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PubMed2026

Insights from expert panels on the EU clinical evaluation consultation procedure.

BACKGROUND: The Clinical Evaluation Consultation Procedure (CECP) under the EU Medical Device Regulation aims to strengthen and harmonize the assessment of high-risk medical devices. This review summarizes early insights from expert panels to support improved clinical evaluation practices. RESEARCH DESIGN AND METHODS: This review analyses 34 expert panel opinions derived from 281 CECP submissions between April 2021 and December 2025. Statements from opinions were systematically extracted, de-duplicated, and grouped into thematic categories, with independent review and validation. The analysis focuses on common challenges found during the consultation procedure of the expert panels on the content of the clinical assessment in relation to clinical evidence, benefit-risk assessment, intended purpose alignment, and post-market clinical follow-up planning. RESULTS: Expert panel findings highlight recurrent issues in the sufficiency, consistency, and transparency of clinical evidence, underscoring the need for improved standardization and clearer guidance. CONCLUSIONS: Strengthening documentation quality and alignment across stakeholders will enhance the robustness, efficiency, and predictability of conformity assessments for high-risk medical devices.

Humans↗
PubMed2026

Delphi study robot consenso: Strategies for the implementation of robotic surgery in general surgery in the Spanish hospital network.

INTRODUCTION: The implementation of robotic surgery in public hospitals presents multiple logistical, educational, and organizational challenges. In the absence of unified guidelines, a national consensus is required to optimize its safe and efficient adoption. This study aimed to establish a set of consensus-based and measurable recommendations for the implementation of robotic surgery programs in hospitals within the Spanish National Health System, based on the experience of centres with established robotic programs and intended to serve as guidance for hospitals that are initiating or planning their implementation. METHODS: A national Delphi study was conducted with the participation of robotic surgery experts from 26 public hospitals. The expert panel was composed exclusively of digestive surgeons with experience in robotic surgery. Three iterative rounds of expert panel evaluation were conducted between March 2024 and March 2025. The questions were grouped into five thematic blocks. Consensus was defined as an agreement level of ≥66.7%. Kendall's W coefficient was used to assess concordance. RESULTS: High levels of consensus were achieved on key aspects related to infrastructure, structured training, cost evaluation, and quality assurance mechanisms. Areas of disagreement were also identified, such as the need for a dedicated anaesthesiologist, purchase of accessory instruments during the initial phase, and official accreditation pathways. CONCLUSIONS: This study provides a guideline for developing a national robotic surgery strategy focused on patient safety, program sustainability, and standardized training of surgical teams. These recommendations can guide hospitals at different stages of robotic technology adoption. Given that the consensus was reached from an exclusively surgical perspective, the recommendations focus on patient safety, program sustainability, and standardized training of the surgical team, and should be interpreted in an adaptable manner according to each centre's context, case volume, and available resources.

Cirugía Asistida por Robot↗
PubMed2026

Distress Intolerance, Social Anxiety, and Depressive Symptoms in Adolescents: Evidence from Random-Intercept Cross-Lagged Panel and Cross-Lagged Panel Network Analyses.

Social anxiety and depressive symptoms frequently co-occur during adolescence, yet the mechanisms underlying their longitudinal associations remain insufficiently understood. Distress intolerance has been proposed as a transdiagnostic risk factor implicated across internalizing symptoms. However, it remains unclear whether distress intolerance is predicted by social anxiety and depressive symptoms, as well as the underlying mechanisms among these three constructs. The specific symptoms most centrally involved in these cross-domain associations remain poorly understood. The present study investigated the longitudinal associations among distress intolerance, social anxiety, and depressive symptoms using a dual-method framework combining random-intercept cross-lagged panel models (RI-CLPM) and cross-lagged panel network (CLPN) analyses. A total of 1,378 Chinese adolescents (Mage = 12.57, SDage = 0.63; 50.4% female) were assessed at three time points with six-month intervals between waves. The RI-CLPM analyses revealed that higher distress intolerance prospectively predicted subsequent increases in both social anxiety and depressive symptoms, whereas elevated social anxiety and depressive symptoms in turn predicted subsequent increases in distress intolerance. Moreover, distress intolerance mediated the longitudinal associations between social anxiety and depressive symptoms. Additionally, distress intolerance was also indirectly associated with its own subsequent levels through social anxiety and depressive symptoms. The CLPN analyses revealed that fear of negative evaluation and fatigue were the strongest predictors of other network nodes from T1 to T2 and from T2 to T3, respectively. In contrast, distress intolerance symptoms were predominantly predicted by other nodes in both cross-lagged networks. These findings extend prior views of distress intolerance as a unidirectional vulnerability by showing that distress intolerance is also predicted by social anxiety and depressive symptoms and accounts for part of their longitudinal associations across adolescence.

