Plasma microbial cell-free DNA following chimeric antigen receptor T cell therapy in pediatric patients with relapsed/refractory leukemia.

Chimeric antigen receptor (CAR) T cell therapy is a promising treatment for pediatric patients with relapsed or refractory B cell acute lymphoblastic leukemia (R/R B ALL). Cytokine release syndrome (CRS) is a common toxicity after CAR T cell therapy and fever is often the first symptom. Differentiating CRS from infection after CAR T cell therapy can be challenging. Plasma microbial cell free DNA (mcfDNA) is a novel diagnostic tool which allows for qualitative and quantitative assessment of over 1000 organisms. This pilot study sought to characterize mcfDNA results in pediatric patients with R/R B ALL in the first 2 months after CAR T cell therapy.

Household income and health-related quality of life in children receiving treatment for acute myeloid leukemia: Potential impact of selection bias in health equity research.

OBJECTIVE: Examine the influence of household income on health-related quality of life (HRQOL) among children with newly diagnosed acute myeloid leukemia (AML). DESIGN: Secondary analysis of data prospectively collected from pediatric patients receiving treatment for AML at 14 hospitals across the United States. EXPOSURE: Household income was self-reported on a demographic survey. The examined mediators included the acuity of presentation and treatment toxicity. OUTCOME: Caregiver proxy reported assessment of patient HRQOL from the Peds QL 4.0 survey. RESULT: Children with AML (n = 131) and caregivers were prospectively enrolled to complete PedsQL assessments. HRQOL scores were better for patients in the lowest versus highest income category (mean ± SD: 76.0 ± 14 household income <$25,000 vs. 59.9 ± 17 income ≥$75,000; adjusted mean difference: 11.2, 95% CI: 2.2-20.2). Seven percent of enrolled patients presented with high acuity (ICU-level care in the first 72 h), and 16% had high toxicity (any ICU-level care); there were no identifiable differences by income, refuting mediating roles in the association between income and HRQOL. Enrolled patients were less likely to be Black/African American (9.9% vs. 22.2%), more likely to be privately insured (50.4% vs. 40.7%), and more likely to have been treated on a clinical trial (26.7% vs. 18.5%) compared to eligible unenrolled patients not enrolled. Evaluations of potential selection bias on the association between income and HRQOL suggested differences in HRQOL may be smaller than observed or even in the opposing direction. CONCLUSIONS: While primary analyses suggested lower household income was associated with superior HRQOL, differential participation may have biased these results. Future studies should partner with patients/families to identify strategies for equitable participation in clinical research.

Characterizing the limitations of using diagnosis codes in the context of machine learning for healthcare.

BACKGROUND: Diagnostic codes are commonly used as inputs for clinical prediction models, to create labels for prediction tasks, and to identify cohorts for multicenter network studies. However, the coverage rates of diagnostic codes and their variability across institutions are underexplored. The primary objective was to describe lab- and diagnosis-based labels for 7 selected outcomes at three institutions. Secondary objectives were to describe agreement, sensitivity, and specificity of diagnosis-based labels against lab-based labels. METHODS: This study included three cohorts: SickKids from The Hospital for Sick Children, and StanfordPeds and StanfordAdults from Stanford Medicine. We included seven clinical outcomes with lab-based definitions: acute kidney injury, hyperkalemia, hypoglycemia, hyponatremia, anemia, neutropenia and thrombocytopenia. For each outcome, we created four lab-based labels (abnormal, mild, moderate and severe) based on test result and one diagnosis-based label. Proportion of admissions with a positive label were presented for each outcome stratified by cohort. Using lab-based labels as the gold standard, agreement using Cohen's Kappa, sensitivity and specificity were calculated for each lab-based severity level. RESULTS: The number of admissions included were: SickKids (n = 59,298), StanfordPeds (n = 24,639) and StanfordAdults (n = 159,985). The proportion of admissions with a positive diagnosis-based label was significantly higher for StanfordPeds compared to SickKids across all outcomes, with odds ratio (99.9% confidence interval) for abnormal diagnosis-based label ranging from 2.2 (1.7-2.7) for neutropenia to 18.4 (10.1-33.4) for hyperkalemia. Lab-based labels were more similar by institution. When using lab-based labels as the gold standard, Cohen's Kappa and sensitivity were lower at SickKids for all severity levels compared to StanfordPeds. CONCLUSIONS: Across multiple outcomes, diagnosis codes were consistently different between the two pediatric institutions. This difference was not explained by differences in test results. These results may have implications for machine learning model development and deployment.

