Real-world Data Sources Research Articles

POSA389 Who Can We See in RWD? Assessing Capture of Demographic Data Across Multiple Countries

Real-world data (RWD) and real-world evidence (RWE) play an increasing role in healthcare decision-making, including regulatory decisions, clinical care, guideline development, and reimbursement/payer decisions. As such, the capture, completeness, and quality of these data underlying these analyses are imperative. Demographic data are critical to the identification of disparities in disease risk and care quality. However, the extent to which these characteristics are collected and recorded in RWD sources is not well known.

Observational designs for real-world evidence studies

In the era of evidence-based medicine, real-world evidence (RWE) studies have opened avenues to utilize real-world data (RWD) effectively for improving clinical decision-making. However, the transformation of RWD into a meaningful RWE can only be achieved when the researcher asks the right clinical question, selects the right RWD source for variables of interest, uses the right study design, and applies the right statistical analysis. The generated RWE needs to have internal as well as external validity to be actionable. The “fit-for-purpose” observational study designs include descriptive, case–control, cross-sectional, and cohort. This article focuses on the advantages and disadvantages including the inherent bias of each study design. The RWE study decision guide has also been provided to aid the selection of appropriate study designs.

An overview of real-world data sources for oncology and considerations for research.

Generating evidence on the use, effectiveness, and safety of new cancer therapies is a priority for researchers, health care providers, payers, and regulators given the rapid pace of change in cancer diagnosis and treatments. The use of real-world data (RWD) is integral to understanding the utilization patterns and outcomes of these new treatments among patients with cancer who are treated in clinical practice and community settings. An initial step in the use of RWD is careful study design to assess the suitability of an RWD source. This pivotal process can be guided by using a conceptual model that encourages predesign conceptualization. The primary types of RWD included are electronic health records, administrative claims data, cancer registries, and specialty data providers and networks. Careful consideration of each data type is necessary because they are collected for a specific purpose, capturing a set of data elements within a certain population for that purpose, and they vary by population coverage and longitudinality. In this review, the authors provide a high-level assessment of the strengths and limitations of each data category to inform data source selection appropriate to the study question. Overall, the development and accessibility of RWD sources for cancer research are rapidly increasing, and the use of these data requires careful consideration of composition and utility to assess important questions in understanding the use and effectiveness of new therapies.

Coping with interoperability in the development of a federated research infrastructure: achievements, challenges and recommendations from the JA-InfAct

BackgroundInformation for Action! is a Joint Action (JA-InfAct) on Health Information promoted by the EU Member States and funded by the European Commission within the Third EU Health Programme (2014–2020) to create and develop solid sustainable infrastructure on EU health information. The main objective of this the JA-InfAct is to build an EU health information system infrastructure and strengthen its core elements by a) establishing a sustainable research infrastructure to support population health and health system performance assessment, b) enhancing the European health information and knowledge bases, as well as health information research capacities to reduce health information inequalities, and c) supporting health information interoperability and innovative health information tools and data sources.MethodsFollowing a federated analysis approach, JA-InfAct developed an ad hoc federated infrastructure based on distributing a well-defined process-mining analysis methodology to be deployed at each participating partners’ systems to reproduce the analysis and pool the aggregated results from the analyses. To overcome the legal interoperability issues on international data sharing, data linkage and management, partners (EU regions) participating in the case studies worked coordinately to query their real-world healthcare data sources complying with a common data model, executed the process-mining analysis pipeline on their premises, and shared the results enabling international comparison and the identification of best practices on stroke care.ResultsThe ad hoc federated infrastructure was designed and built upon open source technologies, providing partners with the capacity to exploit their data and generate dashboards exploring the stroke care pathways. These dashboards can be shared among the participating partners or to a coordination hub without legal issues, enabling the comparative evaluation of the caregiving activities for acute stroke across regions.Nonetheless, the approach is not free of a number of challenges that have been solved, and new challenges that should be addressed in the eventual case of scaling up. For that eventual case, 12 recommendations considering the different layers of interoperability have been provided.ConclusionThe proposed approach, when successfully deployed as a federated analysis infrastructure, such as the one developed within the JA-InfAct, can concisely tackle all levels of the interoperability requirements from organisational to technical interoperability, supported by the close collaboration of the partners participating in the study. Any proposal for extension, should require further thinking on how to deal with new challenges on interoperability.

