Availability of comparative real-world evidence research in Medicare patients: implications for Centers for Medicare and Medicaid Services drug price negotiations.

Aim: To evaluate the availability of published comparative real-world evidence (RWE) studies in Medicare patients for the ten drugs set to undergo Centers for Medicare and Medicaid Services (CMS) price negotiations in 2026. Materials & methods: A scoping review was completed in MEDLINE/PubMed to evaluate the availability of comparative RWE investigations conducted among Medicare-eligible patient populations in the US for the following drugs: apixaban, rivaroxaban, sitagliptin, ibrutinib, empagliflozin, etanercept, dapagliflozin, sacubitril/valsartan, ustekinumab and insulin aspart. Results: Of the 170 real-world comparative studies identified, 55 (32.4%) used Medicare real-world data (RWD) while 34 (20.0%) used commercial claims data in conjunction with either Medicare Advantage or Medicare Supplementary databases. The number of studies varied considerably by drug with apixaban and rivaroxaban studies accounting for the majority (i.e., 67.1%) of comparative RWE studies. Approximately a third or less of the comparative RWE studies were conducted in CMS RWD per drug. Conclusion: Our results demonstrate there is a considerable amount of comparative RWE for apixaban, rivaroxaban, and etanercept but limited comparative RWE for the other drugs set to undergo CMS price negotiations in 2026; additionally, our findings set up a number of next steps (e.g., risk of bias assessments) for further exploration of the available evidence base. Overall, CMS and manufacturers should consider proactively generating high-quality comparative RWE studies in the Medicare population to ensure that future price negotiations are based on robust evidence.

SURF: A Screening Tool (for Sponsors) to Evaluate Whether Using Real-World Data to Support an Effectiveness Claim in an FDA Application Has Regulatory Feasibility.

Based on recent guidance and publicly available approvals, the US Food and Drug Administration (FDA) has demonstrated its openness to considering evidence of effectiveness from real-world data (RWD) and nonrandomized studies (or "real-world evidence (RWE)") in its decision making. Through analysis of the FDA approvals, several authors have identified methodologic issues commonly discussed by FDA reviewers. However, in our analysis of FDA guidance and use cases, acceptability of RWE also critically depends on whether the characteristics of the clinical development program align with circumstances in which the FDA may have flexibility in considering evidence from real-world study designs relative to more robust designs. Successful use of RWD requires advance planning to allocate the necessary resources and time to undertake principled epidemiology approaches to study design, data selection, and implementation of analyses as well as address regulatory feedback. Thus, sponsors benefit from early identification of programs in which successful RWD use is more likely, to ensure efficient use of resources required for the next steps of scientific feasibility assessment. We developed SURF, a screening tool intended to help a sponsor decide whether to prioritize resources for further exploring the feasibility of using an RWD approach to meet the FDA's effectiveness evidentiary standards for a particular clinical development program. Here, we provide an analysis of FDA guidance, highlighting the circumstances in which RWD approaches may be most acceptable, and demonstrate the use of this screening tool, including the rationale for its construction, types of evidence needed, and application to publicly available approvals as support of concept.

A Descriptive Cohort Study of Drug Utilization Patterns Among Patients Hospitalized With Coronavirus Disease 2019 in the United States, January 2021-February 2022.

Background: There is a dearth of drug utilization studies for coronavirus disease 2019 (COVID-19) treatments in 2021 and beyond after the introduction of vaccines and updated guidelines; such studies are needed to contextualize ongoing COVID-19 treatment effectiveness studies during these time periods. This study describes utilization patterns for corticosteroids, interleukin-6 (IL-6) inhibitors, Janus kinase inhibitors, and remdesivir among hospitalized adults with COVID-19, over the entire hospitalization, and within hospitalization periods categorized by respiratory support requirements. Methods: This descriptive cohort study included United States adults hospitalized with COVID-19 admitted from 1 January 2021 through 1 February 2022; data included HealthVerity claims and hospital chargemaster. The number and distribution of patients were reported for the first 3 drug regimen lines initiated. Results: The cohort included 51 066 patients; the most common initial drug regimens were corticosteroids (23.4%), corticosteroids plus remdesivir (25.1%), and remdesivir (4.4%). IL-6 inhibitors and Janus kinase inhibitors were included in later drug regimens and were more commonly administered with both corticosteroids and remdesivir than with corticosteroids alone. IL-6 inhibitors were more commonly administered than Janus kinase inhibitors when patients received high-flow oxygen or ventilation. Conclusions: These findings provide important context for comparative studies of COVID-19 treatments with study periods extending into 2021 and later. While prescribing generally aligned with National Institutes of Health COVID-19 treatment guidelines during this period, these findings suggest that prescribing preference, potential confounding by indication, and confounding by prior/concomitant use of other therapeutics should be considered in the design and interpretation of comparative studies.

