Citations

Abstract Context Patients with mild autonomous cortisol secretion (MACS) can develop adrenal insufficiency after unilateral adrenalectomy. Objective This work aimed to determine the prevalence, duration, and predictors of adrenal insufficiency, and compare postoperative basal cortisol and cosyntropin stimulation test (CST). Methods In this multicenter retrospective study of patients with MACS, adrenal insufficiency was diagnosed when postoperative basal cortisol was less than 10 µg/dL and/or CST < 18 µg/dL. The results were concordant when both tests met cutoffs. Biochemical (BSS) and clinical severity scores (CSS) were calculated. Results Among 281 patients with MACS (80% women), postoperative adrenal insufficiency was diagnosed in 153 (54.5%) patients. Adrenal insufficiency inversely correlated with age (odds ratio [OR] 0.67 per 10 years; 95% CI, 0.53-0.84). Low basal cortisol and CST were associated with younger age (OR 0.64 per 10 years for both) and higher BSS (OR 1.17 and 1.22, respectively). Basal cortisol and CST were discordant in 22% of patients, and the discordance rate was more common in patients with bilateral nodules (32% vs 19%; P < .001). The median time to adrenal insufficiency recovery was 3.9 months (IQR, 3-5.9 months), with longer duration associated with higher BSS and CSS: 3 months for mild, 4 to 5 months for moderate, and 12 to 14 months for severe BSS and CSS. Conclusion Approximately half of patients with MACS developed postoperative adrenal insufficiency, with 50% recovering by 3.9 months after surgery. BSS correlated with basal cortisol, CST, and duration of adrenal insufficiency. As discordant results were noted in 22%, performing both basal cortisol and CST postoperatively should be considered.

Abstract Despite significant therapeutic advances in multiple myeloma (MM), outcomes in patients with plasma cell leukemia (PCL) remain dismal. We conducted a multicenter retrospective analysis of patients with PCL who were treated with the B-cell maturation antigen–directed chimeric antigen receptor T-cell (CAR-T) products idecabtagene vicleucel (ide-cel) and ciltacabtagene autoleucel (cilta-cel). We identified 34 patients; 19 patients received ide-cel and 15 received cilta-cel. With a median follow-up of 11.9 months, the overall median progression-free survival (mPFS) was 9.0 months (95% confidence interval [CI], 4-15) and the median overall survival (mOS) was 13.0 months (95% CI, 8 to not estimable [NE]). The 1-year cumulative incidence of progression or death was 72%, and the 1-year cumulative incidence of death was 47%. Patients who received cilta-cel had a longer mPFS (19.0 months vs 6.0 months) and mOS (>23 months [NE] vs 9.0 months) when compared with those treated with ide-cel. Similarly, the 1-year cumulative incidence of disease progression or death was 37.5% (95% CI, 17.4-68.5) with cilta-cel, whereas all patients treated with ide-cel progressed or died within 12 months of infusion. The rates of hematologic and nonhematologic toxicities were similar between patients treated with cilta-cel and those treated with ide-cel and were consistent with those reported in patients with MM. In this first multicenter study that evaluated patients with PCL who were treated with standard-of-care CAR-T products, we show that CAR-T is safe, feasible, and associated with improved outcomes when compared with historic standards.

Hypertension is the single most important modifiable risk factor for preventable disability and death worldwide and disproportionately affects socially disadvantaged populations. We face a paradox—blood pressure control is low and recent trends suggest it is even declining, despite the availability of inexpensive and effective therapies. A variety of barriers on the system, patient, and healthcare provider side hinder effective drug-based risk factor management. Clinical inertia represents a major barrier on the clinician side, as well as workload and limited education. Common barriers on the patient side include limited English proficiency, low health literacy, and nonadherence with misaligned incentives, limited resources, lack of structured clinical pathways, and reimbursement issues. New innovations in the field of RNA-targeted therapies and device-based interventions could prevent and potentially even cure diseases previously designated as chronic health conditions, such as hypertension. Such novel therapies could potentially overcome several major barriers to effective treatment, including nonadherence. Drug development of novel, long-acting treatments requires consideration of specific clinical trial design aspects, including safety collection, benefit: risk assessment, the development and assessment of novel, qualitative surrogate end points, such as time-in-therapeutic range, the use of representative trial settings as well as the definition of standard of care in placebo-controlled trials, which should be of reasonably high-quality allowing for credible evaluation of effectiveness. Here, we provide an overview on barriers to effective treatment and a framework for trials assessing novel treatments for cardiovascular disease risk factors, including early and broad implementation programs.

