Tobin, W. Oliver

ABSTRACTIntroduction/AimsHealthcare utilization and costs in myotonic dystrophy (DM) are not well understood. This study describes the burden of DM and its associated costs.MethodsWe performed a retrospective study using data from a large U.S. administrative claims database to identify commercially insured individuals with DM and compared healthcare utilization and cost with a matched cohort. Analyses were performed between the cohorts with ≥ 3 years of insured follow‐up.ResultsWe identified 1182 DM individuals with coverage at least 3 year prior and 3 years following an index DM diagnosis from January 1, 2009 to December 31, 2018. Compared to controls, DM individuals were 3.7 times more likely to be hospitalized (p < 0.0001), 2.4 times more likely to visit an emergency department (p < 0.0001), and had twice as many outpatient visits (p < 0.0001) in the first year post‐diagnosis, with similar utilization at 2‐ and 3‐years post‐diagnosis. Annual mean costs were 3.9 times higher for health plan paid costs (p < 0.0001) and 2.6 times higher for patient‐paid costs (p < 0.0001) for DM individuals than controls in the first year post‐diagnosis, with similar costs at 2‐ and 3‐years post‐diagnosis. Factors associated with higher costs included the need for durable medical equipment, including gait aids or respiratory support devices.DiscussionIndividuals with DM experience significantly higher healthcare utilization and associated healthcare costs than controls of similar age, sex, race, and census region. The findings show the high clinical and economic burden of DM, highlighting the importance of improving cost‐effective care delivery in this population.

Background: Erdheim-Chester disease (ECD) manifests as multi-organ infiltration of clonal histiocytes with mutations primarily in the mitogen-activated protein kinase (MAPK) pathway. The revised classification of histiocytosis (2016) categorizes ECD with typical bilateral, symmetric osteosclerosis of the lower extremity long bones as classical (C) and as non-classical (NC) if otherwise. The clinical and biological significance of this classification is unclear. This study compared the clinical and genotypic findings of the 2 subtypes within a large cohort of ECD patients. Methods: We included patients seen at our institution since 1990 meeting the following criteria: A) had an ECD diagnosis based on the revised criteria by Haroche J, et al. (Blood 2020;135:1311-1318); B) completed whole-body imaging studies including long bones of the legs. Classification as C-ECD required symmetric osteosclerosis of the distal femur and/or proximal tibia/fibula. Results: A total of 145 patients were enrolled, comprising a male-to-female ratio of 2:1 (66.2% male). C-ECD was diagnosed in 77.2% of cases, and NC-ECD in 22.8%. The median age at diagnosis was similar with 58.5 years (range, 18-82) in C-ECD and 55 years (range, 20-81) in NC-ECD, (p=0.65). The most frequently affected systems included skeletal (81.4%), renal (60.0%), vascular (45.5%), cardiac (40.0%), central nervous (38.6%), sinus (37.2%), pulmonary (36.6%), and adrenal (32.4%). The numbers of organs involved were significantly higher in C-ECD compared to NC-ECD (median 5 vs 3, p&lt;0.01). Higher rates of skeletal (100% vs. 18.2%, p&lt;0.01), adrenal gland (37.5% vs. 15.2%, p=0.02), and sinus (44.6% vs. 12.1%, p&lt;0.01) involvement were observed in C-ECD. Arginine vasopressin deficiency (AVP-D) was exclusively observed in C-ECD (20.7% vs. 0%, p&lt;0.01). NC-ECD had a higher rate of cardiac involvement (69.7% vs. 31.3%, p&lt;0.01). No significant differences were found in other systems. The overall median time between onset of the first symptoms/signs to diagnosis was 15 months with no significant difference between C-ECD and NC-ECD (17.5 vs. 12 months, p=0.18). The median time to diagnosis of ECD in patients with AVP-D was 38.5 months, compared to 12 months without AVP-D (p=0.09). Genetic testing was conducted in 86.2% of patients and B-Raf proto-oncogene (BRAF) alterations were identified in 59.2% of the tested cases. BRAFV600E was more prevalent in C-ECD (61.3% vs. 21.9%, p&lt;0.01), whereas non-V600 mutations were more commonly found in NC-ECD (12.5% vs. 1.1%, p&lt;0.01). There was no significant difference in the frequency of BRAF fusions. NC-ECD patients exhibited a higher rate of MAP2K1 mutations (25.0% vs. 5.4%, p&lt;0.01). Other frequently mutated genes included KRAS (4.0%), NRAS (2.4%), and CSF1R (2.4%), although no significant difference was observed in their frequency between C-ECD and NC-ECD. Testicular involvement appeared to be more common in patients with MAP2K1 mutations (23.1% vs. 8%, p=0.08). Two patients with pathogenic CSF1R mutations both had central nervous system (CNS) involvement. Among C-ECD patients, BRAFV600E conferred a higher rate of CNS involvement (50.9% vs. 25%, p=0.01). No significant difference was observed in NC-ECD patients (71.4% vs 36%, p=0.09). Among NC-ECD cases, MAP2K1 mutations conferred a reduced risk of cardiac involvement (37.5% vs. 79.2%, p=0.03) and no such difference was observed in patients with C-ECD (40% vs 34.1%, p=0.79). The median numbers of organs involved in patients with BRAF, MAP2K1, and KRAS/NRAS mutations were 5, 3, and 3, respectively, with no significant difference. Conclusions: C-ECD affects more organs and more frequently involves bones, adrenal glands, and sinuses. AVP-D was exclusively observed in C-ECD. Conversely, NC-ECD showed a higher prevalence of cardiac involvement. BRAFV600E was more commonly identified in C-ECD, whereas non-V600 mutations and MAP2K1 mutations were more prevalent in NC-ECD. Among C-ECD patients, BRAFV600E was correlated with a greater likelihood of CNS involvement. Conversely, NC-ECD patients with MAP2K1 mutations had a reduced risk of cardiac involvement. This study highlights the distinct clinical and molecular features of C-ECD and NC-ECD, underscoring the importance of subclassifying ECD into classical and non-classical forms. Further studies are needed to explore differences in the clinical outcomes between the 2 forms.