A Structured Process to Identify Fit-for-Purpose Study Design and Data to Generate Valid and Transparent Real-World Evidence for Regulatory Uses.

Generating evidence from real-world data requires fit-for-purpose study design and data. In addition to validity, decision makers require transparency in the reasoning that underlies study design and data source decisions. The 2019 Structured Preapproval and Postapproval Comparative Study Design Framework to Generate Valid and Transparent Real-World Evidence (SPACE) and the 2021 Structured Process to Identify Fit-For-Purpose Data (SPIFD)-intended to be used together-provide a step-by-step guide to identify decision grade, fit-for-purpose study design and data. In this update (referred to as "SPIFD2" to encompass both the design and data aspects) we provide an update to these frameworks that combines the templates into one, more explicitly calls for articulation of the hypothetical target trial and sources of bias that may arise in the real-world emulation, and provides explicit references to the Structured Template and Reporting Tool for Real-World Evidence (STaRT-RWE) tables that we suggest using immediately after invoking the SPIFD2 framework. Following the steps recommended in the SPIFD2 process requires due diligence on the part of the researcher to ensure that every aspect of study design and data selection is rationalized and supported by evidence. The resulting stepwise documentation enables reproducibility and clear communication with decision makers, and it increases the likelihood that the evidence generated is valid, fit-for-purpose, and sufficient to support healthcare and regulatory decisions.

Using primary care data to assess comparative effectiveness and safety of apixaban and rivaroxaban in patients with nonvalvular atrial fibrillation in the UK: an observational cohort study.

OBJECTIVE: To compare real-world effectiveness and safety of direct oral anticoagulants (DOACs) in patients with nonvalvular atrial fibrillation (AFib) for prevention of stroke. STUDY DESIGN AND SETTING: A comparative cohort study in UK general practice data from The Health Improvement Network database. PARTICIPANTS AND INTERVENTIONS: Before matching, 5655 patients ≥18 years with nonvalvular AFib who initiated at least one DOAC between 1 July 2014 and 31 December 2020 were included. DOACs of interest included apixaban, rivaroxaban, edoxaban and dabigatran, with the primary comparison between apixaban and rivaroxaban. Initiators of DOACs were defined as new users with no record of prescription for any DOAC during 12 months before index date. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was stroke (ischaemic or haemorrhagic). Secondary outcomes included the occurrence of all-cause mortality, myocardial infarction (MI), transient ischaemic attacks (TIA), major bleeding events and a composite angina/MI/stroke (AMS) endpoint. RESULTS: Compared with rivaroxaban, patients initiating apixaban showed similar rates of stroke (HR: 0.93; 95% CI 0.64 to 1.34), all-cause mortality (HR: 1.03; 95% CI 0.87 to 1.22), MI (HR: 0.95; 95% CI 0.54 to 1.68), TIA (HR: 1.03; 95% CI 0.61 to 1.72) and AMS (HR: 0.96; 95% CI 0.72 to 1.27). Apixaban initiators showed lower rates of major bleeding events (HR: 0.60; 95% CI 0.47 to 0.75). CONCLUSIONS: Among patients with nonvalvular AFib, apixaban was as effective as rivaroxaban in reducing rate of stroke and safer in terms of major bleeding episodes. This head-to-head comparison supports conclusions drawn from indirect comparisons of DOAC trials against warfarin and demonstrates the potential for real-world evidence to fill evidence gaps and reduce uncertainty in both health technology assessment decision-making and clinical guideline development.

Real-world comparative effectiveness of mRNA-1273 and BNT162b2 vaccines among immunocompromised adults identified in administrative claims data in the United States.