Physicians’ Experience and Willingness to Participate in Non-Interventional Trials in Bulgaria

Summary Non-interventional studies (NIS) are conducted to obtain additional information about a medicinal product prescribed in the usual manner in compliance with the conditions determined in the marketing authorization. They are a valuable source of real-world data for the effectiveness and safety of medicines. This study aims to assess physicians‘ knowledge of non-interventional studies in Bulgaria and identify the primary factors and barriers hindering the NIS at a national level. An individual anonymous questionnaire with 16 items was distributed among physicians in inpatient and outpatient settings. The results showed that 81.3% (n=147) of the respondents have no experience with non-interventional studies. Physicians‘ willingness to participate in NIS in the future is high and independent of their previous experience. The main barriers hindering conducting NIS in Bulgaria are related to organization, the conduct and the design of the trials, and, sometimes, the investigators‘ concerns. There is a need for proper training of the researchers and expanding healthcare resources to grow the NIS sector in Bulgaria in line with the tendencies in Europe.

Use of Real-World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design.

Interest in real‐world data (RWD) and real‐world evidence (RWE) to expedite and enrich the development of new biopharmaceutical products has proliferated in recent years, spurred by the 21st Century Cures Act in the United States and similar policy efforts in other countries, willingness by regulators to consider RWE in their decisions, demands from third‐party payers, and growing concerns about the limitations of traditional clinical trials. Although much of the recent literature on RWE has focused on potential regulatory uses (e.g., product approvals in oncology or rare diseases based on single‐arm trials with external control arms), this article reviews how biopharmaceutical companies can leverage RWE to inform internal decisions made throughout the product development process. Specifically, this article will review use of RWD to guide pipeline and portfolio strategy; use of novel sources of RWD to inform product development, use of RWD to inform clinical development, use of advanced analytics to harness “big” RWD, and considerations when using RWD to inform internal decisions. Topics discussed will include the use of molecular, clinicogenomic, medical imaging, radiomic, and patient‐derived xenograft data to augment traditional sources of RWE, the use of RWD to inform clinical trial eligibility criteria, enrich trial population based on predicted response, select endpoints, estimate sample size, understand disease progression, and enhance diversity of participants, the growing use of data tokenization and advanced analytical techniques based on artificial intelligence in RWE, as well as the importance of data quality and methodological transparency in RWE.

Integration of Real-World Data and Genetics to Support Target Identification and Validation.

Even modest improvements in the probability of success of selecting drug targets which are ultimately approved can substantially reduce the costs of research and development. Drug targets with human genetic evidence of disease association are twice as likely to lead to approved drugs. A key enabler of identifying and validating these genetically validated targets is access to association results from genome-wide genotyping, whole-exome sequencing, and whole-genome sequencing studies with observable traits (often diseases) across large numbers of individuals. Today, linkage between genotype and real-world data (RWD) provides significant opportunities to not only increase the statistical power of genome-wide association studies by ascertaining additional cases for diseases of interest, but also to improve diversity and coverage of association studies across the disease phenome. As RWD-genetics linked resources continue to grow in diversity of participants, breadth of data captured, length of observation, and number of participants, there is a greater need to leverage the experience of RWD experts, clinicians, and highly experienced geneticists together to understand which lessons and frameworks from general research using RWD sources are relevant to improve genetics-driven drug discovery and development. This paper describes new challenges and opportunities for phenotypes enabled by diverse RWD sources, considerations in the use of RWD phenotypes for disease gene identification across the disease phenome, and challenges and opportunities in leveraging RWD phenotypes in target validation. The paper concludes with views on the future directions for phenotype development using RWD, and key questions requiring further research and development to advance this nascent field.

Real-World Data of Palbociclib in Combination With Endocrine Therapy for the Treatment of Metastatic Breast Cancer in Men.

This report examined the benefits and risks of palbociclib plus endocrine therapy (ET) in men with hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) metastatic breast cancer (MBC). Palbociclib was evaluated using three independent data sources: real-world data from pharmacy and medical claims, a de-identified real-world data source derived from electronic health records (EHRs), and a global safety database. From medical and pharmacy records, 1,139 men with MBC were identified; in the first-line setting, median duration of treatment was longer with palbociclib plus ET (n=37, 8.5months, 95% confidence interval (CI), 4.4-13.0) than ET alone (n=214, 4.3months, 95% CI, 3.0-5.7) and specifically, was longer with palbociclib plus letrozole (n=26, 9.4months, 95% CI, 4.4-14.0) than letrozole alone (n=63, 3.0months, 95% CI, 1.8-4.8). In the EHR-derived database, 59 men received treatment for MBC; real-world response across all lines of therapy in the metastatic setting was reported in 4 of 12 patients (33.3%) in the palbociclib plus ET group vs. 1 of 8 (12.5%) patients in the ET group. Review of the global safety database did not identify any new safety signals in palbociclib-treated men. Real-world data indicated that men with MBC benefit from palbociclib plus ET, with a safety profile consistent with previous observations in women with MBC. Collective data on palbociclib in women and men in this report, including clinical trial data, real-world data, and a well-established risk/benefit profile, led to US approval of an expansion of the palbociclib indication to include men with MBC.

