Scott R. Evans

The safety of long-acting beta-agonists (LABA) to treat asthma has been a lingering issue for the last 25 years after two large randomized trials reported an increased incidence of asthma death with salmeterol. The current dilemma is whether this risk is also increased when LABAs are given with inhaled corticosteroids (ICS). To address this, the FDA required that manufacturers conduct five large randomized trials comparing ICS-LABA combinations to ICS alone on the incidence of major asthma outcomes. The three trials that have been published to date showed that the risk of a serious asthma-related event, including asthma-related death, intubation or hospitalization, was not increased with the addition of the LABA. This finding was similar to a meta-analysis of 57 prior trials involving close to 35,000 asthma patients (RR 0.98; 95% CI: 0.57-1.68). The three trials also found a lower incidence of asthma exacerbation, as did the meta-analysis (RR 0.73; 95% CI: 0.67-0.79). Finally, there were two asthma deaths overall in the three trials under ICS-LABA versus 0 with ICS only (RR 3.00; 95% CI: 0.24-37.70), comparable to the meta-analysis finding (RR 2.96; 95% CI: 0.50-17.57). In all, the three published FDA-mandated trials to assess the safety of ICS-LABA have predictably produced the same results as the meta-analyses of prior trials, including the same lingering asthma death signal. These costly trials with no added benefit leave us no more advanced with respect to the core issue of the link between LABA use and asthma death, which still remains unresolved.

Ceftazidime–avibactam (caz-avi) is a new treatment option for carbapenem-resistant Enterobacteriaceae (CRE). The Consortium on Resistance Against Carbapenems in Klebsiella and other Enterobacteriaceae (CRACKLE-2) is a multi-center, prospective, observational study of 60 hospitals in all five regions of the USA. Hospitalized patients with CRE isolated from clinical cultures are enrolled in CRACKLE-2. CRE was defined per CDC guidelines. Pitt Bacteremia score (PBS) and Charlson comorbidity score (CMS) were calculated. caz–avi susceptibility was tested as clinically indicated in participating clinical laboratories. From June 1, 2016–April 4, 2017, 568 unique patients with 591 admissions and 681 culture episodes (42% infection, 58% colonization) were included. The distribution of 252 first CRE infections per unique patient was 78 (31%) blood, 67 (27%) urine, 37 (15%) respiratory, 34 (13%) intra-abdominal, 30 (12%) wound, and 6 (2%) other. Patients with CRE infections were chronically ill (CMS median [IQR] 3 [1,5]) and acutely ill (PBS median [IQR] 3 [2,6]). Outcomes were available for 198 patients with infections; all-cause mortality was 29/198 (15%) at 14 days, and 55/198 (28%) at 90 days. K. pneumoniae (62%), E. cloacae (17%), and E. coli (13%) were the top three CRE species. A total of 124 isolates were tested for carbapenemase genes; 62/124 (50%), and 29/124 (23%) were positive for blaKPC-2, and blaKPC-3, respectively. Within 96 tested CR K. pneumoniae (CRKP) isolates, 22/96 (23%), 36/96 (38%), 38/96 (40%) were ST258-1, ST258-2, and non-ST258 clades, respectively. Antibiotic data were available for 224 patients with infections. In various combinations, 37/224 (16%) patients received polymyxins, 74/224 (33%) aminoglycosides, 111/224 (49%) carbapenems, 47/224 (21%) ceftazidime/avibactam, and 26/224 (12%) tigecycline. A total of 111 CRE were tested for caz–avi susceptibility; 32/111 (29%) were non-susceptible. All-cause mortality by caz–avi susceptibility did not differ among 62 patients with outcomes (P = 0.74). In this national sample of hospitalized patients with CRE, 29% of tested isolates were caz–avi non-susceptible. Results need to be confirmed by central laboratory testing. D. Van Duin, Astellas: Scientific Advisor, Consulting fee. Achaogen: Scientific Advisor, Consulting fee. Allergan: Scientific Advisor, Consulting fee. MedImmune: Scientific Advisor, Consulting fee. Shionogi: Scientific Advisor, Consulting fee. S. S. Richter, bioMerieux: Investigator, Research support. BD Diagnostics: Investigator, Research support. Roche: Investigator, Research support. BioFire: Investigator, Research support. OpGen: Investigator, Research support. K. S. Kaye, Xellia: Consultant, Consulting fee. Merck: Consultant and Grant Investigator, Consulting fee and Research support. The Medicines Company: Consultant and Grant Investigator, Consulting fee and Research support. C. Arias, Bayer Global: Consultant and Speaker’s Bureau, Consulting fee...

