Leveraging GPT-4 for identifying cancer phenotypes in electronic health records: a performance comparison between GPT-4, GPT-3.5-turbo, Flan-T5, Llama-3-8B, and spaCy's rule-based and machine learning-based methods.

Objective: Accurately identifying clinical phenotypes from Electronic Health Records (EHRs) provides additional insights into patients' health, especially when such information is unavailable in structured data. This study evaluates the application of OpenAI's Generative Pre-trained Transformer (GPT)-4 model to identify clinical phenotypes from EHR text in non-small cell lung cancer (NSCLC) patients. The goal was to identify disease stages, treatments and progression utilizing GPT-4, and compare its performance against GPT-3.5-turbo, Flan-T5-xl, Flan-T5-xxl, Llama-3-8B, and 2 rule-based and machine learning-based methods, namely, scispaCy and medspaCy. Materials and Methods: Phenotypes such as initial cancer stage, initial treatment, evidence of cancer recurrence, and affected organs during recurrence were identified from 13 646 clinical notes for 63 NSCLC patients from Washington University in St. Louis, Missouri. The performance of the GPT-4 model is evaluated against GPT-3.5-turbo, Flan-T5-xxl, Flan-T5-xl, Llama-3-8B, medspaCy, and scispaCy by comparing precision, recall, and micro-F1 scores. Results: GPT-4 achieved higher F1 score, precision, and recall compared to Flan-T5-xl, Flan-T5-xxl, Llama-3-8B, medspaCy, and scispaCy's models. GPT-3.5-turbo performed similarly to that of GPT-4. GPT, Flan-T5, and Llama models were not constrained by explicit rule requirements for contextual pattern recognition. spaCy models relied on predefined patterns, leading to their suboptimal performance. Discussion and Conclusion: GPT-4 improves clinical phenotype identification due to its robust pre-training and remarkable pattern recognition capability on the embedded tokens. It demonstrates data-driven effectiveness even with limited context in the input. While rule-based models remain useful for some tasks, GPT models offer improved contextual understanding of the text, and robust clinical phenotype extraction.

Epigenetic induction of cancer testis antigens and endogenous retroviruses at single-cell level enhances immune recognition and response in glioma.

Glioblastoma (GBM) is the most common malignant primary brain tumor and remains incurable. Previous work has shown that systemic administration of Decitabine (DAC) induces sufficient expression of cancer-testis antigens (CTA) in GBM for targeting by adoptive T-cell therapy in vivo. However, the mechanisms by which DAC enhances immunogenicity in GBM remain to be elucidated. Using NY-ESO-1 as a representative inducible CTA, we demonstrate in patient tissue, immortalized glioma cells, and primary patient-derived gliomaspheres that basal CTA expression is restricted by promoter hypermethylation in gliomas. DAC treatment of glioma cells specifically inhibits DNA methylation silencing to render NY-ESO-1 and other CTA into inducible tumor antigens at single cell resolution. Functionally, NY-ESO-1 TCR engineered effector cell targeting of DAC-induced antigen in primary glioma cells promotes specific and polyfunctional T cell cytokine profiles. In addition to induction of CTA, DAC concomitantly reactivates tumor-intrinsic human endogenous retroviruses, interferon response signatures, and MHC-I. Overall, we demonstrate that DAC induces targetable tumor antigen and enhances T cell functionality against GBM, ultimately contributing to the improvement of targeted immune therapies in glioma.

Cannabis, Tobacco Use, and COVID-19 Outcomes.

Importance: It is unclear whether cannabis use is associated with adverse health outcomes in patients with COVID-19 when accounting for known risk factors, including tobacco use. Objective: To examine whether cannabis and tobacco use are associated with adverse health outcomes from COVID-19 in the context of other known risk factors. Design, Setting, and Participants: This retrospective cohort study used electronic health record data from February 1, 2020, to January 31, 2022. This study included patients who were identified as having COVID-19 during at least 1 medical visit at a large academic medical center in the Midwest US. Exposures: Current cannabis use and tobacco smoking, as documented in the medical encounter. Main Outcomes and Measures: Health outcomes of hospitalization, intensive care unit (ICU) admission, and all-cause mortality following COVID-19 infection. The association between substance use (cannabis and tobacco) and these COVID-19 outcomes was assessed using multivariable modeling. Results: A total of 72 501 patients with COVID-19 were included (mean [SD] age, 48.9 [19.3] years; 43 315 [59.7%] female; 9710 [13.4%] had current smoking; 17 654 [24.4%] had former smoking; and 7060 [9.7%] had current use of cannabis). Current tobacco smoking was significantly associated with increased risk of hospitalization (odds ratio [OR], 1.72; 95% CI, 1.62-1.82; P < .001), ICU admission (OR, 1.22; 95% CI, 1.10-1.34; P < .001), and all-cause mortality (OR, 1.37, 95% CI, 1.20-1.57; P < .001) after adjusting for other factors. Cannabis use was significantly associated with increased risk of hospitalization (OR, 1.80; 95% CI, 1.68-1.93; P < .001) and ICU admission (OR, 1.27; 95% CI, 1.14-1.41; P < .001) but not with all-cause mortality (OR, 0.97; 95% CI, 0.82-1.14, P = .69) after adjusting for tobacco smoking, vaccination, comorbidity, diagnosis date, and demographic factors. Conclusions and Relevance: The findings of this cohort study suggest that cannabis use may be an independent risk factor for COVID-19-related complications, even after considering cigarette smoking, vaccination status, comorbidities, and other risk factors.