How can real-world evidence aid decision making during the life cycle of nonprescription medicines?

Real‐world evidence (RWE) is an emerging scientific discipline which is being increasingly utilized for decision making on prescription‐only medicines. However, there has been little focus to date on the application of RWE within the nonprescription sector. This paper reviews the existing and potential applications of RWE for nonprescription medicines, using the nonprescription medicine life cycle as a framework for discussion. Relevant sources of real‐world data (RWD) are reviewed and compared with those available for prescribed medicines. Existing life‐cycle data gaps are identified where RWE is required or where use of RWE can complement data from randomized controlled trials. Published RWE examples relating to nonprescription medicines are summarized, and potential relevant future sources of RWD discussed. Challenges and limitations to the use of RWE on nonprescription medicines are discussed, and recommendations made to promote optimal and appropriate use of RWE in this sector. Overall, RWE currently plays a key role in specific phases of the nonprescription medicine life cycle, including reclassification and postmarketing safety surveillance. The increasing availability of patient‐generated health data is likely to further increase the utilization of RWE to aid decision making on nonprescription medicines.

A Descriptive Review of Global Real World Evidence Efforts to Advance Drug Discovery and Clinical Development in Amyotrophic Lateral Sclerosis.

Understanding patient clinical progression is a key gateway to planning effective clinical trials and ultimately enabling bringing treatments to patients in need. In a rare disease like amyotrophic lateral sclerosis (ALS), studies of disease natural history critically depend on collaboration between clinical centers, regions, and countries to enable creation of platforms to allow patients, caregivers, clinicians, and researchers to come together and more fully understand the condition. Rare disease registries and collaborative platforms such as those developed in ALS collect real-world data (RWD) in standardized formats, including clinical and biological specimen data used to evaluate risk factors and natural history of disease, treatment patterns and clinical (ClinROs) and patient- reported outcomes (PROs) and validate novel endpoints. Importantly, these data support the development of new therapeutics by supporting the evaluation of feasibility and design of clinical trials and offer valuable information on real-world disease trajectory and outcomes outside of the clinical trial setting for comparative purposes. RWD may help to accelerate therapy development by identifying and validating outcome measures and disease subpopulations. RWD can also make potential contributions to the evaluation of the safety and effectiveness of new indications for approved products and to satisfy post-approval regulatory and market access requirements. There is a lack of amalgamated information on available registries, databases, and other sources of real-world data on ALS; thus, a global review of all available resources was warranted. This targeted review identifies and describes ALS registries, biobanks and collaborative research networks that are collecting and synthesizing RWD for the purposes of increasing patient awareness and advancing scientific knowledge with the hope of expediting future development of new therapies.

FDA Oncology Center of Excellence Review of Real World Data Submissions Supporting Drug Development in Hematologic Malignancies

BackgroundAligning with 21st Century Cures legislation, FDA is exploring methodologies to advance appropriate uses of Real World Data (RWD) to generate Real World Evidence (RWE). RWD to support regulatory decision making has markedly increased in oncology. This review specifically focused on the analysis of RWD containing submissions for medical products in development for the treatment of hematological malignancies and associated treatment related conditions (e.g., Cytokine Release Syndrome (CRS), Graft Versus Host Disease (GVHD).MethodsA systematic search was conducted using internal FDA databases to identify RWD submissions from 2010 to 2020. Search terms included: real world evidence, real world data, electronic health record, cancer registry, administrative claims, external control arm, observational cohort, historical control arm, real world Overall Survival (rwOS) , real world Response Rate (rwRR), real world Overall Response Rate rwORR and real world Complete Response (rwCR). Regulatory submissions specific to malignant hematology and associated treatment related conditions were reviewed, and pre-defined common data elements were extracted and validated by independent dual review. Descriptive statistics were calculated.ResultsA total of 142 regulatory submissions included RWD from 2011-2020. A subset of 94 RWD submissions met the criteria for further evaluation, of which 20 (21%) submissions corresponding with 14 molecular entities were for hematologic malignancies or treatment related conditions (e.g., CRS, GVHD). RWD submissions increased substantially over time, with 14 (70%) of submissions received between 2019-2020. Specific evaluation for pediatric indications was referenced in 15% of submissions. The most commonly referenced RWD source was EHR data (55%), followed by use of multiple sources (20%), and registry data (15%). Approximately 90% of the submissions aimed to support treatment effectiveness. Primary RWD study objectives included supporting approval of a new molecular entity (NME) (40%), expanding an approved indication (25%), conversion from accelerated to regular approval (15%), and providing data to inform postmarketing safety evaluation (20%). Among RWD submissions, response endpoints (e.g., rwORR, rwCR, rwPR, Partial Response) and overall survival (e.g., rwOS) were most frequently selected as primary outcomes for 50% and 20% of proposals respectively; however, these outcomes were included as any endpoint in 65% and 75% of submissions.ConclusionThis review demonstrates increasing use of various RWD sources to support evidence generation for drug development in hematologic malignancies and associated treatment related conditions with the primary objective of supporting demonstration of effectiveness using rwOS or real world response measures as primary endpoints. Given the increased inclusion of RWD in regulatory submissions, further methodological development is needed, including in the selection and validation of rwEndpoints. Appropriate study design must be aligned with a clear regulatory objective to ensure that RWD can be adequately evaluated. Additionally, the development of standardized metrics for data characterization and transparency in reporting of RWD are foundational steps to the evaluation of fit for purpose RWD to support regulatory decision making. DisclosuresNo relevant conflicts of interest to declare.

