals will ensure 1 incorrectly classified dose in 6 opportunities.

CONCLUSION

We recommend that the motivating trial use the spike-and-slab model with a 1:1 randomization ratio for the initial cohort and 2:1 randomization ratio for subsequent cohorts; however, the simpler fixed effects approaches performed similarly well.

Strategies used for the COVID-OUT decentralized trial of outpatient treatment of SARS-CoV-2

The COVID-19 pandemic accelerated the development of decentralized clinical trials (DCT). DCT's are an important and pragmatic method for assessing health outcomes yet comprise only a minority of clinical trials, and few published methodologies exist. In this report, we detail the operational components of COVID-OUT, a decentralized, multicenter, quadruple-blinded, randomized trial that rapidly delivered study drugs nation-wide. The trial examined three medications (metformin, ivermectin, and fluvoxamine) as outpatient treatment of SARS-CoV-2 for their effectiveness in preventing severe or long COVID-19. Decentralized strategies included HIPAA-compliant electronic screening and consenting, prepacking investigational product to accelerate delivery after randomization, and remotely confirming participant-reported outcomes. Of the 1417 individuals with the intention-to-treat sample, the remote nature of the study caused an additional 94 participants to not take any doses of study drug. Therefore, 1323 participants were in the modified intention-to-treat sample, which was the a priori primary study sample. Only 1.4% of participants were lost to follow-up. Decentralized strategies facilitated the successful completion of the COVID-OUT trial without any in-person contact by expediting intervention delivery, expanding trial access geographically, limiting contagion exposure, and making it easy for participants to complete follow-up visits. Remotely completed consent and follow-up facilitated enrollment.

Modified interactive Q-learning for attenuating the impact of model misspecification with treatment effect heterogeneity

A sequential multiple assignment randomized trial, which incorporates multiple stages of randomization, is a popular approach for collecting data to inform personalized and adaptive treatments. There is an extensive literature on statistical methods to analyze data collected in sequential multiple assignment randomized trials and estimate the optimal dynamic treatment regime. Q-learning with linear regression is widely used for this purpose due to its ease of implementation. However, model misspecification is a common problem with this approach, and little attention has been given to the impact of model misspecification when treatment effects are heterogeneous across subjects. This article describes the integrative impact of two possible types of model misspecification related to treatment effect heterogeneity: omitted early-stage treatment effects in late-stage main effect model, and violated linearity assumption between pseudo-outcomes and predictors despite non-linearity arising from the optimization operation. The proposed method, aiming to deal with both types of misspecification concomitantly, builds interactive models into modified parametric Q-learning with Murphy's regret function. Simulations show that the proposed method is robust to both sources of model misspecification. The proposed method is applied to a two-stage sequential multiple assignment randomized trial with embedded tailoring aimed at reducing binge drinking in first-year college students.

Outpatient treatment of COVID-19 and incidence of post-COVID-19 condition over 10 months (COVID-OUT): a multicentre, randomised, quadruple-blind, parallel-group, phase 3 trial

BACKGROUND

Post-COVID-19 condition (also known as long COVID) is an emerging chronic illness potentially affecting millions of people. We aimed to evaluate whether outpatient COVID-19 treatment with metformin, ivermectin, or fluvoxamine soon after SARS-CoV-2 infection could reduce the risk of long COVID.

METHODS

We conducted a decentralised, randomised, quadruple-blind, parallel-group, phase 3 trial (COVID-OUT) at six sites in the USA. We included adults aged 30-85 years with overweight or obesity who had COVID-19 symptoms for fewer than 7 days and a documented SARS-CoV-2 positive PCR or antigen test within 3 days before enrolment. Participants were randomly assigned via 2 × 3 parallel factorial randomisation (1:1:1:1:1:1) to receive metformin plus ivermectin, metformin plus fluvoxamine, metformin plus placebo, ivermectin plus placebo, fluvoxamine plus placebo, or placebo plus placebo. Participants, investigators, care providers, and outcomes assessors were masked to study group assignment. The primary outcome was severe COVID-19 by day 14, and those data have been published previously. Because the trial was delivered remotely nationwide, the a priori primary sample was a modified intention-to-treat sample, meaning that participants who did not receive any dose of study treatment were excluded. Long COVID diagnosis by a medical provider was a prespecified, long-term secondary outcome. This trial is complete and is registered with ClinicalTrials.gov, NCT04510194.

FINDINGS

Between Dec 30, 2020, and Jan 28, 2022, 6602 people were assessed for eligibility and 1431 were enrolled and randomly assigned. Of 1323 participants who received a dose of study treatment and were included in the modified intention-to-treat population, 1126 consented for long-term follow-up and completed at least one survey after the assessment for long COVID at day 180 (564 received metformin and 562 received matched placebo; a subset of participants in the metformin vs placebo trial were also randomly assigned to receive ivermectin or fluvoxamine). 1074 (95%) of 1126 participants completed at least 9 months of follow-up. 632 (56·1%) of 1126 participants were female and 494 (43·9%) were male; 44 (7·0%) of 632 women were pregnant. The median age was 45 years (IQR 37-54) and median BMI was 29·8 kg/m2 (IQR 27·0-34·2). Overall, 93 (8·3%) of 1126 participants reported receipt of a long COVID diagnosis by day 300. The cumulative incidence of long COVID by day 300 was 6·3% (95% CI 4·2-8·2) in participants who received metformin and 10·4% (7·8-12·9) in those who received identical metformin placebo (hazard ratio [HR] 0·59, 95% CI 0·39-0·89; p=0·012). The metformin beneficial effect was consistent across prespecified subgroups. When metformin was started within 3 days of symptom onset, the HR was 0·37 (95% CI 0·15-0·95). There was no effect on cumulative incidence of long COVID with ivermectin (HR 0·99, 95% CI 0·59-1·64) or fluvoxamine (1·36, 0·78-2·34) compared with placebo.

INTERPRETATION

Outpatient treatment with metformin reduced long COVID incidence by about 41%, with an absolute reduction of 4·1%, compared with placebo. Metformin has clinical benefits when used as outpatient treatment for COVID-19 and is globally available, low-cost, and safe.

FUNDING

Parsemus Foundation; Rainwater Charitable Foundation; Fast Grants; UnitedHealth Group Foundation; National Institute of Diabetes, Digestive and Kidney Diseases; National Institutes of Health; and National Center for Advancing Translational Sciences.

Outcome trajectory estimation for optimal dynamic treatment regimes with repeated measures

In recent sequential multiple assignment randomized trials, outcomes were assessed multiple times to evaluate longer-term impacts of the dynamic treatment regimes (DTRs). Q-learning requires a scalar response to identify the optimal DTR. Inverse probability weighting may be used to estimate the optimal outcome trajectory, but it is inefficient, susceptible to model mis-specification, and unable to characterize how treatment effects manifest over time. We propose modified Q-learning with generalized estimating equations to address these limitations and apply it to the M-bridge trial, which evaluates adaptive interventions to prevent problematic drinking among college freshmen. Simulation studies demonstrate our proposed method improves efficiency and robustness.

Metformin reduces SARS-CoV-2 in a Phase 3 Randomized Placebo Controlled Clinical Trial

Current antiviral treatment options for SARS-CoV-2 infections are not available globally, cannot be used with many medications, and are limited to virus-specific targets.1-3 Biophysical modeling of SARS-CoV-2 replication predicted that protein translation is an especially attractive target for antiviral therapy.4 Literature review identified metformin, widely known as a treatment for diabetes, as a potential suppressor of protein translation via targeting of the host mTor pathway.5 In vitro, metformin has antiviral activity against RNA viruses including SARS-CoV-2.6,7 In the COVID-OUT phase 3, randomized, placebo-controlled trial of outpatient treatment of COVID-19, metformin had a 42% reduction in ER visits/hospitalizations/death through 14 days; a 58% reduction in hospitalizations/death through 28 days, and a 42% reduction in Long COVID through 10 months.8,9 Here we show viral load analysis of specimens collected in the COVID-OUT trial that the mean SARS-CoV-2 viral load was reduced 3.6-fold with metformin relative to placebo (-0.56 log10 copies/mL; 95%CI, -1.05 to -0.06, p=0.027) while there was no virologic effect for ivermectin or fluvoxamine vs placebo. The metformin effect was consistent across subgroups and with emerging data.10,11 Our results demonstrate, consistent with model predictions, that a safe, widely available,12 well-tolerated, and inexpensive oral medication, metformin, can be repurposed to significantly reduce SARS-CoV-2 viral load.

