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Real-world data (RWD) and the derivations of these data into real-world evidence (RWE) are rapidly expanding from informing healthcare decisions at the patient and health system level to influencing major health policy decisions, including regulatory approvals and coverage. Recent examples include the approval of palbociclib in combination with endocrine therapy for male breast cancer and the inclusion of RWE in the label of paliperidone palmitate for schizophrenia. This interest has created an urgency to develop processes that promote trust in the evidence-generation process. Key stakeholders and decision-makers include patients and their healthcare providers; learning health systems; health technology assessment bodies and payers; pharmacoepidemiologists and other clinical reseachers, and policy makers interested in bioethical and regulatory issues. A key to optimal uptake of RWE is transparency of the research process to enable decision-makers to evaluate the quality of the methods used and the applicability of the evidence that results from the RWE studies. Registration of RWE studies-particularly for hypothesis evaluating treatment effectiveness (HETE) studies-has been proposed to improve transparency, trust, and research replicability. Although registration would not guarantee better RWE studies would be conducted, it would encourage the prospective disclosure of study plans, timing, and rationale for modifications. A joint task force of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the International Society for Pharmacoepidemiology (ISPE) recommended that investigators preregister their RWE studies and post their study protocols in a publicly available forum before starting studies to reduce publication bias and improve the transparency of research methods. Recognizing that published recommendations alone are insufficient, especially without accessible registration options and with no incentives, a group of experts gathe

Asha Hareendran,1 Nancy K Leidy,2 Brigitta U Monz,3 Randall Winnette,1 Karin Becker,3 Donald A Mahler41United BioSource Corporation, London, UK; 2United BioSource Corporation, Bethesda, MD, USA; 3Boehringer Ingelheim, Ingelheim, Germany; 4Dartmouth Medical School, Hanover, NH, USABackground: Measuring dyspnea intensity associated with exercise provides insights into dyspnea-limited exercise capacity, and has been used to evaluate treatment outcomes for chronic obstructive pulmonary disease (COPD). Three patient-reported outcome scales commonly cited for rating dyspnea during exercise are the modified Borg scale (MBS), numerical rating scale for dyspnea (NRS-D), and visual analogue scale for dyspnea (VAS-D). Various versions of each scale were found. Our objective was to evaluate the content validity of scales commonly used in COPD studies, to explore their ability to capture patients' experiences of dyspnea during exercise, and to evaluate a standardized version of the MBS.Methods: A two-stage procedure was used, with each stage involving one-on-one interviews with COPD patients who had recently completed a clinic-based exercise event on a treadmill or cycle ergometer. An open-ended elicitation interview technique was used to understand patients' experiences of exercise-induced dyspnea, followed by patients completing the three scales. The cognitive interviewing component of the study involved specific questions to evaluate the patients' perspectives of the content and format of the scales. Results from Stage 1 were used to develop a standardized version of the MBS, which was then subjected to further content validity assessment during Stage 2.Results: Thirteen patients participated in the two-stage process (n = 6; n = 7). Mean forced expiratory volume in 1 second (FEV1) percent predicted was 40%, mean age 57 years, and 54% were male. Participants used a variety of terms to describe the intensity and variability of exercise-induced dyspnea. S

Lucas MA Goossens1, Christine L Baker2, Brigitta U Monz3, Kelly H Zou2, Maureen PMH Rutten-van Mölken11Institute for Medical Technology Assessment, Erasmus University, Rotterdam, The Netherlands; 2Pfizer Inc, New York City, NY, USA; 3Boehringer Ingelheim International GmbH, Ingelheim am Rhein, GermanyPurpose: When comparing chronic obstructive lung disease (COPD) interventions in database research, it is important to adjust for severity. Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines grade severity according to lung function. Most databases lack data on lung function. Previous database research has approximated COPD severity using demographics and healthcare utilization. This study aims to derive an algorithm for COPD severity using baseline data from a large respiratory trial (UPLIFT).Methods: Partial proportional odds logit models were developed for probabilities of being in GOLD stages II, III and IV. Concordance between predicted and observed stage was assessed using kappa-statistics. Models were estimated in a random selection of 2/3 of patients and validated in the remainder. The analysis was repeated in a subsample with a balanced distribution across severity stages. Univariate associations of COPD severity with the covariates were tested as well.Results: More severe COPD was associated with being male and younger, having quit smoking, lower BMI, osteoporosis, hospitalizations, using certain medications, and oxygen. After adjusting for these variables, co-morbidities, previous healthcare resource use (eg, emergency room, hospitalizations) and inhaled corticosteroids, xanthines, or mucolytics were no longer independently associated with COPD severity, although they were in univariate tests. The concordance was poor (kappa = 0.151) and only slightly better in the balanced sample (kappa = 0.215).Conclusion: COPD severity cannot be reliably predicted from demographics and healthcare use. This limitation should be considered when