Newark Academy

BACKGROUND:Adolescents and young adults (AYAs) with acute lymphoblastic leukemia (ALL) represent a unique population. Treatment regimens can vary significantly depending on whether they receive care in a pediatric or in an adult setting. They also have distinctive care needs, social risk factors, and disease behavior compared with other age groups. OBJECTIVE:These evidence-based guidelines of the American Society of Hematology (ASH) are intended to support patients, clinicians, and other health care professionals in their decisions about the frontline management of ALL in AYAs. METHODS:ASH formed a multidisciplinary guideline panel including hematologists, AYA psychosocial care specialists, pharmacists, methodologists, and patient representatives with efforts to minimize bias from conflicts of interest. An evidence review team at Brown University supported guideline development, including performing systematic evidence reviews up to November 2023. The panel prioritized clinical questions and outcomes according to importance for clinicians and patients. The panel used grading of recommendations assessment, development, and evaluation (GRADE), including GRADE evidence-to-decision frameworks, to assess evidence and make recommendations, which were subject to public comment. RESULTS:The panel agreed on 15 recommendations and several good practice statements. CONCLUSIONS:Pediatric-inspired regimens containing asparaginase are recommended as frontline therapy compared with more traditional adult-inspired protocols, requiring significant supportive care and close follow-up. Allogeneic hematopoietic stem cell transplantation is not routinely recommended in first remission but may be indicated for higher-risk subsets or those with suboptimal responses to initial therapy. The use of targeted agents in frontline therapy is increasingly supported, although further research is needed to optimize this strategy.

Abstract Background Current machine learning (ML) prediction models offer limited guidance for individualized actionable management. Large language models (LLMs) can transform ML model-predicted risk estimates with Shapley Additive Explanations (SHAP) into clinically meaningful support information, yet the added value of incorporating ML-derived data and the relative performance of different LLMs remain uncertain. To address these gaps, we used our previously developed IMPACT framework to evaluate the quality of LLM-generated outputs. Methods In this retrospective analysis of MIMIC-IV v3.1 intensive care unit (ICU) admissions, we applied a previously developed XGBoost model to estimate ICU mortality risk and derive corresponding SHAP values. GPT-4o transformed the predicted mortality risk, clinical predictors, and their SHAP values into risk interpretation, recommended examinations and management. The primary analysis examined whether augmenting LLM inputs with predicted mortality risk and SHAP values improved clinical response quality, as assessed by the IMPACT framework. We further compared GPT-4o with seven contemporary LLMs; all eight models generated clinical support responses that were scored by Claude 3.7 Sonnet to assess performance differences. Results Claude 3.7 Sonnet showed excellent agreement with human IMPACT ratings (intraclass correlation coefficient [ICC] 0.979, 95% CI 0.973–0.984) and o3-mini (ICC 0.971, 95% CI 0.964–0.980). In the primary analysis, adding predicted ICU mortality risk and SHAP values significantly increased GPT-4o IMPACT scores across prompting strategies. GPT-5 mini (96.0) and gpt-oss-120B (93.4) outperformed GPT-4o (90.4; both p < 0.001) for interpretability and quality. Conclusions Combining ML-derived risk, SHAP explanations and LLMs may modestly improve ICU clinical support information, while LLM-based evaluators demonstrated feasibility for scalable evaluation of generated clinical content.

Background: South Africa's National Tuberculosis (TB) Programme aims to achieve targets set by the World Health Organization's End TB Strategy, including an 80% reduction in TB incidence and a 90% reduction in TB mortality by 2030, compared to 2015 levels. We were tasked to evaluate 1) the impact on TB incidence and mortality of scaling up individual interventions focusing on TB preventive therapy, screening, testing and linkage to treatment as included in the 2023–2028 National Strategic Plan for TB (NSP); 2) the budget required for implementing the NSP; 3) the cost-effectiveness of scaling up individual interventions aligning with NSP targets, and 4) the health impact and cost-effectiveness of additional aggressive screening scenarios to reach the End TB targets. Methods: We used the Thembisa TB model and public-sector costs to estimate the incremental cost-effectiveness per life year saved (LYS) for individual and combined interventions under various scenarios from 2023 to 2042. The NSP scenario included expansions of TB preventive therapy (TPT), symptom screening at primary health clinics and testing with Xpert, screening of household contacts of people with TB, and community-based screening (door-to-door and digital chest X-ray), as well as targeted universal testing for TB (TUTT) in people living with HIV (PLHIV), household contacts of people with TB and individuals with a history of TB, and reduction of initial loss-to-follow-up (ILTFU), all to levels deemed feasible by NSP stakeholders. We also assessed two hypothetical scenarios that largely maximise screening: Max scenario 1 (TPT for PLHIV, quarterly symptom screening for all adults) and Max scenario 2 (TPT for PLHIV, with eligible adults receiving yearly chest X-rays, TB testing, and TPT for household contacts). Results: The NSP achieved a 44% reduction in TB incidence and a 55% reduction in mortality by 2030 relative to 2015, while the aggressive scenarios (Max 1 and Max 2) achieved 57% and 56% reductions in incidence, respectively; and 75% and 71% reductions in mortality, respectively. Among individual NSP interventions, over the period 2023-2043, TPT for PLHIV and Xpert testing for symptomatic individuals seeking TB care were cost-saving. Symptom screening for household contacts ($12/LYS), ILTFU reduction ($13/LYS), TUTT for household contacts ($84/LYS), and TPT for household contacts ($106/LYS) were the most cost-effective interventions. Compared to baseline, the NSP scenario increased cost by 57%, saving 6.6 million life-years at $308/LYS over the period 2023-2042. The Max 1 and Max 2 scenarios increased the cost significantly, by 329% and 1526%, respectively. Max 1 saved 16.5 million life-years at $712/LYS, while Max 2 saved 14.6 million life-years at $3,774/LYS. Conclusion: Scaling up TB interventions to NSP coverage targets will substantially save lives and reduce TB morbidity. However, the End TB targets will not be met even under additional scenarios considered, including more aggressive prevention, expanded screening and testing, and a more aggressive treatment initiation strategy. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement Yes ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: No ethics approval was received. This was a mathematical modeling study which relied on published data and aggregated publicly available data to calibrate the model I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All relevant data are within the manuscript and its Supporting Information files.

Background Clozapine is the gold standard for treatment-resistant schizophrenia but may cause rare pulmonary adverse effects. Most reported cases occur within weeks of initiation. Case presentation We describe a 31-year-old woman with schizophrenia and mild intellectual developmental disorder, treated with clozapine for nearly one year before developing prolonged pulmonary inflammation. Despite antibiotic therapy for an initial infection, symptoms persisted and further investigations revealed organizing pneumonia. Rapid improvement followed clozapine discontinuation. Discussion This case raises the possibility that clozapine contributed to the persistence of pulmonary inflammation following an initial infectious episode. Conclusion Clinicians should consider clozapine as a possible contributor to persistent pulmonary inflammation even after long-term exposure.