Abstract Objective: Electronic Health Record (EHR) data are critical for advancing translational research and AI technologies. The ENACT network offers access to structured EHR data across 57 CTSA hubs. However, substantial information is contained in clinical narratives, requiring natural language processing (NLP) for research. The ENACT NLP Working Group was formed to make NLP-derived clinical information accessible and queryable across the network. Methods: We established the ENACT NLP Working Group with 13 sites selected based on criteria including clinical notes access, IT infrastructure, NLP expertise, and institutional support. We divided sites into five focus groups targeting clinical tasks within disease contexts. Each focus group consisted of two development sites and two validation sites. We extended the ENACT ontology to standardize NLP-derived data and conducted multisite evaluations using the Open Health Natural Language Processing (OHNLP) Toolkit. Results: The working group achieved 100% site retention and deployed NLP infrastructure across all sites. We developed and validated NLP algorithms for rare disease phenotyping, social determinants of health, opioid use disorder, sleep phenotyping, and delirium phenotyping. Performance varied across sites (F1 scores 0.53–0.96), highlighting data heterogeneity impacts. We extended the ENACT common data model and ontology to incorporate NLP-derived data while maintaining Shared Health Research Informatics NEtwork (SHRINE) compatibility. Conclusion: This demonstrates feasibility of deploying NLP infrastructure across large, federated networks. The focus group approach proved more practical than general-purpose approaches. Key lessons include the challenge of data heterogeneity and importance of collaborative governance. This work also provides a foundation that other networks can build on to implement NLP capabilities for translational research.

Abstract Background The isocitrate dehydrogenase (IDH) mutation status is a key molecular marker in diagnosing and treating brain tumors. Currently, it is determined via invasive tissue biopsy. Recent advances in deep learning (DL) have offered promising non-invasive alternatives for determining IDH status. However, their clinical translation is hindered by a significant gap between DL predictions and their clinical applicability. The limited transparency of many DL-networks and inadequate evaluation metrics hinders trust and adoption, as clinicians require clear and validated insights for determining IDH status. These challenges highlight the need for robust validation and measures of predictive reliability to make DL-predictions clinically actionable. Methods We developed a unique approach for non-invasive prediction of IDH status using MRI. We combine a voxel-wise-segmentation network(MC-net) with Bayesian logistic regression (BLR) to provide an IDH status and estimate confidence scores. We utilized a comprehensive dataset of 2,481 glioma cases from eight institutions. Results Our framework(MC-net + BLR) demonstrated robust performance achieving 96.4% and 95.1% classification accuracies on diverse databases, with an AUC of 0.98. The BLR was implemented exclusively on held-out test data, ensuring that the derived confidence scores are independent of the training or validation phases. The derived confidence scores showed a low Brier score of 0.0125, highlighting its superior calibration and uncertainty quantification. Conclusion The developed framework provides an IDH status and a confidence score, offering clinicians an additional layer of assurance in prediction reliability. It bridges the gap between high-performing DL models and their clinical applicability by addressing the challenges in prediction reliability. Our framework is a significant advancement in non-invasive determination of IDH-status and confidence-informed therapeutic decision-making in neuro-oncology.

Abstract The cumulative impact of baseline comorbidities on outcomes of chimeric antigen receptor T-cell (CAR-T) therapy is not well established. Therefore, we developed and validated a Cellular Therapy Comorbidity Index (CT-CI) to predict outcomes following CD19-directed CAR-T therapy for large B-cell lymphoma (LBCL). Patients aged 18 or older receiving commercial CAR-T therapy for LBCL during 2017 to 2020 were selected from the Center for International Blood and Marrow Transplant Research registry. Patients were randomly assigned to training or validation cohorts. Comorbidities given weighted scores comprised the CT-CI, which was then validated for overall survival (OS) prognostication. A total of 1916 patients from 97 medical centers were included, with a median age of 64 years (19-91 years). About 70% of patients had comorbidities, such as cardiac disease (12%); diabetes (14%); hepatic dysfunction (mild, 8%; moderate to severe, 2%); psychiatric disturbance (18%); and pulmonary dysfunction (moderate, 15%; severe, 12%). The CT-CI was calculated, stratified patients in 3 categories, and was associated with increased mortality. Patients with higher CT-CI scores had worse OS (CT-CI 1: hazard ratio [HR], 1.37 [95% confidence interval [CI], 1.16-1.62; P< .001]; CT-CI 2: HR, 1.49 [95% CI, 1.17-1.89; P = .001]; CT-CI ≥ 3: HR, 2.55 [95% CI, 1.90-3.42; P< .001]). Higher CT-CI scores predicted treatment-related mortality and relapse. There was no correlation between the CT-CI score and CAR-T–related toxicities. The novel CT-CI score stratifies the effect of patient comorbidities on survival after CAR-T therapy and can be used for clinical decision-making and treatment selection in high-risk populations. However, comorbidities and fear of increased toxicity should not preclude patients from this effective therapy.