INTRODUCTION: Head-to-head studies comparing COVID-19 mRNA vaccine effectiveness in immunocompromised individuals, who are vulnerable to severe disease are lacking, as large sample sizes are required to make meaningful inferences. METHODS: This observational comparative effectiveness study was conducted in closed administrative claims data from the US HealthVerity database (December 11, 2020-January 10, 2022, before omicron). A 2-dose mRNA-1273 versus BNT162b2 regimen was assessed for preventing medically-attended breakthrough COVID-19 diagnosis and hospitalizations among immunocompromised adults. Inverse probability of treatment weighting was applied to balance baseline characteristics between vaccine groups. Incidence rates from patient-level data and hazard ratios (HRs) using weighted Cox proportional hazards models were calculated. RESULTS: Overall, 57,898 and 66,981 individuals received a 2-dose regimen of mRNA-1273 or BNT161b2, respectively. Among the weighted population, mean age was 51 years, 53 % were female, and baseline immunodeficiencies included prior blood transplant (8%-9%), prior organ transplant (7%), active cancer (12%-13%), primary immunodeficiency (5-6%), HIV (20%-21%), and immunosuppressive therapy use (60%-61%). Rates per 1,000 person-years (PYs; 95% confidence intervals [CI]s) of breakthrough medically-attended COVID-19 were 25.82 (23.83-27.97) with mRNA-1273 and 30.98 (28.93, 33.18) with BNT162b2 (HR, 0.83; 95% CI, 0.75-0.93). When requiring evidence of an antigen or polymerase chain reaction test before COVID-19 diagnosis, the HR for medically-attended COVID-19 was 0.78 (0.67-0.92). Breakthrough COVID-19 hospitalization rates per 1,000 PYs (95% CI) were 3.66 (2.96-4.51) for mRNA-1273 and 4.68 (3.91-5.59) for BNT162b2 (HR, 0.78; 0.59-1.03). Utilizing open and closed claims for outcome capture only, or both cohort entry/outcome capture, produced HRs (95% CIs) for COVID-19 hospitalization of 0.72 (0.57-0.92) and 0.66 (0.58-0.76), respectively. CONCLUSIONS: Among immunocompromised adults, a 2-dose mRNA-1273 regimen was more effective in preventing medically-attended COVID-19 in any setting (inpatient and outpatient) than 2-dose BNT162b2. Results were similar for COVID-19 hospitalization, although statistical power was limited when using closed claims only. STUDY REGISTRATION: NCT05366322.

Describing characteristics and treatment patterns of patients hospitalized with COVID-19 by race and ethnicity in a national RWD during the early months of the pandemic.

OBJECTIVE: To describe differences by race and ethnicity in treatment patterns among hospitalized COVID-19 patients in the US from March-August 2020. METHODS: Among patients in de-identified Optum electronic health record data hospitalized with COVID-19 (March-August 2020), we estimated odds ratios of receiving COVID-19 treatments of interest (azithromycin, dexamethasone, hydroxychloroquine, remdesivir, and other steroids) at hospital admission, by race and ethnicity, after adjusting for key covariates of interest. RESULTS: After adjusting for key covariates, Black/African American patients were less likely to receive dexamethasone (adj. OR [95% CI]: 0.83 [0.71, 0.96]) and more likely to receive other steroids corticosteroids (adj. OR [95% CI]: 2.13 [1.90, 2.39]), relative to White patients. Hispanic/Latino patients were less likely to receive dexamethasone than Not Hispanic/Latino patients (adj. OR [95% CI]: 0.69 [0.58, 0.82]). CONCLUSIONS: Our findings suggest that COVID-19 treatments patients received in Optum varied by race and ethnicity after adjustment for other possible explanatory factors. In the face of rapidly evolving treatment landscapes, policies are needed to ensure equitable access to novel and repurposed therapeutics to avoid disparities in care by race and ethnicity.

Visualizations throughout pharmacoepidemiology study planning, implementation, and reporting.

Transparency is increasingly promoted to instill trust in nonrandomized studies using real-world data. Graphics and data visualizations support transparency by aiding communication and understanding, and can inform study design and analysis decisions. However, other than graphical representation of a study design and flow diagrams (e.g., a Consolidated Standards of Reporting Trials [CONSORT] like diagram), specific standards on how to maximize validity and transparency with visualization are needed. This paper provides guidance on how to use visualizations throughout the life cycle of a pharmacoepidemiology study-from initial study design to final report-to facilitate rationalized and transparent decision-making about study design and implementation, and clear communication of study findings. Our intent is to help researchers align their practices with current consensus statements on transparency.

Treatment effectiveness in a rare oncology indication: Lessons from an external control cohort study.