Real-World Evaluation of the Treatment Landscape for Chronic Lymphocytic Leukemia

Introduction:The treatment paradigm of chronic lymphocytic leukemia (CLL) has changed significantly with the introduction of targeted oral therapies, including Bruton's tyrosine kinase inhibitors (BTKis) and B-cell lymphoma 2 inhibitors (Bcl-2is). As more therapies enter the clinic, real-world data (RWD) are important to understand changes in the CLL treatment landscape and describe treatment patterns, to guide decisions on treatment strategies.Methods:This retrospective analysis used 2 RWD sources. Patients (pts) diagnosed with CLL and treated with chemotherapy, CD20 monoclonal antibodies (mAbs), BTKis, or Bcl-2is were studied in the Optum Clinformatics® Data Mart (CDM), a de-identified US administrative claims database. Pts in the CDM analysis received at least 1 prescription for or administration of a treatment of interest between 2016 and 2020 Q2, and a diagnosis of CLL within 12 months (mo) of treatment start. Cross-sectional annual cohorts were used to understand changes in treatment mix over time, and longitudinal cohorts were formed to identify treatment patterns. Medication adherence was assessed with persistence at 12 mo using a 60-day gap and proportion of days covered (PDC) at 12 mo. Electronic health records from oncology practices were extracted through December 2020 from the COTA real-world evidence database. Adults diagnosed with CLL/small lymphocytic lymphoma and treated with BTKis and/or Bcl-2is were included. Treatment discontinuation was assessed using physician-documented treatment dates and reasons for discontinuation, and overall duration of treatment with targeted therapy was assessed using Kaplan-Meier analysis.Results:In CDM, annual treatment rate among pts diagnosed with CLL increased from 16% (1788/10911) in 2016 to 26% (2441/9349) in 2020. The proportion of pts treated with BTKis and Bcl-2is increased from 40% (2016) to 65% (2020) and <1% (2016) to 13% (2020), respectively; corresponding decreases in the use of chemotherapies and CD20 mAbs were observed (Figure 1A). In pts initiating BTKis, most pts were not previously treated (937/1438; 65%); the most common initial regimens were BTKi monotherapy (mono) (1367/1438; 95%) and BTKi + CD20 mAb (54/1438; 4%). Few pts switched from BTKi mono to CD20 mAb mono (43/1367; 3%) or added CD20 mAb to BTKi mono (44/1367; 3%) within 12 mo. In pts initiating Bcl-2is, most received prior treatment (169/198; 85%); most common regimens were Bcl-2i mono (159/198; 80%), Bcl-2i + CD20 mAb (31/198; 16%), and Bcl-2i + BTKi (8/198; 4%). Among pts initiating Bcl-2i mono, 30% (48/159) added CD20 mAb within 12 mo; among pts initiating Bcl-2i + CD20 mAb, 94% (29/31) switched to Bcl-2i mono within 12 mo. Persistence at 12 mo was similar for BTKis (899/1438; 63%) and Bcl-2is (120/198; 61%) and mean (SD) PDC was similar for BTKis 0.69 (0.31) and Bcl-2is 0.68 (0.29). In COTA, 469 pts treated with BTKis and/orBcl-2is were included. More pts initiated BTKis as first-line (1L) (185/449; 41%) compared with Bcl-2is (13/109; 12%). Among pts initiating targeted therapy as 1L, most pts (81%; 149/185) initiated BTKi mono. Discontinuation rates were high for pts receiving BTKis (62%; 279/449) and Bcl-2is (61%; 67/109). Among BTKi discontinuers, toxicity (54%; 150/279) was the most common reason for discontinuation, followed by disease progression (12%; 34/279) (Figure 1B). Among Bcl-2i discontinuers, toxicity (36%; 24/67) was the most common reason for discontinuation, followed by completion of regimen (30%; 20/67) (Figure 1C). Median duration of treatment was 777 days (95% CI: 632-920) for the BTKis group and 639 days (95% CI: 335-755) for the Bcl-2is group. Median treatment duration in days was comparable between mono and combination regimens in both BTKis (782 vs. 809) and Bcl-2is (747 vs. 718) groups.Conclusions:RWD show standard of care shifted from chemoimmunotherapy to targeted therapies. Pts receiving targeted therapies had high rates of discontinuation, most commonly due to toxicity. Most targeted regimens were mono; more BTKi pts were treatment naive compared to Bcl-2i pts. Slow adoption of fixed-duration therapy with the Bcl-2i combination regimen was observed. The duration of Bcl-2i mono was comparable to that of the Bcl-2i combination regimens, and a high number of pts initiating combo regimens continued on mono regimens in contrast to regimens studied in randomized controlled trials. [Display omitted] DisclosuresSmith: Novartis: Current Employment; Pfizer: Ended employment in the past 24 months. Owusu: Novartis: Current Employment; Roche: Ended employment in the past 24 months. Wormser: Roche: Current equity holder in publicly-traded company; Novartis: Current Employment, Current equity holder in publicly-traded company. Woo: Novartis: Current Employment, Current equity holder in publicly-traded company.