The Statistical and Data Management Center (SDMC) provides the Antibacterial Resistance Leadership Group (ARLG) with statistical and data management expertise to advance the ARLG research agenda. The SDMC is active at all stages of a study, including design; data collection and monitoring; data analyses and archival; and publication of study results. The SDMC enhances the scientific integrity of ARLG studies through the development and implementation of innovative and practical statistical methodologies and by educating research colleagues regarding the application of clinical trial fundamentals. This article summarizes the challenges and roles, as well as the innovative contributions in the design, monitoring, and analyses of clinical trials and diagnostic studies, of the ARLG SDMC.

Decreased efficacy of antibiotics due to resistant pathogens has created a need for the development of more effective medical interventions. Despite the increasing prevalence of pathogens resistant to one or more drugs, identifying and enrolling participants into clinical trials that evaluate new interventions for the treatment of some diseases can be challenging given the low prevalence of disease in which there are no effective treatments. Thus researchers might be tempted to consider externally-controlled trials that may allow for a reduction of the necessary number of prospectively-identified trial participants, thus easing recruitment burden and resulting in more timely trial completion relative to randomized controlled trials. We discuss advantages and disadvantages in externally controlled trials and review requirements for a valid externally-controlled trial. As ECTs are subject to the bias of observational studies, the criteria for a valid ECT should be carefully evaluated before these designs are implemented. Given considerable variation in study results in the resistant pathogen setting, the lack of information on important patient characteristics that may confound estimates of treatment effects, as well as the improvements in medical practice and evolving antibiotic resistance, the use of ECTs in the resistant pathogen setting, is not recommended. ECTs should be should be limited to specific situations where superiority of the effect of the new intervention is dramatic, the usual course of the disease highly predictable, the endpoints are objective (e. g., all-cause mortality) and the impact of baseline and treatment variables on outcomes is well characterized. Given that the resistant pathogen setting does not satisfy these criteria, we conclude that that randomized clinical trials are needed to evaluate new treatments for resistant pathogens. Innovative approaches to trial design that may ease recruitment burden while evaluating the benefits and harms of new treatments are being developed and utilized.

The widespread dissemination of carbapenem-resistant Acinetobacter spp. has created significant therapeutic challenges. At present, rapid molecular diagnostics (RMDs) that can identify this phenotype are not commercially available. Two RMD platforms, PCR combined with electrospray ionization mass spectrometry (PCR/ESI-MS) and molecular beacons (MB), for detecting genes conferring resistance/susceptibility to carbapenems in Acinetobacter spp. were evaluated. An archived collection of 200 clinical Acinetobacter sp. isolates was tested. Predictive values for susceptibility and resistance were estimated as a function of susceptibility prevalence and were based on the absence or presence of beta-lactamase ( bla ) NDM, VIM, IMP, KPC, and OXA carbapenemase genes (e.g., bla _OXA-23 , bla _OXA-24/40 , and bla _OXA-58 found in this study) against the reference standard of MIC determinations. According to the interpretation of MICs, 49% ( n = 98) of the isolates were carbapenem resistant (as defined by either resistance or intermediate resistance to imipenem). The susceptibility sensitivities (95% confidence interval [CI]) for imipenem were 82% (74%, 89%) and 92% (85%, 97%) for PCR/ESI-MS and MB, respectively. Resistance sensitivities (95% CI) for imipenem were 95% (88%, 98%) and 88% (80%, 94%) for PCR/ESI-MS and MB, respectively. PRIMERS III establishes that RMDs can discriminate between carbapenem resistance and susceptibility in Acinetobacter spp. In the context of a known prevalence of resistance, SPVs and RPVs can inform clinicians regarding the best choice for empiric antimicrobial therapy against this multidrug-resistant pathogen.

