Stamas Nicole, Vincent Tom, Evans Kathryn, Li Qian, Danielson Vanessa, Lassagne Reginald, Berger Ariel
Evidera, Bethesda, Maryland, USA.
LivaNova, London, UK.
J Health Econ Outcomes Res. 2024 Feb 27;11(1):57-66. doi: 10.36469/001c.91991. eCollection 2024.
Regulatory bodies, health technology assessment agencies, payers, physicians, and other decision-makers increasingly recognize the importance of real-world evidence (RWE) to provide important and relevant insights on treatment patterns, burden/cost of illness, product safety, and long-term and comparative effectiveness. However, RWE generation requires a careful approach to ensure rigorous analysis and interpretation. There are limited examples of comprehensive methodology for the generation of RWE on patients who have undergone neuromodulation for drug-resistant epilepsy (DRE). This is likely due, at least in part, to the many challenges inherent in using real-world data to define DRE, neuromodulation (including type implanted), and related outcomes of interest. We sought to provide recommendations to enable generation of robust RWE that can increase knowledge of "real-world" patients with DRE and help inform the difficult decisions regarding treatment choices and reimbursement for this particularly vulnerable population. We drew upon our collective decades of experience in RWE generation and relevant disciplines (epidemiology, health economics, and biostatistics) to describe challenges inherent to this therapeutic area and to provide potential solutions thereto within healthcare claims databases. Several examples were provided from our experiences in DRE to further illustrate our recommendations for generation of robust RWE in this therapeutic area. Our recommendations focus on considerations for the selection of an appropriate data source, development of a study timeline, exposure allotment (specifically, neuromodulation implantation for patients with DRE), and ascertainment of relevant outcomes. The need for RWE to inform healthcare decisions has never been greater and continues to grow in importance to regulators, payers, physicians, and other key stakeholders. However, as real-world data sources used to generate RWE are typically generated for reasons other than research, rigorous methodology is required to minimize bias and fully unlock their value.
监管机构、卫生技术评估机构、支付方、医生及其他决策者越来越认识到真实世界证据（RWE）对于提供有关治疗模式、疾病负担/成本、产品安全性以及长期和比较有效性的重要且相关见解的重要性。然而，生成RWE需要谨慎的方法，以确保进行严格的分析和解释。对于接受过耐药性癫痫（DRE）神经调节治疗的患者，生成RWE的综合方法实例有限。这可能至少部分归因于使用真实世界数据来定义DRE、神经调节（包括植入类型）以及相关感兴趣结局时存在的诸多挑战。我们试图提供建议，以生成可靠的RWE，从而增加对“真实世界”DRE患者的了解，并有助于为针对这一特别脆弱人群的治疗选择和报销等艰难决策提供信息。我们借鉴了我们在生成RWE及相关学科（流行病学、卫生经济学和生物统计学）方面几十年的集体经验，来描述该治疗领域固有的挑战，并在医疗保健索赔数据库中提供潜在的解决方案。我们从DRE方面的经验中给出了几个例子，以进一步说明我们在该治疗领域生成可靠RWE的建议。我们的建议侧重于选择合适数据源、制定研究时间表、暴露分配（具体而言，为DRE患者植入神经调节装置）以及确定相关结局等方面的考虑因素。RWE为医疗决策提供信息的需求从未如此迫切，并且对监管机构、支付方、医生及其他关键利益相关者而言，其重要性还在持续增加。然而，由于用于生成RWE的真实世界数据源通常是出于研究以外的原因生成的，因此需要严谨的方法来尽量减少偏差并充分释放其价值。