Humans↗
PubMed2026

The Impact of Chatbot Type and Normative Messaging on Chatbot Usage Intention Based on the Health Technology Acceptance Model: Randomized Controlled Trial.

BACKGROUND: Digital health tools, such as health chatbots, may improve access to scalable health support, but adoption remains inconsistent. Existing models do not fully integrate technology acceptance factors with health motivation factors relevant to digital health use. OBJECTIVE: This study proposed and tested the health technology acceptance model and examined whether normative message framing and chatbot type were associated with health motivation, technology acceptance, and intention to use a health chatbot. METHODS: In October 2025, we conducted a 4 &#xd7; 2 between-participants online experiment with 1000 US adults recruited from a nationally representative YouGov panel. Participants were randomized to 1 of 8 conditions varying norm message type (self-oriented, peer-oriented, expert-oriented, or family-oriented) and chatbot type (AI-powered or rule-based) in a cancer prevention and genetic risk information scenario. Outcomes included descriptive norms, injunctive norms, perceived susceptibility, perceived severity, perceived benefits, self-efficacy, perceived ease of use, trust, privacy concerns, and usage intention. Data were analyzed using a multivariate ANOVA with Bonferroni-adjusted post hoc tests and multiple linear regression. RESULTS: Peer-oriented and family-oriented messages produced higher usage intention than expert-oriented messages, and peer-oriented messages also increased descriptive norms, injunctive norms, self-efficacy, and trust. AI-powered chatbots were associated with higher usage intention (P=.02) and greater trust (P=.008) than rule-based chatbots. In regression analyses, the model explained 50.8% of the variance in usage intention. Usage intention was positively associated with descriptive norms (&#x3b2;=0.087; P=.003), injunctive norms (&#x3b2;=0.078; P=.009), perceived susceptibility (&#x3b2;=0.051; P=.03), perceived benefits (&#x3b2;=0.253; P<.001), and trust (&#x3b2;=0.33; P<.001), and negatively associated with perceived severity (&#x3b2;=-0.047; P=.049) and privacy concerns (&#x3b2;=-0.11; P<.001). Perceived ease of use and self-efficacy were not significant predictors. CONCLUSIONS: The health technology acceptance model was a useful framework for explaining the intention to use a health chatbot by combining technology acceptance and health motivation constructs. Both social design features and chatbot design features shaped adoption-related beliefs, with peer-oriented and family-oriented framing and AI-powered chatbots showing particular promise. Trust and privacy concerns remained central determinants of intended use.

Humans↗
PubMed2026

Feasibility of routine clinical liquid-based cytology for lung cancer compact panel testing.

BACKGROUND: The Lung Cancer Compact Panel (cPANEL) is a recently approved highly sensitive multiplex gene panel in Japan that supports both DNA- and RNA-based next-generation sequencing. Although cytological specimens are acceptable for cPANEL, unfixed cell pellets or dedicated preservation tubes are typically recommended. However, evidence remains limited regarding whether residual liquid-based cytology (LBC) cell suspensions prepared for routine cytological diagnosis can be used directly for cPANEL testing without dedicated molecular preservation or additional preanalytical processing. In this study, we evaluated the feasibility of applying LBC specimens that are widely used in contemporary clinical practice to cPANEL. METHODS: We analyzed DNA and RNA quality in 69 clinical LBC specimens. Among these, 51 specimens containing non-small cell lung cancer cells with previously determined driver alteration status were subjected to cPANEL testing to evaluate assay concordance with clinical companion diagnostic results. RESULTS: DNA integrity was generally well preserved (DNA Integrity Number [DIN]: 6.2&#xa0;&#xb1;&#xa0;1.5). In contrast, RNA integrity showed greater variability (DV200: 16.4&#xa0;&#xb1;&#xa0;12.1%). ThinPrep-fixed specimens demonstrated lower DIN and DV200 values compared with CytoRich Red-fixed specimens. Although all samples successfully passed the DNA-based cPANEL assay, six cases (11.8%) failed the RNA-based assay, with RNA yield being a major contributing factor. Among the 46 evaluable specimens, concordance was 95.7% and sensitivity was 92.3%, or 88.9% including RNA module failures as cPANEL-negative. CONCLUSIONS: With appropriate fixative selection and adequate cellularity, cPANEL using clinical LBC specimens may serve as a practical diagnostic platform. We demonstrated that routine LBC specimens can be directly applied to cPANEL without special preanalytical processing.

