Citations

Introduction: Adult hepatitis B vaccination coverage in the United States remains low despite updated national recommendations supporting universal adult immunization. Many adults remain unaware of their susceptibility to hepatitis B virus (HBV) infection. This quality improvement (QI) study evaluated a stepwise “Offer–Offer–Test–Vaccinate” workflow designed to improve hepatitis B vaccine uptake among vaccine-hesitant adults in a primary care setting. Methods: This retrospective QI study was conducted at a single primary care clinic in Rochester, Minnesota. Adult patients (≥19 years) seen between October 1, 2022, and October 1, 2024, were routinely offered hepatitis B vaccination during rooming. Two participating physicians implemented an enhanced workflow in which patients who declined vaccination were counseled and then offered serologic screening using the 2023 CDC-recommended triple panel (HBsAg, anti-HBs, and total anti-HBc). Patients with negative serology were notified via the patient portal and reoffered vaccination along with a link to the CDC Vaccine Information Statement. The primary endpoint was initiation of the hepatitis B vaccine series following receipt of negative serology results. Preliminary series-completion data through October 1, 2025, were also assessed. Results: Among 501 eligible adults, 104 (20.8%) accepted vaccination at the initial offer. Of the 397 who declined, 106 (26.7%) agreed to serologic testing; 91 (85.8%) were seronegative. Among seronegative patients, 41 (45.1%) subsequently accepted vaccination. Integrating serologic testing increased overall vaccination uptake from 20.8% to 28.9%, an absolute increase of 8.2 percentage points and a relative increase of 39.4%. Approximately 2.6 serologic tests were required to generate 1 additional first-dose vaccination. Preliminary series-completion rates were 74.0% among those vaccinated at the initial offer and 87.8% among those vaccinated following serologic testing. Discussion: In this primary care setting, incorporating serologic testing into the workflow was associated with modestly improved hepatitis B vaccination uptake among vaccine-hesitant adults. Serologic results may help re-engage patients by providing personalized immunity information. Implementation considerations include staffing needs, laboratory access, patient portal engagement, and insurance coverage. Conclusion: The “Offer–Offer–Test–Vaccinate” strategy was associated with a modest increase in hepatitis B vaccine uptake among hesitant adults. This EMR-integrated, stepwise approach may offer a feasible and scalable strategy to reduce missed vaccination opportunities and support HBV prevention in adult primary care.

Background Artificial intelligence (AI)-generated text to video is emerging in medical education, but its effectiveness, accuracy and safety remain uncertain. We aimed to synthesise empirical studies evaluating these tools in learner or patient education. Methods A comprehensive search was conducted in MEDLINE/PubMed, Google Scholar, Scopus, Cochrane Review and Web of Science for studies published up to January 2025. Eligible studies evaluated AI-generated text to video for medical or patient education, reporting both quantitative and qualitative outcomes. Two reviewers screened and extracted data. The review adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results Out of 103 identified studies, five studies met the inclusion criteria: four evaluated patient education and one evaluated physician training. Clinical areas were ophthalmology (2/5), plastic surgery (1/5), dysphagia rehabilitation (1/5) and neurosurgical training (1/5). In ophthalmology, control materials outperformed AI-generated videos on image/script accuracy (p<0.005), with similar script-image alignment. In dysphagia rehabilitation, a randomised trial reported improvements in swallowing function and related outcomes with an AI-assisted video game intervention (p<0.001). A plastic surgery study reported greater user preference for a video avatar tool compared with a text chatbot (63.5% vs 28.1%). Across the reviewed studies, samples were small and CIs were rarely reported. Outcome measures were heterogeneous, and meta-analysis was not feasible. Conclusion AI-generated videos can enhance engagement or selected outcomes in certain contexts, yet concerns about accuracy and inconsistent measurement persist. Current evidence is sparse and mixed. Currently, these tools can complement, rather than replace, standard resources until non-inferiority is demonstrated for the prespecified primary outcomes. PROSPERO registration number CRD42025640042.

Multiplex immunofluorescence and immunohistochemistry (mIF/IHC) are increasingly employed antibody-based technologies that use tissue sparingly and facilitate the detection of co-localized or neighboring biomarkers. Specifically, these platforms enable spatial analyses of the tumor microenvironment as well as extended applications, for example, describing normal tissue anatomy, autoimmunity, infectious diseases, etc. mIF/IHC has greatly enhanced biomarker discovery efforts, and a growing number of studies suggest superiority to traditional IHC. Standardization of staining approaches, reporting of image analysis strategies and resultant data is critical for facilitating cross-study comparisons, validation, deployment, and generalization of findings. To address this challenge, The Society for Immunotherapy of Cancer (SITC) previously published two articles providing best practice guidelines for mIF/IHC staining, image analysis, and data sharing. Here, SITC convened stakeholders to develop the third article in the series, a consensus checklist for scientific reporting of mIF/IHC data to support and complement the best practice guidelines. The checklist includes critical components of mIF/IHC applications to be defined within publications such as detailed descriptions of analytical validation; image acquisition, selection, and registration methods; and cell clustering and spatial analysis strategies, amongst others. Such information will help with data reproducibility and comparison across studies towards future drug and assay development.

