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Increased interest in real-world evidence (RWE) for clinical and regulatory decision making and the need to evaluate long-term benefits and risks of pharmaceutical products raise the importance of understanding the use of external controls (ECs) for uncontrolled extensions of randomized controlled trials (RCTs). We searched clinicaltrials.gov from 2009 to 2019 for uncontrolled extensions and assessed the use of ECs in the trial protocol registry and PubMed. We present characteristics of identified uncontrolled extensions, their adoption of ECs, and a qualitative appraisal of published uncontrolled extensions with ECs according to good pharmacoepidemiologic practice. The number of uncontrolled extensions increased slightly across the study period, resulting in a total of 1,115 studies. Most originated from phase III RCTs (62.2%) and specified safety outcomes (61.9% among those with specified outcomes). Most uncontrolled extensions incorporated no control group with only 7 out of 1,115 (0.6%) employing ECs. For those studies with ECs, all involved treatments for rare conditions and assessment of effectiveness. Attempts to balance comparison groups varied from none mentioned to propensity score matching. We noted consistent deficiencies in outcome ascertainment methods and approaches to address attrition bias. The contrast of the large and growing number of uncontrolled extensions with the small number of studies that utilized ECs showed clear opportunities for enhancement in design, measurement, and analysis of uncontrolled extensions to allow causal inferences on long-term treatment effects. As extensions continue to expand within RWE regulatory frameworks, development of guidelines for use of EC with uncontrolled extensions is needed.

Purpose Clinical trials compare outcomes among patients receiving study treatment with comparators drawn from the same source. These internal controls are missing in single arm trials and from long‐term extensions (LTE) of trials including only the treatment arm. An external control group derived from a different setting is then required to assess safety or effectiveness. Methods We present examples of external control groups that demonstrate some of the issues that arise and make recommendations to address them through careful assessment of the data source fitness for use, design, and analysis steps. Results Inclusion and exclusion criteria and context that produce a trial population may result in trial patients with different clinical characteristics than are present in an external comparison group. If these differences affect the risk of outcomes, then a comparison of outcome occurrence will be confounded. Further, patients who continue into LTE may differ from those initially entering the trial due to treatment effects. Application of appropriate methods is needed to make valid inferences when such treatment or selection effects are present. Outcome measures in a trial may be ascertained and defined differently from what can be obtained in an external comparison group. Differences in sensitivity and specificity for identification or measurement of study outcomes leads to information bias that can also invalidate inferences. Conclusion This review concentrates on threats to the valid use of external control groups both in the scenarios of single arm trials and LTE of randomized controlled trials, along with methodological approaches to mitigate them.

Outbreaks of emerging pathogens pose unique methodological and practical challenges for the design, implementation, and evaluation of vaccine efficacy trials. Lessons learned from COVID-19 highlight the need for innovative and flexible study design and application to quickly identify promising candidate vaccines. Trial design strategies should be tailored to the dynamics of the specific pathogen, location of the outbreak, and vaccine prototypes, within the regional socioeconomic constraints. Mathematical and statistical models can assist investigators in designing infectious disease clinical trials. We introduce key challenges for planning, evaluating, and modelling vaccine efficacy trials for emerging pathogens.

ObjectiveTo provide current estimates of the number of patients with prevalent systemic lupus erythematosus (SLE) by major health insurance types in the US and describe patient characteristics. Four large US health insurance claims databases were analyzed to represent different types of insurance coverage, including private insurance, Medicaid, and Medicare Supplemental. ResultsOverall unadjusted SLE prevalence per 100,000 persons in the US ranged from 150.1 (private insurance) to 252.9 (Medicare Supplemental insurance). Extrapolating to the US civilian population in 2016, we estimated roughly 345,000 to 404,000 prevalent SLE patients with private/Medicare insurance, and 99,000 prevalent SLE patients with Medicaid insurance.Comorbidities, including renal failure/dialysis were commonly observed across multiple organ systems in SLE patients (8.4-21.1%). We estimated a larger number of prevalent SLE cases in the US civilian population than previous reports and observed extensive disease burden based on a 1-year cross-sectional analysis.

Thrombotic Thrombocytopenia after Ad26.COV2.S Vaccination — Manufacturer’s Response The manufacturer of the Ad26.COV2.S vaccine against Covid-19 comments on recent reports of thrombosis, including ...

