Broadening the reach of the FDA Sentinel system: A roadmap for integrating electronic health record data in a causal analysis framework

Desai, Rishi; Matheny, Michael E.; Johnson, Kevin B.; Marsolo, Keith; Curtis, Lesley H.; Nelson, Jennifer C.; Heagerty, Patrick J.; Maro, Judith C.; Brown, Jeffery; Toh, Sengwee; Nguyen, Michael; Ball, Robert; Pan, Gerald J. Dal; Wang, Shirley; Gagne, Joshua J.; Schneeweiß, Sebastian

doi:10.1038/s41746-021-00542-0

Cited by 36 publications

(27 citation statements)

References 22 publications

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“…[35][36][37][38][39][40] Regarding the challenge of integrating data from multiple sources, the FDA Sentinel Innovation Center recently presented a roadmap and outlined plans and visions for the future. 41,42 The Center for Drug Evaluation of the NMPA recently drafted the Guidelines for Design and Protocol Frameworks for Real-World Drug Studies (draft open for comments). 43 The guidelines mention that the source of research data should be clarified, including the research center from which they came, the start and end time of data collection, and the system and record format of data storage.…”

Section: Discussionmentioning

confidence: 99%

Worldwide Trends in Registering Real-World Studies at ClinicalTrials.gov: A Cross-Sectional Analysis

Li¹,

Tian²,

Pei³

et al. 2023

IJGM

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The purpose of this study was to characterize real-world studies (RWSs) registered at ClinicalTrials.gov to help investigators better conduct relevant research in clinical practice. Methods: A retrospective analysis of 944 studies was performed on February 28, 2023. Results: A total of 944 studies were included. The included studies involved a total of 48 countries. China was the leading country in terms of the total number of registered studies (37.9%, 358), followed by the United States (19.7%, 186). Regarding intervention type, 42.4% (400) of the studies involved drugs, and only 9.1% (86) of the studies involved devices. Only 8.5% (80) of the studies mentioned both the detailed study design type and data source in the "Brief Summary". A total of 49.4% (466) of studies had a sample size of 500 participants and above. Overall, 63% (595) of the studies were single-center studies. A total of 213 conditions were covered in the included studies. One-third of the studies (32.7%, 309) involved neoplasms (or tumors). China and the United States were very different regarding the study of different conditions. Conclusion:Although the pandemic has provided new opportunities for RWSs, the rigor of scientific research still needs to be emphasized. Special attention needs to be given to the correct and comprehensive description of the study design in the Brief Summary of registered studies, thereby promoting communication and understanding. In addition, deficiencies in ClinicalTrials.gov registration data remain prominent.

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Section: Discussionmentioning

confidence: 99%

Worldwide Trends in Registering Real-World Studies at ClinicalTrials.gov: A Cross-Sectional Analysis

Li¹,

Tian²,

Pei³

et al. 2023

IJGM

View full text Add to dashboard Cite

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“…This study has several limitations. First, we identified MCI patients and AD onsets using ICD codes (Supplementary Tables 2) which were provided by physicians and validated in 47, 48 , yet there might be a certain level of inaccuracy due to mis- and under-diagnosis or the lack of clinical details in EHRs or claims 38, 49 . Information contained in clinical notes will be explored in the future through natural language processing to complement the structured codes.…”

Section: Discussionmentioning

confidence: 99%

“…• Last, compared with existing AD repurposing studies which typically focused on validating one or two hypotheses with a single type of RWD 31,37,38 , our study offered a high-throughput way of generating and validating AD repurposing hypotheses using both EHRs and claims 39 , which would further catalyze innovation in AD drug discovery at scale, or can be broadly applied to other diseases.…”

Section: Discussionmentioning

confidence: 99%

High-Throughput Clinical Trial Emulation with Real World Data and Machine Learning: A Case Study of Drug Repurposing for Alzheimer’s Disease

Zang

Zhang

et al. 2022

Preprint

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Clinical trial emulation, which is the process of mimicking targeted randomized controlled trials (RCT) with real world data (RWD), has attracted growing attentions and interests in recent years from pharmaceutical industry. Different from RCTs which have stringent eligibility criteria for recruiting participants, RWD are more representative of real world patients whom the drugs will be prescribed to. One technical challenge for trial emulation is how to conduct effective confounding control with complex RWD so that the treatment effects can be objectively derived. Recently many approaches, including deep learning algorithms, have been proposed for this goal, but there is still no systematic evaluation and practical guidance on them. In this paper, we emulate $430,000$ trials from two large-scale RWD warehouses, covering both electronic health records (EHR) and general claims, over 170 million patients spanning more than 10 years, aiming to identify new indications of approved drugs for Alzheimer's disease (AD). We have investigated the behaviors of multiple different approaches including logistic regression and deep learning models, and propose a new model selection strategy that can significantly improve the performance of confounding balance of the participants in different arms of emulated trials. We demonstrate that regularized logistic regression based propensity score (PS) model outperforms deep learning based PS model and others, which contradicts with our intuitions to certain extent. Finally, we identified 8 drugs whose original indications are not AD (pantoprazole, gabapentin, acetaminophen, atorvastatin, albuterol, fluticasone, amoxicillin and omeprazole), hold great potential of being beneficial to AD patients.

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“…The historical distinction between “research” and “treatment” intent is not always clear—nor should this imply that the primary intent (treatment) should prevent other (research) usages. Electronic health records are clearly intended to aid in the treatment of patients, but have been harnessed on a grand scale to simultaneously facilitate research ( Desai et al, 2021 ).…”

Section: Policy Recommendationsmentioning

confidence: 99%

Generating Evidence from Expanded Access Use of Rare Disease Medicines: Challenges and Recommendations

et al. 2022

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Patients with rare diseases often have limited or no options for approved treatments or participation in clinical trials. In such cases, expanded access (or “compassionate use”) provides a potential means of accessing unapproved investigational medicines. It is also possible to capture and analyze clinical data from such use, but doing so is controversial. In this perspective, we offer examples of evidence derived from expanded access programs for rare diseases to illustrate its potential value to the decision-making of regulators and payers in the European Union and the United States. We discuss ethical and regulatory aspects to the use of expanded access data, with a focus on rare disease medicines. The heterogeneous approach to expanded access among countries within the European Union leaves uncertainties to what extent data can be collected and analyzed. We recommend the issuance of new guidance on data collection during expanded access, harmonization of European pathways, and an update of existing European compassionate use guidance. We hereby aim to clarify the supportive role of expanded access in evidence generation. Harmonization across Europe of expanded access regulations could reduce manufacturer burdens, improve patient access, and yield better data. These changes would better balance the need to generate quality evidence with the desire for pre-approval access to investigational medicine.

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Broadening the reach of the FDA Sentinel system: A roadmap for integrating electronic health record data in a causal analysis framework

Cited by 36 publications

References 22 publications

Worldwide Trends in Registering Real-World Studies at ClinicalTrials.gov: A Cross-Sectional Analysis

Worldwide Trends in Registering Real-World Studies at ClinicalTrials.gov: A Cross-Sectional Analysis

High-Throughput Clinical Trial Emulation with Real World Data and Machine Learning: A Case Study of Drug Repurposing for Alzheimer’s Disease

Generating Evidence from Expanded Access Use of Rare Disease Medicines: Challenges and Recommendations

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