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45 Background: dMMR tumors are characterized by rapid primary tumor growth with reduced likelihood for nodal and distant metastases compared to MMR proficient (pMMR) tumors. Neoadjuvant immune checkpoint inhibitors (ICIs) have demonstrated promising efficacy for localized colon cancer with high pathologic complete response rates and low relapse rates. This raises the question if surgical treatment could be avoided with accurate radiographic staging while avoiding overtreatment of early stage tumors. This study assesses the utility of radiographic staging by CT for dMMR tumors compared to pathologic staging. Methods: Patients with stage I-III colon cancer treated with upfront surgical resection were retrospectively reviewed from a single institution from 2012 to 2023 in two cohorts: 1) dMMR colon cancer and 2) pMMR colon cancer limited to similar sample size as matched controls. Clinical stage was determined based on CT scans prior to surgical resection by 2 independent radiologists blinded to pathologic stage, and the results were correlated to pathologic stage. Clinical characteristics were extracted from the electronic medical record. Statistical analysis was performed using SPSS. Results: We identified 80 patients with dMMR colon cancer and 66 with pMMR tumors. CT clinical tumor staging was discordant from pathologic staging for 68% of dMMR tumors and 61% for pMMR tumors. For T4 dMMR tumors, CT had a 74% sensitivity and 44% specificity. T4 tumors were understaged by radiology to less than T4 for 56% of cases. For dMMR nodal staging, CT had 89% sensitivity and 50% specificity (Table 1). For pathologic node positive tumors, 14% were understaged by radiologist CT read to node negative. For pathologic node negative tumors, 50% of tumors were overstaged to node positive by radiologist CT read. There was poor inter-rater reliability for both T stage and N stage for dMMR and pMMR tumors. The weakest agreement between radiologists was for T stage (dMMR kappa = 0.246, mMMR kappa = 0.145). Conclusions: Radiologic clinical staging of dMMR and pMMR colon cancer does not correlate well with pathologic staging. There were high rates of understaging by CT evaluation for patients who may be candidates for neoadjuvant treatment (T4, N+). Furthermore, there was poor inter-rater reliability between radiologists, indicating that CT staging alone may not be sufficient. Additional diagnostic modalities for nodal detection may be necessary to accurately clinically stage patients before neoadjuvant ICIs in patients with locally advanced disease. Comparing utility of pMMR versus dMMR tumors for T4 and node positive disease. pMMR (n = 66) dMMR (n = 80) T4 versus T3 or less Sensitivity (%) 92 74 Specificity (%) 51 47 PPV (%) 80 77 NPV (%) 82 63 Node positive versus node negative Sensitivity (%) 60 50 Specificity (%) 75 89 PPV (%) 81 89 NPV (%) 53 50 Abbreviations: PPV = positive predictive value; NPV = negative predictive value.

ABSTRACT Background Obesity has been linked to a more severe phenotype in patients with ulcerative colitis (UC). Aim To evaluate the impact of obesity on outcomes of advanced therapies in UC. Methods We conducted a retrospective cohort study utilising the TriNetX database comparing the composite score of corticosteroid use, change in advanced therapy or colectomy within two years between two cohorts of patients with UC—those with obesity (BMI ≥ 30 kg/m 2 ) and those without (BMI 18.5–24.9). The risk assessment was stratified to specific advanced therapies, including tumour necrosis factor α inhibitors (TNFi), vedolizumab, ustekinumab and Janus kinase inhibitors (JAKi). We performed 1:1 propensity score matching (PSM) for demographics, co‐morbid conditions, laboratory values and IBD medications including corticosteroids. Results There were 3904, 2025, 1150 and 477 patients on TNFi, vedolizumab, ustekinumab and JAKi, respectively, in the UC obesity cohort. After PSM, the UC obesity cohort was at an increased risk of the composite outcome of corticosteroid use, change in therapy and colectomy compared to the UC control cohort in patients on TNFi (aHR 1.37, 95% CI 1.29–1.49), vedolizumab (aHR 1.29, 95% CI 1.16–1.43), ustekinumab (aHR 1.1.26, 95% CI 1.10–1.44) and JAKi (aHR 1.38, 95% CI 1.13–1.69). Sub‐group analysis based on the specific TNFi also showed an increased risk of composite outcome for infliximab (aHR 1.36, 95% CI 1.22–1.52) and adalimumab (aHR 1.26, 95% CI 1.11–1.42) within 2 years. Conclusions Obesity is associated with lower efficacy of several advanced therapies in patients with UC.