Pragmatic or real-world trials typically incorporate many elements of pragmatism, including a generalizable target patient population for recruitment and collection of data through the process of routine care. However, in some instances critical data will need to be collected outside of usual practice to meet the research objective. This chapter will highlight some pragmatic trials that incorporated bespoke primary data collection into the protocol. These examples illustrate the range of specific study objectives, settings, and the choices made by investigators to maintain a pragmatic approach while still optimizing the validity of the study.

Hana Müllerová,1 Sarah H Landis,1 Zaurbek Aisanov,2 Kourtney J Davis,3 Masakazu Ichinose,4 David M Mannino,5 Joe Maskell,1 Ana M Menezes,6 Thys van der Molen,7 Yeon-Mok Oh,8 Maggie Tabberer,9 MeiLan K Han10 1GSK, Worldwide Epidemiology, Uxbridge, UK; 2Pulmonology Research Institute, Moscow, Russia; 3GSK, Worldwide Epidemiology, Upper Providence, PA, USA; 4Tohoku University Graduate School of Medicine, Sendai, Japan; 5University of Kentucky College of Public Health, Lexington, KY, USA; 6Federal University of Pelotas, Pelotas, Brazil; 7University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; 8University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea; 9GSK, Value Evidence Outcomes, Uxbridge, UK; 10Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI, USA Background and aims: We used data from the Continuing to Confront COPD International Patient Survey to test the hypothesis that patients with COPD who report less engagement with their disease management are also more likely to report greater impact of the disease. Methods: This was a population-based, cross-sectional survey of 4,343 subjects aged ≥40years from 12 countries, fulfilling a case definition of COPD based on self-reported physician diagnosis or symptomatology. The impact of COPD was measured with COPD Assessment Test, modified Medical Research Council Dyspnea Scale, and hospital admissions and emergency department visits for COPD in the prior year. The 13-item Patient Activation Measure (PAM-13) instrument and the 8-item Morisky Medication Adherence Scale (MMAS-8) were used to measure patient disease engagement and medication adherence, respectively. Results: Twenty-eight percent of subjects reported being either disengaged or struggling with their disease (low engagement: PAM-13 levels 1 and 2), and 35% reported poor adherence (MMAS-8

Masking (or blinding) of treatment assignment is routinely implemented in classical randomized clinical trials (RCTs) to isolate the effect of the intervention itself and to minimize the potential for bias that could occur with traditional trials. Such biases could be introduced with the conduct, assessment of endpoints, management of conditions, analysis, and reporting when the treatment assignments are known. However, masking of treatments is not only complex but it hinders how generalizable the findings are to the "real world" clinical setting. Pragmatic RCTs (pRCTs) are intended to evaluate the effects of interventions within routine medical care, and as such, do not typically mask treatment groups; moreover, pRCTs assess comparators that are available in routine medical practice, not masked placebos. Whether pRCTs should be masked if intended for regulatory or other purposes has recently been questioned. The literature on pRCTs, while extensive, does not address how much actual benefit is gained from masking outcomes and how masking may affect the "real world" nature of a study. Here, we propose an approach to evaluate sources of bias, describe stakeholders in the conduct of pRCTs who are most likely affected, and offer a framework for considering how masking may be implemented effectively while maintaining generalizability.

Background Accurate identification of hospitalizations for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) within electronic health care records is important for research, public health, and to inform health care utilization and service provision. We aimed to develop a strategy to identify hospitalizations for AECOPD in secondary care data and to investigate the validity of strategies to identify hospitalizations for AECOPD in primary care data. Methods We identified patients with chronic obstructive pulmonary disease (COPD) in the Clinical Practice Research Datalink (CPRD) with linked Hospital Episodes Statistics (HES) data. We used discharge summaries for recent hospitalizations for AECOPD to develop a strategy to identify the recording of hospitalizations for AECOPD in HES. We then used the HES strategy as a reference standard to investigate the positive predictive value (PPV) and sensitivity of strategies for identifying AECOPD using general practice CPRD data. We tested two strategies: 1) codes for hospitalization for AECOPD and 2) a code for AECOPD other than hospitalization on the same day as a code for hospitalization due to unspecified reason. Results In total, 27,182 patients with COPD were included. Our strategy to identify hospitalizations for AECOPD in HES had a sensitivity of 87.5%. When compared with HES, using a code suggesting hospitalization for AECOPD in CPRD resulted in a PPV of 50.2% (95% confidence interval [CI] 48.5%–51.8%) and a sensitivity of 4.1% (95% CI 3.9%–4.3%). Using a code for AECOPD and a code for hospitalization due to unspecified reason resulted in a PPV of 43.3% (95% CI 42.3%–44.2%) and a sensitivity of 5.4% (95% CI 5.1%–5.7%). Conclusion Hospitalization for AECOPD can be identified with high sensitivity in the HES database. The PPV and sensitivity of strategies to identify hospitalizations for AECOPD in primary care data alone are very poor. Primary care data alone should not be used to identify hospitalizations for AECOPD. Instead, researchers should use data that are linked to data from secondary care.