Single-Agent Ibrutinib Versus Real-World (RW) Treatments for Patients with Previously Untreated Chronic Lymphocytic Leukemia (CLL): Adjusted Comparison of Resonate-2™ with the Cllear and Lyon-Sud Rw Databases

IntroductionIbrutinib, a once-daily oral Bruton's tyrosine kinase inhibitor, has shown progression-free survival (PFS) or overall-survival (OS) benefit over chemoimmunotherapy (CIT) in multiple phase 3 studies in previously untreated patients with CLL, and significantly longer time to next treatment compared with CIT in previously untreated high-risk patients in a RW setting. We conducted an adjusted comparison of ibrutinib versus RW treatment for previously untreated CLL using patient-level data from the phase 3 RESONATE-2™ (NCT01722487) trial and RW databases from 2 countries.MethodsPreviously untreated patients with CLL, fulfilling RESONATE-2™ eligibility criteria (age ≥ 65, no del17p) were selected from 2 RW data sources containing electronic medical records for patients with CLL: Centre Hospitalier Lyon-Sud, France; CLLEAR CLL registry from 7 academic centers in the Czech Republic. PFS and OS were compared between patients from the ibrutinib arm of RESONATE-2™ with a median follow-up of 60 months, and those receiving physicians' choice (PC) treatment other than ibrutinib from the RW database, adjusting for differences in baseline characteristics including age, gender, del11q, IGHV status, RAI/BINET disease stage, and Eastern Cooperative Oncology Group (ECOG) score. Hazard ratios (HRs) for ibrutinib versus RW PC treatment were estimated using a multivariable Cox proportional hazards model including available baseline characteristics as covariates, and using an inverse probability weighted (IPW) Cox model with average treatment effect for treatment (ATT) weights derived from propensity scores estimated from a logistic regression including the same covariates.ResultsThe analysis included 136 patients from the RESONATE-2™ study receiving ibrutinib and 920 previously untreated RW patients receiving PC treatment (Lyon-Sud n = 162, CLLEAR n = 758). Baseline characteristics were generally balanced between treatment groups. The most common PC regimens contained CIT and were fludarabine + cyclophosphamide + rituximab (FCR) (n = 227), bendamustine + rituximab (BR) (n = 201), and rituximab + chlorambucil (R + Chlor) (n = 116). Older age, male gender, del11q and advanced disease stage were independent risk factors for PFS and OS. When comparing ibrutinib versus the overall PC cohort, the adjusted HR (95% confidence interval [CI]) was 0.24 (0.16-0.34) for PFS and 0.33 (0.21-0.52) for OS (both p < 0.0001). IPW-based comparative estimates were highly consistent for both PFS (HR = 0.27 [0.18-0.39]) and OS (HR = 0.39 [0.24-0.62]). ATT-weighted survival curves estimating PFS and OS for the RESONATE-2™ population as if treated with PC, showed a median value of 32.1 months and 72.5 months, respectively, while median values for Ibrutinib were not reached. When comparing ibrutinib versus FCR, BR, and R + Chlor, the adjusted HRs (95% CI) were 0.26 (0.17-0.38), 0.27 (0.18-0.41), and 0.27 (0.17-0.42), respectively, for PFS and 0.34 (0.20-0.56), 0.28 (0.16-0.49), and 0.61 (0.32-1.13), respectively, for OS (Figure).ConclusionsAdjusted comparisons of the RESONATE-2™ trial and RW patient-level data demonstrates significantly improved PFS and OS for ibrutinib versus physician's choice treatment (predominantly CIT) in previously untreated patients with CLL. PFS and OS benefit for ibrutinib was consistent across a range of common regimens: FCR, BR, and R + Chlor. These results are consistent with data from phase 3 studies and support the use of ibrutinib for first-line CLL treatment.Funding Source:Sponsored by Janssen Pharmaceutica NV, and Pharmacyclics LLC, an AbbVie Company. The RW databases are independently owned. Writing assistance was provided by Emma Fulkes and Liqing Xiao of Parexel and funded by Janssen Pharmaceutica NV. [Display omitted] DisclosuresDoubek: Janssen-Cilag, AbbVie, AstraZeneca, Amgen, Gilead, Novartis: Honoraria, Research Funding. Smolej: AbbVie, AstraZeneca, Gilead, Janssen-Cilag, and Roche: Consultancy, Honoraria, Other: Travel Grants. Šimkovič: AbbVie, AstraZeneca, Janssen-Cilag, Gilead, Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Grants. Lysak: Novartis, Janssen-Cilag, AbbVie; AstraZeneca: Honoraria, Research Funding. Bachy: Kite, a Gilead Company: Honoraria; Novartis: Honoraria; Daiishi: Research Funding; Roche: Consultancy; Takeda: Consultancy; Incyte: Consultancy. Ferrant: AbbVie: Honoraria, Other: Travel, Accommodations, Expenses; AstraZeneca: Honoraria; Janssen: Other: Travel, Accommodations, Expenses. Diels: Janssen: Current Employment. Cabrieto: Janssen: Current Employment. Nielsen: Janssen: Current Employment. Salles: Allogene: Consultancy; Regeneron: Consultancy, Honoraria; Velosbio: Consultancy; Takeda: Consultancy; Rapt: Consultancy; Genentech/Roche: Consultancy; Epizyme: Consultancy, Honoraria; Debiopharm: Consultancy; Genmab: Consultancy; Incyte: Consultancy; Ipsen: Consultancy; Janssen: Consultancy; Kite/Gilead: Consultancy; Loxo: Consultancy; Miltneiy: Consultancy; Morphosys: Consultancy, Honoraria; Novartis: Consultancy; BMS/Celgene: Consultancy; Beigene: Consultancy; Abbvie: Consultancy, Honoraria; Bayer: Honoraria.

