By Patrick Wulf Hanson
(Reviewed, adjusted and approved by Dr. Frederik Persson, Head of Clinic, Steno Diabetes Center, Copenhagen, Denmark)
1. Introduction
Globally, obesity has emerged as a critical public health challenge, contributing to substantial morbidity and mortality, and it is a leading risk factor for diseases such as type 2 diabetes, cardiometabolic conditions, and certain cancers (1). Addressing this epidemic requires robust research to inform public health strategies, develop personalized interventions, and evaluate the real-world effectiveness of treatments (2).
Traditional randomized controlled trials (RCTs) have provided significant insights into the treatment of obesity. However, these studies are conducted under tightly controlled conditions, which may not reflect the diverse realities of clinical practice. RWE fills this critical gap by using data from routine clinical practice to bridge the translational gap between clinical trials and real-world applications. RWE offers insights into the effectiveness, safety, and economic impact of interventions in broader populations (3).
The rapid development of innovative therapies for obesity further underscores the importance of RWE. New drugs with distinct mechanisms, varying price points, and diverse side effect profiles are entering the market, creating an urgent need for robust real-world evaluation to guide their optimal use.
2. Opportunities and importance of RWE in obesity research
RWE represents an indispensable tool in obesity research, complementing RCTs by capturing data from real-world settings. Unlike controlled trials, RWE includes a diverse population base, revealing trends that might not emerge in homogeneous clinical trial populations (4).
Comprehensive data collection
Traditional clinical trials often exclude certain patient groups, such as those with multiple comorbidities or older individuals, to minimize variability. RWE studies, however, capture data from broader populations, making findings more generalizable. By leveraging large-scale datasets like electronic health records (EHRs) or insurance claims, RWE provides insights into long-term outcomes, such as sustained weight loss or the development of comorbidities (5).
Informing policy and practice
RWE studies offer valuable information to policymakers by evaluating the cost-effectiveness and scalability of obesity interventions. For example, RWE data has been instrumental in supporting reimbursement decisions for anti-obesity pharmacotherapies and bariatric surgery. Policymakers use these insights to prioritize interventions with the greatest societal impact, such as programs targeting childhood obesity (7).
Personalized medicine
Obesity is a heterogeneous disease with varying genetic, behavioral, and environmental factors. RWE helps identify patient subgroups that respond to specific treatments, such as individuals benefiting from GLP-1 receptor agonists due to metabolic profiles (4).
Enhanced opportunity
As new obesity treatments emerge RWE becomes even more critical in evaluating their real-world effectiveness and safety. This includes determining how diverse mechanisms of action impact patient adherence and outcomes, providing invaluable insights for clinical decision-making and policy development.
RWE is transforming how we understand and manage obesity by providing comprehensive, actionable insights that inform clinical practice, public health policy, and personalized medicine. It bridges the gap between clinical trials and real-world applications, making it a cornerstone of modern obesity research.
3. Barriers to conducting RWE studies in obesity
While the value of RWE in obesity research is clear, several challenges limit its utility. These barriers must be addressed to fully realize the potential of RWE in advancing obesity treatment and prevention.
Inconsistent recognition and coding of obesity
Obesity is not uniformly recognized as a disease worldwide. For example, while the U.S. and WHO classify obesity as a chronic disease, many European and Asian countries do not. This inconsistency leads to variations in diagnostic coding, complicating patient identification across geographies (7).
Data quality and completeness
Obesity is often underreported by healthcare providers or inaccurately recorded in medical records. Physicians may prioritize comorbidities like diabetes or hypertension, neglecting to record obesity as a primary diagnosis. Additionally, key metrics such as BMI, waist circumference, or body composition are often missing or inconsistently measured (4).
Ethical and privacy concerns
Data on obesity often includes sensitive information about patients’ weight, dietary habits, and exercise patterns. Regulations like GDPR in Europe and HIPAA in the U.S. impose strict requirements on data handling, making multi-regional studies complex and time-consuming (5).
Regulatory hurdles
Varying regulations across countries impact data sharing and study standardization. Some nations allow the use of de-identified health data, while others require explicit patient consent, creating logistical and financial barriers for large-scale RWE studies (6).
The challenges of RWE studies in obesity highlight the need for harmonized standards, robust data infrastructure, and clear regulatory frameworks to unlock the full potential of this research methodology.
4. Future perspectives: expanding the scope of RWE in obesity
The obesity treatment landscape is evolving rapidly, with new therapies offering unprecedented efficacy in weight management and metabolic improvements. These therapies come with diverse mechanisms of action, price points, and side effect profiles, further emphasizing the need for RWE to guide their optimal use.
Emerging therapies and mechanisms
Novel therapies, such as dual and triple agonists, target multiple biological pathways to regulate appetite, energy expenditure, and fat metabolism. Evaluating their performance in real-world settings will help identify the patient populations most likely to benefit (8).