Humans↗
PubMed2026

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans↗
PubMed2026

Current Concepts and Emerging Technologies in Aesthetic Outcome Assessment of Breast Reconstruction.

Aesthetic outcomes are a crucial determinant of the overall success of breast reconstruction. Recently, aesthetic assessment has evolved from relying mainly on subjective impressions to incorporating more quantitative methods. This systematic review summarizes current concepts and emerging technologies in aesthetic outcome assessment after breast reconstruction. A comprehensive search of studies evaluating aesthetic outcomes following implant-based, autologous or hybrid breast reconstruction was performed between 2000 and 2025. Assessments were classified as subjective or objective. Extracted variables included assessment characteristics, aesthetic outcome domains, and patient-centered outcomes. Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Levels of evidence were classified according to the Oxford Centre for Evidence-Based Medicine. A total of 51 studies involving 7711 participants from 16 countries were included. Subjective tools were most frequently employed, led by the BREAST-Q (35/51, 69%), followed by expert- or panel-based evaluations (17/51, 33%) and the visual analog scale (2/51, 4%). Objective methods were applied in 19 studies and included 3-dimensional surface imaging (8/51, 16%), BCCT.core (7/51, 14%), eye tracking (3/51, 6%), and artificial intelligence-based analyses (3/51, 6%). Although subjective tools captured satisfaction with breast appearance, objective tools quantified morphological parameters and positional landmarks. BREAST-Q remains the cornerstone of outcome evaluation after breast reconstruction, providing patient-centered perspectives, including, but not limited to, aesthetic perception. A progressive shift toward multimodal evaluation was noticed, as no single modality comprehensively addressed all aesthetic domains. Future research should focus on integrating subjective and objective assessment methods within a unified framework. Level of Evidence: 3 (Therapeutic) For image description, please refer to the figure legend and surrounding text.

Humans↗
PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗
PubMed2026

Solutions for engaging priority populations in HIV cure research: a hybrid Delphi consensus-building process.

BACKGROUND: To achieve consensus on barriers and strategies to improve the engagement of three priority populations - Black and Latino/a/x individuals, cisgender women, and transgender women in HIV cure research. METHODS: We assembled a panel of 54 experts assigned to six groups in a hybrid Delphi process: (1) HIV community members, (2) biomedical researchers, (3) medical providers, (4) funders and private industry members, (5) bioethicists and regulators, and (6) social scientists. Over 18 months, we conducted four iterative survey rounds and three group discussions to identify barriers and strategies to arrive at a consensus on how to engage these priority populations in HIV cure research. RESULTS: For Black and Latino/a/x populations, the panellists identified inadequate outreach and a lack of accessible educational information as primary barriers and emphasised community-driven engagement and partnerships with trusted leaders as key strategies. For cisgender women, logistical hurdles, caregiving responsibilities and time constraints were identified as major barriers, with flexible trial designs and equitable compensation proposed as solutions. For transgender women, the lack of transgender-focused research design, including misrepresentation and exclusion, was identified as a key barrier, while centring transgender-specific needs in study design achieved consensus as the most effective strategy. CONCLUSION: Among all four priority populations, investment in outreach, engagement along the research process, better integration of health needs with research, and enhanced incentives are not novel ideas, but remain obviously ignored in a way that has led to underrepresentation of people in HIV cure research, who carry the greatest burden of HIV in the U.S. SUMMARY: This paper uses a hybrid Delphi process to identify and reach consensus on key barriers and strategies to engage underrepresented groups: Black and Latino/a/x individuals, cisgender women, and transgender women in HIV cure research across the United States.

Humans↗
PubMed2026

Time to subsequent therapy (TTST) as an endpoint in clinical studies: development of standardized documentation of subsequent therapy through systematic literature review, expert interviews, and Delphi survey.

