The maze of real-world evidence frameworks: from a desert to a jungle! An environmental scan and comparison across regulatory and health technology assessment agencies.

Aim: Regulatory and health technology assessment (HTA) agencies have increasingly published frameworks, guidelines, and recommendations for the use of real-world evidence (RWE) in healthcare decision-making. Variations in the scope and content of these documents, with updates running in parallel, may create challenges for their implementation especially during the market authorization and reimbursement phases of a medicine's life cycle. This environmental scan aimed to comprehensively identify and summarize the guidance documents for RWE developed by most well-established regulatory and reimbursement agencies, as well as other organizations focused on healthcare decision-making, and present their similarities and differences. Methods: RWE guidance documents, including white papers from regulatory and HTA agencies, were reviewed in March 2024. Data on scope and recommendations from each body were extracted by two reviewers and similarities and differences were summarized across four topics: study planning, choosing fit-for-purpose data, study conduct, and reporting. Post-authorization or non-pharmacological guidance was excluded. Results: Forty-six documents were identified across multiple agencies; US FDA produced the most RWE-related guidance. All agencies addressed specific and often similar methodological issues related to study design, data fitness-for-purpose, reliability, and reproducibility, although inconsistency in terminologies on these topics was noted. Two HTA bodies (National Institute for Health and Care Excellence [NICE] and Canada's Drug Agency) each centralized all related RWE guidance under a unified framework. RWE quality tools and checklists were not consistently named and some differences in preferences were noted. European Medicines Agency, NICE, Haute Autorité de Santé, and the Institute for Quality and Efficiency in Health Care included specific recommendations on the use of analytical approaches to address RWE complexities and increase trust in its findings. Conclusion: Similarities in agencies' expectations on RWE studies design, quality elements, and reporting will facilitate evidence generation strategy and activities for manufacturers facing multiple, including global, regulatory and reimbursement submissions and re-submissions. A strong preference by decision-making bodies for local real-world data generation may hinder opportunities for data sharing and outputs from international federated data networks. Closer collaboration between decision-making agencies towards a harmonized RWE roadmap, which can be centrally preserved in a living mode, will provide manufacturers and researchers clarity on minimum acceptance requirements and expectations, especially as novel methodologies for RWE generation are rapidly emerging.

A Systematic Review of Modeling Approaches to Evaluate Treatments for Relapsed Refractory Multiple Myeloma: Critical Review and Considerations for Future Health Economic Models.

BACKGROUND AND OBJECTIVE: Multiple myeloma is a rare incurable hematological cancer in which most patients relapse or become refractory to treatment. This systematic literature review aimed to critically review the existing economic models used in economic evaluations of systemic treatments for relapsed/refractory multiple myeloma and to summarize how the models addressed differences in the line of therapy and exposure to prior treatment. METHODS: Following a pre-approved protocol, literature searches were conducted on 17 February, 2023, in relevant databases for models published since 2014. Additionally, key health technology assessment agency websites were manually searched for models published as part of submission dossiers since 2018. Reported information related to model conceptualization, structure, uncertainty, validation, and transparency were extracted into a pre-defined extraction sheet. RESULTS: In total, 49 models assessing a wide range of interventions across multiple lines of therapy were included. Only five models specific to heavily pre-treated patients and/or those who were refractory to multiple treatment classes were identified. Most models followed a conventional simple methodology, such as partitioned survival (n = 28) or Markov models (n = 9). All included models evaluated specific interventions rather than the whole treatment sequence. Where subsequent therapies were included in the model, these were generally only considered from a cost and resource use perspective. The models generally used overall and progression-free survival as model inputs, although data were often immature. Sensitivity analyses were frequently reported (n = 41) whereas validation was only considered in less than half (n = 19) of the models. CONCLUSIONS: Published economic models in relapsed/refractory multiple myeloma rarely followed an individual patient approach, mainly owing to the higher need for complex data assumptions compared with simpler modeling approaches. As many patients experience disease progression on multiple treatment lines, there is a growing need for modeling complex treatment strategies, leading to more sophisticated approaches in the future. Maintaining transparency, high reporting standards, and thorough analyses of uncertainty are crucial to support these advancements.

Mondor's penile disease requiring thrombectomy: A case report and literature review.

The thrombophlebitis of the superficial dorsal vein of the penis, called Mondor's penile disease (PMD), is a condition with a low incidence worldwide. In general, it is considered a self-limited disease that usually resolves with conservative management and very rarely requires surgical intervention. We report the case of a 41-year-old patient, who presented PMD which persists after medical treatment with nonsteroidal antiinflammatory drug and low molecular weight heparin. Surgery was decided and thrombectomy plus resection of the superficial penile vein was performed with satisfactory results. A review of the literature is presented, focusing on the limited available evidence of surgical management.

EEG-Based Detection of Braking Intention Under Different Car Driving Conditions.

The anticipatory recognition of braking is essential to prevent traffic accidents. For instance, driving assistance systems can be useful to properly respond to emergency braking situations. Moreover, the response time to emergency braking situations can be affected and even increased by different driver's cognitive states caused by stress, fatigue, and extra workload. This work investigates the detection of emergency braking from driver's electroencephalographic (EEG) signals that precede the brake pedal actuation. Bioelectrical signals were recorded while participants were driving in a car simulator while avoiding potential collisions by performing emergency braking. In addition, participants were subjected to stress, workload, and fatigue. EEG signals were classified using support vector machines (SVM) and convolutional neural networks (CNN) in order to discriminate between braking intention and normal driving. Results showed significant recognition of emergency braking intention which was on average 71.1% for SVM and 71.8% CNN. In addition, the classification accuracy for the best participant was 80.1 and 88.1% for SVM and CNN, respectively. These results show the feasibility of incorporating recognizable driver's bioelectrical responses into advanced driver-assistance systems to carry out early detection of emergency braking situations which could be useful to reduce car accidents.