Neuromodulation Through Spinal Cord Stimulation Restores Ability to Voluntarily Cycle After Motor Complete Paraplegia

Abstract Epidural spinal cord stimulation (eSCS) of the lower thoracic spinal cord has been shown to partially restore volitional movement in patients with complete chronic spinal cord injury (cSCI). Combining eSCS with intensive locomotor training improves motor function, including standing and stepping, but many patients with cSCI suffer from long-standing muscle atrophy and loss of bone mineral density, which may prohibit safe implementation. Safe, accessible, and effective avenues for pairing neuromodulation with activity-based therapy remain unexplored. Cycling is one such option that can be utilized as an eSCS therapy given its low-risk and low-weight-bearing requirement. We investigated the feasibility and kinematics of motor-assisted and passive cycle-based therapy for cSCI patients with epidural spinal cord stimulation. Seven participants who underwent spinal cord stimulation surgery in the Epidural Stimulation After Neurologic Damage (E-STAND) trial (NCT03026816) participated in a cycling task using the motor assist MOTOmed Muvi 300. A factorial design was used such that participants were asked to cycle with and without conscious effort with and without stimulation. We used mixed effects models assessing maximum power output and time pedaling unassisted to evaluate the interaction between stimulation and conscious effort. Cycling was well-tolerated and we observed no adverse events, including in participants up to 17 years post-initial injury and up to 58 years old. All participants were found to be able to pedal without motor assist, which primarily occurred when stimulation and effort were applied together (p = 0.001). Additionally, the combination of stimulation and intention was significantly associated with higher maximum power production (p < 0.0001) and distance pedaled (p = 0.0001). No association was found between volitional movement and participant factors: age, time since injury, and spinal cord atrophy. With stimulation and conscious effort, all participants were able to achieve active cycling without motor assistance. Thus, our stationary cycling factorial study design demonstrated volitional movement restoration with eSCS in a diverse study population of cSCI participants. Further, motor-assist cycling was well-tolerated without any adverse events. Cycling has the potential to be a safe research assessment and physical therapy modality for cSCI patients utilizing eSCS who have a high risk of injury with weight bearing exercise. The cycling modality in this study was demonstrated to be a straightforward assessment of motor function and safe for all participants regardless of age or time since initial injury.

Outpatient treatment of Covid-19 with metformin, ivermectin, and fluvoxamine and the development of Long Covid over 10-month follow-up

Background

Long Covid is an emerging chronic illness potentially affecting millions, sometimes preventing the ability to work or participate in normal daily activities. COVID-OUT was an investigator-initiated, multi-site, phase 3, randomized, quadruple-blinded placebo-controlled clinical trial (NCT04510194). The design simultaneously assessed three oral medications (metformin, ivermectin, fluvoxamine) using two by three parallel treatment factorial assignment to efficiently share placebo controls and assessed Long Covid outcomes for 10 months to understand whether early outpatient treatment of SARS-CoV-2 with metformin, ivermectin, or fluvoxamine prevents Long Covid.

Methods

This was a decentralized, remotely delivered trial in the US of 1,125 adults age 30 to 85 with overweight or obesity, fewer than 7 days of symptoms, and enrolled within three days of a documented SARS-CoV-2 infection. Immediate release metformin titrated over 6 days to 1,500mg per day 14 days total; ivermectin 430mcg/kg/day for 3 days; fluvoxamine, 50mg on day one then 50mg twice daily through 14 days. Medical-provider diagnosis of Long Covid, reported by participant by day 300 after randomization was a pre-specified secondary outcome; the primary outcome of the trial was severe Covid by day 14.

Result

The median age was 45 years (IQR 37 to 54), 56% female of whom 7% were pregnant. Two percent identified as Native American; 3.7% as Asian; 7.4% as Black/African American; 82.8% as white; and 12.7% as Hispanic/Latino. The median BMI was 29.8 kg/m2 (IQR 27 to 34); 51% had a BMI >30kg/m2. Overall, 8.4% reported having received a diagnosis of Long Covid from a medical provider: 6.3% in the metformin group and 10.6% in the metformin control; 8.0% in the ivermectin group and 8.1% in the ivermectin control; and 10.1% in the fluvoxamine group and 7.5% in the fluvoxamine control. The Hazard Ratio (HR) for Long Covid in the metformin group versus control was 0.58 (95% CI 0.38 to 0.88); 0.99 (95% CI 0.592 to 1.643) in the ivermectin group; and 1.36 in the fluvoxamine group (95% CI 0.785 to 2.385).

Conclusions

There was a 42% relative decrease in the incidence of Long Covid in the metformin group compared to its blinded control in a secondary outcome of this randomized phase 3 trial.

Design considerations and analytical framework for reliably identifying a beneficial individualized treatment rule

An individualized treatment rule (ITR) formalizes personalized medicine by assigning treatment as a function of patients' clinical information, which contrasts with a static treatment rule that assigns everyone the same treatment. ITR identification has become a common aim in randomized clinical trials but sample size considerations for this aim are lacking. One approach is to select a sample size that will reliably identify an ITR with a performance close to the theoretical optimal rule. However, this approach could still lead to identifying ITRs that perform worse than the optimal static rule, particularly in the absence of substantial effect heterogeneity. This limitation motivates sample size considerations aimed at reliable identification of a beneficial ITR, which outperforms the optimal static rule, and analysis methods that identify the estimated optimal static rule when there is substantial uncertainty about whether an ITR will improve outcomes. To address these limitations, we propose a sample size approach based on the probability of identifying a beneficial ITR and introduce an approach for selecting the LASSO penalty parameter such that in the absence of treatment effect heterogeneity the estimated optimal static rule is identified with high probability. We apply these approaches to the PLUTO trial aimed at developing methods to assist with smoking cessation.

Tixagevimab-cilgavimab for treatment of patients hospitalised with COVID-19: a randomised, double-blind, phase 3 trial

BACKGROUND

Tixagevimab-cilgavimab is a neutralising monoclonal antibody combination hypothesised to improve outcomes for patients hospitalised with COVID-19. We aimed to compare tixagevimab-cilgavimab versus placebo, in patients receiving remdesivir and other standard care.

METHODS

In a randomised, double-blind, phase 3, placebo-controlled trial, adults with symptoms for up to 12 days and hospitalised for COVID-19 at 81 sites in the USA, Europe, Uganda, and Singapore were randomly assigned in a 1:1 ratio to receive intravenous tixagevimab 300 mg-cilgavimab 300 mg or placebo, in addition to remdesivir and other standard care. Patients were excluded if they had acute organ failure including receipt of invasive mechanical ventilation, extracorporeal membrane oxygenation, vasopressor therapy, mechanical circulatory support, or new renal replacement therapy. The study drug was prepared by an unmasked pharmacist; study participants, site study staff, investigators, and clinical providers were masked to study assignment. The primary outcome was time to sustained recovery up to day 90, defined as 14 consecutive days at home after hospital discharge, with co-primary analyses for the full cohort and for participants who were neutralising antibody-negative at baseline. Efficacy and safety analyses were done in the modified intention-to-treat population, defined as participants who received a complete or partial infusion of tixagevimab-cilgavimab or placebo. This study is registered with ClinicalTrials.gov, NCT04501978 and the participant follow-up is ongoing.

FINDINGS

From Feb 10 to Sept 30, 2021, 1455 patients were randomly assigned and 1417 in the primary modified intention-to-treat population were infused with tixagevimab-cilgavimab (n=710) or placebo (n=707). The estimated cumulative incidence of sustained recovery was 89% for tixagevimab-cilgavimab and 86% for placebo group participants at day 90 in the full cohort (recovery rate ratio [RRR] 1·08 [95% CI 0·97-1·20]; p=0·21). Results were similar in the seronegative subgroup (RRR 1·14 [0·97-1·34]; p=0·13). Mortality was lower in the tixagevimab-cilgavimab group (61 [9%]) versus placebo group (86 [12%]; hazard ratio [HR] 0·70 [95% CI 0·50-0·97]; p=0·032). The composite safety outcome occurred in 178 (25%) tixagevimab-cilgavimab and 212 (30%) placebo group participants (HR 0·83 [0·68-1·01]; p=0·059). Serious adverse events occurred in 34 (5%) participants in the tixagevimab-cilgavimab group and 38 (5%) in the placebo group.

INTERPRETATION

Among patients hospitalised with COVID-19 receiving remdesivir and other standard care, tixagevimab-cilgavimab did not improve the primary outcome of time to sustained recovery but was safe and mortality was lower.

FUNDING

US National Institutes of Health (NIH) and Operation Warp Speed.

Impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Vaccination and Booster on Coronavirus Disease 2019 (COVID-19) Symptom Severity Over Time in the COVID-OUT Trial

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination has decreasing protection from acquiring any infection with emergence of new variants; however, vaccination continues to protect against progression to severe coronavirus disease 2019 (COVID-19). The impact of vaccination status on symptoms over time is less clear.

METHODS

Within a randomized trial on early outpatient COVID-19 therapy testing metformin, ivermectin, and/or fluvoxamine, participants recorded symptoms daily for 14 days. Participants were given a paper symptom diary allowing them to circle the severity of 14 symptoms as none (0), mild (1), moderate (2), or severe (3). This is a secondary analysis of clinical trial data on symptom severity over time using generalized estimating equations comparing those unvaccinated, SARS-CoV-2 vaccinated with primary vaccine series only, or vaccine-boosted.

RESULTS

The parent clinical trial prospectively enrolled 1323 participants, of whom 1062 (80%) prospectively recorded some daily symptom data. Of these, 480 (45%) were unvaccinated, 530 (50%) were vaccinated with primary series only, and 52 (5%) vaccine-boosted. Overall symptom severity was least for the vaccine-boosted group and most severe for unvaccinated at baseline and over the 14 days (P < .001). Individual symptoms were least severe in the vaccine-boosted group including cough, chills, fever, nausea, fatigue, myalgia, headache, and diarrhea, as well as smell and taste abnormalities. Results were consistent over Delta and Omicron variant time periods.