Digital "flipbooks" for enhanced visual assessment of simple and complex brain tumors.

Typical longitudinal radiographic assessment of brain tumors relies on side-by-side qualitative visualization of serial magnetic resonance images (MRIs) aided by quantitative measurements of tumor size. However, when assessing slowly-growing tumors and/or complex tumors, side-by-side visualization and quantification may be difficult or unreliable. Whole-brain, patient-specific "digital flipbooks" of longitudinal scans are a potential method to augment radiographic side-by-side reads in clinical settings by enhancing the visual perception of changes in tumor size, mass effect, and infiltration across multiple slices over time. In this approach, co-registered, consecutive MRI scans are displayed in a slide deck, where one slide displays multiple brain slices of a single timepoint in an array (e.g. 3x5 "mosaic" view of slices). The flipbooks are viewed similar to an animated flipbook of cartoons/photos so that subtle radiographic changes are visualized via perceived motion when scrolling through the slides. Importantly, flipbooks can be created easily with free, open-source software. This article describes the step-by-step methodology for creating flipbooks and discusses clinical scenarios for which flipbooks are particularly useful. Example flipbooks are provided in the Online Supplemental Material.

Pseudo-Resting-State Functional MRI Derived from Dynamic Susceptibility Contrast Perfusion MRI Can Predict Cognitive Impairment in Glioma.

BACKGROUND AND PURPOSE: Resting-state functional MRI (rs-fMRI) can be used to estimate functional connectivity (FC) between different brain regions, which may be of value for identifying cognitive impairment in patients with brain tumors. Unfortunately, neither rs-fMRI nor neurocognitive assessments are routinely assessed clinically, mostly due to limitations in examination time and cost. Since DSC perfusion MRI is often used clinically to assess tumor vascularity and similarly uses a gradient-echo-EPI sequence for T2*-sensitivity, we theorized a "pseudo-rs-fMRI" signal could be derived from DSC perfusion to simultaneously quantify FC and perfusion metrics, and these metrics can be used to estimate cognitive impairment in patients with brain tumors. MATERIALS AND METHODS: Twenty-four consecutive patients with gliomas were enrolled in a prospective study that included DSC perfusion MRI, resting-sate functional MRI (rs-fMRI), and neurocognitive assessment. Voxelwise modeling of contrast bolus dynamics during DSC acquisition was performed and then subtracted from the original signal to generate a residual "pseudo-rs-fMRI" signal. Following the preprocessing of pseudo-rs-fMRI, full rs-fMRI, and a truncated version of the full rs-fMRI (first 100 timepoints) data, the default mode, motor, and language network maps were generated with atlas-based ROIs, Dice scores were calculated for the resting-state network maps from pseudo-rs-fMRI and truncated rs-fMRI using the full rs-fMRI maps as reference. Seed-to-voxel and ROI-to-ROI analyses were performed to assess FC differences between cognitively impaired and nonimpaired patients. RESULTS: Dice scores for the group-level and patient-level (mean±SD) default mode, motor, and language network maps using pseudo-rs-fMRI were 0.905/0.689 ± 0.118 (group/patient), 0.973/0.730 ± 0.124, and 0.935/0.665 ± 0.142, respectively. There was no significant difference in Dice scores between pseudo-rs-fMRI and the truncated rs-fMRI default mode (P = .97) or language networks (P = .30), but there was a difference in motor networks (P = .02). A multiple logistic regression classifier applied to ROI-to-ROI FC networks using pseudo-rs-fMRI could identify cognitively impaired patients (sensitivity = 84.6%, specificity = 63.6%, receiver operating characteristic area under the curve (AUC) = 0.7762 ± 0.0954 (standard error), P = .0221) and performance was not significantly different from full rs-fMRI predictions (AUC = 0.8881 ± 0.0733 (standard error), P = .0013, P = .29 compared with pseudo-rs-fMRI). CONCLUSIONS: DSC perfusion MRI-derived pseudo-rs-fMRI data can be used to perform typical rs-fMRI FC analyses that may identify cognitive decline in patients with brain tumors while still simultaneously performing perfusion analyses.