Prospective External Validation of the Esbenshade Vanderbilt Models Accurately Predicts Bloodstream Infection Risk in Febrile Non-Neutropenic Children With Cancer.

PURPOSE: The optimal management of fever without severe neutropenia (absolute neutrophil count [ANC] ≥500/µL) in pediatric patients with cancer is undefined. The previously proposed Esbenshade Vanderbilt (EsVan) models accurately predict bacterial bloodstream infections (BSIs) in this population and provide risk stratification to aid management, but have lacked prospective external validation. MATERIALS AND METHODS: Episodes of fever with a central venous catheter and ANC ≥500/µL occurring in pediatric patients with cancer were prospectively collected from 18 academic medical centers. Variables included in the EsVan models and 7-day clinical outcomes were collected. Five versions of the EsVan models were applied to the data with calculation of C-statistics for both overall BSI rate and high-risk organism BSI (gram-negative and Staphylococcus aureus BSI), as well as model calibration. RESULTS: In 2,565 evaluable episodes, the BSI rate was 4.7% (N = 120). Complications for the whole cohort were rare, with 1.1% (N = 27) needing intensive care unit (ICU) care by 7 days, and the all-cause mortality rate was 0.2% (N = 5), with only one potential infection-related death. C-statistics ranged from 0.775 to 0.789 for predicting overall BSI, with improved accuracy in predicting high-risk organism BSI (C-statistic 0.800-0.819). Initial empiric antibiotics were withheld in 14.9% of episodes, with no deaths or ICU admissions attributable to not receiving empiric antibiotics. CONCLUSION: The EsVan models, especially EsVan2b, perform very well prospectively across multiple academic medical centers and accurately stratify risk of BSI in episodes of non-neutropenic fever in pediatric patients with cancer. Implementation of routine screening with risk-stratified management for non-neutropenic fever in pediatric patients with cancer could safely reduce unnecessary antibiotic use.

Adjunctive Diagnostic Studies Completed Following Detection of Candidemia in Children: Secondary Analysis of Observed Practice From a Multicenter Cohort Study Conducted by the Pediatric Fungal Network.

BACKGROUND: Adjunctive diagnostic studies (aDS) are recommended to identify occult dissemination in patients with candidemia. Patterns of evaluation with aDS across pediatric settings are unknown. METHODS: Candidemia episodes were included in a secondary analysis of a multicenter comparative effectiveness study that prospectively enrolled participants age 120 days to 17 years with invasive candidiasis (predominantly candidemia) from 2014 to 2017. Ophthalmologic examination (OE), abdominal imaging (AbdImg), echocardiogram, neuroimaging, and lumbar puncture (LP) were performed per clinician discretion. Adjunctive diagnostic studies performance and positive results were determined per episode, within 30 days from candidemia onset. Associations of aDS performance with episode characteristics were evaluated via mixed-effects logistic regression. RESULTS: In 662 pediatric candidemia episodes, 490 (74%) underwent AbdImg, 450 (68%) OE, 426 (64%) echocardiogram, 160 (24%) neuroimaging, and 76 (11%) LP; performance of each aDS per episode varied across sites up to 16-fold. Longer durations of candidemia were associated with undergoing OE, AbdImg, and echocardiogram. Immunocompromised status (58% of episodes) was associated with undergoing AbdImg (adjusted odds ratio [aOR] 2.38; 95% confidence intervals [95% CI] 1.51-3.74). Intensive care at candidemia onset (30% of episodes) was associated with undergoing echocardiogram (aOR 2.42; 95% CI 1.51-3.88). Among evaluated episodes, positive OE was reported in 15 (3%), AbdImg in 30 (6%), echocardiogram in 14 (3%), neuroimaging in 9 (6%), and LP in 3 (4%). CONCLUSIONS: Our findings show heterogeneity in practice, with some clinicians performing aDS selectively, potentially influenced by clinical factors. The low frequency of positive results suggests that targeted application of aDS is warranted.

Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.

OBJECTIVE: Development of electronic health records (EHR)-based machine learning models for pediatric inpatients is challenged by limited training data. Self-supervised learning using adult data may be a promising approach to creating robust pediatric prediction models. The primary objective was to determine whether a self-supervised model trained in adult inpatients was noninferior to logistic regression models trained in pediatric inpatients, for pediatric inpatient clinical prediction tasks. MATERIALS AND METHODS: This retrospective cohort study used EHR data and included patients with at least one admission to an inpatient unit. One admission per patient was randomly selected. Adult inpatients were 18 years or older while pediatric inpatients were more than 28 days and less than 18 years. Admissions were temporally split into training (January 1, 2008 to December 31, 2019), validation (January 1, 2020 to December 31, 2020), and test (January 1, 2021 to August 1, 2022) sets. Primary comparison was a self-supervised model trained in adult inpatients versus count-based logistic regression models trained in pediatric inpatients. Primary outcome was mean area-under-the-receiver-operating-characteristic-curve (AUROC) for 11 distinct clinical outcomes. Models were evaluated in pediatric inpatients. RESULTS: When evaluated in pediatric inpatients, mean AUROC of self-supervised model trained in adult inpatients (0.902) was noninferior to count-based logistic regression models trained in pediatric inpatients (0.868) (mean difference = 0.034, 95% CI=0.014-0.057; P < .001 for noninferiority and P = .006 for superiority). CONCLUSIONS: Self-supervised learning in adult inpatients was noninferior to logistic regression models trained in pediatric inpatients. This finding suggests transferability of self-supervised models trained in adult patients to pediatric patients, without requiring costly model retraining.

Child and family perceptions of satisfaction with neutropenia management in pediatric acute myeloid leukemia.

PURPOSE: Chemotherapy for pediatric acute myeloid leukemia (AML) is very intensive and many, but not all centers, require extended hospitalization until neutrophil recovery. Child and family preferences, beliefs, and experiences around hospitalization have not been systematically assessed. PATIENTS AND METHODS: We recruited children with AML and their parents from nine pediatric cancer centers across the United States for a qualitative interview about their experiences of neutropenia management. Interviews were analyzed using a conventional content analysis approach. RESULTS: Of 116 eligible individuals, 86 (74.1%) agreed to participate. Interviews were conducted with 32 children and 54 parents from 57 families. Of these 57 families, 39 were cared for as inpatients and 18 were managed as outpatients. A very high proportion of respondents in both groups reported satisfaction with the discharge management strategy recommended by the treating institution: 86% (57 individuals) of respondents who experienced inpatient management and 85% (17 individuals) of respondents who experienced outpatient management expressed satisfaction. Respondent perceptions associated with satisfaction related to safety (access to emergency interventions, infection risk, close monitoring) and psychosocial concerns (family separation, low morale, social support). Respondents believed it could not be assumed that all children would have the same experience due to varied life circumstances. CONCLUSION: Children with AML and their parents express a very high degree of satisfaction with the discharge strategy recommended by their treating institution. Respondents saw a nuanced tradeoff between patient safety and psychosocial concerns that was mediated by a child's life circumstances.

Symptom management care pathway adaptation process and specific adaptation decisions.

