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Learning from multimodal data sets can leverage complementary information and lead to improved performance for prediction tasks. A commonly used strategy to account for feature correlations in high-dimensional data sets is the latent variable approach. Several latent variable methods have been proposed for multimodal data sets; however, these methods either focus on extracting a shared component across all modalities or extracting a shared component and individual components specific to each modality, overlooking correlations within partial subsets of modalities. We propose multimodal fission learning (MMFL), the first supervised latent variable model that adopts a generalizable decomposition into globally joint, partially joint, and individual components from multimodal data sets. A key strength of MMFL is a natural extension to incorporate incomplete multimodal data in either training and test phases by leveraging the learned modality structure. Through simulation studies, we demonstrate that MMFL outperforms a variety of existing multimodal algorithms under both complete modality and incomplete modality settings. We applied MMFL to two real-world case studies: early prediction of Alzheimer’s disease using neuroimaging and genetic data and predicting posttraumatic headache improvement using clinical data collected via questionnaires and brain neuroimaging data. MMFL achieved improved predictive accuracy and enhanced interpretability offering insights for within- and cross-modal relationships of multimodal data sets. History: Rema Padman served as the senior editor for this article. Funding: This research was supported by the National Institutes of Health [Grants 2R42AG053149-02A1, R01AG069453, 30AG072980, R01AG069453, and 1R61NS113315-01], the National Science Foundation [Grant DMS-2053170], and the Department of Defense [Award W81XWH-19-0534]. The grantee organization is the Northern California Institute for Research and Education. In the past, ADNI has also received funding from the National Institute of Biomedical Imaging and Bioengineering, the Canadian Institutes of Health Research, and private sector contributions through the Foundation for the National Institutes of Health including generous contributions from the following: AbbVie, Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. Data Ethics & Reproducibility Note: The code capsule is available at https://github.com/lingchm/MMFL and in the e-Companion to this article (available at https://doi.org/10.1287/ijds.2024.0059 ).

Abstract Secondary central nervous system (CNS) large B-cell lymphoma (SCNSL) occurs in the de novo setting, as a CNS-isolated relapse, or synchronous (concomitant CNS and systemic) relapse. SCNSL is a devastating event without therapeutic consensus. Thus, we aimed to evaluate treatment outcomes in an international cohort. Progression-free survival (PFS), overall survival (OS), and cumulative incidence of relapse (CIR, estimated using competing-risk models) were reported. Prognostic factors were identified in a 6-month landmark multivariate analysis. Outcomes after thiotepa autologous stem cell transplant (ASCT) and chimeric antigen receptor (CAR) T-cell therapy (CAR-T) delivered at relapse were compared after propensity score matching (PSM). A total of 1139 patients were included in the analysis (de novo: 537; relapsed SCNSL: 602). Two-year PFS estimates were 40.4%, 43.9%, and 16.2% for de novo SCNSL, CNS-isolated relapse, and synchronous relapse, respectively. Patients with CNS-isolated relapse demonstrated low rates of systemic recurrence (24-month CIR, 6%). Thiotepa-ASCT correlated with longer survival in de novo SCNSL (PFS: hazard ratio [HR], 0.57; P = .005; and OS: HR, 0.62; P = .023) and CNS-isolated relapses (PFS: HR, 0.55; P = .002; and OS: HR, 0.39; P< .0001). ASCT (thiotepa or no thiotepa) also associated with improved survival in synchronous relapses (PFS: HR, 0.57; P = .023; and OS: HR, 0.48; P = .019). Higher survival with thiotepa-ASCT than CAR-T was observed after PSM (PFS: HR, 0.45; P = .005 and OS: HR, 0.41; P = .014). These data support thiotepa-ASCT in eligible patients, particularly de novo disease and CNS-isolated relapses. CNS-isolated relapse was infrequently associated with systemic recurrence, supporting treatment regimens adopted from primary CNS lymphoma.

ABSTRACT Lymphocytic colitis (LC) is a subtype of microscopic colitis, often associated with chronic watery diarrhea and characterized by an increase in intraepithelial lymphocytes. Although various medications are implicated in drug-induced LC, its incidence as a treatment-related adverse effect of rearrangement during transfection-selective tyrosine kinase inhibitors is not known. We report a case of pralsetinib-induced LC in a patient with stage 3c nonsmall cell lung cancer. This case highlights pralsetinib-induced LC as a cause of persistent diarrhea that is refractory to standard antidiarrheal treatments and prompts gastrointestinal evaluation and histopathological examination to facilitate early diagnosis and management.