Cost-effectiveness and economic impact
RWE will help determine the long-term cost-effectiveness of these therapies by analyzing healthcare utilization, quality of life improvements, and prevention of obesity-related complications (7).
Long-term safety monitoring
While clinical trials establish short-term safety, RWE provides crucial insights into rare or long-term adverse events that may arise during widespread use (5).
Personalized treatment strategies
By analyzing large datasets, RWE enables precision medicine approaches, tailoring treatments based on patient-specific factors such as genetics, lifestyle, and comorbidities (3).
Summary
The rapid development of obesity therapies highlights the growing importance of RWE. It will provide critical insights to optimize therapy selection, ensure patient safety, and evaluate economic impacts, ultimately transforming obesity care.
5. The role of RCTs and RWE: a new paradigm
RCTs remain the gold standard in clinical research due to their ability to minimize bias and establish causality. However, RWE offers unique advantages by complementing RCTs with real-world data. This is not a question of choosing one over the other but rather recognizing their distinct yet synergistic roles.
Detailed points
Strengths of RCTs
RCTs are designed to minimize bias, ensuring internal validity through randomization and standardized protocols. For example, semaglutide's efficacy in obesity was established through rigorous RCTs (5).
Complementary role of RWE
RWE addresses limitations of RCTs, such as limited generalizability and short follow-up periods. By studying diverse populations over longer periods, RWE provides insights into adherence, long-term safety, and cost-effectiveness (3).
Summary
RCTs and RWE are not mutually exclusive; together, they provide a comprehensive evidence base. This dual approach is critical for advancing obesity research and care.
6. Conclusions and recommendations
The potential of RWE in obesity research is vast, but its full utility can only be realized through collaborative efforts to overcome existing barriers and embrace its unique strengths.
Conclusions
The obesity epidemic presents a significant global health challenge, underscoring the urgent need for effective strategies to manage and treat this complex disease. While RCTs remain indispensable for establishing efficacy, RWE complements these trials. It provides insights into the effectiveness, safety, and cost-effectiveness of interventions in broader, more diverse populations.
The rapid development of innovative obesity therapies, including those with novel mechanisms of action and diverse cost and safety profiles, further emphasizes the critical role of RWE in optimizing their use. However, conducting RWE studies in obesity is fraught with challenges, including inconsistent recognition of obesity as a disease, data quality issues, regulatory hurdles, and privacy concerns.
Addressing these barriers through harmonized standards, robust data infrastructure, and international collaboration is essential for leveraging RWE's full potential. Together, RCTs and RWE offer a comprehensive evidence base, driving progress in obesity care, policy-making, and public health strategies.
Recommendations
To unlock the transformative potential of RWE in obesity research, stakeholders must prioritize harmonization of standards for defining and diagnosing obesity, ensuring consistency across regions and healthcare systems.
Investments in data infrastructure are critical, with a focus on integrating standardized metrics such as BMI and comorbidity data into electronic health records (EHRs). Ethical and transparent practices must guide the use of sensitive patient data, with compliance to international regulations like GDPR and HIPAA fostering public trust.
Additionally, fostering collaboration between academic researchers, industry leaders, policymakers, and regulatory agencies is essential to address methodological challenges and promote innovation in the design and execution of RWE studies.
Finally, embracing the complementary roles of RCTs and RWE will support the evaluation of new therapies, ensure equitable access, and optimize treatment strategies tailored to diverse patient needs.
References
- Hanson, Patrick Wulf. (2015) Obesity. Causes & Consequences. Link to Amazon: Obesity. Causes & Consequences
- World Health Organization (WHO). (2024). Obesity and Overweight. Link to FDA: Obesity and Overweight
- Sherman, R. E., et al. (2016). Real-world evidence – What is it and what can it tell us? The New England Journal of Medicine. Link to PubMed: Real-world evidence – What is it and what can it tell us?
- Makady, A., et al. (2017). What is real-world data? A review of definitions based on literature and stakeholder interviews. Value in Health. Link to PubMed: What is real-world data? A review of definitions based on literature and stakeholder interviews?
- FDA. (2018). Framework for Real-World Evidence Program. Link to FDA: Framework for Real-World Evidence Program.
- FDA. (2021b). Considerations for the Use of Real-World Data and Real-World Evidence to Support Regulatory Decision-Making for Drug and Biological Products. Link to FDA: Considerations for the Use of Real-World Data and Real-World Evidence to Support Regulatory Decision-Making for Drug and Biological Products.
- Avalere Health. (2023). Coding, Billing, and Reimbursement Barriers to Obesity Care. Link to Avalere: Coding, Billing, and Reimbursement Barriers to Obesity Care.
- Schmidt, A. M. (2023). Obesity research: Moving from bench to bedside to population PLOS Biology. Link to PubMed: Obesity research: Moving from bench to bedside to population PLOS Biology.