Safety and Efficacy of Wharton's Jelly Connective Tissue Allograft for Rotator Cuff Tears: Findings from a Retrospective Observational Study.

With the increasing occurrence of rotator cuff injuries every year, there is a great need for a reliable treatment option. Wharton's Jelly contains several components that can positively impact the replacement and repair of musculoskeletal defects. The overall objective of this study is to evaluate the improvement of patient-reported pain scales after applying Wharton's Jelly (WJ) in rotator cuff defects. Eighty-seven patients with rotator cuff defects who failed at least eight weeks of conservative treatment were selected from the retrospective repository. A total of 2 cc of WJ flowable allograft was applied to the specific affected anatomy, the most common being supraspinatus tendon, biceps tendon insertion, labral tear, and subscapularis tear. No adverse reactions were reported. Statistically significant improvements were found from the initial to Day 90 in all scales. Patient satisfaction was calculated using minimal clinically important differences. No statistically significant differences were found in mean changes between gender, BMI, and age. Scanning electron microscopy images reveal the similarities between the collagen matrix in WJ and the rotator cuff. The significant improvement in patient outcomes coincides with the current literature analyzing WJ applications with other structural defects around the body. WJ is a promising alternative for musculoskeletal defects when the standard of care fails.

Low- and High-Grade Glioma-Associated Vascular Cells Differentially Regulate Tumor Growth.

A key feature distinguishing high-grade glioma (HG) from low-grade glioma (LG) is the extensive neovascularization and endothelial hyperproliferation. Prior work has shown that tumor-associated vasculature from HG is molecularly and functionally distinct from normal brain vasculature and expresses higher levels of protumorigenic factors that promote glioma growth and progression. However, it remains unclear whether vessels from LG also express protumorigenic factors, and to what extent they functionally contribute to glioma growth. Here, we profile the transcriptomes of glioma-associated vascular cells (GVC) from IDH-mutant (mIDH) LG and IDH-wild-type (wIDH) HG and show that they exhibit significant molecular and functional differences. LG-GVC show enrichment of extracellular matrix-related gene sets and sensitivity to antiangiogenic drugs, whereas HG-GVC display an increase in immune response-related gene sets and antiangiogenic resistance. Strikingly, conditioned media from LG-GVC inhibits the growth of wIDH glioblastoma cells, whereas HG-GVC promotes growth. In vivo cotransplantation of LG-GVC with tumor cells reduces growth, whereas HG-GVC enhances tumor growth in orthotopic xenografts. We identify ASPORIN (ASPN), a small leucine-rich repeat proteoglycan, highly enriched in LG-GVC as a growth suppressor of wIDH glioblastoma cells in vitro and in vivo. Together, these findings indicate that GVC from LG and HG are molecularly and functionally distinct and differentially regulate tumor growth. Implications: This study demonstrated that vascular cells from IDH-mutant LG and IDH-wild-type HG exhibit distinct molecular signatures and have differential effects on tumor growth via regulation of ASPN-TGFß1-GPM6A signaling.

D-2-HG Inhibits IDH1mut Glioma Growth via FTO Inhibition and Resultant m6A Hypermethylation.