Real-world data (RWD) reflecting patient treatment in routine clinical practice can be used to develop external control groups for single-arm trials. External controls can provide valuable benchmark results on potential comparator drug effectiveness, particularly in rare indications when randomized controlled trials are either infeasible or unethical. This paper describes lessons learned from a descriptive real-world external control cohort study conducted to provide benchmark data for a single-arm clinical trial in a rare oncology biomarker driven disease. Conducting external control cohort studies to evaluate treatment effectiveness in rare indications likely will present data and analysis challenges as seen in the example study. However, there are mitigating measures that can be applied in the study design, identification of RWD sources, and data analysis. The lessons learned and reported here with a proposal of an external control study framework can provide guidance for future research in this area, and may be applicable as well in other rare indications. Taking these learnings into consideration, the use of real-world external controls to contextualize treatment effectiveness in rare indications is a valuable approach and warrants further application in the future.

A Comparison of Seven Oncology External Control Arm Case Studies: Critiques From Regulatory and Health Technology Assessment Agencies.

OBJECTIVES: The development of accelerated approval programs for high morbidity and unmet need conditions has driven the use of single-arm studies in drug development. Regulatory and health technology assessment (HTA) agencies are recognizing that high-quality external control arms (ECAs), built using real-world data, can reduce uncertainties arising from single-arm studies. This review compared 7 case studies of regulatory and HTA agencies' evaluations of oncology ECAs. METHODS: Food and Drug Administration multidisciplinary reviews for oncology submissions from 2014 to 2021 were screened to identify 7 cases (2 blinatumomab indications, avelumab, and erdafitinib, entrectinib, trastuzumab deruxtecan, and idecabtagene vicleucel) with ECAs to support efficacy claims. Regulatory (Food and Drug Administration, European Medicines Agency, Health Canada) and HTA (pan-Canadian Oncology Drug Review, National Institute for Health and Care Excellence, Federal Joint Committee, Haute Autorité de Santé, and Pharmaceutical Benefits Advisory Committee) submissions for these cases were reviewed. The decision makers' ECA critiques and the level of influence on the decision were analyzed and categorized. RESULTS: Across case studies, selection bias and confounding were the most common ECA critiques. Nevertheless, agreement in critiques between and among regulators and HTA bodies was low. ECA influence on agencies' decisions also varied. CONCLUSIONS: Evaluating the same ECA evidence, agencies focused on methodologic issues (ie, selection bias and confounding), but were often not aligned on their critiques. Further research is needed to fully characterize how agencies evaluate ECAs. This study is a first step in critically evaluating agencies' critiques of ECAs and highlights the need for future guidance development around ECA design and generation.

Categorization of COVID-19 severity to determine mortality risk.

PURPOSE: Algorithms for classification of inpatient COVID-19 severity are necessary for confounding control in studies using real-world data. METHODS: Using Healthverity chargemaster and claims data, we selected patients hospitalized with COVID-19 between April 2020 and February 2021, and classified them by severity at admission using an algorithm we developed based on respiratory support requirements (supplemental oxygen or non-invasive ventilation, O2/NIV, invasive mechanical ventilation, IMV, or NEITHER). To evaluate the utility of the algorithm, patients were followed from admission until death, discharge, or a 28-day maximum to report mortality risks and rates overall and by stratified by severity. Trends for heterogeneity in mortality risk and rate across severity classifications were evaluated using Cochran-Armitage and Logrank trend tests, respectively. RESULTS: Among 118 117 patients, the algorithm categorized patients in increasing severity as NEITHER (36.7%), O2/NIV (54.3%), and IMV (9.0%). Associated mortality risk (and 95% CI) was 11.8% (11.6-12.0%) overall and increased with severity [3.4% (3.2-3.5%), 11.5% (11.3-11.8%), 47.3% (46.3-48.2%); p < 0.001]. Mortality rate per 1000 person-days (and 95% CI) was 15.1 (14.9-15.4) overall and increased with severity [5.7 (5.4-6.0), 14.5 (14.2-14.9), 32.7 (31.8-33.6); p < 0.001]. CONCLUSION: As expected, we observed a positive association between the algorithm-defined severity on admission and 28-day mortality risk and rate. Although performance remains to be validated, this provides some assurance that this algorithm may be used for confounding control or stratification in treatment effect studies.

The Structured Process to Identify Fit-For-Purpose Data: A Data Feasibility Assessment Framework.