ABSTRACT Objective To evaluate the long‐term safety and clinical effect of INO‐3107 immunotherapy in adults with recurrent respiratory papillomatosis (RRP). Methods RRP‐002 was a retrospective, observational extension study that followed patients enrolled in the 52‐week RRP‐001 study. Patients with moderate to severe juvenile or adult‐onset RRP who had undergone ≥ 2 surgical interventions in the year preceding dosing were eligible for enrollment in RRP‐001. Participants underwent surgical debulking within 14 days prior to initial dosing and then received INO‐3107 on Day 0, Weeks 3, 6, and 9. Efficacy assessments during RRP‐002 follow‐up were the frequency of surgical interventions and alternative medication use. The safety evaluation included reported serious adverse events (SAEs). Results Twenty‐eight (28) of 32 participants from the 52‐week RRP‐001 study were enrolled in RRP‐002. The median follow‐up time for RRP‐002 was 1.8 years (range: 1.2–2.4 years) for a total median assessment time of 2.8 years (range: 1.0–3.5 years). There were no SAEs or long‐term safety concerns identified. The mean number of surgeries was reduced from 4.1 in the pre‐treatment period to 1.7 in the first year post‐INO‐3107 treatment (Year 1) to 0.9 in the second year (Year 2). The complete response rate (0 surgeries per year) increased from 28% (9/32) in Year 1 to 50% (14/28) in Year 2. Conclusion INO‐3107 is well tolerated and provides a continued clinical effect against HPV‐6 and 11 RRP that results in further reduction of the surgical burden observed in Year 1. These data support the role of INO‐3107 immunotherapy for adult patients with RRP. Level of Evidence: III.

ABSTRACT Rationale Longer duration of epilepsy before surgery is a predictor of poor outcome. While referral delays of surgical candidates are well documented, factors causing delay during the presurgical evaluation remain unclear and may vary depending on institutional characteristics. By benchmarking the duration of presurgical evaluation across multiple centers and identifying patient and evaluation characteristics contributing to duration, we can ascertain best practices and address modifiable contributors to reduce delays. Methods We queried the Pediatric Epilepsy Research Consortium Surgery Database, a prospective, observational multicenter study enrolling children 0–18 years at 27 US pediatric epilepsy centers, for all patients undergoing initial presurgical evaluation for drug‐resistant epilepsy (DRE). We included patients with completed evaluations and data on duration from initiation of presurgical evaluation to final surgical decision. We compared patient characteristics and evaluation components between those with long duration evaluations (> 75% quartile) and those with short evaluations (< 25% quartile). Akaike information criteria selection identified variables associated with longer duration. From these, we developed a logistic prediction model for evaluation duration, using a random 80/20 training/testing split of the entire cohort. The model was tested among institutions with ≥ 10 patients in the cohort to assess its accuracy in predicting long durations. Linear models for each site assessed each variable's impact on duration. Variables with < 10% of the patient population at each site were excluded. Beta values were compared to identify intra‐ and inter‐institution variability and to delineate institutions with the shortest added duration for each variable. Results Of 2318 patients undergoing surgical evaluation, 1655 (71%) from 23 sites had complete data. Median evaluation duration was 8 weeks (interquartile range 3–22); 453 (27%) were short‐duration evaluations and 414 (25%) were long‐duration evaluations. Multiple patient and evaluation characteristics were associated with duration (Table 1). Table 6 provides the average duration each variable contributes to evaluation by site, highlighting the shortest durations compared with other groups. Conclusions Duration of presurgical evaluation for DRE can be accurately modeled using multiple patient characteristics and testing strategies commonly employed in epilepsy surgery evaluations. This predictive model can not only estimate evaluation duration but also identify opportunities to improve systemic efficiency. Institution‐level modeling identifies specific program strengths, providing an opportunity to learn from successful processes. Subsequent research will focus on institutional process mapping to better understand systemic practices that lead to improved efficiencies, then sharing these processes across the consortium to shorten evaluation durations.