Citations

AbstractA 61‐year‐old female presented with progressive plaques on the left forehead and right labia.

Pancreatic cancer (PC), characterized by a dismal 5-year survival rate of approximately 12%, remains one of the most aggressive cancers. Majority of cases are identified at advanced stages, which are beyond the scope of surgical resection. Importantly, while the overall prognosis for PC is poor, localized stages of the disease can significantly enhance survival chances because of the potential for curative interventions. We explore the evolution of early detection strategies, including screening methods for high-risk individuals, the yield of diagnostic tests, and the impact of emerging technologies. Special emphasis is given to the role of artificial intelligence in overcoming the limitations of standard imaging practices, thereby refining diagnostic accuracy, and predicting patient outcomes. Our review synthesizes current controversies and addresses the technological advancements that could potentially shift the paradigm toward improved survival rates for patients with PC.

Abstract Transcriptome profiling using RNA sequencing (RNA-seq) of bulk formalin-fixed paraffin-embedded (FFPE) tissue blocks is a standard method in biomedical research. However, when used on tissues with diverse cell type compositions, it yields averaged gene expression profiles, complicating biomarker identification due to variations in cell proportions. To address the need for optimized strategies for defining individual cell type compositions from bulk FFPE samples, we constructed single-cell RNA-seq reference data for breast tissue and tested cell type deconvolution methods. Initial simulation experiments showed similar performances across multiple commonly used deconvolution methods. However, the introduction of FFPE artifacts significantly impacted their performances, with a root mean squared error (RMSE) ranging between 0.04 and 0.17. Scaden, a deep learning-based method, consistently outperformed the others, demonstrating robustness against FFPE artifacts. Testing these methods on our 62-sample RNA-seq benign breast disease cohort in which cell type composition was estimated using digital pathology approaches, we found that pre-filtering of the reference data enhanced the accuracy of most methods, realizing up to a 32% reduction in RMSE. To support further research efforts in this domain, we introduce SCdeconR, an R package designed for streamlined cell type deconvolution assessments and downstream analyses.

PURPOSE The enhanced, electronic health record (EHR)–facilitated cancer symptom control (E2C2) trial is a cohort cluster-randomized, stepped-wedge, hybrid type II trial that leverages EHR systems to facilitate a collaborative care model (CCM) approach with the goal of improving cancer symptom management. Understanding factors that influence care team adoption of EHR systems remains a critical understudied area of research. This study examines how oncology care teams' perceptions regarding the feasibility, acceptability, and appropriateness of E2C2 EHR systems preimplementation were associated with adoption 3 months after implementation and characterizes differences in adoption by individual- and system-level factors. METHODS Care team members completed an electronic survey before and 3 months after implementation of E2C2 for their respective sequence. Adoption was defined as frequency of use to statements aligned with care team–directed EHR systems designed to facilitate CCM approaches. Chi-square tests assessed differences in adoption while logistic regression models estimated associations between baseline mean scores of acceptability, feasibility, and appropriateness on care team adoption at 3 months. RESULTS Results from 94 care team members (37.2% oncologists, 72.6% female, 55.3% in their role for 6+ years) found that adoption rates ranged from 48.9% to 71.7%, with significant differences observed by location (community-based health care systems v tertiary medical center) and professional role. Adjusting for professional role, care team members reporting higher levels of perceived acceptability and appropriateness at baseline had greater odds of adopting EHR systems at 3 months. CONCLUSION EHR systems perceived as acceptable and appropriate are more likely to be adopted by oncology care teams in our sample. Future implementation efforts should consider tailored strategies to facilitate adoption of EHR systems designed to promote CCM-based approaches to improve cancer symptom management.