IDH1mut gliomas produce high levels of D-2-hydroxyglutarate (D-2-HG), an oncometabolite capable of inhibiting α-ketoglutarate-dependent dioxygenases critical to a range of cellular functions involved in gliomagenesis. IDH1mut gliomas also exhibit slower growth rates and improved treatment sensitivity compared with their IDH1wt counterparts. This study explores the mechanism driving apparent reduced growth in IDH1mut gliomas. Specifically, we investigated the relationship between IDH1mut and the RNA N6-methyladenosine (m6A) demethylases FTO and ALKBH5, and their potential for therapeutic targeting. We investigated the role of D-2-HG and m6A in tumor proliferation/viability using glioma patient tumor samples, patient-derived gliomaspheres, and U87 cells, as well as with mouse intracranial IDH1wt gliomasphere xenografts. Methylation RNA immunoprecipitation sequencing (MeRIP-seq) RNA sequencing was used to identify m6A-enriched transcripts in IDH1mut glioma. We show that IDH1mut production of D-2-HG is capable of reducing glioma cell growth via inhibition of the m6A epitranscriptomic regulator, FTO, with resultant m6A hypermethylation of a set of mRNA transcripts. On the basis of unbiased MeRIP-seq epitranscriptomic profiling, we identify ATF5 as a hypermethylated, downregulated transcript that potentially contributes to increased apoptosis. We further demonstrate how targeting this pathway genetically and pharmacologically reduces the proliferative potential of malignant IDH1wt gliomas, both in vitro and in vivo. Our work provides evidence that selective inhibition of the m6A epitranscriptomic regulator FTO attenuates growth in IDH1wt glioma, recapitulating the clinically favorable growth phenotype seen in the IDH1mut subtype. SIGNIFICANCE: We show that IDH1mut-generated D-2-HG can reduce glioma growth via inhibition of the m6A demethylase, FTO. FTO inhibition represents a potential therapeutic target for IDH1wt gliomas and possibly in conjunction with IDH1mut inhibitors for the treatment of IDH1mut glioma. Future studies are necessary to demonstrate the role of ATF5 downregulation in the indolent phenotype of IDH1mut gliomas, as well as to identify other involved gene transcripts deregulated by m6A hypermethylation.

Quantification of T2-FLAIR Mismatch in Nonenhancing Diffuse Gliomas Using Digital Subtraction.

BACKGROUND AND PURPOSE: The T2-FLAIR mismatch sign on MR imaging is a highly specific imaging biomarker of isocitrate dehydrogenase (IDH)-mutant astrocytomas, which lack 1p/19q codeletion. However, most studies using the T2-FLAIR mismatch sign have used visual assessment. This study quantified the degree of T2-FLAIR mismatch using digital subtraction of fluid-nulled T2-weighted FLAIR images from non-fluid-nulled T2-weighted images in human nonenhancing diffuse gliomas and then used this information to assess improvements in diagnostic performance and investigate subregion characteristics within these lesions. MATERIALS AND METHODS: Two cohorts of treatment-naïve, nonenhancing gliomas with known IDH and 1p/19q status were studied (n = 71 from The Cancer Imaging Archive (TCIA) and n = 34 in the institutional cohort). 3D volumes of interest corresponding to the tumor were segmented, and digital subtraction maps of T2-weighted MR imaging minus T2-weighted FLAIR MR imaging were used to partition each volume of interest into a T2-FLAIR mismatched subregion (T2-FLAIR mismatch, corresponding to voxels with positive values on the subtraction maps) and nonmismatched subregion (T2-FLAIR nonmismatch corresponding to voxels with negative values on the subtraction maps). Tumor subregion volumes, percentage of T2-FLAIR mismatch volume, and T2-FLAIR nonmismatch subregion thickness were calculated, and 2 radiologists assessed the T2-FLAIR mismatch sign with and without the aid of T2-FLAIR subtraction maps. RESULTS: Thresholds of ≥42% T2-FLAIR mismatch volume classified IDH-mutant astrocytoma with a specificity/sensitivity of 100%/19.6% (TCIA) and 100%/31.6% (institutional); ≥25% T2-FLAIR mismatch volume showed 92.0%/32.6% and 100%/63.2% specificity/sensitivity, and ≥15% T2-FLAIR mismatch volume showed 88.0%/39.1% and 93.3%/79.0% specificity/sensitivity. In IDH-mutant astrocytomas with ≥15% T2-FLAIR mismatch volume, T2-FLAIR nonmismatch subregion thickness was negatively correlated with the percentage T2-FLAIR mismatch volume (P < .0001) across both cohorts. The percentage T2-FLAIR mismatch volume was higher in grades 3-4 compared with grade 2 IDH-mutant astrocytomas (P < .05), and ≥15% T2-FLAIR mismatch volume IDH-mutant astrocytomas were significantly larger than <15% T2-FLAIR mismatch volume IDH-mutant astrocytoma (P < .05) across both cohorts. When evaluated by 2 radiologists, the additional use of T2-FLAIR subtraction maps did not show a significant difference in interreader agreement, sensitivity, or specificity compared with a separate evaluation of T2-FLAIR and T2-weighted MR imaging alone. CONCLUSIONS: T2-FLAIR digital subtraction maps may be a useful, automated tool to obtain objective segmentations of tumor subregions based on quantitative thresholds for classifying IDH-mutant astrocytomas using the percentage T2 FLAIR mismatch volume with 100% specificity and exploring T2-FLAIR mismatch/T2-FLAIR nonmismatch subregion characteristics. Conversely, the addition of T2-FLAIR subtraction maps did not enhance the sensitivity or specificity of the visual T2-FLAIR mismatch sign assessment by experienced radiologists.

dCas9/CRISPR-based methylation of O-6-methylguanine-DNA methyltransferase enhances chemosensitivity to temozolomide in malignant glioma.