ABSTRACT Background and Aims Chronic inflammatory demyelinating polyradiculoneuropathy ( CIDP ) is a common, treatable, autoimmune, neuropathy frequently misdiagnosed. The complex electrodiagnostic ( EDX ) criteria required for diagnosis are challenging to apply in routine practice. This study evaluates the effectiveness of a machine‐assisted EDX tool in real‐time identification of demyelinating nerve conduction studies ( NCS ) stipulated by 2021‐ EAN / PNS CIDP criteria in conjunction with an online CIDP clinical probability calculator. Methods We prospectively evaluated 100 consecutive patients with referral or EDX diagnosis of polyradiculoneuropathy beginning January 1, 2024. Fifty patients were included, each from Jacksonville and Rochester Mayo Clinics. Routine electromyography ( EMG ) reports were compared to a machine‐assisted support tool applying 2021‐ EAN / PNS CIDP EDX criteria to NCS assessing demyelination. The EDX ‐assistant performance was compared to the final clinical diagnosis and our previously reported online CIDP clinical prediction tool ( https://news.mayocliniclabs.com/cidp‐calculator/ ). Results Among 100 patients (60% male; median age 64), 30 had a final clinical CIDP diagnosis with 29 having intravenous immunoglobulin follow‐up; 27 (93%) improved and 2 (7%) stabilized. Routine EMGs reported demyelination in 14 of 30 (47%), with 46% sensitivity and 79% specificity. The EDX ‐assistant identified CIDP demyelination in 28 of 30 (93%), with 93% sensitivity and 57% specificity. The clinical calculator detected CIDP in 30 of 30 (100%) with 86% specificity, increasing to 94% after excluding false positives lacking demyelinating features on the EDX tool. Interpretation A real‐time machine‐assisted EDX support tool, used with a clinical web‐based calculator, streamlines CIDP assessment by improving standardized identification of 2021‐EAN/PNS CIDP demyelinating NCS criteria and aiding clinical decisions.

Introduction Despite the identification of multiple susceptibility loci by genome-wide association studies (GWAS), considerable chronic obstructive pulmonary disease (COPD) heritability remains unexplained. Aim To identify interaction networks of airway epithelial cell DNA methylation in COPD and further explore potential correlations with airway bacterial composition, as potentially collective regulators of biological pathways influencing COPD severity. Methods Using DNA isolated from bronchial airway brushings of 67 ever-smokers (>20 pack-years) from the SubPopulations and InteRmediate Outcomes Measures in COPD Study (SPIROMICS), we assessed proportion of DNA methylation (β) by epigenome-wide association study (EWAS) and examined associations of differentially methylated CpG probes (DMPs) with risk for moderate-to-severe COPD (N=34) versus absent or mild COPD (N=33). We tested co-methylation modules generated by Weighted Correlation Network Analyses (WGCNA) for associations with moderate-to-severe COPD and with bacterial genus-level relative abundances (16S rRNA sequencing). Results EWAS-identified nominally significant DMPs enriched for lung function GWAS loci. Eigengenes in six WGCNA modules were associated with moderate-to-severe COPD (false discovery rate <0.05). Four of those modules were enriched for forced expiratory volume in 1 s/forced vital capacity GWAS loci, and five overlapped with DMPs from EWAS. Overlapping CpG loci in three COPD-associated modules were adjacent to mucin genes; one had 10 genes highly ranked by connectivity with MUC5B, including important pathway genes: B3GNT6 , DGKI and ITGA8 . CpGs in an independent COPD-associated module showed the most correlations with Rothia , with directionality suggestive of negative associations with moderate-severe COPD. Conclusions Bronchial epithelial DNA methylation modules enriched for lung function GWAS loci associate with COPD severity in SPIROMICS. Potential module relationships to bronchial bacterial composition require further validation.

Importance Molecular analyses of biospecimens collected from study participants are essential for identifying biomarkers that can tailor treatments to specific subsets of patients who are most likely to benefit. Sharing of data and biospecimens from clinical trials enables personalized, patient-centric use of cancer therapies and accelerates the development of new treatments. Objective To describe obstacles to sharing data and biospecimens and to propose strategies to enhance access and collaboration. Evidence Review This is a Special Communication authored by 53 academic investigators and patient representatives from the breast cancer community with extensive experience in conducting clinical and translational research. The article also evaluates the impact of biomarker research on specifying responsive subpopulations in the 29 registrational clinical trials that have led to approval of a new drug for treatment of breast cancer between 2017 and 2024. Findings Clinical trial participants are increasingly asked to provide tissue and/or body fluid biospecimens for biomarker research that is typically controlled by the sponsoring pharmaceutical company, but published biomarker studies are rare. Among 29 breast cancer registrational studies reported in the past 8 years, none resulted in biomarker research that restricted a drug’s approved indication. Herein, strategies to maximize the value of clinical data and biospecimens contributed by participants are proposed, thereby supporting the shared goals of the pharmaceutical industry and academia to improve patient care. These strategies include (1) establishing coleadership structures involving academia and patients in clinical trial design and conduct, (2) ensuring that informed consent forms state that data and biospecimens will be shared with academia for future research, (3) requiring the sharing of clinical data as a condition for regulatory approval, and (4) enabling access to biospecimens and translational research data for independent studies on biomarkers that may indicate drug efficacy and toxicity. Conclusions and Relevance Data and biospecimen sharing from registrational trials has been suboptimal. Improving clinical data, biospecimens, and biospecimens’ related data sharing requires concrete actions and a multidimensional stakeholder approach to accelerate the impact of clinical cancer research on the quality of patient care.