To complement real-world evidence (RWE) guidelines, the 2019 Structured Preapproval and Postapproval Comparative study design framework to generate valid and transparent real-world Evidence (SPACE) framework elucidated a process for designing valid and transparent real-world studies. As an extension to SPACE, here, we provide a structured framework for conducting feasibility assessments-a step-by-step guide to identify decision grade, fit-for-purpose data, which complements the United States Food and Drug Administration (FDA)'s framework for a RWE program. The process was informed by our collective experience conducting systematic feasibility assessments of existing data sources for pharmacoepidemiology studies to support regulatory decisions. Used with the SPACE framework, the Structured Process to Identify Fit-For-Purpose Data (SPIFD) provides a systematic process for conducting feasibility assessments to determine if a data source is fit for decision making, helping ensure justification and transparency throughout study development, from articulation of a specific and meaningful research question to identification of fit-for-purpose data and study design.

Organized structure of real-world evidence best practices: moving from fragmented recommendations to comprehensive guidance.

Decision-makers have become increasingly interested in incorporating real-world evidence (RWE) into their decision-making process. Due to concerns regarding the reliability and quality of RWE, stakeholders have issued numerous recommendation documents to assist in setting RWE standards. The fragmented nature of these documents poses a challenge to researchers and decision-makers looking for guidance on what is 'high-quality' RWE and how it can be used in decision-making. We offer researchers and decision-makers a structure to organize the landscape of RWE recommendations and identify consensus and gaps in the current recommendations. To provide researchers with a much needed pathway for generating RWE, we discuss how decision-makers can move from fragmented recommendations to comprehensive guidance.

COVID-19 Evidence Accelerator: A parallel analysis to describe the use of Hydroxychloroquine with or without Azithromycin among hospitalized COVID-19 patients.

BACKGROUND: The COVID-19 pandemic remains a significant global threat. However, despite urgent need, there remains uncertainty surrounding best practices for pharmaceutical interventions to treat COVID-19. In particular, conflicting evidence has emerged surrounding the use of hydroxychloroquine and azithromycin, alone or in combination, for COVID-19. The COVID-19 Evidence Accelerator convened by the Reagan-Udall Foundation for the FDA, in collaboration with Friends of Cancer Research, assembled experts from the health systems research, regulatory science, data science, and epidemiology to participate in a large parallel analysis of different data sets to further explore the effectiveness of these treatments. METHODS: Electronic health record (EHR) and claims data were extracted from seven separate databases. Parallel analyses were undertaken on data extracted from each source. Each analysis examined time to mortality in hospitalized patients treated with hydroxychloroquine, azithromycin, and the two in combination as compared to patients not treated with either drug. Cox proportional hazards models were used, and propensity score methods were undertaken to adjust for confounding. Frequencies of adverse events in each treatment group were also examined. RESULTS: Neither hydroxychloroquine nor azithromycin, alone or in combination, were significantly associated with time to mortality among hospitalized COVID-19 patients. No treatment groups appeared to have an elevated risk of adverse events. CONCLUSION: Administration of hydroxychloroquine, azithromycin, and their combination appeared to have no effect on time to mortality in hospitalized COVID-19 patients. Continued research is needed to clarify best practices surrounding treatment of COVID-19.

Real-World Evidence for Assessing Pharmaceutical Treatments in the Context of COVID-19.

The emergence and global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in an urgent need for evidence on medical interventions and outcomes of the resulting disease, coronavirus disease 2019 (COVID-19). Although many randomized controlled trials (RCTs) evaluating treatments and vaccines for COVID-19 are already in progress, the number of clinical questions of interest greatly outpaces the available resources to conduct RCTs. Therefore, there is growing interest in whether nonrandomized real-world evidence (RWE) can be used to supplement RCT evidence and aid in clinical decision making, but concerns about nonrandomized RWE have been highlighted by a proliferation of RWE studies on medications and COVID-19 outcomes with widely varying conclusions. The objective of this paper is to review some clinical questions of interest, potential data types, challenges, and merits of RWE in COVID-19, resulting in recommendations for nonrandomized RWE designs and analyses based on established RWE principles.

Determining the Suitability of Registries for Embedding Clinical Trials in the United States: A Project of the Clinical Trials Transformation Initiative.