BACKGROUND: There is substantial heterogeneity in symptom management provided to pediatric patients with cancer. The primary objective was to describe the adaptation process and specific adaptation decisions related to symptom management care pathways based on clinical practice guidelines. The secondary objective evaluated if institutional factors were associated with adaptation decisions. METHODS: Fourteen previously developed symptom management care pathway templates were reviewed by an institutional adaptation team composed of two clinicians at each of 10 institutions. They worked through each statement for all care pathway templates sequentially. The institutional adaptation team made the decision to adopt, adapt or reject each statement, resulting in institution-specific symptom management care pathway drafts. Institutional adaption teams distributed the 14 care pathway drafts to their respective teams; their feedback led to care pathway modifications. RESULTS: Initial care pathway adaptation decision making was completed over a median of 4.2 (interquartile range 2.0-5.3) weeks per institution. Across all institutions and among 1350 statements, 551 (40.8%) were adopted, 657 (48.7%) were adapted, 86 (6.4%) were rejected and 56 (4.1%) were no longer applicable because of a previous decision. Most commonly, the reason for rejection was not agreeing with the statement (70/86, 81.4%). Institutional-level factors were not significantly associated with statement rejection. CONCLUSIONS: Acceptability of the 14 care pathways was evident by most statements being adopted or adapted. The adaptation process was accomplished over a relatively short timeframe. Future work should focus on evaluation of care pathway compliance and determination of the impact of care pathway-consistent care on patient outcomes. TRIAL REGISTRATION: clinicaltrials.gov, NCT04614662. Registered 04/11/2020, https://clinicaltrials.gov/ct2/show/NCT04614662?term=NCT04614662&draw=2&rank=1 .

Survival outcomes of children with relapsed or refractory myeloid leukemia associated with Down syndrome.

Children with Down syndrome (DS) are at a significantly higher risk of developing acute myeloid leukemia, also termed myeloid leukemia associated with DS (ML-DS). In contrast to the highly favorable prognosis of primary ML-DS, the limited data that are available for children who relapse or who have refractory ML-DS (r/r ML-DS) suggest a dismal prognosis. There are few clinical trials and no standardized treatment approach for this population. We conducted a retrospective analysis of international study groups and pediatric oncology centers and identified 62 patients who received treatment with curative intent for r/r ML-DS between year 2000 to 2021. Median time from diagnosis to relapse was 6.8 (range, 1.1-45.5) months. Three-year event-free survival (EFS) and overall survival (OS) were 20.9 ± 5.3% and 22.1 ± 5.4%, respectively. Survival was associated with receipt of hematopoietic stem cell transplantation (HSCT) (hazard ratio [HR], 0.28), duration of first complete remission (CR1) (HR, 0.31 for > 12 months) and attainment of remission after relapse (HR, 4.03). Patients who achieved complete remission (CR) before HSCT, had an improved OS and EFS of 56.0 ± 11.8% and 50.5 ± 11.9%, respectively compared to those who underwent HSCT without CR (3-year OS and EFS of 10.0 ± 9.5%). Treatment failure after HSCT was predominantly because of disease recurrence (52%) followed by treatment-related mortality (10%). The prognosis of r/r ML-DS remains dismal even in the current treatment period and serve as a reference point for current prognostication and future interventional studies. Clinical trials aimed at improving the survival of patients with r/r ML-DS are needed.

Role of peripheral blood MRD and 18F-FDG PET in the post-CAR relapse setting: a case study of discordant peripheral blood and bone marrow MRD.

