Citations

Glioblastoma is the most common form of brain cancer in adults and remains one of the most lethal forms of cancer. Treating glioblastoma is uniquely challenging due to its aggressive nature and its critical location, the brain, which must remain largely undamaged. Due to these difficulties, there is a lack of effective treatment options. Computer models simulating tumors and their response to therapy, known as digital twins, provide a promising new strategy. These model systems are mathematical equations that capture the biological knowledge of how cells interact during tumor growth and in response to treatment. By solving these equations, we can create virtual patients that provide accurate predictions of real patients’ tumor progression. This approach has the potential to improve outcomes by designing therapies for the specific needs of each patient, moving beyond the limitations of the “one-size-fits-all” approach that is currently used.

Abstract Purpose Medical school applicants engage in informal preference signaling by submitting letters of intent (which include a commitment to accept an admission offer) and letters of interest (which include no such commitment). Commitments are unenforceable and are based on an honor system. Applicants submit letters to medical schools before receiving financial aid offers, potentially disadvantaging low socioeconomic status (SES) applicants. This study describes postinterview communication patterns and analyzes associations among applicant demographics, letter submission rates, and admissions outcomes. It tests the hypothesis that low SES is negatively associated with letter of intent submission. Method The authors collected postinterview communications from all interviewees at the Mayo Clinic Alix School of Medicine during 3 admissions cycles (2021-2023). Authors developed and validated codebook definitions for the 2 letter types. SES was defined using the Association of American Medical Colleges education-occupation indicator. Letter submission rates were compared using mixed-effects logistic regression. Results Of 1,313 applicants, 1,109 submitted 1 letter or more. The sample included 257 (19.6%) low-SES and 1,056 (80.4%) non–low-SES applicants. Coders showed excellent interrater reliability (Gwet AC1 range, 0.89-0.995). Low-SES applicants submitted letters of intent with similar frequency to higher-SES applicants (33.9% [87/257] vs 33.5% [354/1,056]; odds ratio, 1.02; 95% CI, 0.76-1.37; P = .88) and submitted letters of interest at similar frequency (55.6% [143/257] vs 59.5% [628/1,056]; odds ratio, 0.86; 95% CI, 0.65-1.13; P = .27). Among 116 applicants who wrote letters of intent and were offered admission, 20 (17.2%) declined the admission offer. Conclusions There was no difference in letter of intent submission based on SES, and letter of intent submission was positively associated with matriculation. Among letter of intent writers who were offered admission, 1 in 6 declined. Undergraduate medical education may wish to consider a formalized preference signaling system to promote an honest and transparent application process.

Heart failure with preserved ejection fraction (HFpEF) is associated with exercise intolerance, with respiratory muscle dysfunction as a contributing factor. Patients with HFpEF have exaggerated cardiovascular responses to respiratory muscle metaboreflex activation. In this study, we determined the impact of inspiratory muscle training (IMT) on the respiratory muscle metaboreflex in HFpEF. We found that 8 wk of IMT improved inspiratory muscle strength and attenuated the respiratory muscle metaboreflex-mediated cardiovascular responses in patients with HFpEF.

Abstract Objectives Accurate and timely prediction of physiological deterioration in hospitalized patients is essential, but existing deep learning models, which rely solely on structured electronic health record (EHR) data, generate high false-positive rates by missing crucial contextual information in clinical notes. We present DETERIO-LLM, a hybrid prediction model that selectively integrates large language models (LLMs) with a deep learning model (DETERIO) to reclassify borderline-risk alerts using narrative clinical notes. Materials and Methods This retrospective study used a cohort of 1000 inpatients (4.6% deterioration prevalence). DETERIO-LLM selectively analyzed narrative notes for alerts in the uncertainty range (scores 2.5-3.5). Performance was evaluated using sensitivity, positive predictive value (PPV), and F1 score, benchmarked against comparators including the best-established ML model, eCART. Results DETERIO-LLM significantly improved predictive precision over all comparators. At its optimal threshold, the model achieved a PPV of 30.6% and an F1 score of 37.3%, outperforming eCART. This selective integration reduced false-positive alerts by 46.5% within the uncertainty range while maintaining comparable sensitivity. Discussion This study demonstrates a practical, interpretable method for integrating LLM-derived contextual knowledge into existing structured EHR prediction workflows. By focusing LLM analysis on high-uncertainty alerts, DETERIO-LLM substantially improves clinical utility through a marked reduction in false-positive cases, which is critical for mitigating alert fatigue. Conclusion Selective LLM integration with structured EHR models offers a viable, interpretable path to improving early warning systems in clinical care by leveraging narrative context to reduce alert fatigue while enhancing predictive performance.