BACKGROUND: Malignant glioma carries a poor prognosis despite current therapeutic modalities. Standard of care therapy consists of surgical resection, fractionated radiotherapy concurrently administered with temozolomide (TMZ), a DNA-alkylating chemotherapeutic agent, followed by adjuvant TMZ. O-6-methylguanine-DNA methyltransferase (MGMT), a DNA repair enzyme, removes alkylated lesions from tumor DNA, thereby promoting chemoresistance. MGMT promoter methylation status predicts responsiveness to TMZ; patients harboring unmethylated MGMT (~60% of glioblastoma) have a poorer prognosis with limited treatment benefits from TMZ. METHODS: Via lentiviral-mediated delivery into LN18 glioma cells, we employed deactivated Cas9-CRISPR technology to target the MGMT promoter and enhancer regions for methylation, as mediated by the catalytic domain of the methylation enzyme DNMT3A. Methylation patterns were examined at a clonal level in regions containing Differentially Methylation Regions (DMR1, DMR2) and the Methylation Specific PCR (MSP) region used for clinical assessment of MGMT methylation status. Correlative studies of genomic and transcriptomic effects of dCas9/CRISPR-based methylation were performed via Illumina 850K methylation array platform and bulk RNA-Seq analysis. RESULTS: We used the dCas9/DNMT3A catalytic domain to achieve targeted MGMT methylation at specific CpG clusters in the vicinity of promoter, enhancer, DMRs and MSP regions. Consequently, we observed MGMT downregulation and enhanced glioma chemosensitivity in survival assays in vitro, with minimal off-target effects. CONCLUSION: dCas9/CRISPR is a viable method of epigenetic editing, using the DNMT3A catalytic domain. This study provides initial proof-of-principle for CRISPR technology applications in malignant glioma, laying groundwork for subsequent translational studies, with implications for future epigenetic editing-based clinical applications.

Leveraging GPT-4 for Identifying Cancer Phenotypes in Electronic Health Records: A Performance Comparison between GPT-4, GPT-3.5-turbo, Flan-T5 and spaCy's Rule-based & Machine Learning-based methods.

Objective: Accurately identifying clinical phenotypes from Electronic Health Records (EHRs) provides additional insights into patients' health, especially when such information is unavailable in structured data. This study evaluates the application of OpenAI's Generative Pre-trained Transformer (GPT)-4 model to identify clinical phenotypes from EHR text in non-small cell lung cancer (NSCLC) patients. The goal was to identify disease stages, treatments and progression utilizing GPT-4, and compare its performance against GPT-3.5-turbo, Flan-T5-xl, Flan-T5-xxl, and two rule-based and machine learning-based methods, namely, scispaCy and medspaCy. Materials and Methods: Phenotypes such as initial cancer stage, initial treatment, evidence of cancer recurrence, and affected organs during recurrence were identified from 13,646 records for 63 NSCLC patients from Washington University in St. Louis, Missouri. The performance of the GPT-4 model is evaluated against GPT-3.5-turbo, Flan-T5-xxl, Flan-T5-xl, medspaCy and scispaCy by comparing precision, recall, and micro-F1 scores. Results: GPT-4 achieved higher F1 score, precision, and recall compared to Flan-T5-xl, Flan-T5-xxl, medspaCy and scispaCy's models. GPT-3.5-turbo performed similarly to that of GPT-4. GPT and Flan-T5 models were not constrained by explicit rule requirements for contextual pattern recognition. SpaCy models relied on predefined patterns, leading to their suboptimal performance. Discussion and Conclusion: GPT-4 improves clinical phenotype identification due to its robust pre-training and remarkable pattern recognition capability on the embedded tokens. It demonstrates data-driven effectiveness even with limited context in the input. While rule-based models remain useful for some tasks, GPT models offer improved contextual understanding of the text, and robust clinical phenotype extraction.

Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI.