CONCLUSIONS

SARS-CoV-2 vaccine-boosted participants had the least severe symptoms during COVID-19, which abated the quickest over time. Clinical Trial Registration. NCT04510194.

Renin-Angiotensin System Inhibitors in Patients With COVID-19: A Meta-Analysis of Randomized Controlled Trials Led by the International Society of Hypertension

Background

Published randomized controlled trials are underpowered for binary clinical end points to assess the safety and efficacy of renin‐angiotensin system inhibitors (RASi) in adults with COVID‐19. We therefore performed a meta‐analysis to assess the safety and efficacy of RASi in adults with COVID‐19.

Methods and Results

MEDLINE, EMBASE, ClinicalTrials.gov, and the Cochrane Controlled Trial Register were searched for randomized controlled trials that randomly assigned patients with COVID‐19 to RASi continuation/commencement versus no RASi therapy. The primary outcome was all‐cause mortality at ≤30 days. A total of 14 randomized controlled trials met the inclusion criteria and enrolled 1838 participants (aged 59 years, 58% men, mean follow‐up 26 days). Of the trials, 11 contributed data. We found no effect of RASi versus control on all‐cause mortality (7.2% versus 7.5%; relative risk [RR], 0.95; [95% CI, 0.69–1.30]) either overall or in subgroups defined by COVID‐19 severity or trial type. Network meta‐analysis identified no difference between angiotensin‐converting enzyme inhibitors versus angiotensin II receptor blockers. RASi users had a nonsignificant reduction in acute myocardial infarction (2.1% versus 3.6%; RR, 0.59; [95% CI, 0.33–1.06]), but increased risk of acute kidney injury (7.0% versus 3.6%; RR, 1.82; [95% CI, 1.05–3.16]), in trials that initiated and continued RASi. There was no increase in need for dialysis or differences in congestive cardiac failure, cerebrovascular events, venous thromboembolism, hospitalization, intensive care admission, inotropes, or mechanical ventilation.

Conclusions

This meta‐analysis of randomized controlled trials evaluating angiotensin‐converting enzyme inhibitors/angiotensin II receptor blockers versus control in patients with COVID‐19 found no difference in all‐cause mortality, a borderline decrease in myocardial infarction, and an increased risk of acute kidney injury with RASi. Our findings provide strong evidence that RASi can be used safely in patients with COVID‐19.

Randomized Trial of Metformin, Ivermectin, and Fluvoxamine for Covid-19

BACKGROUND

Early treatment to prevent severe coronavirus disease 2019 (Covid-19) is an important component of the comprehensive response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic.

METHODS

In this phase 3, double-blind, randomized, placebo-controlled trial, we used a 2-by-3 factorial design to test the effectiveness of three repurposed drugs - metformin, ivermectin, and fluvoxamine - in preventing serious SARS-CoV-2 infection in nonhospitalized adults who had been enrolled within 3 days after a confirmed diagnosis of infection and less than 7 days after the onset of symptoms. The patients were between the ages of 30 and 85 years, and all had either overweight or obesity. The primary composite end point was hypoxemia (≤93% oxygen saturation on home oximetry), emergency department visit, hospitalization, or death. All analyses used controls who had undergone concurrent randomization and were adjusted for SARS-CoV-2 vaccination and receipt of other trial medications.

RESULTS

A total of 1431 patients underwent randomization; of these patients, 1323 were included in the primary analysis. The median age of the patients was 46 years; 56% were female (6% of whom were pregnant), and 52% had been vaccinated. The adjusted odds ratio for a primary event was 0.84 (95% confidence interval [CI], 0.66 to 1.09; P = 0.19) with metformin, 1.05 (95% CI, 0.76 to 1.45; P = 0.78) with ivermectin, and 0.94 (95% CI, 0.66 to 1.36; P = 0.75) with fluvoxamine. In prespecified secondary analyses, the adjusted odds ratio for emergency department visit, hospitalization, or death was 0.58 (95% CI, 0.35 to 0.94) with metformin, 1.39 (95% CI, 0.72 to 2.69) with ivermectin, and 1.17 (95% CI, 0.57 to 2.40) with fluvoxamine. The adjusted odds ratio for hospitalization or death was 0.47 (95% CI, 0.20 to 1.11) with metformin, 0.73 (95% CI, 0.19 to 2.77) with ivermectin, and 1.11 (95% CI, 0.33 to 3.76) with fluvoxamine.

CONCLUSIONS

None of the three medications that were evaluated prevented the occurrence of hypoxemia, an emergency department visit, hospitalization, or death associated with Covid-19. (Funded by the Parsemus Foundation and others; COVID-OUT ClinicalTrials.gov number, NCT04510194.).

An alternative metric for evaluating the potential patient benefit of response-adaptive randomization procedures

When planning a two-arm group sequential clinical trial with a binary primary outcome that has severe implications for quality of life (e.g., mortality), investigators may strive to find the design that maximizes in-trial patient benefit. In such cases, Bayesian response-adaptive randomization (BRAR) is often considered because it can alter the allocation ratio throughout the trial in favor of the treatment that is currently performing better. Although previous studies have recommended using fixed randomization over BRAR based on patient benefit metrics calculated from the realized trial sample size, these previous comparisons have been limited by failures to hold type I and II error rates constant across designs or consider the impacts on all individuals directly affected by the design choice. In this paper, we propose a metric for comparing designs with the same type I and II error rates that reflects expected outcomes among individuals who would participate in the trial if enrollment is open when they become eligible. We demonstrate how to use the proposed metric to guide the choice of design in the context of two recent trials in persons suffering out of hospital cardiac arrest. Using computer simulation, we demonstrate that various implementations of group sequential BRAR offer modest improvements with respect to the proposed metric relative to conventional group sequential monitoring alone. This article is protected by copyright. All rights reserved.

Efficacy of Losartan in Hospitalized Patients With COVID-19-Induced Lung Injury: A Randomized Clinical Trial

Importance

SARS-CoV-2 viral entry may disrupt angiotensin II (AII) homeostasis, contributing to COVID-19 induced lung injury. AII type 1 receptor blockade mitigates lung injury in preclinical models, although data in humans with COVID-19 remain mixed.

Objective

To test the efficacy of losartan to reduce lung injury in hospitalized patients with COVID-19.

Design, Setting, and Participants

This blinded, placebo-controlled randomized clinical trial was conducted in 13 hospitals in the United States from April 2020 to February 2021. Hospitalized patients with COVID-19 and a respiratory sequential organ failure assessment score of at least 1 and not already using a renin-angiotensin-aldosterone system (RAAS) inhibitor were eligible for participation. Data were analyzed from April 19 to August 24, 2021.

Interventions

Losartan 50 mg orally twice daily vs equivalent placebo for 10 days or until hospital discharge.

Main Outcomes and Measures

The primary outcome was the imputed arterial partial pressure of oxygen to fraction of inspired oxygen (Pao2:Fio2) ratio at 7 days. Secondary outcomes included ordinal COVID-19 severity; days without supplemental o2, ventilation, or vasopressors; and mortality. Losartan pharmacokinetics and RAAS components (AII, angiotensin-[1-7] and angiotensin-converting enzymes 1 and 2)] were measured in a subgroup of participants.

Results

A total of 205 participants (mean [SD] age, 55.2 [15.7] years; 123 [60.0%] men) were randomized, with 101 participants assigned to losartan and 104 participants assigned to placebo. Compared with placebo, losartan did not significantly affect Pao2:Fio2 ratio at 7 days (difference, -24.8 [95%, -55.6 to 6.1]; P = .12). Compared with placebo, losartan did not improve any secondary clinical outcomes and led to fewer vasopressor-free days than placebo (median [IQR], 9.4 [9.1-9.8] vasopressor-free days vs 8.7 [8.2-9.3] vasopressor-free days).

Conclusions and Relevance

This randomized clinical trial found that initiation of orally administered losartan to hospitalized patients with COVID-19 and acute lung injury did not improve Pao2:Fio2 ratio at 7 days. These data may have implications for ongoing clinical trials.

Trial Registration

ClinicalTrials.gov Identifier: NCT04312009.

Responses to a Neutralizing Monoclonal Antibody for Hospitalized Patients With COVID-19 According to Baseline Antibody and Antigen Levels : A Randomized Controlled Trial

BACKGROUND

In a randomized, placebo-controlled, clinical trial, bamlanivimab, a SARS-CoV-2-neutralizing monoclonal antibody, given in combination with remdesivir, did not improve outcomes among hospitalized patients with COVID-19 based on an early futility assessment.

OBJECTIVE

To evaluate the a priori hypothesis that bamlanivimab has greater benefit in patients without detectable levels of endogenous neutralizing antibody (nAb) at study entry than in those with antibodies, especially if viral levels are high.

DESIGN

Randomized, placebo-controlled trial. (ClinicalTrials.gov: NCT04501978).

SETTING

Multicenter trial.

PATIENTS

Hospitalized patients with COVID-19 without end-organ failure.

INTERVENTION

Bamlanivimab (7000 mg) or placebo.

MEASUREMENTS

Antibody, antigen, and viral RNA levels were centrally measured on stored specimens collected at baseline. Patients were followed for 90 days for sustained recovery (defined as discharge to home and remaining home for 14 consecutive days) and a composite safety outcome (death, serious adverse events, organ failure, or serious infections).

