Citations

Abstract Background Physical activity (PA) is an established protective factor for colorectal cancer (CRC), but it is unclear if genetic variants modify this effect. To investigate this possibility, we conducted a genome-wide gene–PA interaction analysis. Methods Using logistic regression and two-step and joint tests, we analyzed interactions between common genetic variants across the genome and PA in relation to CRC risk. Self-reported PA levels were categorized as active (≥ 8.75 MET-h/wk) vs. inactive (< 8.75 MET-h/wk) and as study- and sex-specific quartiles of activity. Results PA had an overall protective effect on CRC (OR [active vs. inactive] = 0.85; 95%CI = 0.81–0.90). The two-step GxE method identified an interaction between rs4779584, an intergenic variant near the GREM1 and SCG5 genes, and PA for CRC risk (p-interaction = 2.6×10 − 8 ). Stratification by genotype at this locus showed a significant reduction in CRC risk by 20% in active vs. inactive participants with the CC genotype (OR = 0.80; 95%CI = 0.75–0.85), but no significant PA–CRC association among CT or TT carriers. When PA was modeled as quartiles, the 1-d.f. GxE test identified that rs56906466, an intergenic variant near the KCNG1 gene, modified the association between PA and CRC (p-interaction = 3.5×10 − 8 ). Stratification at this locus showed that increase in PA (highest vs. lowest quartile) was associated with a lower CRC risk solely among TT carriers (OR = 0.77; 95%CI = 0.72–0.82). Conclusions In summary, we identified two genetic variants that modified the association between PA and CRC risk. One of them, related to GREM1 and SCG5 , suggests that the bone morphogenetic protein (BMP)-related, inflammatory, and/or insulin signaling pathways may be associated with the protective influence of PA on colorectal carcinogenesis.

Background Sex affects the prevalence of atherosclerotic cardiovascular disease (ASCVD) risk factors but whether sex differences exist in the associations between ASCVD risk burden and cognitive function is unclear. Methods This cross‐sectional study included participants from a population‐based cohort study in China that recruited community‐dwelling adults aged 50 to 75 years without baseline cardiovascular disease and stroke. The 10‐year ASCVD risk burden was quantified with 3 multivariate risk prediction equations. Cognitive domains of memory, attention, visuospatial function, executive function, and processing speed were assessed. Multivariable linear regression models were used to examine the interaction terms between sex and ASCVD risk scores on cognition. Results The final analytical sample included 2180 participants. Mean±SD age was 60.14 (6.38) and 52.1% were women. Men showed significantly higher ASCVD risk burden than women at baseline but the effect of ASCVD risk on 2‐year cognition were amplified in women compared with men, for the domains of memory (eg, β=−0.20 [95% CI, –0.26 to −0.13] versus β=−0.11 [95% CI, –0.16 to −0.07]), executive function (eg, β=−0.23 [95% CI, –0.31 to −0.16] versus β=−0.16 [95% CI, –0.21 to −0.10]), and processing speed (eg, β=−0.33 [95% CI, –0.39 to −0.27] versus β=−0.17 [95% CI, –0.21 to −0.13]). Sex‐stratified analyses showed different neuropsychological profiles at moderate ASCVD risk burden levels, suggesting sex‐specific ASCVD‐risk related cognitive phenotypes. Conclusions Sex differences in cognitive health affected by ASCVD risk underscore the importance of sex‐specific cognitive monitoring during ASCVD risk management and better vascular risk control in women to prevent cognitive decline.

Abstract Despite significant therapeutic advances in multiple myeloma (MM), outcomes in patients with plasma cell leukemia (PCL) remain dismal. We conducted a multicenter retrospective analysis of patients with PCL who were treated with the B-cell maturation antigen–directed chimeric antigen receptor T-cell (CAR-T) products idecabtagene vicleucel (ide-cel) and ciltacabtagene autoleucel (cilta-cel). We identified 34 patients; 19 patients received ide-cel and 15 received cilta-cel. With a median follow-up of 11.9 months, the overall median progression-free survival (mPFS) was 9.0 months (95% confidence interval [CI], 4-15) and the median overall survival (mOS) was 13.0 months (95% CI, 8 to not estimable [NE]). The 1-year cumulative incidence of progression or death was 72%, and the 1-year cumulative incidence of death was 47%. Patients who received cilta-cel had a longer mPFS (19.0 months vs 6.0 months) and mOS (&gt;23 months [NE] vs 9.0 months) when compared with those treated with ide-cel. Similarly, the 1-year cumulative incidence of disease progression or death was 37.5% (95% CI, 17.4-68.5) with cilta-cel, whereas all patients treated with ide-cel progressed or died within 12 months of infusion. The rates of hematologic and nonhematologic toxicities were similar between patients treated with cilta-cel and those treated with ide-cel and were consistent with those reported in patients with MM. In this first multicenter study that evaluated patients with PCL who were treated with standard-of-care CAR-T products, we show that CAR-T is safe, feasible, and associated with improved outcomes when compared with historic standards.