BACKGROUND: The endpoint Time to Subsequent Therapy (TTST) is an intermediate endpoint used in research and regulatory assessments. TTST denotes initiation of subsequent therapy and is a clearly definable, clinically relevant event for healthcare professionals. However, it has not been systematically established to which extent TTST is subjectively meaningful to patients. The objective of this study was to define TTST as a patient-relevant intermediate endpoint. METHODS: The study examined five oncological indications (breast cancer, prostate cancer, melanoma, multiple myeloma, and non-small cell lung cancer) using a systematic literature review, analysis of case report forms used in international randomized controlled trials, review of German Federal Joint Committee (G-BA) documents, semi-structured interviews and a two-stage Delphi survey with healthcare professionals, patients, and relatives. RESULTS: A total of 35 individuals participated in qualitative interviews. Most of them rated TTST as particularly significant. The Delphi Survey included 264 interviewees in round one, and 117 in round two. Patient-relevance of TTST was confirmed by 81% of respondents (95% confidence interval 76%, 85%). Nine treatment scenarios that justify TTST were identified. To capture patient-relevance, prospective collection of reasons for and consequences of therapy change are required. A checklist with standardized response formats plus free-text fields was developed: a comprehensive master checklist for flexible, complete documentation and a short version focused on therapy change-specific items. CONCLUSIONS: TTST is an intermediate endpoint whose systematic documentation of characteristics demonstrating patient-relevance can be standardized in research and clinical practice using the developed checklists.

Humans↗
PubMed2026

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans↗
PubMed2026

Molecular diagnostic yield and barriers in inherited retinal diseases: a retrospective cohort study.

OBJECTIVE: To evaluate the diagnostic yield of panel-based genetic testing for inherited retinal diseases (IRDs) and identify barriers to molecular resolution. DESIGN: Retrospective cohort. PARTICIPANTS: A total of 404 patients with clinically confirmed IRDs who were evaluated at the Adult Inherited Retinal Dystrophy Service, Ontario, Canada (October 2021-September 2024). METHODS: Patients underwent targeted massive parallel sequencing panel testing. Diagnostic yield was calculated, and unresolved cases were reviewed. Associations between yield, phenotype, ethnicity, and sex were assessed using &#x3c7;&#xb2; analysis. RESULTS: Of 685 referrals, 570 had confirmed IRDs. After we excluded 140 pending results and 26 patients who declined testing, 404 patients were analyzed. At referral, 94 patients (23.2%) had a previous molecular diagnosis, and 138 (34.0%) were diagnosed through clinic-initiated testing, giving an overall yield of 57.4%. Yield varied significantly by phenotype (&#x3c7;&#xb2;, P&#x202f;=&#x202f;1.4&#x202f;&#xd7;&#x202f;10&#x207b;&#x2076;), from 94.4% in vitelliform macular dystrophies to 25.0% in vitreoretinopathies, with no sex association (P&#x202f;=&#x202f;1.0). Disease-causing variants were identified in 83 IRD-associated genes, most frequently ABCA4, USH2A, and BEST1. Of 172 unresolved cases, 62 (36.0%) had negative panels, and 110 (63.9%) were inconclusive, including 30 with unphased pathogenic variants in recessive genes and 10 with high-suspicion variants of uncertain significance. Key barriers included limited family availability for phasing, restricted access to functional assays, and lack of public coverage for whole-exome or whole-genome sequencing. CONCLUSIONS: Massive parallel sequencing-based panel testing achieved a 57% diagnostic yield in this IRD population. Success was strongly phenotype-dependent with substantial heterogeneity. Whole-exome sequencing, whole-genome sequencing, family segregation, and functional genomics could improve diagnostic outcomes and management.

Humans↗
PubMed2026

Crinecerfont: emerging role in the management of congenital adrenal hyperplasia.