RESULTS

Among 314 participants (163 receiving bamlanivimab and 151 placebo), the median time to sustained recovery was 19 days and did not differ between the bamlanivimab and placebo groups (subhazard ratio [sHR], 0.99 [95% CI, 0.79 to 1.22]; sHR > 1 favors bamlanivimab). At entry, 50% evidenced production of anti-spike nAbs; 50% had SARS-CoV-2 nucleocapsid plasma antigen levels of at least 1000 ng/L. Among those without and with nAbs at study entry, the sHRs were 1.24 (CI, 0.90 to 1.70) and 0.74 (CI, 0.54 to 1.00), respectively (nominal P for interaction = 0.018). The sHR (bamlanivimab vs. placebo) was also more than 1 for those with plasma antigen or nasal viral RNA levels above median level at entry and was greatest for those without antibodies and with elevated levels of antigen (sHR, 1.48 [CI, 0.99 to 2.23]) or viral RNA (sHR, 1.89 [CI, 1.23 to 2.91]). Hazard ratios for the composite safety outcome (<1 favors bamlanivimab) also differed by serostatus at entry: 0.67 (CI, 0.37 to 1.20) for those without and 1.79 (CI, 0.92 to 3.48) for those with nAbs.

LIMITATION

Subgroup analysis of a trial prematurely stopped because of futility; small sample size; multiple subgroups analyzed.

CONCLUSION

Efficacy and safety of bamlanivimab may differ depending on whether an endogenous nAb response has been mounted. The limited sample size of the study does not allow firm conclusions based on these findings, and further independent trials are required that assess other types of passive immune therapies in the same patient setting.

PRIMARY FUNDING SOURCE

U.S. government Operation Warp Speed and National Institute of Allergy and Infectious Diseases.

Body mass index prediction rule for mid-upper arm circumference: the atherosclerosis risk in communities study

OBJECTIVES

Electronic health records (EHR) are a convenient data source for clinical trial recruitment and allow for inexpensive participant screening. However, EHR may lack pertinent screening variables. One strategy is to identify surrogate EHR variables which can predict the screening variable of interest. In this article, we use BMI to develop a prediction rule for arm circumference using data from the Atherosclerosis Risk in Communities (ARIC) Study. This work applies to EHR patient screening for clinical trials of hypertension.

METHODS

We included 11 585 participants aged 52-75 years with BMI and arm circumference measured at ARIC follow-up visit 4 (1996-1998). We selected the following arm circumference cutpoints based on the American Heart Association recommendations for blood pressure (BP) cuffs: small adult (≤26 cm), adult (≤34 cm) and large adult (≤44 cm). We calculated the sensitivity and specificity of BMI values for predicting arm circumference using receiver operating characteristic curves. We report the BMI threshold that maximized Youden's Index for each arm circumference upper limit of a BP cuff.

RESULTS

Participants' mean BMI and arm circumference were 28.8 ± 5.6 kg/m2 and 33.4 ± 4.3 cm, respectively. The BMI-arm circumference Pearson's correlation coefficient was 0.86. The BMI threshold for arm circumference≤26 cm was 23.0 kg/m2, arm circumference≤34 cm was 29.2 kg/m2 and arm circumference≤44 cm was 37.4 kg/m2. Only the BMI threshold for arm circumference≤34 cm varied significantly by sex.

CONCLUSIONS

BMI predicts arm circumference with high sensitivity and specificity and can be an accurate surrogate variable for arm circumference. These findings are useful for participant screening for hypertension trials. Providers can use this information to counsel patients on appropriate cuff size for BP self-monitoring.

Design and implementation of an international, multi-arm, multi-stage platform master protocol for trials of novel SARS-CoV-2 antiviral agents: Therapeutics for Inpatients with COVID-19 (TICO/ACTIV-3)

BACKGROUND/AIMS

Safe and effective therapies for COVID-19 are urgently needed. In order to meet this need, the Accelerating COVID-19 Therapeutic Interventions and Vaccines public-private partnership initiated the Therapeutics for Inpatients with COVID-19. Therapeutics for Inpatients with COVID-19 is a multi-arm, multi-stage platform master protocol, which facilitates the rapid evaluation of the safety and efficacy of novel candidate antiviral therapeutic agents for adults hospitalized with COVID-19. Five agents have so far entered the protocol, with rapid answers already provided for three of these. Other agents are expected to enter the protocol throughout 2021. This protocol contains a number of key design and implementation features that, along with challenges faced by the protocol team, are presented and discussed.

METHODS

Three clinical trial networks, encompassing a global network of clinical sites, participated in the protocol development and implementation. Therapeutics for Inpatients with COVID-19 utilizes a multi-arm, multi-stage design with an agile and robust approach to futility and safety evaluation at 300 patients enrolled, with subsequent expansion to full sample size and an expanded target population if the agent shows an acceptable safety profile and evidence of efficacy. Rapid recruitment to multiple agents is enabled through the sharing of placebo, the confining of agent-specific information to protocol appendices, and modular consent forms. In collaboration with the Food and Drug Administration, a thorough safety data collection and Data and Safety Monitoring Board schedule was developed for the study of potential therapeutic agents with limited in-human data in hospitalized patients with COVID-19.

RESULTS

As of 8 August 2021, five agents have entered the Therapeutics for Inpatients with COVID-19 master protocol and a total of 1909 participants have been randomized to one of these agents or matching placebo. There were a number of challenges faced by the study team that needed to be overcome in order to successfully implement Therapeutics for Inpatients with COVID-19 across a global network of sites. These included ensuring drug supply and reliable recruitment allowing for changing infection rates across the global network of sites, the need to balance the collection of data and samples without overburdening clinical staff and obtaining regulatory approvals across a global network of sites.

CONCLUSION

Through a robust multi-network partnership, the Therapeutics for Inpatients with COVID-19 protocol has been successfully used across a global network of sites for rapid generation of efficacy data on multiple novel antiviral agents. The protocol design and implementation features used in this protocol, and the approaches to address challenges, will have broader applicability. Mechanisms to facilitate improved communication and harmonization among country-specific regulatory bodies are required to achieve the full potential of this approach in dealing with a global outbreak.

Bayesian variable selection in hierarchical difference-in-differences models

A popular method for estimating a causal treatment effect with observational data is the difference-in-differences model. In this work, we consider an extension of the classical difference-in-differences setting to the hierarchical context in which data cannot be matched at the most granular level. Our motivating example is an application to assess the impact of primary care redesign policy on diabetes outcomes in Minnesota, in which the policy is administered at the clinic level and individual outcomes are not matched from pre- to post-intervention. We propose a Bayesian hierarchical difference-in-differences model, which estimates the policy effect by regressing the treatment on a latent variable representing the mean change in group-level outcome. We present theoretical and empirical results showing a hierarchical difference-in-differences model that fails to adjust for a particular class of confounding variables, biases the policy effect estimate. Using a structured Bayesian spike-and-slab model that leverages the temporal structure of the difference-in-differences context, we propose and implement variable selection approaches that target sets of confounding variables leading to unbiased and efficient estimation of the policy effect. We evaluate the methods' properties through simulation, and we use them to assess the impact of primary care redesign of clinics in Minnesota on the management of diabetes outcomes from 2008 to 2017.

Feasibility of an Exercise and CBT Intervention for Treatment of Depression: A Pilot Randomized Controlled Trial

Depression (DEP) is prevalent and current treatments are ineffective for many people. This pilot study's purpose was to assess the feasibility, acceptability, and plausible efficacy of an 8-week intervention employing 30 min of prescribed moderate intensity exercise ("ActiveCBT") compared to 30 min of usual activities ("CalmCBT") immediately prior to weekly online CBT sessions. Ten adults with DSM-5-diagnosed current DEP were randomized to groups and completed: an intake assessment, eight weekly CBT sessions, final assessment, and 3-month follow-up. ActiveCBT participants were prescribed 30-min of moderate exercise immediately prior to each standardized 50-min CBT session. CalmCBT participants continued with normal activities for 30 min before therapy. Questionnaires regarding DEP symptom severity (Patient Health Questionnaire-9 [PHQ-9]), between-session effectiveness (Behavioral Activation for Depression Survey [BADS], Automatic Thoughts Questionnaire [ATQ]), in-session effectiveness (Working Alliance Inventory-Short Revised [WAI]), and state anhedonia (Dimension Analog Rating Scale [DARS], Visual Analog Scale [VAS]; assessed 3 times: before Active/Calm condition, after, and after therapy) were completed each week. Therapy fidelity ratings were independently coded via a standardized codebook. The Structured Clinical Interview for DSM-5 (SCID) and Hamilton Rating Scale for Depression (HAMD) were used to assess DEP at intake, final, and 3-month follow-up. We found strong feasibility and acceptability (100% adherence, 100% retention at final visit, 74.6% therapy fidelity, and high patient satisfaction ratings). Differences between groups favoring ActiveCBT in anhedonia (DARS, Hedges' g = 0.92; VAS, g = 3.16), within- (WAI, g = 0.1.10), and between-session effectiveness (ATQ g = -0.65; BADS g = -1.40), suggest plausible efficacy of ActiveCBT for enhancing CBT. DEP rates were reduced in both groups from baseline to final (60% MDD SCID remission) and at follow up (Active: 40%; Calm: 25%). Larger and potentially quicker symptom improvement was found favoring the Active condition to the final visit (HAMD, between-group changes g = -1.33; PHQ-9, g = -0.62), with small differences remaining at follow-up (HAMD, g = -0.45; PHQ-9, g = -0.19). Exercise priming appears acceptable and plausibly efficacious for enhancing mechanisms of CBT and overall outcomes, though the present small sample precludes efficacy determinations. It appears feasible to conduct a randomized controlled trial comparing ActiveCBT to CalmCBT. Future trials evaluating this potentially promising treatment approach and mediating mechanisms are warranted.