Rosai–Dorfman Disease (RDD), also known as sinus histiocytosis with massive lymphadenopathy, is a rare non-Langerhans cell histiocytic neoplasm. Although the disease classically presents as massive painless lymphadenopathy in young adults, RDD can also involve the central nervous system in some patients. CNS lesions, can cause headaches, neurologic deficits, and even neurologic deficits. The imaging appearance of CNS RDD typically mimics that of meningiomas: well-circumscribed dural-based lesions that often have dural tails. However, some imaging clues also exist that might help a radiologist recognize RDD, even before histopathologic confirmation. This radiology-pathology report of a patient with CNS RDD highlights the most pertinent clinical, imaging, and pathologic features of CNS RDD, and discusses what the neuroradiologist needs to know about the disease.

Abstract Clinical management of IDH wildtype glioblastoma (GBM) and tumefactive multiple sclerosis (tMS) is drastically different. GBM requires maximal safe resection followed by chemoradiation, while tMS outcome is worsened by surgery and radiotherapy. Noninvasive methods are needed to help with accurate diagnosis of tumor and non-tumor etiologies. To develop an MRI-based classification model, tMS subjects diagnosed prior to January 1, 2020, were matched to tMS by age at diagnosis, sex, index MRI date, and 2D/3D acquisition. Inclusion criteria included one cm minimal lesion size and pre-operative post-contrast T1 and T2 images available for analysis. A 3D-DenseNet121 was used to develop a classification model using prespecified parameters: 650 epochs, batch size 16, learning rate 10-3, cross-entropy loss, and AdamW optimizer. The stopping rule was defined as three sequential differences in epoch cross-entropy loss &lt;0.02. Models were developed using both T1gd and T2, as well as from only T1gd and only T2. Training included 220 subjects (110 GBM, 110 tMS). A 2-stage validation design was used, which included both retrospective and prospective cohorts. Stage 1 consisted of 272 retrospective GBM (diagnosed prior to January 1, 2020). Stage 2 consisted of 69 and 34 prospective (diagnosed after January 1, 2020) GBM and tMS, respectively. External validation on the 272 retrospective GBM demonstrated accuracy of 91%, 84%, and 78% for T1gd+T2, T1gd only, and T2 only, respectively. External validation on the 69 prospective GBM demonstrated an accuracy of 87%, 64%, and 67% for T1gd+T2, T1gd only, and T2 only, respectively. The 34 prospective tMS demonstrated accuracy of 76%, 76%, and 82% for T1gd+T2, T1gd only, and T2 only, respectively. This shows the feasibility of deep learning to aid in differential diagnosis of brain lesions. Future work entails the integration of germline variants into the classification model, including variants associated with the risk of glioma or MS.