ABSTRACT Gain-of-function mutations in the transient receptor potential 6 (TRPC6) channel have recently been recognized as risk factors for both doxorubicin (DOX)-induced cardiomyopathy. Functional evaluation of TRPC6 missense variants is therefore important for cancer patients undergoing anthracycline treatment. However, traditional electrophysiological methods are labor-intensive and time-consuming. In this study, we compared the functional responses of TRPC6 missense variants to 1-oleoyl-2-acetyl-sn-glycerol (OAG), a TRPC6 agonist, using molecular docking and patch clamp recording techniques. For the wild-type (WT) TRPC6 structure (PDB ID: 6UZ8), OAG exhibited a binding energy of -4.49 kcal/mol and a dissociation constant (Kd) of 0.511 mM. Twenty TRPC6 missense variants were identified from cancer patients in the Mayo Clinic database. Of these, fifteen variants had resolvable structures, nine of which displayed increased Kd values and six decreased Kd values compared to WT in molecular docking analysis. Patch clamp recordings revealed that TRPC6 WT and mutant channels were inactive at baseline but were activated upon 50 μM OAG stimulation, except two loss-of-function variants. Moreover, a 24-h treatment with 0.5 μM DOX significantly enhanced OAG-induced channel activation. All three variants identified in patients with heart failure demonstrated gain-of-function properties in both electrophysiological measurements and in-silico predictions. Importantly, the results obtained from molecular docking and patch clamp recordings were strongly correlated, showing an 82% concordance, higher than the predictions from AlphaMissense. These findings indicate that our computational analysis provides a rapid and reliable method for predicting the functional impact of TRPC6 missense variants, which may aid clinical decision-making in cancer patients receiving chemotherapy.

ABSTRACT Objective To comprehensively evaluate the validity of ICD-10-CM codes for both prevalent diagnoses and less common diseases, and to assess the performance of a large language model (LLM)-based system in validating these codes. Materials and Methods This retrospective study analyzed hospital admissions from the Medical Information Mart for Intensive Care (MIMIC-IV) database. We developed a validated LLM-based system using GPT-4o, refined through iterative prompt engineering, to assess ICD-10-CM code validity. We measured the PPV of ICD-10-CM codes, PPV of principal and secondary diagnoses, and the performance of an LLM-based system in code validation. Results Among 865,079 assigned codes, the PPV was 84.6% (95% CI, 84.5%-84.6%). Principal diagnoses had a PPV of 93.9% (95% CI, 93.7%-94.1%), while secondary diagnoses had a PPV of 83.8% (95% CI, 83.7%-83.9%). The LLM system demonstrated high performance in validating ICD codes, achieving 93.6% accuracy, 95.4% sensitivity and 85.2% specificity. Among correctly assigned secondary diagnoses, the majority (67.9%) represented historical or baseline conditions, while 32.1% reflected active conditions that deviated from baseline status; 22.3% of these emerged after hospital admission. PPV decreases with later diagnosis positions, with the largest decline occurring between principal and secondary diagnoses. Discussion and Conclusion In this large-scale evaluation, ICD-10-CM codes exhibited generally high accuracy, though variability existed by position and condition type. A validated LLM system performed comparably to physician review and offers a scalable means to improve coding accuracy. These findings support the potential for integrating LLM-based auditing into routine workflows to strengthen the quality of administrative and research data.

INTRODUCTION: Evidence on the comparative real-world effectiveness of terlipressin vs midodrine plus octreotide (MO) for hepatorenal syndrome-acute kidney injury (HRS-AKI) in the United Kingdom and the United States is limited. METHODS: Using individual-level chart review data for patients across the United Kingdom (2013–2017) and the United States (2016–2019), an indirect treatment comparison was conducted comparing the efficacy of terlipressin (UK cohort) with MO (US cohort). Covariate balancing propensity scoring matched the cohorts on baseline serum creatinine (SCr), presence of encephalopathy and/or ascites, albumin use and duration, age, and sex. The primary endpoint was HRS reversal, defined as achieving SCr ≤1.5 mg/dL by the last day of treatment. RESULTS: At treatment initiation, 90.2% of UK patients received terlipressin (194/215), while 89.2% of US patients received MO (140/157). Concomitant albumin was administered in 67.9% of UK and 98.7% of US patients. In a covariate balancing propensity score-adjusted cohort, HRS reversal was achieved in 53.2% of terlipressin-treated patients (the United Kingdom, weighted effective sample size of 75) compared with 16.9% of MO-treated patients (the United States, n = 89) (adjusted mean difference (95% CI) 36.3% (22.4, 50.2), P < 0.0001). In adjusted analysis, individuals treated with terlipressin experienced an overall reduction in SCr at completion of treatment (SCr decrease 1.00 mg/dL vs increase of 0.08 mg/dL for MO-treated patients, P < 0.0001). DISCUSSION: HRS-AKI treatment and outcomes differ between the United Kingdom and the United States, attributed to the historical standard of care MO in the United States. In adjusted analyses, real-world use of terlipressin was more effective than MO at improving kidney function and achieving HRS-AKI reversal.