Robust Adaptive Incorporation of Historical Control Data in a Randomized Trial of External Cooling to Treat Septic Shock

This paper proposes randomized controlled clinical trial design to evaluate external cooling as a means to control fever and thereby reduce mortality in patients with septic shock. The trial will include concurrent external cooling and control arms while adaptively incorporating historical control arm data. Bayesian group sequential monitoring will be done using a posterior comparative test based on the 60-day survival distribution in each concurrent arm. Posterior inference will follow from a Bayesian discrete time survival model that facilitates adaptive incorporation of the historical control data through an innovative regression framework with a multivariate spike-and-slab prior distribution on the historical bias parameters. For each interim test, the amount of information borrowed from the historical control data will be determined adaptively in a manner that reflects the degree of agreement between historical and concurrent control arm data. Guidance is provided for selecting Bayesian posterior probability group-sequential monitoring boundaries. Simulation results elucidating how the proposed method borrows strength from the historical control data are reported. In the absence of historical control arm bias, the proposed design controls the type I error rate and provides substantially larger power than reasonable comparators, whereas in the presence bias of varying magnitude, type I error rate inflation is curbed.

A multi-center phase II randomized clinical trial of losartan on symptomatic outpatients with COVID-19

BACKGROUND

The SARS-CoV-2 virus enters cells via Angiotensin-converting enzyme 2 (ACE2), disrupting the renin-angiotensin-aldosterone axis, potentially contributing to lung injury. Treatment with angiotensin receptor blockers (ARBs), such as losartan, may mitigate these effects, though induction of ACE2 could increase viral entry, replication, and worsen disease.

METHODS

This study represents a placebo-controlled blinded randomized clinical trial (RCT) to test the efficacy of losartan on outpatients with COVID-19 across three hospital systems with numerous community sites in Minnesota, U.S. Participants included symptomatic outpatients with COVID-19 not already taking ACE-inhibitors or ARBs, enrolled within 7 days of symptom onset. Patients were randomized to 1:1 losartan (25 mg orally twice daily unless estimated glomerular filtration rate, eGFR, was reduced, when dosing was reduced to once daily) versus placebo for 10 days, and all patients and outcome assesors were blinded. The primary outcome was all-cause hospitalization within 15 days. Secondary outcomes included functional status, dyspnea, temperature, and viral load. (clinicatrials.gov, NCT04311177, closed to new participants).

FINDINGS

From April to November 2020, 117 participants were randomized 58 to losartan and 59 to placebo, and all were analyzed under intent to treat principles. The primary outcome did not differ significantly between the two arms based on Barnard's test [losartan arm: 3 events (5.2% 95% CI 1.1, 14.4%) versus placebo arm: 1 event (1.7%; 95% CI 0.0, 9.1%)]; proportion difference -3.5% (95% CI -13.2, 4.8%); p = 0.32]. Viral loads were not statistically different between treatment groups at any time point. Adverse events per 10 patient days did not differ signifcantly [0.33 (95% CI 0.22-0.49) for losartan vs. 0.37 (95% CI 0.25-0.55) for placebo]. Due to a lower than expected hospitalization rate and low likelihood of a clinically important treatment effect, the trial was terminated early.

INTERPRETATION

In this multicenter blinded RCT for outpatients with mild symptomatic COVID-19 disease, losartan did not reduce hospitalizations, though assessment was limited by low event rate. Importantly, viral load was not statistically affected by treatment. This study does not support initiation of losartan for low-risk outpatients.

Morbidity and Mortality Trends of Pancreatitis: An Observational Study

Background: Pancreatitis accounts for more than $2.5 billion of healthcare costs and remains the most common gastrointestinal (GI) admission. Few contemporary studies have assessed temporal trends of incidence, complications, management, and outcomes for acute pancreatitis in hospitalized patients at the national level. Methods: We used data from one of the largest hospital-based databases available in the United States, the Healthcare Cost and Utilization Project's (HCUP) State Inpatient Database, from 10 states between 2008 and 2015. We included patients with a diagnosis of acute pancreatitis (ICD-9 CM 577.0). Patient- and hospital-level data were used to estimate incidence and inpatient mortality rates. Results: From 80,736,256 hospitalizations, 929,914 (1.15%) cases of acute pancreatitis were identified, 186,226 (20.2%) of which were caused by gallbladder disease). The median age was 53 years (interquartile range [IQR], 41-67) and 50.8% were men. In-hospital mortality was 2.5% and crude mortality rates declined from 2.9% to 2.0% over the study period. Admission year remained significant after adjusting for patient demographics and comorbidities (odds ratio [OR], 0.90; 95% confidence interval [CI], 0.89-0.90; p < 0.001). Gallbladder disease was associated with decreased odds of mortality (OR, 0.60; 95% CI, 0.57-0.62). Median length of stay was four days (IQR, 2-7) and decreased over time. The rates of surgical and endoscopic interventions were highest in 2011 (peak incidence of 16.1% and 9.5%, respectively) and have been decreasing since. Surgical providers were, on average, more likely than medical providers to perform surgery in both those with and without gallbladder disease etiology (gallbladder disease OR, 7.11; 95% CI, 5.46-9.25; non-gallbladder disease OR, 20.50; 95% CI, 16.81-25.01), endoscopy (gallbladder disease OR, 1.22; 95% CI, 0.87-1.72; non-gallbladder disease OR, 1.60; 95% CI, 1.18-2.16), or both (gallbladder disease OR, 7.00; 95% CI, 5.22-9.37; non-gallbladder disease OR, 8.85; 95% CI, 5.61-13.96). Conclusions: The incidence of pancreatitis, from 2008 to 2015, has increased whereas inpatient mortality (i.e., case fatality) has decreased. Understanding temporal trends in outcomes and management along with provider, hospital, and regional variation can better identify areas for future research and collaboration in managing these patients.

Design and implementation of an international, multi-arm, multi-stage platform master protocol for trials of novel SARS-CoV-2 antiviral agents: Therapeutics for Inpatients with COVID-19 (TICO/ACTIV-3)

BACKGROUND

Safe and effective therapies for COVID-19 are urgently needed. In order to meet this need, the Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) public-private partnership initiated the Therapeutics for Inpatients with COVID-19 (TICO). TICO is a multi-arm, multi-stage (MAMS) platform master protocol, which facilitates the rapid evaluation of the safety and efficacy of novel candidate anti-viral therapeutic agents for adults hospitalized with COVID-19. Four agents have so far entered the protocol, with rapid answers already provided for three of these. Other agents are expected to enter the protocol throughout 2021. This protocol contains a number of key design and implementation features that, along with challenges faced by the protocol team, are presented and discussed.

PROTOCOL DESIGN AND IMPLEMENTATION

Three clinical trial networks, encompassing a global network of clinical sites, participated in the protocol development and implementation. TICO utilizes a MAMS design with an agile and robust approach to futility and safety evaluation at 300 patients enrolled, with subsequent expansion to full sample size and an expanded target population if the agent shows an acceptable safety profile and evidence of efficacy. Rapid recruitment to multiple agents is enabled through the sharing of placebo as well as the confining of agent-specific information to protocol appendices, and modular consent forms. In collaboration with the Food and Drug Administration, a thorough safety data collection and DSMB schedule was developed for the study of agents with limited in-human data.

CHALLENGES

Challenges included ensuring drug supply and reliable recruitment allowing for changing infection rates across the global network of sites, the need to balance the collection of data and samples without overburdening clinical staff, and obtaining regulatory approvals across a global network of sites.

CONCLUSION

Through a robust multi-network partnership, the TICO protocol has been successfully used across a global network of sites for rapid generation of efficacy data on multiple novel antiviral agents. The protocol design and implementation features used in this protocol, and the approaches to address challenges, will have broader applicability. Mechanisms to facilitate improved communication and harmonization among country-specific regulatory bodies are required.

Logistic retainment interval dose exploration design for Phase I clinical trials of cytotoxic agents

Phase I studies of a cytotoxic agent often aim to identify the dose that provides an investigator specified target dose-limiting toxicity (DLT) probability. In practice, an initial cohort receives a dose with a putative low DLT probability, and subsequent dosing follows by consecutively deciding whether to retain the current dose, escalate to the adjacent higher dose, or de-escalate to the adjacent lower dose. This article proposes a Phase I design derived using a Bayesian decision-theoretic approach to this sequential decision-making process. The design consecutively chooses the action that minimizes posterior expected loss where the loss reflects the distance on the log-odds scale between the target and the DLT probability of the dose that would be given to the next cohort under the corresponding action. A logistic model is assumed for the log odds of a DLT at the current dose with a weakly informative t-distribution prior centered at the target. The key design parameters are the pre-specified odds ratios for the DLT probabilities at the adjacent higher and lower doses. Dosing rules may be pre-tabulated, as these only depend on the outcomes at the current dose, which greatly facilitates implementation. The recommended default version of the proposed design improves dose selection relative to many established designs across a variety of scenarios.