Regulator-Requested Non-Interventional Postauthorization Safety and Effectiveness Studies for Oncology Drugs: A Systematic Review.

There has been a growing number of oncology drug approvals. Non-interventional postauthorization safety/effectives studies (PASSs/PAESs) aim to provide real-world evidence on the safety/effectiveness of oncology drugs postapproval. To understand the current landscape, a comprehensive search as of March 1, 2021, was conducted in major register/databases. We found that requested studies increased from 1 in 2006-2010 to 47 in 2016-2020. Of 78 total studies identified, 50 focused on safety/risk assessment (64.1%), 6 on effectiveness (7.7%), 3 on drug utilization (3.8%), 1 on disease epidemiology (1.3%), and 18 on effectiveness of additional risk minimization measures (23.1%). For safety/risk assessment studies, 58.9% focused on nonspecific end points (e.g., frequency of adverse events). For effectiveness studies, the leading primary outcome was overall survival. Overall, safety/risk assessment studies concerning nonspecific end points for vascular endothelial growth factor (receptor) inhibitors were most requested. Regarding data sources, though a majority (71.8%) used primary data collection, a growing proportion utilized secondary data sources. Among 23 studies with information available on study design, 10 (43.5%) were single-arm cohort studies, 9 (39.1%) were cross-sectional studies, 3 (13.1%) were comparative cohort studies, and 1 (4.3%) was a nested-case-control study. In conclusion, there was an increasing number of oncology-specific non-interventional PASSs/PAESs, with a majority on safety/risk assessment. Although most utilized primary data collection, there was an increasing use of secondary real-world data sources. Few conducted comparative analyses, and most used single-arm designs. Future efforts are needed to assess how findings of these studies would impact regulatory decisions and improve knowledge of toxicity for clinical/translational development.

The Multiple Sclerosis Data Alliance Catalogue: Enabling Web-Based Discovery of Metadata from Real-World Multiple Sclerosis Data Sources.

One of the major objectives of the Multiple Sclerosis Data Alliance (MSDA) is to enable better discovery of multiple sclerosis (MS) real-world data (RWD). We implemented the MSDA Catalogue, which is available worldwide. The current version of the MSDA Catalogue collects descriptive information on governance, purpose, inclusion criteria, procedures for data quality control, and how and which data are collected, including the use of e-health technologies and data on collection of COVID-19 variables. The current cataloguing procedure is performed in several manual steps, securing an effective catalogue. Herein we summarize the status of the MSDA Catalogue as of January 6, 2021. To date, 38 data sources across five continents are included in the MSDA Catalogue. These data sources differ in purpose, maturity, and variables collected, but this landscaping effort shows that there is substantial alignment on some domains. The MSDA Catalogue shows that personal data and basic disease data are the most collected categories of variables, whereas data on fatigue measurements and cognition scales are the least collected in MS registries/cohorts. The Web-based MSDA Catalogue provides strategic overview and allows authorized end users to browse metadata profiles of data cohorts and data sources. There are many existing and arising RWD sources in MS. Detailed cataloguing of MS RWD is a first and useful step toward reducing the time needed to discover MS RWD sets and promoting collaboration.