Introduction/Purpose The multicenter, prospective, single‐arm, controlled, non‐randomized SCENT trial on flow diverter (FD) treatment for intracranial aneurysms (IA) was analyzed for patients’ age and IA characteristics impacting stroke and occlusion rates over 5 years. Materials and Methods Impact on major ipsilateral stroke and IA occlusion was studied by stratifying age as </= 65 years versus >65 years. Twice as many subjects treated were </= 65 years old (n=119/180). Product‐limit (Kaplan‐Meier) estimates of time to both endpoints, stratified by age group, were created. Univariate predictors of time to stroke were identified by including candidate variables in univariable proportional hazards regression models. Those variables found to be significant (p<0.10) at the univariate level were entered into a multivariable survival model to identify independent predictors. The stepwise selection produced a final reduced model with a significance level to both enter and stay set at 0.05. Results When parent artery stenosis and IA size were entered into a multiple‐stepwise survival model, only stenosis remained as an independently significant predictor of time to stroke. At 3‐year follow‐up, there were a total of 23 strokes (12.8%), with 11 (47.8%) occurring in subjects </= 65 years; there was a greater risk for seniors (HR1.96, 95% CI 0.83‐4.78, p=.122). Four patients (4/180; 2.2%) experienced aneurysm ruptured within the first week post‐treatment, with 3 being </= 65 and the fourth aged 66 years. No new strokes were reported between 3 and 5 years. Complete IA occlusion rates for seniors were 60.0% (33/55), 67.6% (25/37), and 85.7% (18/21) at 12, 36, and 60 months, respectively, as compared to 79.1% (87/110), 82.5% (66/80), and 91.8% (56/61) for younger subjects. The time to complete IA occlusion was shorter in younger patients (HR1.53, 95% CI 1.07‐2.19, p=.020). Five subjects (2.8%) underwent retreatment, 2 in 60‐year‐old patients, and one each aged 64, 70, and 75. Conclusion Stroke, early rupture risk, and aneurysm occlusion in patients treated with FD are related to age and pre‐existing parent artery stenosis, IA size, and location. With demographic shifts, future treatments need to focus on expedited and improved healing.

Abstract Although social determinants of health (SDoH) investigations have shown limited analyses of socioeconomic and race-ethnic status on certain hematologic malignancies, the impact of factors beyond those across a fuller scope of hematologic cancers remains unknown. The Social Vulnerability Index (SVI), a tool for assessing varied US census–derived sociodemographic factors, allows for the specific quantification of SDoH in dynamic, regional contexts for their associations with hematologic malignancy inequities. To assess the summative influence of varied SDoH factors on hematologic malignancy outcomes and discern which SDoH factors contributed the largest associations toward disparities, 796 005 adults with hematologic malignancies between 1975 to 2017 were identified for this retrospective cohort study. Vulnerability in 15 SDoH factors was measured using composite and subcategory SVI scores geographically matched to patients. Regressions between SVI factors and follow-up time after diagnosis and survival period were performed. Increasing overall SVI correlated with significantly decreased surveillance period in 11 of 14 hematologic malignancies, with decreases upward of 33.4% (39.0-26.0 months for acute lymphocytic leukemia). Increasing SVI significantly associated with decreased survival period across 11 of 14 hematologic malignancies, with decreases upward of 47.2% (89.5-47.3 months for Hodgkin lymphoma). Socioeconomic status and housing and transportation vulnerabilities showed the largest magnitude of contributions, followed by minority language and household composition. Significant decreases in hematologic malignancy prognosis associate with increasing overall SDoH vulnerability in varied sociodemographic contexts in the United States. Furthermore, there are quantifiable differences in which types of SDoH contribute more to trends per malignancy type. These findings demonstrate specific SDoH targets for further research and policy initiatives to combat hematologic malignancy disparity more effectively.

ABSTRACTBackground and AimsChronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is difficult to distinguish from mimicking disorders, with misdiagnosis resulting in IVIG overutilization. We evaluate a clinical‐electrophysiological model to facilitate CIDP versus mimic neuropathy prediction.MethodsUsing the European Academy of Neurology/Peripheral Nerve Society (EAN/PNS) 2021 CIDP guidelines we derived 26 clinical and 144 nerve conduction variables. The model was generated and validated utilizing total CIDP (n = 129) and mimics (n = 309); including (1) IgG4‐nodopathies; (2) POEMS (polyneuropathy–organomegaly–endocrinopathy–monoclonal protein‐skin changes); (3) anti‐myelin‐associated‐glycoprotein; (4) paraneoplastic; (5) Waldenström B‐cell lymphoma; (6) diabetic neuropathies; (7) amyloidosis; (8) Charcot–Marie–Tooth; (9) motor neuropathies/neuronopathies; and (10) idiopathic‐inflammatory‐myopathies.ResultsWe analyzed 9282 clinical and 51 408 electrophysiological data points. Univariate analysis identified 11 of 26 clinical variables with significant odds ratios. A multivariate regression model using four clinical and two electrophysiologic variables achieved 93% area‐under‐curve (95% CI 91–95): progression over 8 weeks (OR 40.66, 95% CI 5.31–311.36), absent autonomic involvement (OR 17.82, 95% CI 2.93–108.24), absent muscle atrophy (OR 16.65, 95% CI 3.27–84.73), proximal weakness (OR 3.63, 95% CI 1.58–8.33), ulnar motor conduction velocity slowing < 35.7 m/s (OR 5.21, 95% CI 2.13–12.76), and ulnar motor conduction block (OR 13.37, 95% CI 2.47–72.40). A web‐based probability calculator (https://news.mayocliniclabs.com/cidp‐calculator/) was developed, with 100% sensitivity and 68% specificity at a 92% probability threshold. Specificity improved to 93% when considering “red flags,” electrophysiologic criteria, and laboratory testing.InterpretationA probability calculator using clinical electrophysiological variables assists CIDP differentiation from mimics, with scores below 92% unlikely to have CIDP. The highest specificity is achieved by considering clinical “red flags,” electrophysiologic demyelination, and laboratory testing.