BACKGROUND: Chimeric antigen receptor (CAR) T cell therapy is an effective salvage therapy for pediatric relapsed B-cell acute lymphoblastic leukemia (B-ALL), yet is challenged by high rates of post-CAR relapse. Literature describing specific relapse patterns and extramedullary (EM) sites of involvement in the post-CAR setting remains limited, and a clinical standard for post-CAR disease surveillance has yet to be established. We highlight the importance of integrating peripheral blood minimal residual disease (MRD) testing and radiologic imaging into surveillance strategies, to effectively characterize and capture post-CAR relapse. MAIN BODY: Here, we describe the case of a child with multiply relapsed B-ALL who relapsed in the post-CAR setting with gross non-contiguous medullary and EM disease. Interestingly, her relapse was identified first from peripheral blood flow cytometry MRD surveillance, in context of a negative bone marrow aspirate (MRD <0.01%). Positron emission tomography with 18F-fluorodeoxyglucose revealed diffuse leukemia with innumerable bone and lymph node lesions, interestingly sparing her sacrum, the site of her bone marrow aspirate sampling. CONCLUSIONS: We highlight this case as both peripheral blood MRD and 18F-fluorodeoxyglucose positron emission tomography imaging were more sensitive than standard bone marrow aspirate testing in detecting this patient's post-CAR relapse. Clinical/Biologic Insight: In the multiply relapsed B-ALL setting, where relapse patterns may include patchy medullary and/or EM disease, peripheral blood MRD and/or whole body imaging, may carry increased sensitivity at detecting relapse in patient subsets, as compared with standard bone marrow sampling.

Evaluation of Feature Selection Methods for Preserving Machine Learning Performance in the Presence of Temporal Dataset Shift in Clinical Medicine.

BACKGROUND: Temporal dataset shift can cause degradation in model performance as discrepancies between training and deployment data grow over time. The primary objective was to determine whether parsimonious models produced by specific feature selection methods are more robust to temporal dataset shift as measured by out-of-distribution (OOD) performance, while maintaining in-distribution (ID) performance. METHODS: Our dataset consisted of intensive care unit patients from MIMIC-IV categorized by year groups (2008-2010, 2011-2013, 2014-2016, and 2017-2019). We trained baseline models using L2-regularized logistic regression on 2008-2010 to predict in-hospital mortality, long length of stay (LOS), sepsis, and invasive ventilation in all year groups. We evaluated three feature selection methods: L1-regularized logistic regression (L1), Remove and Retrain (ROAR), and causal feature selection. We assessed whether a feature selection method could maintain ID performance (2008-2010) and improve OOD performance (2017-2019). We also assessed whether parsimonious models retrained on OOD data performed as well as oracle models trained on all features in the OOD year group. RESULTS: The baseline model showed significantly worse OOD performance with the long LOS and sepsis tasks when compared with the ID performance. L1 and ROAR retained 3.7 to 12.6% of all features, whereas causal feature selection generally retained fewer features. Models produced by L1 and ROAR exhibited similar ID and OOD performance as the baseline models. The retraining of these models on 2017-2019 data using features selected from training on 2008-2010 data generally reached parity with oracle models trained directly on 2017-2019 data using all available features. Causal feature selection led to heterogeneous results with the superset maintaining ID performance while improving OOD calibration only on the long LOS task. CONCLUSIONS: While model retraining can mitigate the impact of temporal dataset shift on parsimonious models produced by L1 and ROAR, new methods are required to proactively improve temporal robustness.

Risk of bacterial bloodstream infection does not vary by central-line type during neutropenic periods in pediatric acute myeloid leukemia.

BACKGROUND: Bloodstream infections (BSIs) are a frequent cause of morbidity in patients with acute myeloid leukemia (AML), due in part to the presence of central venous access devices (CVADs) required to deliver therapy. OBJECTIVE: To determine the differential risk of bacterial BSI during neutropenia by CVAD type in pediatric patients with AML. METHODS: We performed a secondary analysis in a cohort of 560 pediatric patients (1,828 chemotherapy courses) receiving frontline AML chemotherapy at 17 US centers. The exposure was CVAD type at course start: tunneled externalized catheter (TEC), peripherally inserted central catheter (PICC), or totally implanted catheter (TIC). The primary outcome was course-specific incident bacterial BSI; secondary outcomes included mucosal barrier injury (MBI)-BSI and non-MBI BSI. Poisson regression was used to compute adjusted rate ratios comparing BSI occurrence during neutropenia by line type, controlling for demographic, clinical, and hospital-level characteristics. RESULTS: The rate of BSI did not differ by CVAD type: 11 BSIs per 1,000 neutropenic days for TECs, 13.7 for PICCs, and 10.7 for TICs. After adjustment, there was no statistically significant association between CVAD type and BSI: PICC incident rate ratio [IRR] = 1.00 (95% confidence interval [CI], 0.75-1.32) and TIC IRR = 0.83 (95% CI, 0.49-1.41) compared to TEC. When MBI and non-MBI were examined separately, results were similar. CONCLUSIONS: In this large, multicenter cohort of pediatric AML patients, we found no difference in the rate of BSI during neutropenia by CVAD type. This may be due to a risk-profile for BSI that is unique to AML patients.