Abstract Objectives To enable users with modest technical background to perform biomedical natural language processing (NLP). Materials and Methods We developed medspacyV using the Python graphical programming tkinter library, following the model-view-controller (MVC) design pattern. The interface wraps around a rule-based pipeline for sentence splitting, section segmentation, concept identification, and negation detection. Results The primary window allows the user to configure the project and NLP rules, execute the pipeline, and save the outputs into a table. A separate annotation viewer window can be launched to inspect the immediate or previous NLP outputs. Discussion We developed medspacyV with three rationales: controllability, explainability, and economy. The rule-based approach is sufficient for many NLP use cases. Conclusion The medspacyV program is publicly available at https://github.com/medspacy/medspacyV, targeting use by healthcare professionals and researchers in their NLP projects.

ABSTRACT Background Prompt detection and intervention are crucial for improving outcomes in acute invasive fungal rhinosinusitis (AIFS). Diagnostic prediction models assist in risk‐stratification, but their accuracy requires testing through external validation. This study aims to validate a previously published diagnostic prediction model for AIFS in an independent cohort. Methods A retrospective chart review was conducted at a tertiary care center (2008–2023) to identify patients with an otolaryngology consult for suspected AIFS. Of 65 patients identified, 11 (16.9%) were diagnosed with AIFS based on histopathology. Risk was calculated using Yin et al.’s predictive model. Predictive performance was assessed by calibration and discrimination. Results Patients had significantly higher rates of diabetes (46.2% vs. 26.1%, p = 0.002), long‐term steroid use (60% vs. 28.2%, p < 0.0001), and solid organ transplantation (38.5% vs. 8.5%, p < 0.001), compared with the development cohort, with conversely lower rates of hematologic malignancy (29.2% vs. 58.7, p < 0.001) and neutropenia (19.4% vs. 41%, p = 0.001). Despite these differences, both the three‐variable (C‐index: 0.844; 95% CI, 0.736–0.952) and four‐variable models (C‐index: 0.963; 95% CI, 0.919–1) showed adequate discrimination. Both models exhibited slight overprediction of risk, with a calibration‐in‐the‐large predicted risk of 24.1% (95% CI, 13.68–34.46) for the three‐variable model and 24.2% (95% CI, 13.76–34.57) for the four‐variable model. Calibration plots confirmed overprediction. Conclusion The AIFS diagnostic model demonstrates acceptable discrimination and calibration on external validation, with generalizability to patients with different comorbidities. Larger studies are recommended to further test the model's predictive performance and clinical applicability.

Background and objectives Arteriovenous malformations (AVMs) with perinidal aneurysms and single draining vein are associated with an elevated risk of rupture and increased procedural complexity. The role of preoperative embolization in this high-risk anatomical subset remains unclear. This study aimed to evaluate the safety and efficacy of microsurgery with preoperative embolization, compared with microsurgery alone in patients with such AVMs. Methods We conducted a multicenter retrospective analysis of an AVM registry from the MISTA (Multicenter International Study for Treatment of Brain AVMs) consortium and included AVMs with perinidal aneurysms and a single draining vein. Baseline characteristics, angiographic outcomes, functional outcomes, and complication rates were compared. Propensity score weighting (PSW) using the covariate balancing method was applied to adjust for baseline differences. Results Out of a total of 1919 patients, 65 met the inclusion criteria; 45 patients underwent preoperative embolization followed by microsurgery, and 20 underwent microsurgery alone. After adjustment, complete obliteration rates were similar between groups (OR 0.87, 95% CI 0.04 to 16.33, P=0.92), as were rates of functional independence at discharge and follow-up. Overall complication, symptomatic complication, and mortality rates did not differ significantly between groups. However, permanent complications were significantly lower in patients with preoperative embolization (OR 0.06, 95% CI 0.004 to 0.84, P=0.03). Discussion In patients with AVMs featuring perinidal aneurysms and single draining vein, preoperative embolization followed by microsurgery was associated with fewer permanent complications and no increase in adverse outcomes compared with microsurgery alone. However, given the small number of events, this finding should be interpreted cautiously.