DEK::AFF2 fusion nonkeratinizing squamous cell carcinoma (NKSCC) is an emerging entity in the sinonasal tract, temporal bone, and skull base. However, the clinical behavior of these tumors has not been well studied. Here, we report the largest cohort of DEK::AFF2 carcinomas to determine if morphology, mitotic rate, and/or Ki-67 IHC are associated with patient outcomes, including a comparison with high-risk human papillomavirus (HPV)-associated and independent patients. We solicited cases of molecularly or AFF2 immunohistochemistry (IHC) proven DEK::AFF2 SCC from surgical pathologists to collect patient demographic, clinical, and outcome data. Using representative H&E slides, we characterized the morphology and counted mitoses. Ki-67 immunohistochemistry was performed. We also compared the DEK::AFF2 survival rates to those in a cohort of AFF2 IHC-negative HPV-associated and HPV-independent SCC. DEK::AFF2 carcinomas most commonly arose in the nasal cavity (13/30, 43%), and the average number of recurrences was 1.8 (range: 0 to 10). At the last follow-up, most patients were disease free (19/30, 63%) or were alive with disease (9/30, 30%). There was an average mitotic rate of 2 per 2 mm2 (range: 0 to 9) and Ki-67 proliferation rate of 26% (range: 3% to 60%). Local recurrence was common, but morphology, mitotic activity, and Ki-67 index were not associated with recurrence or survival. On Kaplan-Meier survival analysis, DEK::AFF2 patients had lower disease-free survival but otherwise had similar outcomes to conventional SCC patients. Our multi-institutional study shows that local recurrence is common in DEK::AFF2 fusion nonkeratinizing SCC patients, but patients have survival rates similar to conventional SCC. Despite showing a range of different features and proliferation rates, traditional grading by morphology, mitotic rate, and/or Ki-67 activity does not seem to be predictive of outcome.

Abstract Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significance Integration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.

Abstract Biomarkers that aid in early detection of neurodegeneration are needed to enable early symptomatic treatment and enable identification of people who may benefit from neuroprotective interventions. Increasing evidence suggests that sleep biomarkers may be useful, given the bi-directional relationship between sleep and neurodegeneration and the prominence of sleep disturbances and altered sleep architectural characteristics in several neurodegenerative disorders. This study aimed to demonstrate that sleep can accurately characterize specific neurodegenerative disorders (NDD). A four-class machine-learning algorithm was trained using age and nine sleep biomarkers from patients with clinically-diagnosed manifest and prodromal NDDs, including Alzheimer’s disease dementia (AD = 27), Lewy body dementia (LBD = 18), and isolated REM sleep behavior disorder (iRBD = 15), as well as a control group (CG = 58). The algorithm was validated in a total of 381 recordings, which included the training data set plus an additional AD = 10, iRBD = 18, Parkinson disease without dementia (PD = 29), mild cognitive impairment (MCI = 78) and CG = 128. Test-retest consistency was then assessed in LBD = 10, AD = 9, and CG = 46. The agreement between the NDD profiles and their respective clinical diagnoses exceeded 75% for the AD, LBD, and CG, and improved when NDD participants classified Likely Normal with NDD indications consistent with their clinical diagnosis were considered. Profiles for iRBD, PD and MCI participants were consistent with the heterogeneity of disease severities, with the majority of overt disagreements explained by normal sleep characterization in 27% of iRBD, 21% of PD, and 26% of MCI participants. For test-retest assignments, the same or similar NDD profiles were obtained for 88% of LBD, 86% in AD, and 98% of CG participants. The potential utility for NDD subtyping based on sleep biomarkers demonstrates promise and requires further prospective development and validation in larger NDD cohorts.