Rapid identification of inflammatory arthritis and associated adverse events following immune checkpoint therapy: a machine learning approach.

Introduction: Immune checkpoint inhibitor-induced inflammatory arthritis (ICI-IA) poses a major clinical challenge to ICI therapy for cancer, with 13% of cases halting ICI therapy and ICI-IA being difficult to identify for timely referral to a rheumatologist. The objective of this study was to rapidly identify ICI-IA patients in clinical data and assess associated immune-related adverse events (irAEs) and risk factors. Methods: We conducted a retrospective study of the electronic health records (EHRs) of 89 patients who developed ICI-IA out of 2451 cancer patients who received ICI therapy at Northwestern University between March 2011 to January 2021. Logistic regression and random forest machine learning models were trained on all EHR diagnoses, labs, medications, and procedures to identify ICI-IA patients and EHR codes indicating ICI-IA. Multivariate logistic regression was then used to test associations between ICI-IA and cancer type, ICI regimen, and comorbid irAEs. Results: Logistic regression and random forest models identified ICI-IA patients with accuracies of 0.79 and 0.80, respectively. Key EHR features from the random forest model included ICI-IA relevant features (joint pain, steroid prescription, rheumatoid factor tests) and features suggesting comorbid irAEs (thyroid function tests, pruritus, triamcinolone prescription). Compared to 871 adjudicated ICI patients who did not develop arthritis, ICI-IA patients had higher odds of developing cutaneous (odds ratio [OR]=2.66; 95% Confidence Interval [CI] 1.63-4.35), endocrine (OR=2.09; 95% CI 1.15-3.80), or gastrointestinal (OR=2.88; 95% CI 1.76-4.72) irAEs adjusting for demographics, cancer type, and ICI regimen. Melanoma (OR=1.99; 95% CI 1.08-3.65) and renal cell carcinoma (OR=2.03; 95% CI 1.06-3.84) patients were more likely to develop ICI-IA compared to lung cancer patients. Patients on nivolumab+ipilimumab were more likely to develop ICI-IA compared to patients on pembrolizumab (OR=1.86; 95% CI 1.01-3.43). Discussion: Our machine learning models rapidly identified patients with ICI-IA in EHR data and elucidated clinical features indicative of comorbid irAEs. Patients with ICI-IA were significantly more likely to also develop cutaneous, endocrine, and gastrointestinal irAEs during their clinical course compared to ICI therapy patients without ICI-IA.

Predictive Value of Relative Apical Sparing of Longitudinal Strain on Echocardiography for Cardiac Amyloidosis.

Relative apical longitudinal sparing (RALS) on echocardiography has become an increasingly used tool to evaluate for cardiac amyloidosis (CA), but the predictive value of this finding remains unclear. This is a retrospective analysis at a single tertiary care center across 3 years. Patients were included if they had RALS, defined by strain ratio ≥2.0 on echocardiography, and sufficient laboratory, imaging, or histopathologic workup to indicate their likelihood of CA. Patients were stratified by their likelihood of CA, and contributions of other co-morbidities previously shown to be associated with RALS. Of the 220 patients who had adequate workup to determine their likelihood of having CA, 50 (22.7%) had confirmed CA, 35 (15.9%) had suspicious CA, 83 (37.7%) had unlikely CA, and 52 (23.7%) had ruled-out CA. The positive predictive value of RALS for CA was 38.6% for confirmed or suspicious CA. The remaining 61.4% of patients who were unlikely or ruled out for CA had other co-morbidities such as hypertension, chronic kidney disease, malignancy, or aortic stenosis, 17.0% of this group had none of these co-morbidities. In our tertiary care cohort of patients with RALS pattern on echocardiography, we found that fewer than half of patients with RALS were likely to have CA. Given the increasing use of strain technology, further studies are warranted to determine the optimal strategy for assessing CA in a patient with RALS.

Neurological applications of belzutifan in von Hippel-Lindau disease.

Von Hippel-Lindau (VHL) disease is a tumor predisposition syndrome caused by mutations in the VHL gene that presents with visceral neoplasms and growths, including clear cell renal cell carcinoma, and central nervous system manifestations, such as hemangioblastomas of the brain and spine. The pathophysiology involves dysregulation of oxygen sensing caused by the inability to degrade HIFα, leading to the overactivation of hypoxic pathways. Hemangioblastomas are the most common tumors in patients with VHL and cause significant morbidity. Until recently, there were no systemic therapies available for patients that could effectively reduce the size of these lesions. Belzutifan, the first approved HIF-2α inhibitor, has demonstrated benefit in VHL-associated tumors, with a 30% response rate in hemangioblastomas and ~30%-50% reduction in their sizes over the course of treatment. Anemia is the most prominent adverse effect, affecting 76%-90% of participants and sometimes requiring dose reduction or transfusion. Other significant adverse events include hypoxia and fatigue. Overall, belzutifan is well tolerated; however, long-term data on dosing regimens, safety, and fertility are not yet available. Belzutifan holds promise for the treatment of neurological manifestations of VHL and its utility may influence the clinical management paradigms for this patient population.

Severity of Illness Caused by Severe Acute Respiratory Syndrome Coronavirus 2 Variants of Concern in Children: A Single-Center Retrospective Cohort Study.