Development of clinical pathways to improve multidisciplinary care of high-risk pediatric oncology patients.

Clinical pathways are evidence-based tools that have been integrated into many aspects of pediatric hospital medicine and have proven effective at reducing in-hospital complications from a variety of diseases. Adaptation of similar tools for specific, high-risk patient populations in pediatric oncology has been slower, in part due to patient complexities and variations in management strategies. There are few published studies of clinical pathways for pediatric oncology patients. Pediatric patients with a new diagnosis of leukemia or lymphoma often present with one or more "oncologic emergencies" that require urgent intervention and deliberate multidisciplinary care to prevent significant consequences. Here, we present two clinical pathways that have recently been developed using a multidisciplinary approach at a single institution, intended for the care of patients who present with hyperleukocytosis or an anterior mediastinal mass. These clinical care pathways have provided a critical framework for the immediate care of these patients who are often admitted to the pediatric intensive care unit for initial management. The goal of the pathways is to facilitate multidisciplinary collaborations, expedite diagnosis, and streamline timely treatment initiation. Standardizing the care of high-risk pediatric oncology patients will ultimately decrease morbidity and mortality associated with these diseases to increase the potential for excellent outcomes.

Perspective Toward Machine Learning Implementation in Pediatric Medicine: Mixed Methods Study.

BACKGROUND: Given the costs of machine learning implementation, a systematic approach to prioritizing which models to implement into clinical practice may be valuable. OBJECTIVE: The primary objective was to determine the health care attributes respondents at 2 pediatric institutions rate as important when prioritizing machine learning model implementation. The secondary objective was to describe their perspectives on implementation using a qualitative approach. METHODS: In this mixed methods study, we distributed a survey to health system leaders, physicians, and data scientists at 2 pediatric institutions. We asked respondents to rank the following 5 attributes in terms of implementation usefulness: the clinical problem was common, the clinical problem caused substantial morbidity and mortality, risk stratification led to different actions that could reasonably improve patient outcomes, reducing physician workload, and saving money. Important attributes were those ranked as first or second most important. Individual qualitative interviews were conducted with a subsample of respondents. RESULTS: Among 613 eligible respondents, 275 (44.9%) responded. Qualitative interviews were conducted with 17 respondents. The most common important attributes were risk stratification leading to different actions (205/275, 74.5%) and clinical problem causing substantial morbidity or mortality (177/275, 64.4%). The attributes considered least important were reducing physician workload and saving money. Qualitative interviews consistently prioritized implementations that improved patient outcomes. CONCLUSIONS: Respondents prioritized machine learning model implementation where risk stratification would lead to different actions and clinical problems that caused substantial morbidity and mortality. Implementations that improved patient outcomes were prioritized. These results can help provide a framework for machine learning model implementation.

Management of Chronic Myeloid Leukemia in Children and Young Adults.