Comparison of Machine Learning Approaches for Missing Data Imputation Among Non-Small Cell Lung Cancer Patients

<h3>Purpose/Objective(s)</h3> Cancer registries are important sources of real-world data capturing a large number of complex data elements such as cancer stage and treatments, but the prevalence of missing data is often high. Previous research suggest missing data can identify patients within cancer registries with worse survival outcomes, potentially introducing substantial bias in studies using complete case analysis. Recent computational advances have enabled the application of machine learning (ML) imputation methods to large real-world datasets, however, the efficacy of these approaches for cancer patients is unknown. <h3>Materials/Methods</h3> We queried the National Cancer Database for non-small cell lung cancer (NSCLC) patients diagnosed in 2014 with complete data in 19 variables of known clinical and prognostic significance. Complete records were chosen given a reference value is needed to compare the efficacy of imputation techniques. We performed data preprocessing and generated synthetic missing data in 10 to 50% of records at random for each variable, then performed imputation using substitution (control) and five different ML approaches: Bayesian ridge regression under a multivariate imputation by chained equations (MICE) framework, k-nearest neighbors (KNN), matrix completion by spectral regularization (SoftImpute), iterative random forests (MissForest), and denoising autoencoders (DA). Imputation efficacy was measured by normalized root-mean-square error (RMSE) for continuous variables and proportion of falsely classified entries (PFC) for categorical variables. Algorithm runtimes were measured using a cloud computing instance with 16 virtual processors and 42 gigabytes of memory. <h3>Results</h3> We identified 50,790 NSCLC patients with complete data, each with 81 features after data preprocessing. Mean substitution for continuous variables had a RMSE of 0.091, and mode substitution for categorical variables had a PFC of 0.406. In comparison, among the tested ML methods, MICE had the lowest RMSE (best performance) for continuous variables ranging from 0.069 to 0.077 for 10 to 50% missing data, and MissForest had the lowest PFC (best performance) for categorical variables ranging from 0.251 to 0.311 for 10 to 50% missing data. Runtimes for MICE ranged from 118.9 to 267.9 seconds and for MissForest ranged from 112.0 to 186.8 seconds. KNN and DA had higher runtimes despite lower performance, while substitution runtimes were under 0.1 second for all levels of missing data. <h3>Conclusion</h3> ML methods achieved promising levels of imputation efficacy with acceptable computing runtimes for NSCLC patients within a large national cancer registry. These approaches can potentially improve clinical insights from registry data for NSLCC patients through enabling more complete cohorts incorporating ML imputed information.

Replication of Oncology Randomized Trial Results using Swedish Registry Real World-Data: A Feasibility Study.

Nationwide healthcare registries are potential important real-world data (RWD) sources for assessing drug effectiveness in oncology. However, it is unclear whether registry-derived RWD are suitable for clinical development. In this study, we replicate results from the comparator arm of two previously published oncology randomized controlled trials (RCTs) using RWD from Swedish nationwide healthcare registries. For replication 1, the RCT included 553 patients and the RWD included 283 patients treated with sorafenib for advanced hepatocellular cancer. The median overall survival (OS) was 11.2 (95% confidence interval (CI): 10.1-13.2) months in the RCT and 8.2 (95% CI: 7.0-9.9) months in the RWD, unadjusted hazard ratio (HR) 0.75 (95% CI: 0.63-0.88). For time-to-treatment discontinuation (TTD), the HR was 1.00 (95% CI: 0.87-1.16). For replication 2, the RCT included 154 patients and the RWD included 704 patients treated with melphalan, prednisone, and thalidomide for untreated multiple myeloma. The median OS was 52.6 (95% CI: 40-not applicable) months in the RCT and 36.9 (95% CI: 33.8-40.5) months in the RWD, unadjusted HR 0.67 (95% CI: 0.51-0.87). For TTD, the HR was 0.89 (95% CI: 0.74-1.06). The results were similar when applying various propensity-based confounding adjustments. In conclusion, OS was shorter in the RWD, whereas TTD was similar. Importantly, the data necessary (ex: eligibility criteria and baseline confounders) for replicating RCTs was mostly not available and these results further underscore the importance of developing frameworks for capturing relevant patient-level RWD for clinical and regulatory decision making in oncology.