OBJECTIVE: To determine the feasibility and biologic correlations of dynamic susceptibility contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from contrast leakage effects obtained simultaneously in gliomas using dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI) during a single contrast injection. MATERIALS AND METHODS: Thirty-eight patients with enhancing brain gliomas were prospectively imaged with dynamic SAGE-EPI, which was processed to compute traditional DSC metrics (normalized relative cerebral blood flow [nrCBV], percentage of signal recovery [PSR]), DCE metrics (volume transfer constant [Ktrans], extravascular compartment [ve]), and leakage effect metrics: ΔR2,ss* (reflecting T2*-leakage effects), ΔR1,ss (reflecting T1-leakage effects), and the transverse relaxivity at tracer equilibrium (TRATE, reflecting the balance between ΔR2,ss* and ΔR1,ss). These metrics were compared between patient subgroups (treatment-naïve [TN] vs recurrent [R]) and biological features (IDH status, Ki67 expression). RESULTS: In IDH wild-type gliomas (IDHwt-i.e., glioblastomas), previous exposure to treatment determined lower TRATE (p = 0.002), as well as higher PSR (p = 0.006), Ktrans (p = 0.17), ΔR1,ss (p = 0.035), ve (p = 0.006), and ADC (p = 0.016). In IDH-mutant gliomas (IDHm), previous treatment determined higher Ktrans and ΔR1,ss (p = 0.026). In TN-gliomas, dynamic SAGE-EPI metrics tended to be influenced by IDH status (p ranging 0.09-0.14). TRATE values above 142 mM-1s-1 were exclusively seen in TN-IDHwt, and, in TN-gliomas, this cutoff had 89% sensitivity and 80% specificity as a predictor of Ki67 > 10%. CONCLUSIONS: Dynamic SAGE-EPI enables simultaneous quantification of brain tumor perfusion and permeability, as well as mapping of novel metrics related to cytoarchitecture (TRATE) and blood-brain barrier disruption (ΔR1,ss), with a single contrast injection. CLINICAL RELEVANCE STATEMENT: Simultaneous DSC and DCE analysis with dynamic SAGE-EPI reduces scanning time and contrast dose, respectively alleviating concerns about imaging protocol length and gadolinium adverse effects and accumulation, while providing novel leakage effect metrics reflecting blood-brain barrier disruption and tumor tissue cytoarchitecture. KEY POINTS: • Traditionally, perfusion and permeability imaging for brain tumors requires two separate contrast injections and acquisitions. • Dynamic spin-and-gradient-echo echoplanar imaging enables simultaneous perfusion and permeability imaging. • Dynamic spin-and-gradient-echo echoplanar imaging provides new image contrasts reflecting blood-brain barrier disruption and cytoarchitecture characteristics.

Association Between Socioeconomic Factors, Race, and Use of a Specialty Memory Clinic.

BACKGROUND AND OBJECTIVES: The capacity of specialty memory clinics in the United States is very limited. If lower socioeconomic status or minoritized racial group is associated with reduced use of memory clinics, this could exacerbate health care disparities, especially if more effective treatments of Alzheimer disease become available. We aimed to understand how use of a memory clinic is associated with neighborhood-level measures of socioeconomic factors and the intersectionality of race. METHODS: We conducted an observational cross-sectional study using electronic health record data to compare the neighborhood advantage of patients seen at the Washington University Memory Diagnostic Center with the catchment area using a geographical information system. Furthermore, we compared the severity of dementia at the initial visit between patients who self-identified as Black or White. We used a multinomial logistic regression model to assess the Clinical Dementia Rating at the initial visit and t tests to compare neighborhood characteristics, including Area Deprivation Index, with those of the catchment area. RESULTS: A total of 4,824 patients seen at the memory clinic between 2008 and 2018 were included in this study (mean age 72.7 [SD 11.0] years, 2,712 [56%] female, 543 [11%] Black). Most of the memory clinic patients lived in more advantaged neighborhoods within the overall catchment area. The percentage of patients self-identifying as Black (11%) was lower than the average percentage of Black individuals by census tract in the catchment area (16%) (p < 0.001). Black patients lived in less advantaged neighborhoods, and Black patients were more likely than White patients to have moderate or severe dementia at their initial visit (odds ratio 1.59, 95% CI 1.11-2.25). DISCUSSION: This study demonstrates that patients living in less affluent neighborhoods were less likely to be seen in one large memory clinic. Black patients were under-represented in the clinic, and Black patients had more severe dementia at their initial visit. These findings suggest that patients with a lower socioeconomic status and who identify as Black are less likely to be seen in memory clinics, which are likely to be a major point of access for any new Alzheimer disease treatments that may become available.

Change in volumetric tumor growth rate after cytotoxic therapy is predictive of overall survival in recurrent glioblastoma.