BACKGROUND: Patient registries are organized systems that use observational methods to collect uniform data on specified outcomes in a population defined by a particular disease, condition, or exposure. Data collected in registries often coincide with data that could support clinical trials. Integrating clinical trials within registries to create registry-embedded clinical trials offers opportunities to reduce duplicative data collection, identify and recruit patients more efficiently, decrease time to database lock, accelerate time to regulatory decision-making, and reduce clinical trial costs. This article describes a project of the Clinical Trials Transformation Initiative (CTTI) intended to help clinical trials researchers determine when a registry could potentially serve as the platform for the conduct of a clinical trial. METHODS: Through a review of registry-embedded clinical trials and commentaries, semi-structured interviews with experts, and a multi-stakeholder expert meeting, the project team addressed how to identify and describe essential registry characteristics, practices, and processes required to for conducting embedded clinical trials intended for regulatory submissions in the United States. RESULTS: Recommendations, suggested practices, and decision trees that facilitate the assessment of whether a registry is suitable for embedding clinical trials were developed, as well as considerations for the design of new registries. Essential registry characteristics include relevancy, robustness, reliability, and assurance of patient protections. CONCLUSIONS: The project identifies a clear role for registries in creating a sustainable and reusable infrastructure to conduct clinical trials. Adoption of these recommendations will facilitate the ability to perform high-quality and efficient prospective registry-based clinical trials.

Association of Azithromycin Use With Cardiovascular Mortality.

Importance: Azithromycin is one of the most commonly prescribed antibiotics in the US. It has been associated with an increased risk of cardiovascular death in some observational studies. Objective: To estimate the relative and absolute risks of cardiovascular and sudden cardiac death after an outpatient azithromycin prescription compared with amoxicillin, an antibiotic not known to increase cardiovascular events. Design, Setting, and Participants: This retrospective cohort study included 2 large, diverse, community-based integrated care delivery systems with comprehensive capture of encounters and prescriptions from January 1, 1998, to December 31, 2014. The cohort included patients aged 30 to 74 years who had at least 12 months of health-plan enrollment prior to antibiotic exposure. The exclusion criteria were absence of prescription benefits, prescription for more than 1 type of study antibiotic within 10 days, hospitalization or nursing home residence, and serious medical conditions. Risk of cardiovascular death associated with azithromycin vs amoxicillin exposure was calculated after controlling for confounding factors using a propensity score. Data were analyzed from December 1, 2016, to March 30, 2020. Exposures: Outpatient prescription of azithromycin or amoxicillin. Main Outcomes and Measures: The primary outcomes were cardiovascular death and sudden cardiac death. An a priori subgroup analysis quantified the effects of azithromycin exposure among patients with increased baseline cardiovascular risk. The secondary outcomes were noncardiovascular death and all-cause mortality. Results: The study included 7 824 681 antibiotic exposures, including 1 736 976 azithromycin exposures (22.2%) and 6 087 705 amoxicillin exposures (77.8%), among 2 929 008 unique individuals (mean [SD] age, 50.7 [12.3] years; 1 810 127 [61.8%] women). Azithromycin was associated with a significantly increased hazard of cardiovascular death (hazard ratio [HR], 1.82; 95% CI, 1.23-2.67) but not sudden cardiac death (HR, 1.59; 95% CI, 0.90-2.81) within 5 days of exposure. No increases in risk were found 6 to 10 days after exposure. Similar results were observed in patients within the top decile of cardiovascular risk (HR, 1.71; 95% CI, 1.06-2.76). Azithromycin was also associated with an increased risk of noncardiovascular death (HR, 2.17; 95% CI, 1.44-3.26) and all-cause mortality (HR, 2.00; 95% CI, 1.51-2.63) within 5 days of exposure. Conclusions and Relevance: These findings suggest that outpatient azithromycin use was associated with an increased risk of cardiovascular death and noncardiovascular death. Causality cannot be established, particularly for noncardiovascular death, owing to the likelihood of residual confounding.

Pulmonary and cardiovascular safety of inhaled insulin in routine practice: The Exubera Large Simple Trial (VOLUME).