Cirrhosis remains a major global cause of morbidity and mortality, with rapidly evolving etiologic drivers. This review summarizes the contemporary global epidemiology of cirrhosis, highlighting regional patterns and major transitions in underlying causes to inform prevention and policy. In 2021, cirrhosis and chronic liver disease accounted for ~1.4 million deaths worldwide. Although age-standardized mortality rates have declined in many regions, the absolute burden continues to rise due to population growth and aging. Reductions in hepatitis B and C–related cirrhosis, driven by vaccination, screening, and antiviral therapy, have been offset by a growing contribution from steatotic liver disease. High–sociodemographic index (SDI) regions exhibit lower mortality but increasing prevalence, reflecting improved survival and expanding metabolic risk, whereas low- and lower-middle–SDI regions continue to experience high mortality. Addressing the global burden of cirrhosis will require sustained public health investment focused on viral hepatitis elimination, alcohol-associated harm reduction, metabolic risk management, and equitable access to early detection and care.

ASCO Guidelines provide recommendations with comprehensive review and analyses of the relevant literature for each recommendation, following the guideline development process as outlined in the https://www.asco.org/practice-patients/guidelines/guideline-methodology . ASCO Guidelines follow the https://www.asco.org/about-asco/legal/conflict-interest-coi . Clinical Practice Guidelines and other guidance (“Guidance”) provided by ASCO is not a comprehensive or definitive guide to treatment options. It is intended for voluntary use by clinicians and should be used in conjunction with independent professional judgment. Guidance may not be applicable to all patients, interventions, diseases or stages of diseases. Guidance is based on review and analysis of relevant literature, and is not intended as a statement of the standard of care. ASCO does not endorse third-party drugs, devices, services, or therapies and assumes no responsibility for any harm arising from or related to the use of this information. See complete disclaimer in Appendix 1 and Appendix 2 (online only) for more . PURPOSE To offer clinicians recommendations concerning breast cancer follow-up and surveillance after primary treatment. METHODS ASCO convened an Expert Panel to develop recommendations based on a systematic review and a formal consensus process. RESULTS One randomized controlled trial (RCT) was identified and formed the evidentiary basis for the surveillance mammography guideline recommendation. No RCTs were identified that evaluated different follow-up approaches by risk of relapse in patients treated for early-stage breast cancer. Given the dearth of evidence identified in the systematic review of the literature, formal modified Delphi consensus-based recommendations were generated. RECOMMENDATIONS The guideline offers recommendations on the role of a risk-based approach to the frequency and intensity of follow-up among patients with breast cancer in the adjuvant setting. Regular history, physical examination, and mammography are recommended for breast cancer follow-up. Either virtual or in-person visits can be offered. Certain patients at a high risk of cancer recurrence warrant closer surveillance, such as those patients with locally advanced disease or residual disease following neoadjuvant chemotherapy. Recommendations on the use of blood-based biomarkers and supplemental imaging are provided. Guideline recommendations will be updated once additional evidence-based tools become available to better individualize surveillance. Additional information is available at www.ascopubs.org/topics/asco-guidelines/breast-cancer .

Abstract This study examined the extent to which goodness of pronunciation (GoP) scores and phonological posterior probabilities capture perceptual ratings of speech severity in individuals with motor speech disorders (MSD). Speech recordings of the word catastrophe were obtained from 489 participants, including 333 neurologically typical controls and 156 individuals with MSD. GoP scores were derived using traditional acoustic features and self-supervised speech representations, including WavLM and XLS-R, across multiple modeling approaches, while phonological posterior probabilities were extracted using Phonet. Model performance was evaluated using Kendall’s rank correlations, regression, and receiver operating characteristic analyses against speech-language pathologists’ perceptual ratings of sound distortion and intelligibility. Both GoP and phonological posterior probabilities were significantly associated with perceptual ratings. Self-supervised speech representations substantially outperformed traditional acoustic features, with WavLM-based GoP using k-nearest neighbors achieving the strongest performance. Across correlation, regression, and classification analyses, GoP consistently outperformed phonological posterior probabilities for both sound distortion and intelligibility. Age and gender had minimal influence on model-derived measures or their relationships with perceptual ratings. These findings demonstrate the value of self-supervised GoP as an objective measure of speech impairment while highlighting the complementary role of phonological posterior probabilities in characterizing articulatory aspects of motor speech disorders.