PURPOSE OF REVIEW: Due to lack of pediatric-specific data, the management of chronic myeloid leukemia (CML) in pediatric, adolescents, and young adults is guided by adult CML evidence-based recommendations. Pediatric CML presents differently than adult CML and is often a more aggressive disease with different biological and host factors, yet there is sparse literature on how to address those differences. RECENT FINDINGS: Over the past two decades, tyrosine kinase inhibitors (TKIs) have changed the way CML is treated. There are currently three FDA-approved TKIs (imatinib, dasatinib, and nilotinib) for pediatric patients. When choosing which TKI to begin treatment with, there are many factors that should be considered on a case-to-case basis to obtain optimal outcomes. The safety profiles for long-term TKI use in pediatrics require further study. Unlike adults, children are still actively growing during TKI use, and the effect on development can be detrimental. TKI therapy is not recommended during pregnancy with variable but significant risk of fetal abnormalities and miscarriage, warranting counseling for young female patients prior to beginning TKIs. Attempts for treatment-free remission (TFR) by planned TKI cessation in eligible adult patients in deep and sustained molecular remission are now done as a standard of practice. However, data is sparse in the pediatric population. There is currently an ongoing Children's Oncology Group (COG) study to determine the feasibility of TFR as a treatment goal. Further research and additional pediatric trials are needed to characterize the unique aspects of CML in children and adolescents and optimize outcomes.

Clostridioides difficile infection in paediatric patients with cancer and haematopoietic stem cell transplant recipients.

BACKGROUND: Epidemiology of Clostridioides difficile infection (CDI) in paediatric cancer patients is uncertain. The primary objective was to describe the prevalence of CDI outcomes among paediatric patients receiving cancer treatments. Secondary objectives were to describe clinical features of CDI, propose a definition of severe CDI and to determine risk factors for CDI clinical outcomes. METHODS: A multi-centre retrospective cohort study that included paediatric patients (1-18 years of age) receiving cancer treatments with CDI. Severe CDI definition was achieved by consensus. Univariable and multivariable regression was conducted to evaluate risk factors for CDI outcomes. RESULTS: There were 627 eligible patients who experienced 721 CDI episodes. The prevalence of clinical cure was 82.9%, recurrence was 9.6%, global cure was 75.0% and repeated new CDI episode was 12.8%. The proposed definition of severe CDI was the presence of colitis, pneumatosis intestinalis, pseudomembranous colitis, ileus or surgery for CDI, occurring in 70 (9.7%) episodes. In univariable regression, initial oral metronidazole or initial oral vancomycin were not significantly associated with failure to achieve clinical cure or CDI recurrence. In multiple regression, oral metronidazole was significantly associated with higher odds (odds ratio (OR) 1.7, 95% confidence interval (CI) 1.0-2.7) and oral vancomycin was significantly associated with lower odds (OR 0.4, 95% CI 0.2-0.8) of repeated new episodes. CONCLUSION: The prevalence of clinical cure was 82.9% and recurrence was 9.6% in pediatric patients receiving cancer treatments. Severe CDI, as per our proposed definition, occurred in 9.7% episodes. Initial oral vancomycin was significantly associated with a reduction in repeated new CDI episodes.

Neutropenia and Infection Prophylaxis in Childhood Cancer.

PURPOSE OF REVIEW: Pediatric oncology patients frequently experience episodes of prolonged neutropenia which puts them at high risk for infection with significant morbidity and mortality. Here, we review the data on infection prophylaxis with a focus on both pharmacologic and ancillary interventions. This review does not include patients receiving hematopoietic stem cell transplantation. RECENT FINDINGS: Patients with hematologic malignancies are at highest risk for infection. Bacterial and fungal prophylaxis decrease the risk of infection in certain high-risk groups. Ancillary measures such as ethanol locks, chlorhexidine gluconate baths, GCSF, IVIG, and mandatory hospitalization do not have enough data to support routine use. There is limited data on risk of infection and role of prophylaxis in patients receiving immunotherapy and patients with solid tumors. Patients with Down syndrome and adolescent and young adult patients may benefit from additional supportive care measures and protocol modifications. Consider utilizing bacterial and fungal prophylaxis in patients with acute myeloid leukemia or relapsed acute lymphoblastic leukemia. More research is needed to evaluate other supportive care measures and the role of prophylaxis in patients receiving immunotherapy.