Abstract Acquired tumor alterations are part of the WHO diagnosis of glioma. However, germline predisposition to these alterations is unknown. GWAS in European and Asian populations identified germline variants in 30 regions, many in or near genes that also acquire alterations, suggesting that interactions between inherited and acquired genetics are involved in glioma development. To evaluate such interactions, we used 3686 glioma cases and 1889 controls. A case-control design and multinomial logistic regression were used to identify germline variants associated with development of TERT-promoter mutant gliomas, generating two interesting observations. First, TERT germline variants were associated with predisposition to IDHwt glioma that have a TERT promoter mutation, but not with IDH-mutant codeleted gliomas that have a TERT promoter mutation. Second, two novel regions were observed in this more homogeneous subgroup of TERT mutated tumors: variants in TXNDC11 (OR=2.66, p=5.7x10-8) and RUVBL2 (OR=3.1, p=5.8x10-8). High tumor expression of TXNDC11 is associated with poor prognosis in glioma and RUVBL2 interacts with TERT to affect telomerase activity. Similar analyses are being performed on additional clinically relevant acquired alterations. In parallel, case-case GWAS analyses were performed to evaluate germline variants associated with other tumor alterations. Comparing IDH-mutant versus IDHwt stratified by rs55705857 genotype, the most significant variants were PHLDB1 (p=1.2x10-13) and D2HGDH (p=2.1x10-10), highlighting the importance of these two variants independent of CCDC26 for the development of IDH-mutant glioma. As a parallel approach, we utilized recursive partitioning and regression trees (rpart) to classify IDH mutation status using the 30 known variants. The top four branches of the regression tree included CCDC26, D2HGDH, PHLDB1, and MAML2, as well as two Asian variants (RAB27A, CYP4F12). This highlights the importance of utilizing variants discovered in non-European populations in analyses. Overall, understanding these interactions are necessary to develop therapeutics, stratify clinical trials, and to develop relevant tumor models.

AbstractBackgroundCrystal‐storing histiocytosis (CSH) is a rare form of histiocytosis with intralysosomal accumulations of immunoglobulins or paraproteins that aggregate as crystals. Central nervous system (CNS) involvement of CSH is uncommon but should be considered in cases of persistent parenchymal enhancement on neuroimaging.MethodsWe describe one local case of CNS CSH and 10 additional cases identified by literature review.ResultsAmong 11 CSH patients, lesions involved either the dura (2/11) or brain parenchyma (9/11). Two cases had leptomeningeal enhancement. One case had spinal cord involvement. Two cases were associated with marginal zone lymphoma; one case was associated with an immunoglobulin A‐plasma cell dyscrasia. Eight of 11 cases had outcome data available: 7/8 cases had clinical and/or radiological improvement and 1/8 had radiological stability.ConclusionsCentral nervous system involvement of CSH is rare. Potential cases should be comprehensively evaluated for lymphoma or myeloma with positron emission tomography/computed tomography (CT) of the body or alternatively, CT of the chest, abdomen, pelvis and nuclear bone scan, bone marrow biopsy, serum protein electrophoresis, and cerebrospinal fluid protein electrophoresis. Treatment is targeted toward the underlying malignancy.

ObjectiveTo evaluate the cerebrospinal fluid (CSF) cytokine/chemokine profile of central nervous system (CNS) neurosarcoidosis (NS), and its utility in differential diagnosis, treatment, and prognostication.MethodsIn this case–control study, we validated 17 cytokines/chemokines (interleukin [IL]‐1‐beta, IL‐2, IL‐4, IL‐5, IL‐6, IL‐10, IL‐12p70, IL‐13, IL‐17A, BAFF, IL‐8/CXCL8, CXCL9, CXCL10, CXCL13, GM‐CSF, interferon‐gamma, and tumor necrosis factor [TNF]‐alpha) in a multiplexed automated immunoassay system (ELLA; Bio‐Techne, Minneapolis, MN, USA), and assessed them in CSF and serum of symptomatic patients with probable or definite CNS NS (01/2011–02/2023) with gadolinium enhancement and/or CSF pleocytosis. Patients with multiple sclerosis, primary CNS lymphoma, aquaporin‐4 immunoglobulin G positivity, non‐inflammatory disorders, and healthy individuals were used as controls.ResultsA total of 32 NS patients (59% women; median age, 59 years [19–81]) were included; concurrent sera were available in 12. CSF controls consisted of 26 multiple sclerosis, 8 primary CNS lymphoma, 84 aquaporin‐4 immunoglobulin G positive, and 34 patients with non‐inflammatory disorders. Gadolinium enhancement was present in 31 of 32 NS patients, and CSF pleocytosis in 27 of 32 (84%). CSF IL‐2, IL‐6, IL‐10, IL‐13, BAFF, IL‐8/CXCL8, CXCL9, CXCL10, CXCL13, GM‐CSF, interferon‐gamma, and TNF‐alpha levels were significantly higher in NS patients compared with non‐inflammatory controls (p ≤ 0.02); elevations were more common in CSF than serum. Concurrent elevation of IL‐6, CXCL9, CXCL10, GM‐CSF, interferon‐gamma, and TNF‐alpha was present in 18 of 32 NS patients, but only in 1 control. Elevated IL‐6, IL‐10, IL‐13, CXCL9, CXL10, GM‐CSF, and TNF‐alpha associated with measures of disease activity.InterpretationNS CSF cytokine/chemokine profiles suggest T cell (mainly T helper cell type 1), macrophage, and B‐cell involvement. These signatures aid in NS diagnosis, indicate disease activity, and suggest therapeutic avenues. ANN NEUROL 2024;96:704–714