A Neutralizing Monoclonal Antibody for Hospitalized Patients with Covid-19

BACKGROUND

LY-CoV555, a neutralizing monoclonal antibody, has been associated with a decrease in viral load and the frequency of hospitalizations or emergency department visits among outpatients with coronavirus disease 2019 (Covid-19). Data are needed on the effect of this antibody in patients who are hospitalized with Covid-19.

METHODS

In this platform trial of therapeutic agents, we randomly assigned hospitalized patients who had Covid-19 without end-organ failure in a 1:1 ratio to receive either LY-CoV555 or matching placebo. In addition, all the patients received high-quality supportive care as background therapy, including the antiviral drug remdesivir and, when indicated, supplemental oxygen and glucocorticoids. LY-CoV555 (at a dose of 7000 mg) or placebo was administered as a single intravenous infusion over a 1-hour period. The primary outcome was a sustained recovery during a 90-day period, as assessed in a time-to-event analysis. An interim futility assessment was performed on the basis of a seven-category ordinal scale for pulmonary function on day 5.

RESULTS

On October 26, 2020, the data and safety monitoring board recommended stopping enrollment for futility after 314 patients (163 in the LY-CoV555 group and 151 in the placebo group) had undergone randomization and infusion. The median interval since the onset of symptoms was 7 days (interquartile range, 5 to 9). At day 5, a total of 81 patients (50%) in the LY-CoV555 group and 81 (54%) in the placebo group were in one of the two most favorable categories of the pulmonary outcome. Across the seven categories, the odds ratio of being in a more favorable category in the LY-CoV555 group than in the placebo group was 0.85 (95% confidence interval [CI], 0.56 to 1.29; P = 0.45). The percentage of patients with the primary safety outcome (a composite of death, serious adverse events, or clinical grade 3 or 4 adverse events through day 5) was similar in the LY-CoV555 group and the placebo group (19% and 14%, respectively; odds ratio, 1.56; 95% CI, 0.78 to 3.10; P = 0.20). The rate ratio for a sustained recovery was 1.06 (95% CI, 0.77 to 1.47).

CONCLUSIONS

Monoclonal antibody LY-CoV555, when coadministered with remdesivir, did not demonstrate efficacy among hospitalized patients who had Covid-19 without end-organ failure. (Funded by Operation Warp Speed and others; TICO ClinicalTrials.gov number, NCT04501978.).

A Neutralizing Monoclonal Antibody for Hospitalized Patients with Covid-19

BACKGROUND

LY-CoV555, a neutralizing monoclonal antibody, has been associated with a decrease in viral load and the frequency of hospitalizations or emergency department visits among outpatients with coronavirus disease 2019 (Covid-19). Data are needed on the effect of this antibody in patients who are hospitalized with Covid-19.

METHODS

In this platform trial of therapeutic agents, we randomly assigned hospitalized patients who had Covid-19 without end-organ failure in a 1:1 ratio to receive either LY-CoV555 or matching placebo. In addition, all the patients received high-quality supportive care as background therapy, including the antiviral drug remdesivir and, when indicated, supplemental oxygen and glucocorticoids. LY-CoV555 (at a dose of 7000 mg) or placebo was administered as a single intravenous infusion over a 1-hour period. The primary outcome was a sustained recovery during a 90-day period, as assessed in a time-to-event analysis. An interim futility assessment was performed on the basis of a seven-category ordinal scale for pulmonary function on day 5.

RESULTS

On October 26, 2020, the data and safety monitoring board recommended stopping enrollment for futility after 314 patients (163 in the LY-CoV555 group and 151 in the placebo group) had undergone randomization and infusion. The median interval since the onset of symptoms was 7 days (interquartile range, 5 to 9). At day 5, a total of 81 patients (50%) in the LY-CoV555 group and 81 (54%) in the placebo group were in one of the two most favorable categories of the pulmonary outcome. Across the seven categories, the odds ratio of being in a more favorable category in the LY-CoV555 group than in the placebo group was 0.85 (95% confidence interval [CI], 0.56 to 1.29; P = 0.45). The percentage of patients with the primary safety outcome (a composite of death, serious adverse events, or clinical grade 3 or 4 adverse events through day 5) was similar in the LY-CoV555 group and the placebo group (19% and 14%, respectively; odds ratio, 1.56; 95% CI, 0.78 to 3.10; P = 0.20). The rate ratio for a sustained recovery was 1.06 (95% CI, 0.77 to 1.47).

CONCLUSIONS

Monoclonal antibody LY-CoV555, when coadministered with remdesivir, did not demonstrate efficacy among hospitalized patients who had Covid-19 without end-organ failure. (Funded by Operation Warp Speed and others; TICO ClinicalTrials.gov number, NCT04501978.).

Mobile Health Intervention to Close the Guidelines-To-Practice Gap in Hypertension Treatment: Protocol for the mGlide Randomized Controlled Trial

Background

Suboptimal treatment of hypertension remains a widespread problem, particularly among minorities and socioeconomically disadvantaged groups. We present a health system–based intervention with diverse patient populations using readily available smartphone technology. This intervention is designed to empower patients and create partnerships between patients and their provider team to promote hypertension control.

Objective

The mGlide randomized controlled trial is a National Institutes of Health–funded study, evaluating whether a mobile health (mHealth)-based intervention that is an active partnership between interprofessional health care teams and patients results in better hypertension control rates than a state-of-clinical care comparison.

Methods

We are recruiting 450 participants including stroke survivors and primary care patients with elevated cardiovascular disease risk from diverse health systems. These systems include an acute stroke service (n=100), an academic medical center (n=150), and community medical centers including Federally Qualified Health Centers serving low-income and minority (Latino, Hmong, African American, Somali) patients (n=200). The primary aim tests the clinical effectiveness of the 6-month mHealth intervention versus standard of care. Secondary aims evaluate sustained hypertension control rates at 12 months; describe provider experiences of system usability and satisfaction; examine patient experiences, including medication adherence and medication use self-efficacy, self-rated health and quality of life, and adverse event rates; and complete a cost-effectiveness analysis.

Results

To date, we have randomized 107 participants (54 intervention, 53 control).

Conclusions

This study will provide evidence for whether a readily available mHealth care model is better than state-of-clinical care for bridging the guideline-to-practice gap in hypertension treatment in health systems serving diverse patient populations.

Trial Registration

Clinicaltrials.gov NCT03612271; https://clinicaltrials.gov/ct2/show/NCT03612271

International Registered Report Identifier (IRRID)

DERR1-10.2196/25424

Advanced reperfusion strategies for patients with out-of-hospital cardiac arrest and refractory ventricular fibrillation (ARREST): a phase 2, single centre, open-label, randomised controlled trial

BACKGROUND

Among patients with out-of-hospital cardiac arrest (OHCA) and ventricular fibrillation, more than half present with refractory ventricular fibrillation unresponsive to initial standard advanced cardiac life support (ACLS) treatment. We did the first randomised clinical trial in the USA of extracorporeal membrane oxygenation (ECMO)-facilitated resuscitation versus standard ACLS treatment in patients with OHCA and refractory ventricular fibrillation.

METHODS

For this phase 2, single centre, open-label, adaptive, safety and efficacy randomised clinical trial, we included adults aged 18-75 years presenting to the University of Minnesota Medical Center (MN, USA) with OHCA and refractory ventricular fibrillation, no return of spontaneous circulation after three shocks, automated cardiopulmonary resuscitation with a Lund University Cardiac Arrest System, and estimated transfer time shorter than 30 min. Patients were randomly assigned to early ECMO-facilitated resuscitation or standard ACLS treatment on hospital arrival by use of a secure schedule generated with permuted blocks of randomly varying block sizes. Allocation concealment was achieved by use of a randomisation schedule that required scratching off an opaque layer to reveal assignment. The primary outcome was survival to hospital discharge. Secondary outcomes were safety, survival, and functional assessment at hospital discharge and at 3 months and 6 months after discharge. All analyses were done on an intention-to-treat basis. The study qualified for exception from informed consent (21 Code of Federal Regulations 50.24). The ARREST trial is registered with ClinicalTrials.gov, NCT03880565.

FINDINGS

Between Aug 8, 2019, and June 14, 2020, 36 patients were assessed for inclusion. After exclusion of six patients, 30 were randomly assigned to standard ACLS treatment (n=15) or to early ECMO-facilitated resuscitation (n=15). One patient in the ECMO-facilitated resuscitation group withdrew from the study before discharge. The mean age was 59 years (range 36-73), and 25 (83%) of 30 patients were men. Survival to hospital discharge was observed in one (7%) of 15 patients (95% credible interval 1·6-30·2) in the standard ACLS treatment group versus six (43%) of 14 patients (21·3-67·7) in the early ECMO-facilitated resuscitation group (risk difference 36·2%, 3·7-59·2; posterior probability of ECMO superiority 0·9861). The study was terminated at the first preplanned interim analysis by the National Heart, Lung, and Blood Institute after unanimous recommendation from the Data Safety Monitoring Board after enrolling 30 patients because the posterior probability of ECMO superiority exceeded the prespecified monitoring boundary. Cumulative 6-month survival was significantly better in the early ECMO group than in the standard ACLS group. No unanticipated serious adverse events were observed.

