2026年为什么肥胖需要新的证据范式报告

Why Obesity Requires a NewEvidence Paradigm From fragmented signals to actionable insights in a rapidlyevolving market HARVEY JENNER,Principal – Real World Networks & Partnerships, IQVIAMEGGIE HOTARD, Associate Principal – Real World Networks & Partnerships, IQVIA Table of contents Introduction1A market defined by heterogeneity, not averages2Why traditional obesity data can fall short3The patient experience is key to understanding obesity and contextualizing clinical data3The case for purpose-built obesity evidence4The potential offered by better obesity data5Scientific stewardship in a rapidly evolving market5Looking ahead: From data access to better decisions6Authors7References8 Introduction The obesity market has entered a phase of unprecedented dynamics.What was once viewed primarily as a lifestyle condition is now recognizedas a chronic, progressive disease with far reaching clinical, economic, andsocietal implications. At the same time, scientific innovation has accelerateddramatically. Novel generations of obesity medications, expanding indications,new mechanisms of action, and alternative modes of administration arereshaping treatment expectations and care pathways at speed. For organizations operating in this space — whetherdeveloping therapies, shaping access strategies, orinforming clinical and payer decision-making — thisprogress brings both opportunity and challenge. Theopportunity lies in redefining care and outcomes formillions of people living with obesity. The challengelies in understanding a market that is evolving faster than traditional data sources can reasonably support,for example, we are seeing new sources of funding (i.e.self-pay) evolve rapidly and new channels e.g. digitalhealth platforms becoming very popular.1 As obesity science advances, the evidence frameworksused to understand it must evolve as well. A market defined by heterogeneity, not averages One of the defining features of today’s obesitylandscape is heterogeneity. Patients enteringtreatment differ widely in terms of biology,comorbidities, metabolic profiles, social context,and treatment goals. Weight loss may be theprimary objective for some, while others prioritizecardiometabolic risk reduction, mobility, quality of life,or long-term disease management. These parallel ecosystems create very differentpatterns of uptake, persistence, and outcomes. In addition to weight loss as a segment of treatment,we are starting to see the emergence of weightmanagement as an additional segment. An exampleof this is the Eli Lilly’s orflorglipron ATTAIN-MAINTAINtrials.2The ATTAIN-MAINTAIN trials evaluate long-term weight maintenance following initial weightreduction, highlighting the growing importance ofsustainedoutcomes. At the same time, obesity treatment pathways havediversified. Pharmacologic therapies increasinglycoexist with lifestyle interventions, digital health tools,bariatric surgery, and patient-led care models. Twostructurally different markets now operate in parallel: Understanding obesity at the population leveltherefore requires far more than tracking prescriptionsor diagnostic codes. It requires understanding of •A medically-led, reimbursed pathway shapedby clinical guidelines, benefit design, and healthsystemconstraints •whopatients are •howthey navigate care •A consumer-driven, out-of-pocket pathwayinfluenced by affordability, access, perception, andconvenience •whytheir real-world decisions often diverge fromprotocol driven expectations Why traditional obesity datacan fall short Despite the growing importance of obesity across lifesciences and healthcare, most commonly used real-world data sources were never designed with obesityas a primary analytical focus. As a result, decision-makers often encounter significant blind spots whenattempting to answer business critical questions. Key limitations occur across datasets: •Inconsistent anthropometric capture, includingmissing or irregular BMI, waist circumference, andbody composition measures3,4 »Recent IQVIA studies have shown the under-collection of BMI in EMR, demonstrating that fewerthan half of adults in the UK (41.5%) had a BMIrecorded and only 10.8% in Germany in 20235,6 The patient experience is keyto understanding obesity andcontextualizing clinical data •Limited visibility into dosing, titration, adherence,and treatment holidays, particularly across longperiods of follow-up Perhaps the most significant gap in current evidenceframeworks is the limited presence of the patient voice.Obesity is a condition where day to day experience— drug tolerability, motivation, stigma, affordability,lifestyle trade offs — plays a critical role in long-termoutcomes. Yet these factors are rarely captured inroutine clinical data. •Poor insight into patient access routes, includingout-of-pocket purchasing, online pharmacies,andcompounding •Critical obesity relevant information locked inunstructured clinical notes, requiring additionalprocessing to bec