5.12 Relationship Between Polypharmacy and Clinical Functioning in Patients With ADHD: A Retrospective Analysis of Real-World Data

Polypharmacy is common in the treatment of ADHD, but little is known about its relation to clinical functioning. The primary objective of this analysis was to use a large real-world data (RWD) source derived from electronic health records to examine this relationship in patients with ADHD across the life span. Notably, this RWD source includes information regarding both medications and clinical functioning, measured with a clinician-rated Clinical Global Impression-Severity (CGI-S) score. The NeuroBlu™ database includes deidentified data from more than 550,000 unique patients over 20 years, including CGI-S scores. Data were from US sites using a common electronic health record system. All patients with an ICD diagnosis of ADHD were included. Additional inclusion criteria included: ≥3 clinical visits within a 12-month period, CGI-S recorded at initial visit, and prescription medication information. Cohorts were defined by the maximum number of simultaneous medications prescribed in a 12-month time frame and included patients prescribed 0, 1, 2, 3, 4, and 5 or more medications at a single time point. Mean and median CGI-S scores at initial ADHD diagnosis were compared across cohorts. Cohorts were further stratified for children (aged 0-12 years), adolescents (aged 13-17 years), and adults (aged 18 years and older). Of 53,744 patients with ADHD, 31,824 met the eligibility criteria; 59% were White, and 58% were male. The proportion of patients included in each of the polypharmacy cohorts was as follows: 0 (6%); 1 (21%); 2 (24%); 3 (19%); 4 (13%); and 5+ (18%). Patients on 0-4 medications had a median CGI of 4, and those with 5+ medications had a median CGI of 5. Although there was a statistically significant difference across cohorts with respect to mean CGI-S score, the clinical significance of this difference was small. Pairwise comparisons indicated that there were no differences in CGI-S scores between patients receiving 0, 1, or 2 medications and only a nominal difference between those receiving 0 and 3 medications. Results were similar when examined across age groups. Polypharmacy practices in patients with ADHD may not be meaningfully associated with clinical functioning. Findings highlight the need for additional research with RWD sources to better understand these prescribing practices.

Allergen immunotherapy: The growing role of observational and randomized trial "Real-World Evidence".

Although there is a considerable body of knowledge about allergen immunotherapy (AIT), there is a lack of data on the reliability of real-world evidence (RWE) in AIT, and consequently, a lack of information on how AIT effectively works in real life. To address the current unmet need for an appraisal of the quality of RWE in AIT, the European Academy of Allergy and Clinical Immunology Methodology Committee recently initiated a systematic review of observational studies of AIT, which will use the RELEVANT tool and the Grading of Recommendations Assessment, Development and Evaluation approach (GRADE) to rate the quality of the evidence base as a whole. The next step will be to develop a broadly applicable, pragmatic "real-world" database using systematic data collection. Based on the current RWE base, and perspectives and recommendations of authorities and scientific societies, a hierarchy of RWE in AIT is proposed, which places pragmatic trials and registry data at the positions of highest level of evidence. There is a need to establish more AIT registries that collect data in a cohesive way, using standardized protocols. This will provide an essential source of real-world data that can be easily shared, promoting evidence-based research and quality improvement in study design and clinical decision-making.

Use of Real-World Evidence for Regulatory Approval and Coverage of Medical Devices: A Landscape Assessment

ObjectivesTo enhance the generalizability of the evidence it reviews, the US Food and Drug Administration (FDA) has encouraged manufacturers to expand the submission of real-world evidence (RWE). The extent to which this evidence, which is generated outside of research settings, can support decision making remains unclear. We described the current use of RWE for medical devices, assessed manufacturers’ challenges in generating and using it for regulatory and coverage decisions, and identified opportunities to expand its use. MethodsWe conducted 27 solo and group interviews with FDA officials and representatives of device manufacturers, payers, and health technology assessment organizations. All interviews used a semistructured protocol and were transcribed to allow thematic analysis. ResultsAccessing and linking real-world data sources, identifying unique devices, capturing longitudinal data, limited staff expertise, and uncertain return on investment have hampered efforts to use real-world data. Many companies in our sample were conducting research using real-world data, but none had submitted RWE as the primary evidence supporting a premarket approval. FDA guidance was helpful, but regulatory requirements remained ambiguous and examples of successful regulatory decisions based on RWE were limited. Payers mainly used RWE to supplement experimental evidence in coverage decisions, evaluated both types of evidence in similar ways, and had concerns about the rigor of RWE. ConclusionsTechnical challenges may slow efforts to generate and use RWE in the near term. Additional regulatory guidance and examples, greater use of rigorous study designs and analytic methods, and continued stakeholder engagement could accelerate the use of RWE.