INTRODUCTION: Congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency is a rare genetic endocrine disorder characterized by impaired cortisol synthesis, excessive adrenal androgen production, and elevated adrenocorticotropic hormone (ACTH) concentrations. The current standard of care involves supraphysiologic doses of glucocorticoids to suppress ACTH and manage androgen excess, often leading to long-term complications. AREAS COVERED: A literature search of PubMed was conducted. This review critically examines the pharmacology, clinical efficacy, and potential role of crinecerfont in redefining CAH management. EXPERT OPINION: Crinecerfont, a selective corticotropin-releasing factor type 1 receptor (CRF1) antagonist, offers a novel therapeutic approach by targeting ACTH secretion at its hypothalamic origin. Recent Phase 2 and Phase 3 trials have demonstrated promising efficacy and safety across adult, adolescent, and pediatric populations. Crinecerfont may represent a promising adjunctive therapy in CAH management, addressing both biochemical control as well as quality of life and potentially long-term outcomes.

Humans↗
PubMed2026

A status update on the unkept promise of high-frequency spinal cord stimulation for treatment-refractory chronic migraine.

INTRODUCTION: Chronic migraine (CM) refractory to conventional pharmacotherapy (r-CM) remains a debilitating neurological condition with limited therapeutic options. High-frequency spinal cord stimulation at 10 kilohertz (HF-SCS) has recently emerged as a distinct neuromodulatory paradigm for this patient population. Unlike traditional spinal cord stimulation, HF-SCS operates above the frequency range that generates paresthesia, thereby eliminating stimulation-induced sensation while potentially engaging unique analgesic mechanisms. AREAS COVERED: This focused narrative review synthesizes the available clinical evidence, technical considerations, and mechanistic hypotheses specifically pertaining to cervical HF-SCS for refractory chronic migraine (r-CM). The authors further provide their expert perspectives on the future of this technology as a treatment option for refractory chronic migraine. EXPERT OPINION: Current data from prospective open-label studies and retrospective case series suggest that cervical HF-SCS may reduce monthly migraine days, facilitate conversion from chronic to episodic migraine patterns in some implanted patients, and may improve headache-related disability and quality of life over at least 52&#x2009;weeks of follow-up. The paresthesia-free nature of HF-SCS confers a distinct advantage for both patient tolerability and future trial design, as it permits sham-controlled methodologies that have historically been impossible with conventional neurostimulation. However, these findings remain preliminary and should be considered hypothesis-generating pending confirmation in adequately powered randomized sham-controlled trials.

Humans↗
PubMed2026

Hand Pain and Sensory Deficits: Carpal Tunnel Syndrome: 2026 Revision. Using the Evidence to Guide Musculoskeletal Rehabilitation Practice.

SYNOPSIS: Carpal tunnel syndrome is common in women, manual laborers, and during pregnancy; it is often associated with medical conditions such as obesity and diabetes. The musculoskeletal rehabilitation clinician's approach to managing hand pain and sensory deficits associated with carpal tunnel syndrome should include prescribing a neutral-positioned wrist orthosis plus instructing the patient on how to modify activities, adjust ergonomics, and reduce exposure to risk factors. Here, we present for clinicians the most up-to-date information to guide their work in managing hand pain and sensory deficits associated with carpal tunnel syndrome. J Orthop Sports Phys Ther 2026;56(9):622-623. doi:10.2519/jospt.2026.0502.

Humans↗
PubMed2026

Review of regulatory requirements for benefit-risk assessment for medical devices: uncovering existing methodologies.

INTRODUCTION: A positive benefit-risk profile is a prerequisite for the market approval of medical devices. However, regulations are often criticized for providing limited information on benefit-risk assessment (BRA) despite growing expectations for quantitative methods. A clearer understanding of regulatory requirements, existing methodologies, and unresolved issues is needed. AREAS COVERED: Relevant regulatory documents referencing BRA for medical devices were systematically identified, with a primary focus on the European regulation followed by screening to extract BRA&#x2011;related requirements and any explicitly or implicitly described methods. The findings were analyzed and consolidated by BRA context, type, objective, methodological description, and implementation, thereby establishing a basis for the BRA methodological landscape. EXPERT OPINION: BRA is not a single concept, but a set of context&#x2011;dependent assessments across lifecycle of a medical device. BRA within clinical evaluation framed into BRAs of risk management holds a pivotal role and is supported by the most detailed methodological guidance, although BRAs in other contexts are important. A structured overview of existing BRA requirements clarifies their treatment across regulatory documents. By differentiating BRA contexts, types, objectives, and required methodological detail, the analysis supports a more transparent understanding of BRA and helps identify priorities for methodological refinement and interface clarification.

Risk Assessment↗