ABSTRACT Background and Objectives The relevance of Cochrane systematic reviews depends on timely completion and updates. This study aimed to empirically assess the lifecycles of Cochrane reviews published from 2003 to 2024, including transitions from protocol to review, update patterns, and withdrawals. Methods We extracted data from Cochrane Library publications between 2003 and 2024. Each review topic was identified using a unique six‐digit DOI‐based ID. We recorded protocol publication, review publication, updates, and withdrawals (i.e., removed from the Cochrane Library for editorial or procedural reasons), calculating time intervals between stages and conducting subgroup analyses by review type. Results Of 8137 protocols, 71.9% progressed to reviews (median 25.7 months), 2.4% were updated during the protocol stage, and 10.0% were withdrawn. Among 8477 reviews, 64.3% were never updated by the time of our analysis; for those updated at least once, the median interval between updates was 57.2 months. Withdrawal occurred in 2.5% of reviews (median 67.6 months post‐publication). Subgroup analyses showed variation across review types; diagnostic and qualitative reviews tended to have longer protocol‐to‐review times than other types of reviews. Conclusions Cochrane reviews show long development and update intervals, with variation by review type. Greater use of automation and targeted support may improve review efficiency and timeliness.

Effective healthcare referral triage poses a significant challenge, especially extracting referral notes on time for scheduling. To offset this issue, this study aims to develop an optimized Random Forest classifier to recreate the referral notes content and identify patients requiring Spinal Cord Stimulation procedures. A performance index was introduced to improve accuracy, while a consistency index was designed to prevent overfitting. The optimized classifier, with the optimal selection at the number of estimates being 5 trees and tree depth being 4, achieved an accuracy of 0.74 with a lower standard deviation, demonstrating its reliability and effectiveness.

ABSTRACT Rationale Longer duration of epilepsy before surgery is a predictor of poor outcome. While referral delays of surgical candidates are well documented, factors causing delay during the presurgical evaluation remain unclear and may vary depending on institutional characteristics. By benchmarking the duration of presurgical evaluation across multiple centers and identifying patient and evaluation characteristics contributing to duration, we can ascertain best practices and address modifiable contributors to reduce delays. Methods We queried the Pediatric Epilepsy Research Consortium Surgery Database, a prospective, observational multicenter study enrolling children 0–18 years at 27 US pediatric epilepsy centers, for all patients undergoing initial presurgical evaluation for drug‐resistant epilepsy (DRE). We included patients with completed evaluations and data on duration from initiation of presurgical evaluation to final surgical decision. We compared patient characteristics and evaluation components between those with long duration evaluations (> 75% quartile) and those with short evaluations (< 25% quartile). Akaike information criteria selection identified variables associated with longer duration. From these, we developed a logistic prediction model for evaluation duration, using a random 80/20 training/testing split of the entire cohort. The model was tested among institutions with ≥ 10 patients in the cohort to assess its accuracy in predicting long durations. Linear models for each site assessed each variable's impact on duration. Variables with < 10% of the patient population at each site were excluded. Beta values were compared to identify intra‐ and inter‐institution variability and to delineate institutions with the shortest added duration for each variable. Results Of 2318 patients undergoing surgical evaluation, 1655 (71%) from 23 sites had complete data. Median evaluation duration was 8 weeks (interquartile range 3–22); 453 (27%) were short‐duration evaluations and 414 (25%) were long‐duration evaluations. Multiple patient and evaluation characteristics were associated with duration (Table 1). Table 6 provides the average duration each variable contributes to evaluation by site, highlighting the shortest durations compared with other groups. Conclusions Duration of presurgical evaluation for DRE can be accurately modeled using multiple patient characteristics and testing strategies commonly employed in epilepsy surgery evaluations. This predictive model can not only estimate evaluation duration but also identify opportunities to improve systemic efficiency. Institution‐level modeling identifies specific program strengths, providing an opportunity to learn from successful processes. Subsequent research will focus on institutional process mapping to better understand systemic practices that lead to improved efficiencies, then sharing these processes across the consortium to shorten evaluation durations.