Background: Alterations in tumor growth rate (TGR) in recurrent glioblastoma (rGBM) after treatment may be useful for identifying therapeutic activity. The aim of this study was to assess the impact of volumetric TGR alterations on overall survival (OS) in rGBM treated with chemotherapy with or without radiation therapy (RT). Methods: Sixty-one rGBM patients treated with chemotherapy with or without concomitant radiation therapy (RT) at 1st or 2nd recurrence were retrospectively examined. Pre- and post-treatment contrast enhancing volumes were computed. Patients were considered "responders" if they reached progression-free survival at 6 months (PFS6) and showed a decrease in TGR after treatment and "non-responders" if they didn't reach PFS6 or if TGR increased. Results: Stratification by PFS6 and based on TGR resulted in significant differences in OS both for all patients and for patients without RT (P < 0.05). A decrease of TGR (P = 0.009), smaller baseline tumor volume (P = 0.02), O6-methylguanine-DNA methyltransferase promoter methylation (P = 0.048) and fewer number of recurrences (P = 0.048) were significantly associated with longer OS after controlling for age, sex and concomitant RT. Conclusion: A decrease in TGR in patients with PFS6, along with smaller baseline tumor volume, were associated with a significantly longer OS in rGBM treated with chemotherapy with or without radiation. Importantly, all patients that exhibited PFS6 also showed a measurable decrease in TGR.

Low- and high-grade glioma endothelial cells differentially regulate tumor growth.

Background: A key feature distinguishing high-grade glioma (HGG) from low-grade glioma (LGG) is the extensive neovascularization and endothelial hyperproliferation. Prior work has shown that tumor endothelial cells (TEC) from HGG are molecularly and functionally distinct from normal brain EC and secrete higher levels of pro-tumorigenic factors that promote glioma growth and progression. However, it remains unclear whether TEC from LGG also express pro-tumorigenic factors, and to what extent they functionally contribute to glioma growth. Methods: Transcriptomic profiling was conducted on tumor endothelial cells (TEC) from grade II/III (LGG, IDH-mutant) and grade IV HGG (IDH-wildtype). Functional differences between LGG- and HGG-TEC were evaluated using growth assays, resistance to anti-angiogenic drugs and radiation therapy. Conditioned media and specific factors from LGG- and HGG-TEC were tested on patient-derived gliomasphere lines using growth assays in vitro and in co-transplantation studies in vivo in orthotopic xenograft models. Results: LGG-TEC showed enrichment of extracellular matrix and cell cycle-related gene sets and sensitivity to anti-angiogenic therapy whereas HGG-TEC displayed an increase in immune response-related gene sets and anti-angiogenic resistance. LGG- and HGG-TEC displayed opposing effects on growth and proliferation of IDH-wildtype and mutant tumor cells. Asporin (ASPN), a small leucine rich proteoglycan enriched in LGG-TEC was identified as a growth suppressor of IDH-wildtype GBM by modulating TGFΒ1-GPM6A signaling. Conclusions: Our findings indicate that TEC from LGG and HGG are molecularly and functionally heterogeneous and differentially regulate the growth of IDH-wildtype and mutant tumors.

Electronic health record data quality assessment and tools: a systematic review.

OBJECTIVE: We extended a 2013 literature review on electronic health record (EHR) data quality assessment approaches and tools to determine recent improvements or changes in EHR data quality assessment methodologies. MATERIALS AND METHODS: We completed a systematic review of PubMed articles from 2013 to April 2023 that discussed the quality assessment of EHR data. We screened and reviewed papers for the dimensions and methods defined in the original 2013 manuscript. We categorized papers as data quality outcomes of interest, tools, or opinion pieces. We abstracted and defined additional themes and methods though an iterative review process. RESULTS: We included 103 papers in the review, of which 73 were data quality outcomes of interest papers, 22 were tools, and 8 were opinion pieces. The most common dimension of data quality assessed was completeness, followed by correctness, concordance, plausibility, and currency. We abstracted conformance and bias as 2 additional dimensions of data quality and structural agreement as an additional methodology. DISCUSSION: There has been an increase in EHR data quality assessment publications since the original 2013 review. Consistent dimensions of EHR data quality continue to be assessed across applications. Despite consistent patterns of assessment, there still does not exist a standard approach for assessing EHR data quality. CONCLUSION: Guidelines are needed for EHR data quality assessment to improve the efficiency, transparency, comparability, and interoperability of data quality assessment. These guidelines must be both scalable and flexible. Automation could be helpful in generalizing this process.

Multi-nuclear sodium, diffusion, and perfusion MRI in human gliomas.