INTERPRETATION

Early ECMO-facilitated resuscitation for patients with OHCA and refractory ventricular fibrillation significantly improved survival to hospital discharge compared with standard ACLS treatment.

FUNDING

National Heart, Lung, and Blood Institute.

Rationale and methods of the Advanced R2Eperfusion STrategies for Refractory Cardiac Arrest (ARREST) trial

BACKGROUND

Venoarterial extracorporeal membrane oxygenation has emerged as a prominent therapy for patients with refractory cardiac arrest. However, the optimal time of initiation remains unknown.

AIM

The aim was to assess the rate of survival to hospital discharge in adult patients with refractory ventricular fibrillation/pulseless ventricular tachycardia out-of-hospital cardiac arrest treated with 1 of 2 local standards of care: (1) early venoarterial extracorporeal membrane oxygenation-facilitated resuscitation for circulatory support and percutaneous coronary intervention, when needed, or (2) standard advanced cardiac life support resuscitation.

DESIGN

Phase II, single-center, partially blinded, prospective, intention-to-treat, safety and efficacy clinical trial.

POPULATION

Adults (aged 18-75), initial out-of-hospital cardiac arrest rhythm of ventricular fibrillation/pulseless ventricular tachycardia, no ROSC following 3 shocks, body morphology to accommodate a Lund University Cardiac Arrest System automated cardiopulmonary resuscitation device, and transfer time of <30 minutes.

SETTING

Hospital-based.

OUTCOMES

Primary: survival to hospital discharge. Secondary: safety, survival, and functional assessment at hospital discharge and 3 and 6 months, and cost.

SAMPLE SIZE

Assuming success rates of 12% versus 37% in the 2 arms and 90% power, a type 1 error rate of .05, and a 15% rate of withdrawal prior to hospital discharge, the required sample size is N = 174 evaluated patients.

CONCLUSIONS

The ARREST trial will generate safety/effectiveness data and comparative costs associated with extracorporeal cardiopulmonary resuscitation, informing broader implementation and a definitive Phase III clinical trial.

Observational Study of Metformin and Risk of Mortality in Patients Hospitalized with Covid-19

Background Type 2 diabetes (T2DM) and obesity are significant risks for mortality in Covid19. Metformin has been hypothesized as a treatment for COVID19. Metformin has sex specific immunomodulatory effects which may elucidate treatment mechanisms in COVID-19. In this study we sought to identify whether metformin reduced mortality from Covid19 and if sex specific interactions exist. Methods De-identified claims data from UnitedHealth were used to identify persons with at least 6 months continuous coverage who were hospitalized with Covid-19. Persons in the metformin group had at least 90 days of metformin claims in the 12 months before hospitalization. Unadjusted and multivariate models were conducted to assess risk of mortality based on metformin as a home medication in individuals with T2DM and obesity, controlling for pre-morbid conditions, medications, demographics, and state. Heterogeneity of effect was assessed by sex. Results 6,256 persons were included; 52.8% female; mean age 75 years. Metformin was associated with decreased mortality in women by logistic regression, OR 0.792 (0.640, 0.979); mixed effects OR 0.780 (0.631, 0.965); Cox proportional-hazards: HR 0.785 (0.650, 0.951); and propensity matching, OR of 0.759 (0.601, 0.960). TNF-alpha inhibitors were associated with decreased mortality in the 38 persons taking them, by propensity matching, OR 0.19 (0.0378, 0.983). Conclusions Metformin was significantly associated with reduced mortality in women with obesity or T2DM in observational analyses of claims data from individuals hospitalized with Covid-19. This sex-specific finding is consistent with metformin reducing TNF-alpha in females over males, and suggests that metformin conveys protection in Covid-19 through TNF-alpha effects. Prospective studies are needed to understand mechanism and causality.

Batch Bayesian optimization design for optimizing a neurostimulator

Recently, spinal epidural neurostimulation is being considered for rehabilitation of persons suffering from partial spinal-cord injury. The neurostimulator must be programmed by a neurosurgeon, yet little work has been done to develop rigorous methods for optimally programming the device. We propose an adaptive design to efficiently optimize programming of the neurostimulator based on specified interim evaluations of patient reported preferences. Preferences for the eligible device configurations are estimated after each interim analysis through a conditionally autoregressive model that assumes preference for one configuration is related to preferences for neighboring configurations. Using the adaptively updated preferences, a group of configurations is programmed into the device for the patient to evaluate during the next follow-up period. This selection is based on a balance of device exploration and preference maximization. We repeat this process until a specified stopping rule or the calibration end is reached. We show simulation studies to evaluate the overall quality of the adaptive calibration for various configuration selection strategies and the effects of stopping it early.

A Bayesian Machine Learning Approach for Optimizing Dynamic Treatment Regimes

Medical therapy often consists of multiple stages, with a treatment chosen by the physician at each stage based on the patient's history of treatments and clinical outcomes. These decisions can be formalized as a dynamic treatment regime. This paper describes a new approach for optimizing dynamic treatment regimes that bridges the gap between Bayesian inference and existing approaches, like Q-learning. The proposed approach fits a series of Bayesian regression models, one for each stage, in reverse sequential order. Each model uses as a response variable the remaining payoff assuming optimal actions are taken at subsequent stages, and as covariates the current history and relevant actions at that stage. The key difficulty is that the optimal decision rules at subsequent stages are unknown, and even if these decision rules were known the relevant response variables may be counterfactual. However, posterior distributions can be derived from the previously fitted regression models for the optimal decision rules and the counterfactual response variables under a particular set of rules. The proposed approach averages over these posterior distributions when fitting each regression model. An efficient sampling algorithm for estimation is presented, along with simulation studies that compare the proposed approach with Q-learning.

A utility-based design for randomized comparative trials with ordinal outcomes and prognostic subgroups

A design is proposed for randomized comparative trials with ordinal outcomes and prognostic subgroups. The design accounts for patient heterogeneity by allowing possibly different comparative conclusions within subgroups. The comparative testing criterion is based on utilities for the levels of the ordinal outcome and a Bayesian probability model. Designs based on two alternative models that include treatment-subgroup interactions are considered, the proportional odds model and a non-proportional odds model with a hierarchical prior that shrinks toward the proportional odds model. A third design that assumes homogeneity and ignores possible treatment-subgroup interactions also is considered. The three approaches are applied to construct group sequential designs for a trial of nutritional prehabilitation versus standard of care for esophageal cancer patients undergoing chemoradiation and surgery, including both untreated patients and salvage patients whose disease has recurred following previous therapy. A simulation study is presented that compares the three designs, including evaluation of within-subgroup type I and II error probabilities under a variety of scenarios including different combinations of treatment-subgroup interactions.

Robust treatment comparison based on utilities of semi-competing risks in non-small-cell lung cancer

A design is presented for a randomized clinical trial comparing two second-line treatments, chemotherapy versus chemotherapy plus reirradiation, for treatment of recurrent non-small-cell lung cancer. The central research question is whether the potential efficacy benefit that adding reirradiation to chemotherapy may provide justifies its potential for increasing the risk of toxicity. The design uses two co-primary outcomes: time to disease progression or death, and time to severe toxicity. Because patients may be given an active third-line treatment at disease progression that confounds second-line treatment effects on toxicity and survival following disease progression, for the purpose of this comparative study follow-up ends at disease progression or death. In contrast, follow-up for disease progression or death continues after severe toxicity, so these are semi-competing risks. A conditionally conjugate Bayesian model that is robust to misspecification is formulated using piecewise exponential distributions. A numerical utility function is elicited from the physicians that characterizes desirabilities of the possible co-primary outcome realizations. A comparative test based on posterior mean utilities is proposed. A simulation study is presented to evaluate test performance for a variety of treatment differences, and a sensitivity assessment to the elicited utility function is performed. General guidelines are given for constructing a design in similar settings, and a computer program for simulation and trial conduct is provided.

Flexible Bayesian survival modeling with semiparametric time-dependent and shape-restricted covariate effects

Presently, there are few options with available software to perform a fully Bayesian analysis of time-to-event data wherein the hazard is estimated semi- or non-parametrically. One option is the piecewise exponential model, which requires an often unrealistic assumption that the hazard is piecewise constant over time. The primary aim of this paper is to construct a tractable semiparametric alternative to the piecewise exponential model that assumes the hazard is continuous, and to provide modifiable, user-friendly software that allows the use of these methods in a variety of settings. To accomplish this aim, we use a novel model formulation for the log-hazard based on a low-rank thin plate linear spline that readily facilitates adjustment for covariates with time-dependent and proportional hazards effects, possibly subject to shape restrictions. We investigate the performance of our model choices via simulation. We then analyze colorectal cancer data from a clinical trial comparing the effectiveness of two novel treatment regimes relative to the standard of care for overall survival. We estimate a time-dependent hazard ratio for each novel regime relative to the standard of care while adjusting for the effect of aspartate transaminase, a biomarker of liver function, that is subject to a non-decreasing shape restriction.