OBJECTIVE: VOLUME is a randomized, open-label, post-approval pragmatic trial aiming to evaluate long-term pulmonary and cardiovascular safety of Exubera® (EXU; insulin human [rDNA origin] Inhalation Powder) in routine clinical practice. The primary study objective is to compare risk of persistent decline in forced expiratory volume in 1 second (FEV1) among patients treated with and without EXU. RESEARCH DESIGN AND METHODS: Patients eligible to take EXU per approved local label were randomized to EXU or routine care and followed per usual care, with scheduled FEV1 tests at baseline, 6 months, and yearly.Randomization halted in October 2007 after Pfizer announced it would stop marketing EXU due to low sales. EXU patients were subsequently transitioned to usual care and all patients were followed for 6 additional months. RESULTS: Although there was insufficient power to evaluate the primary endpoint (37% of the planned 5,300 were randomized), the study provided important descriptive information.Per the primary endpoint definition, more EXU group patients (n = 8) experienced a persistent decline in FEV1 (n = 0 in usual care). Using a broader, clinically relevant pre-specified supplementary definition of persistent decline, similar numbers were observed in the EXU (n = 27) and usual care (n = 24) groups. Slightly more pulmonary and allergic serious adverse event composite endpoints were seen in the EXU group. There were no consistent treatment group differences in the cardiovascular composite endpoint, all-cause mortality, or glycemic control. CONCLUSIONS: Clinically important declines in lung function that persisted more than 60 days were uncommon and of similar frequency in Exubera and usual care. CLINICALTRIALSGOV: NCT00359801.

Implications of product withdrawal on a post-approval pragmatic trial: The VOLUME study experience.

INTRODUCTION: Many clinical trials terminate early due to safety and efficacy concerns, and less often due to unexpected "positive" findings. However, early termination of post-approval (Phase IV) pragmatic randomized trials for commercial reasons is less frequent, may be more complex, and may require added flexibility in closure methods, including short term follow-up. VOLUME was a randomized, open-label, post-approval pragmatic clinical trial (PCT) or large simple trial that terminated early due to product withdrawal. The aim of this paper is to describe circumstances unique to post-approval PCTs that may require a closure amendment rather than immediate study termination, and our recommendations for operational study closure in these circumstances. We use the VOLUME case study throughout to provide a practical example. METHODS: Study closeout considerations at the study level include: notifying external governance bodies, e.g., data monitoring committees (DMC), and scientific steering committees (SSC); executing a study closure amendment; notifying and training of study physicians; and institutional review board (IRB)/ethics committee (EC) approvals. Study closure considerations at the patient level focus on patient safety and include: patient notification, efficient transition to alternative treatments, the need for re-consenting; and drug supply shortages. CONCLUSIONS: Early study closeout logistics require careful analysis, detailed planning, and close coordination, and are ideally considered at the study planning phase. Lessons learned from the VOLUME closeout should help other researchers devise contingencies when terminating post approval pragmatic trials that utilize a marketed product.ClinicalTrials.gov: NCT00359801.

Lung Cancer-Related Mortality With Inhaled Insulin or a Comparator: Follow-Up Study of patients previously enrolled in Exubera Controlled Clinical Trials (FUSE) Final Results.

OBJECTIVE: The Follow-Up Study of patients previously enrolled in Exubera controlled clinical trials (FUSE) was designed to evaluate whether patients previously treated with Exubera (EXU; insulin human [rDNA origin], inhaled powder) in controlled clinical trials died because of incident primary lung cancer at a substantially higher rate than patients treated with a comparator. RESEARCH DESIGN AND METHODS: FUSE is a hybrid, randomized, controlled trial/cohort study including participants of 17 prior EXU clinical trials. Pooled patient data from these trials were used, and the subset of patients enrolled in the follow-up cohort study was followed prospectively for 2 years in order to evaluate the incidence of fatal and nonfatal primary lung cancers and all-cause mortality. RESULTS: There were 24,409 person-years (PY) of observation among 7,439 trial patients, with 4,017 PY (16.5%) from the period after the trials but before the prospective follow-up and 5,299 PY (21.7%) from the prospective follow-up. Just over half of the 2,631 patients (51.6%) in the prospective follow-up were randomized to EXU in the original trial. The incidence density ratio was 2.8 (95% CI 0.5, 28.5) for lung cancer-related mortality and 3.7 (95% CI 1.0, 20.7) for incident primary lung cancer. The hazard ratio for all-cause mortality was 0.81 (95% CI 0.60, 1.10). CONCLUSIONS: These data cannot exclude an increased risk of lung cancer-related mortality associated with EXU use. If real, the absolute increased risk of lung cancer-related mortality was small (0.48 cases per 1,000 PY). For all-cause mortality-the most reliably measured end point with the clearest interpretation-EXU users did not experience an excess all-cause death rate (relative or absolute) compared with users of other diabetes treatments over the study period.