Müllerová H, Landis SH, Aisanov Z, et al. Int J Chron Obstruct Pulmon Dis. 2016;11:881–890.On page 882, right column, second paragraph, the sentence “The primary hypotheses were addressed using the PAM-13,2 and Morisky Medication Adherence Scale (MMAS)-8.18 should have read “The primary hypotheses were addressed using the PAM-13,2 and Morisky Medication Adherence Scale (MMAS)-8.18,40,41On page 882, right column, last paragraph, the sentence “Adherence is classified as low (score 1–5), medium (score 6–7), or high (score 8) according to the overall score.” should read “Adherence is classified as low (score ,6), medium (score 6 to ,8), or high (score 8) according to the overall score.”On page 886, Table 3, the copyright statement “Use of the ©MMAS is protected by US copyright laws. Permission for use is required. A license agreement is available from: Donald E Morisky, ScD, ScM, MSPH, Professor, Department of Community Health Sciences, UCLA School of Public Health, 650 Charles E. Young Drive South, Los Angeles, CA 90095-1772.18,40,41” was not included in the Note section.Read the original article

Background Acute Exacerbations of COPD (AECOPD) identified from electronic healthcare records (EHR) are important for research, public health and to inform healthcare utilisation and service provision. However, there is no standardised method of identifying AECOPD in UK EHR. We aimed to validate the recording of AECOPD in UK EHR. Methods We randomly selected 1385 patients with COPD from the Clinical Practice Research Datalink. We selected dates of possible AECOPD based on 15 different algorithms between January 2004 and August 2013. Questionnaires were sent to GPs asking for confirmation of their patients’ AECOPD on the dates identified and for any additional relevant information. Responses were reviewed independently by two respiratory physicians. Positive predictive value (PPV) and sensitivity were calculated. Results The response rate was 71.3%. AECOPD diagnostic codes, lower respiratory tract infection (LRTI) codes, and prescriptions of antibiotics and oral corticosteroids (OCS) together for 5–14 days had a high PPV (>75%) for identifying AECOPD. Symptom-based algorithms and prescription of antibiotics or OCS alone had lower PPVs (60–75%). A combined strategy of antibiotic and OCS prescriptions for 5–14 days, or LRTI or AECOPD code resulted in a PPV of 85.5% (95% CI, 82.7–88.3%) and a sensitivity of 62.9% (55.4–70.4%). Conclusion Using a combination of diagnostic and therapy codes, the validity of AECOPD identified from EHR can be high. These strategies are useful for understanding health-care utilisation for AECOPD, informing service provision and for researchers. These results highlight the need for common coding strategies to be adopted in primary care to allow easy and accurate identification of events.

Ana M Menezes,1 Sarah H Landis,2 MeiLan K Han,3 Hana Muellerova,2 Zaurbek Aisanov,4 Thys van der Molen,5 Yeon-Mok Oh,6 Masakazu Ichinose,7 David M Mannino,8 Kourtney J Davis9 1Federal University of Pelotas, Pelotas, Brazil; 2Worldwide Epidemiology, GlaxoSmithKline, Uxbridge, UK; 3Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI, USA; 4Pulmonology Research Institute, Moscow, Russia; 5University Medical Center Groningen, University of Groningen, Groningen, the Netherlands; 6University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea; 7Tohoku University Graduate School of Medicine, Sendai, Japan; 8University of Kentucky College of Public Health, Lexington, KY, USA; 9Worldwide Epidemiology, GlaxoSmithKline, Wavre, Belgium Purpose: Using data from the Continuing to Confront COPD International Physician and Patient Surveys, this paper describes physicians’ attitudes and beliefs regarding chronic obstructive pulmonary disease (COPD) prognosis, and compares physician and patient perceptions with respect to COPD. Methods: In 12 countries worldwide, 4,343 patients with COPD were identified through systematic screening of population samples, and 1,307 physicians who regularly saw patients with COPD were sampled from in-country professional databases. Both patients and physicians completed surveys about their COPD knowledge, beliefs, and perceptions; physicians answered further questions about diagnostic methods and treatment choices for COPD. Results: Most physicians (79%) responded that the long-term health outlook for patients with COPD has improved over the past decade, largely attributed to the introduction of better medications. However, patient access to medication remains an issue in many countries, and some physicians (39%) and patients (46%) agreed/strongly agreed with the statement “there are no truly effective treatments for COPD”. There was strong concordance between physicians and patients regarding COPD management practices, including the use of spirometry (86% of physicians and 76% of patients reporting they used/had undergone a spirometry test) and smoking cessation counseling (76% of physicians reported they counseled their smoking patients at every clinic visit, and 71% of smoking patients stated that they had received counseling in the past year). However, the groups differed in their perception about the role of smoking in COPD, with 78% of physicians versus 38% of patients strongly agreeing with the statement “smoking is the cause of most cases of COPD”. Conclusion: The Continuing to Confront COPD International Surveys demonstrate that while physicians and patients largely agreed about COPD management practices and the need for more effective treatments for COPD, a gap exists about the causal role of smoking in COPD. Keywords: chronic obstructive pulmonary disease, physician survey, patient survey, beliefs, perceptions