Breakthrough Trichosporon asahii in a Patient With New Diagnosis B-ALL on Echinocandin Prophylaxis: A Case Report.

Invasive fungal disease is a difficult to diagnose complication of therapy in patients with hematologic malignancy. Antifungal prophylaxis is recommended in high-risk populations, but its use in other populations is less clear. This brief report describes a patient with Trisomy 21 on caspofungin prophylaxis who died of disseminated Trichosporon asahii during induction therapy for new diagnosis low-risk B-cell acute lymphoblastic leukemia, accompanied by a review of similar cases in the literature. Her case highlights the utility of relatively novel diagnostic modalities and reinforces the need for caution in placing patients on antifungal prophylaxis.

Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine.

Temporal dataset shift associated with changes in healthcare over time is a barrier to deploying machine learning-based clinical decision support systems. Algorithms that learn robust models by estimating invariant properties across time periods for domain generalization (DG) and unsupervised domain adaptation (UDA) might be suitable to proactively mitigate dataset shift. The objective was to characterize the impact of temporal dataset shift on clinical prediction models and benchmark DG and UDA algorithms on improving model robustness. In this cohort study, intensive care unit patients from the MIMIC-IV database were categorized by year groups (2008-2010, 2011-2013, 2014-2016 and 2017-2019). Tasks were predicting mortality, long length of stay, sepsis and invasive ventilation. Feedforward neural networks were used as prediction models. The baseline experiment trained models using empirical risk minimization (ERM) on 2008-2010 (ERM[08-10]) and evaluated them on subsequent year groups. DG experiment trained models using algorithms that estimated invariant properties using 2008-2016 and evaluated them on 2017-2019. UDA experiment leveraged unlabelled samples from 2017 to 2019 for unsupervised distribution matching. DG and UDA models were compared to ERM[08-16] models trained using 2008-2016. Main performance measures were area-under-the-receiver-operating-characteristic curve (AUROC), area-under-the-precision-recall curve and absolute calibration error. Threshold-based metrics including false-positives and false-negatives were used to assess the clinical impact of temporal dataset shift and its mitigation strategies. In the baseline experiments, dataset shift was most evident for sepsis prediction (maximum AUROC drop, 0.090; 95% confidence interval (CI), 0.080-0.101). Considering a scenario of 100 consecutively admitted patients showed that ERM[08-10] applied to 2017-2019 was associated with one additional false-negative among 11 patients with sepsis, when compared to the model applied to 2008-2010. When compared with ERM[08-16], DG and UDA experiments failed to produce more robust models (range of AUROC difference, - 0.003 to 0.050). In conclusion, DG and UDA failed to produce more robust models compared to ERM in the setting of temporal dataset shift. Alternate approaches are required to preserve model performance over time in clinical medicine.

Molecular and phenotypic diversity of CBL-mutated juvenile myelomonocytic leukemia.

Mutations in the gene CBL were first identified in adults with various myeloid malignancies. Some patients with juvenile myelomonocytic leukemia (JMML) were also noted to harbor mutations in CBL, but were found to have generally less aggressive disease courses compared to other forms of Ras pathway-mutant JMML. Importantly, and in contrast to most reports in adults, the majority of CBL mutations in JMML patients are germline with acquired uniparental disomy occurring in affected marrow cells. Here, we systematically studied a large cohort of 33 JMML patients with CBL mutations and found this disease to be highly diverse in presentation and overall outcome. Moreover, we discovered somatically-acquired CBL mutations in 15% of pediatric patients who presented with more aggressive disease. Neither clinical features nor methylation profiling were able to distinguish somatic CBL patients from germline CBL patients, highlighting the need for germline testing. Overall, we demonstrate that disease courses are quite heterogeneous even among germline CBL patients. Prospective clinical trials are warranted to find ideal treatment strategies for this diverse cohort of patients.