In the future, clinical trials will have an increased emphasis on pragmatism, providing a practical description of the effects of new treatments in realistic clinical settings. Accomplishing pragmatism requires better summaries of the totality of the evidence in ways that clinical trials consumers—patients, physicians, insurers—find transparent and allow for informed benefit:risk decision-making. The current approach to the analysis of clinical trials is to analyze efficacy and safety separately and then combine these analyses into a benefit:risk assessment. Many assume that this will effectively describe the impact on patients. But this approach is suboptimal for evaluating the totality of effects on patients. We discuss methods for benefit:risk assessment that have greater pragmatism than methods that separately analyze efficacy and safety. These include the concepts of within-patient analyses and composite benefit:risk endpoints with a goal of understanding how to analyze one patient before trying to figure out how to analyze many. We discuss the desirability of outcome ranking (DOOR) and introduce the partial credit strategy using an example in a clinical trial evaluating the effects of a new antibiotic. As part of the example, we introduce a strategy to engage patients as a resource to inform benefit:risk analyses consistent with the goal of measuring and weighing outcomes that are most important from the patient's perspective. We describe a broad vision for the future of clinical trials consistent with increased pragmatism. Greater focus on using endpoints to analyze patients rather than patients to analyze endpoints particularly in late-phase/stage clinical trials is an important part of this vision.

A structured benefit-risk assessment (BRA) is critical for drug development and lifecycle management. How to select B-R endpoints, determine weighting for these endpoints, and evaluate uncertainties are key aspects of the B-R decision-making process. In this article, we discuss key considerations on endpoint selection, challenges of double counting and correlated endpoints, and methods that can be used to address these challenges. In addition, we discuss the use of qualitative and quantitative weighting in BRA, techniques useful for weight construction, and weights based on empirical preferences. Potential sources for uncertainties in BRA, the approaches to illustrate and to address these uncertainties are described. Finally, we emphasize that benefit-risk assessment is a continuous process and requires cross-functional efforts.

Comparing diagnostic tests on accuracy alone can be inconclusive. For example, a test may have better sensitivity than another test yet worse specificity. Comparing tests on benefit risk may be more conclusive because clinical consequences of diagnostic error are considered. For benefit-risk evaluation, we propose diagnostic yield, the expected distribution of subjects with true positive, false positive, true negative, and false negative test results in a hypothetical population. We construct a table of diagnostic yield that includes the number of false positive subjects experiencing adverse consequences from unnecessary work-up. We then develop a decision theory for evaluating tests. The theory provides additional interpretation to quantities in the diagnostic yield table. It also indicates that the expected utility of a test relative to a perfect test is a weighted accuracy measure, the average of sensitivity and specificity weighted for prevalence and relative importance of false positive and false negative testing errors, also interpretable as the cost-benefit ratio of treating non-diseased and diseased subjects. We propose plots of diagnostic yield, weighted accuracy, and relative net benefit of tests as functions of prevalence or cost-benefit ratio. Concepts are illustrated with hypothetical screening tests for colorectal cancer with test positive subjects being referred to colonoscopy.

The medical community needs systematic and pragmatic approaches for evaluating the benefit-risk trade-offs of diagnostics that assist in medical decision making. Benefit-Risk Evaluation of Diagnostics: A Framework (BED-FRAME) is a strategy for pragmatic evaluation of diagnostics designed to supplement traditional approaches. BED-FRAME evaluates diagnostic yield and addresses 2 key issues: (1) that diagnostic yield depends on prevalence, and (2) that different diagnostic errors carry different clinical consequences. As such, evaluating and comparing diagnostics depends on prevalence and the relative importance of potential errors. BED-FRAME provides a tool for communicating the expected clinical impact of diagnostic application and the expected trade-offs of diagnostic alternatives. BED-FRAME is a useful fundamental supplement to the standard analysis of diagnostic studies that will aid in clinical decision making.

We thank the authors for their thoughtful comments [ 1]. DOOR/RADAR (Desirability of Outcome Ranking/Response Adjusted for Duration of Antibiotic Risk) [ 2] is a new paradigm and thorough evaluation of the methodology is helpful to better understand its strengths and limitations in different settings.