BACKGROUND: Recent COVID-19 surges are attributed to emergence of more transmissible SARS-CoV-2 variants of concern (VOCs). The relative severity of VOCs in children is unknown. METHODS: We performed a single-center retrospective cohort study of children ≤18 years old diagnosed with COVID-19 from October 2020-February 2022 and whose SARS-CoV-2 isolate underwent Illumina sequencing. We measured the frequency of five markers of COVID-19 severity. Logistic regression models were fitted to estimate the odds of each severity marker with each VOC. RESULTS: Among 714 children, 471 (66.0%) were infected with a VOC: 96 (13.4%) alpha, 38 (5.3%) gamma, 119 (16.7%) delta, and 215 (30.1%) omicron. High-risk medical conditions and increasing age were independently associated with COVID-19 severity. After adjusting for age, race, ethnicity, high-risk medical conditions, and COVID-19 community incidence, neither alpha, delta, nor omicron was associated with severe COVID-19. Gamma was independently associated with hospitalization (OR 6.7, 95% CI 2.0-22.1); pharmacologic treatment (OR 5.7, 95% CI 1.2-26.8); respiratory support (OR 11.9, 95% CI 2.7-62.4); and severe disease per the WHO Clinical Progression Scale (OR 11.7, 95% CI 2.1-90.5). Upon subgroup analyses, omicron was independently associated with ICU admission and severe disease per the WHO Clinical Progression Scale in children without SARS-CoV-2 immunization or prior COVID-19 infection. CONCLUSIONS: Compared to non-VOC COVID-19, the gamma VOC was independently associated with increased COVID-19 severity, as was omicron in children without SARS-CoV-2 immunization or prior COVID-19 infection. SARS-CoV-2 vaccination and prior COVID-19 prevented severe outcomes during the omicron surge.

Genome-wide promoter assembly in E. coli measured at single-base resolution.

When detected at single-base-pair resolution, the genome-wide location, occupancy level, and structural organization of DNA-binding proteins provide mechanistic insights into genome regulation. Here we use ChIP-exo to provide a near-base-pair resolution view of the epigenomic organization of the Escherichia coli transcription machinery and nucleoid structural proteins at the time when cells are growing exponentially and upon rapid reprogramming (acute heat shock). We examined the site specificity of three sigma factors (RpoD/σ70, RpoH/σ32, and RpoN/σ54), RNA polymerase (RNAP or RpoA, -B, -C), and two nucleoid proteins (Fis and IHF). We suggest that DNA shape at the flanks of cognate motifs helps drive site specificity. We find that although RNAP and sigma factors occupy active cognate promoters, RpoH and RpoN can occupy quiescent promoters without the presence of RNAP. Thus, promoter-bound sigma factors can be triggered to recruit RNAP by a mechanism that is distinct from an obligatory cycle of free sigma binding RNAP followed by promoter binding. These findings add new dimensions to how sigma factors achieve promoter specificity through DNA sequence and shape, and further define mechanistic steps in regulated genome-wide assembly of RNAP at promoters in E. coli.

Severity of Illness Caused by Severe Acute Respiratory Syndrome Coronavirus 2 Variants of Concern in Children: A Single-Center Retrospective Cohort Study.

BACKGROUND: Recent surges in coronavirus 2019 disease (COVID-19) is attributed to the emergence of more transmissible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs). However, the relative severity of SARS-CoV-2 VOCs in children is unknown. METHODS: This retrospective single-center cohort study was performed at the Ann & Robert H. Lurie Children's Hospital of Chicago, academic free-standing children's hospital. We included all children ≤ 18 years-old diagnosed with COVID-19 between October 15 th , 2020 and August 31 st , 2021 and whose SARS-CoV-2 isolate was sequenced using the Illumina platform. For each patient sample, we identified the SARS-CoV-2 lineage, which was assigned to one of the following groups: Non-VOC, alpha VOC, beta VOC, gamma VOC, or delta VOC. We measured frequency of 5 markers of COVID-19 severity: hospitalization; COVID-19 pharmacologic treatment; respiratory support; intensive care unit admission; and severe disease as classified by the COVID-19 World Health Organization (WHO) Clinical Progression Scale (severe disease; score ≥ 6). A series of logistic regression models were fitted to estimate odds of each severity marker with each VOC (in comparison to non-VOCs), adjusting for COVID-19 community incidence and demographic and clinical co-variates. RESULTS: During the study period, 2,025 patients tested positive for SARS-CoV-2; 1,422 (70.2%) had sufficient viral load to permit sequencing. Among the 499 (35.1%) patients whose isolate was sequenced, median (inter-quartile range) age was 7 (1,12) years; 256 (51.3%) isolates were a VOC: 96 (37.5%) alpha, 38 (14.8%) gamma, and 119 (46.5%) delta. After adjusting for age, Black race, Hispanic ethnicity, high-risk medical conditions, and COVID-19 community incidence, neither alpha nor delta was associated with severe COVID-19. Gamma was independently associated with hospitalization (OR 5.9, 95% CI 1.6-21.5, p =0.007), respiratory support (OR 8.3, 95% CI 1.5-56.3, p =0.02), and severe disease as classified by the WHO Clinical Progression Scale (OR 7.7, 95% CI 1.0-78.1, p =0.05). CONCLUSIONS: Compared to non-VOC COVID-19 infections, the gamma VOC, but not the alpha or delta VOCs, was associated with increased severity. These data suggest that recent increased in pediatric COVID-19 hospitalizations are related to increased delta COVID-19 incidence rather than increased delta virulence in children.

Electronic Health Record Network Research in Infectious Diseases.

With the marked increases in electronic health record (EHR) use for providing clinical care, there have been parallel efforts to leverage EHR data for research. EHR repositories offer the promise of vast amounts of clinical data not easily captured with traditional research methods and facilitate clinical epidemiology and comparative effectiveness research, including analyses to identify patients at higher risk for complications or who are better candidates for treatment. These types of studies have been relatively slow to penetrate the field of infectious diseases, but the need for rapid turnaround during the COVID-19 global pandemic has accelerated the uptake. This review discusses the rationale for her network projects, opportunities and challenges that such networks present, and some prior studies within the field of infectious diseases.