Abstract Rationale Fibrosing mediastinitis (FM) is an uncommon fibroinflammatory condition without established or effective medical therapies. Infiltrating B lymphocytes are commonly present, and progressive fibrosis compromises mediastinal structures, including blood vessels and airways, resulting in significant morbidity and mortality. Objective To evaluate the benefits and side effects of rituximab in patients with progressive and symptomatic FM. Methods We treated 22 patients (median age, 35 yr; range, 15–68 yr; 45% female) with metabolically active, progressive FM with rituximab on an off-label basis. Additionally, patients were administered pneumocystis and antifungal prophylaxis when immunosuppressed with rituximab. Modeling of longitudinal treatment response based on changes in relative lesion volume from baseline was performed retrospectively using functional data analysis, and time-to-event modeling was performed to estimate treatment response rates based on a >30% reduction in pretreatment volume. The primary endpoints were lack of disease progression and change in mediastinal lesion volume on computed tomography (evaluated retrospectively). Results No patient experienced disease progression after rituximab therapy. Median clinical follow-up was 42 months (range, 7–94 mo) and imaging follow-up 21 months (range, 7–62 mo). A total of 82% of patients had confirmed histoplasmosis-associated FM. After rituximab treatment, a 49.6% (95% confidence interval, 17.5–64.4%) mean estimated decrease in pretreatment lesion volume was observed at 24 months. The estimated objective treatment response rate was 47.9% (95% confidence interval, 26.7–70.3%). Conclusions This observational study suggests that rituximab is a well tolerated and potentially effective therapy in a cohort of patients with symptomatic and progressive FM.

Introduction: Transcribing disordered speech can be useful when diagnosing motor speech disorders such as primary progressive apraxia of speech (PPAOS), who have sound additions, deletions, and substitutions, or distortions and/or slow, segmented speech. Since transcribing speech can be a laborious process and requires an experienced listener, using automatic speech recognition (ASR) systems for diagnosis and treatment monitoring is appealing. This study evaluated the efficacy of a readily available ASR system (wav2vec 2.0) in transcribing speech of PPAOS patients to determine if the word error rate (WER) output by the ASR can differentiate between healthy speech and PPAOS and/or among its subtypes, whether WER correlates with AOS severity, and how the ASR's errors compare to those noted in manual transcriptions. Method: Forty-five patients with PPAOS and 22 healthy controls were recorded repeating 13 words, 3 times each, which were transcribed manually and using wav2vec 2.0. The WER and phonetic and prosodic speech errors were compared between groups, and ASR results were compared against manual transcriptions. Results: Mean overall WER was 0.88 for patients and 0.33 for controls. WER significantly correlated with AOS severity and accurately distinguished between patients and controls but not between AOS subtypes. The phonetic and prosodic errors from the ASR transcriptions were also unable to distinguish between subtypes, whereas errors calculated from human transcriptions were. There was poor agreement in the number of phonetic and prosodic errors between the ASR and human transcriptions. Conclusions: This study demonstrates that ASR can be useful in differentiating healthy from disordered speech and evaluating PPAOS severity but does not distinguish PPAOS subtypes. ASR transcriptions showed weak agreement with human transcriptions; thus, ASR may be a useful tool for the transcription of speech in PPAOS, but the research questions posed must be carefully considered within the context of its limitations. Supplemental Material: https://doi.org/10.23641/asha.26359417

Background As no consensus exists on the optimal postoperative rehabilitation protocol in terrible triad injuries, we sought to characterize the reported protocols and relate them to postoperative range of motion (ROM) measures and Mayo Elbow Performance Score (MEPS). Methods A systematic review was performed by searching PubMed/MEDLINE, Embase, Web of Science, and Cochrane databases to identify articles on the operative treatment of terrible triad injuries reporting postoperative rehabilitation protocols were included. Included studies were descriptively summarized. Methodologic quality was assessed using the Methodological Index for Non-randomized Studies criteria. Meta-analysis compared postoperative ROM measures and the MEPS between patients initiating passive ROM exercises at ≤7 days vs. >7 days. Results Our review included 36 articles with 1123 elbows (66% male, mean age: 43 years, follow-up: 27 months). Of the studies reporting physical therapy protocols, it was most commonly initiated at 7 days postoperatively (6/36, 17%), passive ROM exercises at 7 days (3/25, 12%), and active ROM at 21 days (4/26, 15%). On meta-analysis, early passive ROM initiation was not associated with improved elbow ROM or MEPS. Discussion While rehabilitation protocols commonly advised passive ROM at one week post-operatively, meta-analysis did not support functional benefits of early passive ROM. Study design Systematic Review; Level of evidence, 4.