Background: The purpose of this study was to determine whether placement of triangular titanium implants (TTI) suprajacent to S2-alar-iliac (S2AI) pelvic fixation screws during multilevel spinal fusion surgery for adult spine deformity reduces pelvic fixation failures. Methods: This prospective, multicenter, international, partially blinded randomized clinical trial included 222 patients scheduled for multilevel spinal fusion surgery with S2AI-based pelvic fixation. In the S2AI+TTI group, the mean age was 64.9 years, 54.1% were female, 3.7% were Hispanic, 5.5% were African American, and 1.8% were Asian. In the S2AI-alone group, the mean age was 64.8 years, 58.4% were female, 3.5% were Hispanic, 7.1% were African American, and 0.9% were Asian. Subjects were randomized to pelvic fixation using S2AI screws alone versus S2AI+TTI. Scheduled follow-up included a 24-month full-spine radiograph and a high-resolution computed tomography (CT) scan, which was independently interpreted. Results: The primary composite radiographic end point (S2AI screw breakage, lucency, or pullout, or posterior spinal rod breakage distal to S1) occurred less frequently in the S2AI+TTI group than in the S2AI-alone group (11.0% versus 20.4%, p = 0.0415). Except for rod-screw dissociation and rod fracture distal to S1, all components of the primary composite end point occurred less frequently in the S2AI+TTI group. TTI placement did not affect sagittal or coronal spinal alignment parameters. The rate of rod fracture throughout the spinal construct was slightly higher in the S2AI+TTI group (9.2% versus 5.3%) but the difference was not significant (p = 0.197). Conclusions: Placement of TTI suprajacent to S2AI screws reduced the rate of pelvic fixation failure in patients undergoing multilevel spinal fusion with pelvic fixation. Level of Evidence: Therapeutic Level I . See Instructions for Authors for a complete description of levels of evidence.

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

OBJECTIVE To examine kidney disease outcomes associated with dipeptidyl peptidase 4 inhibitors (DPP-4i). RESEARCH DESIGN AND METHODS In this target trial emulation, claims data from enrollees in commercial, Medicare Advantage, and traditional Medicare health plans were used to identify adults ≥21 years old with type 2 diabetes, with moderate cardiovascular risk, and without stage 3 or worse chronic kidney disease (CKD) initiating alogliptin, linagliptin, saxagliptin, or sitagliptin between 2014 and 2021. The primary outcome was a composite of incident CKD stages 3–5, kidney failure, or kidney replacement therapy. Random treatment assignment was emulated using propensity scores, estimated using the super learner ensemble method and incorporated as inverse probability of treatment weights into proportional hazards models. RESULTS The weighted study cohort included 3,026 individuals starting alogliptin, 38,213 starting linagliptin, 14,934 starting saxagliptin, and 115,091 starting sitagliptin. One year after treatment initiation, the primary outcome occurred in 1.4%, 2.7%, 2.2%, and 2.4% of patients initiating alogliptin, linagliptin, saxagliptin, and sitagliptin, respectively, increasing to 3.2%, 6.2%, 5.0%, and 5.4%, respectively, at 3 years. Alogliptin was associated with lower risk of stage 3 or worse CKD than linagliptin (hazard ratio [HR] 0.50; 95% CI 0.37–0.69), saxagliptin (HR 0.63; 95% CI 0.45–0.86), and sitagliptin (HR 0.58; 95% CI 0.42–0.79), while saxagliptin was associated with lower risk than linagliptin (HR 0.80; 95% CI 0.73–0.87). Conversely, linagliptin was associated with higher risk than sitagliptin (HR 1.15, 95% CI 1.10–1.21). CONCLUSIONS Alogliptin was associated with lower risk of moderate-to-severe kidney disease than other DPP-4i, while linagliptin was associated with higher risk. Limitations include lack of laboratory data and potential unmeasured confounding.