PURPOSE: There is limited knowledge about the associations between sodium and proton MRI measurements in brain tumors. The purpose of this study was to quantify intra- and intertumoral correlations between sodium, diffusion, and perfusion MRI in human gliomas. METHODS: Twenty glioma patients were prospectively studied on a 3T MRI system with multinuclear capabilities. Three mutually exclusive tumor volumes of interest (VOIs) were segmented: contrast-enhancing tumor (CET), T2/FLAIR hyperintense non-enhancing tumor (NET), and necrosis. Median and voxel-wise associations between apparent diffusion coefficient (ADC), normalized relative cerebral blood volume (nrCBV), and normalized sodium measurements were quantified for each VOI. RESULTS: Both relative sodium concentration and ADC were significantly higher in areas of necrosis compared to NET (P = 0.003 and P = 0.008, respectively) and CET (P = 0.02 and P = 0.02). Sodium concentration was higher in CET compared to NET (P = 0.04). Sodium and ADC were higher in treated compared to treatment-naïve gliomas within NET (P = 0.006 and P = 0.01, respectively), and ADC was elevated in CET (P = 0.03). Median ADC and sodium concentration were positively correlated across patients in NET (r = 0.77, P < 0.0001) and CET (r = 0.84, P < 0.0001), but not in areas of necrosis (r = 0.45, P = 0.12). Median nrCBV and sodium concentration were negatively correlated across patients in areas of NET (r=-0.63, P = 0.003). Similar associations were observed when examining voxel-wise correlations within VOIs. CONCLUSION: Sodium MRI is positively correlated with proton diffusion MRI measurements in gliomas, likely reflecting extracellular water. Unique areas of multinuclear MRI contrast may be useful in future studies to understand the chemistry of the tumor microenvironment.

Retrospective examination of pseudoprogression in IDH mutant gliomas.

Background: Tumor surveillance of isocitrate dehydrogenase (IDH) mutant gliomas is accomplished via serial contrast MRI. When new contrast enhancement (CEnew) is detected during postsurgical surveillance, clinicians must assess whether CEnew indicates pseudoprogression (PsP) or tumor progression (TP). PsP has been better studied in IDH wild-type glioblastoma but has not been well characterized in IDH mutant gliomas. We conducted a retrospective study evaluating the incidence, predictors, natural history, and survival of PsP patients in a large cohort of IDH mutant glioma patients treated at a single institution. Methods: We identified 587 IDH mutant glioma patients treated at UCLA. We directly inspected MRI images and radiology reports to identify CEnew and categorized CEnew into TP or PsP using MRI or histopathology. Results: Fifty-six percent of patients developed CEnew (326/587); of these, 92/326 patients (28% of CEnew; 16% of all) developed PsP and 179/326 (55%) developed TP. All PsP patients had prior radiation, chemotherapy, or chemoradiotherapy. PsP was associated with longer overall survival (OS) versus TP patients and similar OS versus no CEnew. PsP differs from TP based on earlier time of onset (median 5.8 vs 17.4 months from treatment, P < .0001) and MRI features that include punctate enhancement and enhancement location. Conclusion: PsP patients represented 28% of CEnew patients and 16% of all patients; PsP patients demonstrated superior outcomes to TP patients, and equivalent survival to patients without CEnew. PsP persists for <1 year, occurs after treatment, and differs from TP based on time of onset and radiographic features. Poor outcomes after CEnew are driven by TP.

A single-institution retrospective analysis of pathologically determined malignant transformation in IDH mutant glioma patients.

Background: Lower-grade IDH mutant glioma patients frequently undergo malignant transformation (MT), with apparent worse prognosis. Many studies examine MT in mixed IDH status cohorts and define MT using imaging, not histopathology. Our study examines the timing, predictors, and prognostic implications of pathologically determined MT in a large, exclusively IDH mutant cohort. Methods: We identified 193 IDH mutant lower-grade glioma patients at UCLA who received multiple surgeries. We examined the outcomes of pathologically determined MT patients. Results: Time to MT is longer in grade 2 oligodendroglioma (G2 Oligo) than in grade 2 astrocytoma (G2 Astro) (HR = 0.46, P = .0007). The grade 3 astrocytoma (G3 Astro) to grade 4 astrocytoma (G4 Astro) interval is shorter in stepwise MT (G2 to G3 to G4 Astro) patients than in initial G3 Astro patients (P = .03). Novel contrast enhancement had 65% positive predictivity, 67% negative predictivity, 75% sensitivity, and 55% specificity in indicating pathologically defined MT. In G2 Astro, initial gross total resection delayed MT (HR = 0.50, P = .02) and predicted better overall survival (OS) (HR = 0.34, P = .009). In G2 Oligo, spontaneous MT occurred earlier than treated MT (HR = 11.43, P = .0002), but treatment did not predict improved OS (P = .8). MT patients (n = 126) exhibited worse OS than non-MT patients (n = 67) in All (HR = 2.54, P = .0009) and G2 Astro (HR = 4.26, P = .02). Conclusion: Our study expands the understanding of MT to improve IDH mutant lower-grade glioma management.