Utility-based designs for randomized comparative trials with categorical outcomes

A general utility-based testing methodology for design and conduct of randomized comparative clinical trials with categorical outcomes is presented. Numerical utilities of all elementary events are elicited to quantify their desirabilities. These numerical values are used to map the categorical outcome probability vector of each treatment to a mean utility, which is used as a one-dimensional criterion for constructing comparative tests. Bayesian tests are presented, including fixed sample and group sequential procedures, assuming Dirichlet-multinomial models for the priors and likelihoods. Guidelines are provided for establishing priors, eliciting utilities, and specifying hypotheses. Efficient posterior computation is discussed, and algorithms are provided for jointly calibrating test cutoffs and sample size to control overall type I error and achieve specified power. Asymptotic approximations for the power curve are used to initialize the algorithms. The methodology is applied to re-design a completed trial that compared two chemotherapy regimens for chronic lymphocytic leukemia, in which an ordinal efficacy outcome was dichotomized, and toxicity was ignored to construct the trial's design. The Bayesian tests also are illustrated by several types of categorical outcomes arising in common clinical settings. Freely available computer software for implementation is provided. Copyright © 2016 John Wiley & Sons, Ltd.

COMBINING NONEXCHANGEABLE FUNCTIONAL OR SURVIVAL DATA SOURCES IN ONCOLOGY USING GENERALIZED MIXTURE COMMENSURATE PRIORS

Conventional approaches to statistical inference preclude structures that facilitate incorporation of supplemental information acquired from similar circumstances. For example, the analysis of data obtained using perfusion computed tomography to characterize functional imaging biomarkers in cancerous regions of the liver can benefit from partially informative data collected concurrently in non-cancerous regions. This paper presents a hierarchical model structure that leverages all available information about a curve, using penalized splines, while accommodating important between-source features. Our proposed methods flexibly borrow strength from the supplemental data to a degree that reflects the commensurability of the supplemental curve with the primary curve. We investigate our method's properties for nonparametric regression via simulation, and apply it to a set of liver cancer data. We also apply our method for a semiparametric hazard model to data from a clinical trial that compares time to disease progression for three colorectal cancer treatments, while supplementing inference with information from a previous trial that tested the current standard of care.

Semiparametric Bayesian commensurate survival model for post-market medical device surveillance with non-exchangeable historical data

Trial investigators often have a primary interest in the estimation of the survival curve in a population for which there exists acceptable historical information from which to borrow strength. However, borrowing strength from a historical trial that is non-exchangeable with the current trial can result in biased conclusions. In this article we propose a fully Bayesian semiparametric method for the purpose of attenuating bias and increasing efficiency when jointly modeling time-to-event data from two possibly non-exchangeable sources of information. We illustrate the mechanics of our methods by applying them to a pair of post-market surveillance datasets regarding adverse events in persons on dialysis that had either a bare metal or drug-eluting stent implanted during a cardiac revascularization surgery. We finish with a discussion of the advantages and limitations of this approach to evidence synthesis, as well as directions for future work in this area. The article's Supplementary Materials offer simulations to show our procedure's bias, mean squared error, and coverage probability properties in a variety of settings.

Bayesian adaptive design for device surveillance

BACKGROUND

Postmarket device surveillance studies often have important primary objectives tied to estimating a survival function at some future time $$T$$ with a certain amount of precision.

PURPOSE

This article presents the details and various operating characteristics of a Bayesian adaptive design for device surveillance, as well as a method for estimating a sample size vector (determined by the maximum sample size and a preset number of interim looks) that will deliver the desired power.

METHODS

We adopt a Bayesian adaptive framework, which recognizes the fact that persons enrolled in a study report their results over time, not all at once. At each interim look, we assess whether we expect to achieve our goals with only the current group or the achievement of such goals is extremely unlikely even for the maximum sample size.

RESULTS

Our Bayesian adaptive design can outperform two nonadaptive frequentist methods currently recommended by Food and Drug Administration (FDA) guidance documents in many settings.

LIMITATIONS

Our method's performance can be sensitive to model misspecification and changes in the trial's enrollment rate.

CONCLUSIONS

The proposed design provides a more efficient framework for conducting postmarket surveillance of medical devices.

EPR, ENDOR, and special TRIPLE measurements of P(*+) in wild type and modified reaction centers from Rb. sphaeroides

The influence of the protein environment on the primary electron donor, P, a bacteriochlorophyll a dimer, of reaction centers from Rhodobacter sphaeroides, has been investigated using electron paramagnetic resonance and electron nuclear double resonance spectroscopy. These techniques were used to probe the effects on P that are due to alteration of three amino acid residues, His L168, Asn L170, and Asn M199. The introduction of Glu at L168, Asp at L170, or Asp at M199 changes the oxidation/reduction midpoint potential of P in a pH-dependent manner (Williams et al. (2001) Biochemistry 40, 15403-15407). For the double mutant His L168 to Glu and Asn at L170 to Asp, excitation results in electron transfer along the A-side branch of cofactors at pH 7.2, but at pH 9.5, a long-lived state involving B-side cofactors is produced (Haffa et al. (2004) J Phys Chem B 108, 4-7). Using electron paramagnetic resonance spectroscopy, the mutants with alterations of each of the three individual residues and a double mutant, with changes at L168 and L170, were found to have increased linewidths of 10.1-11.0 G compared to the linewidth of 9.6 G for wild type. The Special TRIPLE spectra were pH dependent, and at pH 8, the introduction of aspartate at L170 increased the spin density ratio, rho (L)/rho (M), to 6.1 while an aspartate at the symmetry related position, M199, decreased the ratio to 0.7 compared to the value of 2.1 for wild type. These results indicate that the energy of the two halves of P changes by about 100 meV due to the mutations and are consistent with the interpretation that electrostatic interactions involving these amino acid residues contribute to the switch in pathway of electron transfer.

Relationships between throwing mechanics and shoulder distraction in professional baseball pitchers

The extreme forces and torques and the high speeds and excessive ranges of motion of baseball pitching place tremendous stress on the soft tissues of the throwing shoulder. Little is known about the relationship between pitching mechanics and shoulder joint stress, especially in professional athletes. The purpose of this study was to quantify joint loads and kinematic parameters of pitching mechanics at the major league level and to study their relationships. Three-dimensional, high-speed video data were collected on 40 professional pitchers during the 1998 Cactus League spring training. A clinically significant distraction force was calculated at the shoulder joint, which reached an average peak value of 947 +/- 162 N (108% +/- 16% body weight). Descriptive statistics and a multiple linear regression analysis were used to relate shoulder distraction to kinematic and kinetic parameters of pitching mechanics. This study was undertaken not only to investigate the peak forces and torques on the shoulder, but also to identify potential areas of intervention that might prevent throwing injuries. Knowledge of joint ranges of motion, angular velocities, and joint-reaction forces can provide a scientific basis for improved preventive and rehabilitative protocols for baseball pitchers.

The effects of extended play on professional baseball pitchers

The purpose of this study was to investigate kinematic and kinetic changes as a result of extended play in baseball pitching. Seven major league baseball pitchers were videotaped with high-speed (120 Hz) cameras during multiple innings of the same game. For each athlete, two fastballs (one thrown during the initial inning of play and one from the final inning) were chosen for analysis. Twenty-one physical landmarks were manually digitized from the video data. Kinematic and kinetic parameters were subsequently calculated relative to four phases of the pitching motion: windup, cocking, acceleration, and follow-through. Paired t-tests revealed that seven parameters changed significantly between early and late innings. These included decreases in maximum external rotation of the shoulder, knee angle at ball release, ball velocity, maximum distraction force at both the shoulder and elbow, and horizontal adduction torque at both release and its maximum value. Ultimately, a decline in performance was evident by a 2 m/s (5 mph) drop in ball speed. It is unclear whether the kinematic and kinetic changes occurred because of fatigue or if protective mechanisms were adopted.

Production and characterization of Ti:sapphire thin films grown by reactive laser ablation with elemental precursors

Crystalline Ti:sapphire (Ti:Al(2)O(3)) thin films were grown at low temperatures upon Al(2)O(3) (0001) substrates by reactive crossed-beam laser ablation at 248 nm by use of a liquid Ti-Al alloy target and O(2) . The films were investigated ex situ by x-ray diffraction, x-ray photoelectron spectroscopy, and Rutherford backscattering spectrometry. Low-temperature luminescence was identical to that for Ti(3+) ions in bulk samples of Al(2)O(3) .

Implications for staff development of perceived self-efficacy in nurses who changed to home care practice

As reform activities continue to restructure health care, traditional roles of nurses are being reshaped and redefined. Many nurses displaced by organizational downsizing are seeking employment "outside of the hospital walls," including home care practice. Novice home care nurses may lack confidence in their ability to care for clients in the home. The purpose of this study was to examine the extent to which perceived self-efficacy is associated with job satisfaction in nurses who have recently changed from hospital-based practice to home care. Self-efficacy correlated significantly with job satisfaction. Nurses with high perceptions of self-efficacy tended to be more satisfied with their jobs. Using the theoretical framework of self-efficacy, educators can structure orientation programs to enhance the new nurse's perception of self-efficacy and, thereby, increase job satisfaction.