Kourtney J Davis,1 Sarah H Landis,2 Yeon-Mok Oh,3 David M Mannino,4 MeiLan K Han,5 Thys van der Molen,6 Zaurbek Aisanov,7 Ana M Menezes,8 Masakazu Ichinose,9 Hana Muellerova11Worldwide Epidemiology, GlaxoSmithKline, Wavre, Belgium; 2Worldwide Epidemiology, GlaxoSmithKline, Uxbridge, UK; 3University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea; 4University of Kentucky College of Public Health, Lexington, KY, USA; 5Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI, USA; 6University Medical Center Groningen, University of Groningen, Groningen, the Netherlands; 7Pulmonology Research Institute, Moscow, Russia; 8Federal University of Pelotas, Pelotas, Brazil; 9Tohoku University Graduate School of Medicine, Sendai, JapanAim: Utilizing data from the Continuing to Confront COPD (chronic obstructive pulmonary disease) International Physician Survey, this study aimed to describe physicians’ knowledge and application of the GOLD (Global initiative for chronic Obstructive Lung Disease) Global Strategy for the Diagnosis, Management and Prevention of COPD diagnosis and treatment recommendations and compare performance between primary care physicians (PCPs) and respiratory specialists.Materials and methods: Physicians from 12 countries were sampled from in-country professional databases; 1,307 physicians (PCP to respiratory specialist ratio three to one) who regularly consult with COPD, emphysema, or chronic bronchitis patients were interviewed online, by telephone or face to face. Physicians were questioned about COPD risk factors, prognosis, diagnosis, and treatment, including knowledge and application of the GOLD global strategy using patient scenarios.Results: Physicians reported using spirometry routinely (PCPs 82%, respiratory specialists 100%; P

Objectives The optimal method of identifying people with chronic obstructive pulmonary disease (COPD) from electronic primary care records is not known. We assessed the accuracy of different approaches using the Clinical Practice Research Datalink, a UK electronic health record database. Setting 951 participants registered with a CPRD practice in the UK between 1 January 2004 and 31 December 2012. Individuals were selected for ≥1 of 8 algorithms to identify people with COPD. General practitioners were sent a brief questionnaire and additional evidence to support a COPD diagnosis was requested. All information received was reviewed independently by two respiratory physicians whose opinion was taken as the gold standard. Primary outcome measure The primary measure of accuracy was the positive predictive value (PPV), the proportion of people identified by each algorithm for whom COPD was confirmed. Results 951 questionnaires were sent and 738 (78%) returned. After quality control, 696 (73.2%) patients were included in the final analysis. All four algorithms including a specific COPD diagnostic code performed well. Using a diagnostic code alone, the PPV was 86.5% (77.5–92.3%) while requiring a diagnosis plus spirometry plus specific medication; the PPV was slightly higher at 89.4% (80.7–94.5%) but reduced case numbers by 10%. Algorithms without specific diagnostic codes had low PPVs (range 12.2–44.4%). Conclusions Patients with COPD can be accurately identified from UK primary care records using specific diagnostic codes. Requiring spirometry or COPD medications only marginally improved accuracy. The high accuracy applies since the introduction of an incentivised disease register for COPD as part of Quality and Outcomes Framework in 2004.