New Cohort Of Patients Research Articles

Social work practice for COVID-19 in the acute hospital setting: Recommendations for psychosocial assessment

Abstract The global coronavirus SARS-CoV2 (COVID-19) pandemic outbreak caused immediate, far-reaching social schisms and created unprecedented challenges for hospital social work services worldwide. Existing hospital disaster plans were inadequately equipped for pandemics and organisational plans needed to quickly adapt to respond to the increased clinical demands and unique logistical considerations triggered by the virus. Literature reviews provided little in the way of precise guidance for practitioners. Hospital social workers responded not only to a new cohort of patients, but also to all patients affected by the societal repercussions of the pandemic and by governments’ attempts to mitigate the impacts of the virus. Psychosocial assessments, the bedrock of social work intervention, needed to adapt and evolve to encompass and address the exacerbation of existing social risks in new ways. This article originated from the authors’ interest in identifying practice implications for hospital social work during the COVID-19 pandemic. The authors briefly outline the distinct impact of COVID-19 on psychosocial issues such as domestic and family violence, elder abuse, child protection, financial stress and social isolation. They create a forum of international hospital social work centres to develop a consensus approach for addressing these issues in the context of a social work psychosocial assessment.

MPN-390: Study Design and Objectives for a New Cohort of Patients with Myelofibrosis (MF) Enrolled in the Ongoing Connect® Myeloid Disease Registry

<h3>Context</h3> MF is a life-threatening type of myeloproliferative neoplasm (MPN) with significant morbidity and mortality. Current treatments aim to manage symptoms, improve anemia, and delay progression to acute myeloid leukemia (AML); however, limited real-world data hinder understanding of the safety and effectiveness of emerging therapies and the association between treatment patterns and patient outcomes. <h3>Objective</h3> To examine the effectiveness and safety of different therapeutics, treatment patterns, clinical outcomes, and patient-reported outcomes (PROs) in patients with MF or MF-related cytopenias. <h3>Design</h3> The Connect® Myeloid Disease Registry (NCT01688011; formerly Connect® MDS/AML Disease Registry) is a large, US, multicenter, prospective study of patients with newly diagnosed AML or myelodysplastic syndromes (MDS; Steensma et al. <i>BMC Cancer</i> 2016). A new cohort of patients diagnosed with MF began enrollment in February 2021. <h3>Patients</h3> Eligible patients are ≥18 years of age, must have an MF diagnosis (primary or secondary MF) and have initiated therapy ≤60 days prior to informed consent. 800 patients (n=400 patients receiving first active systemic treatment for MF and n=400 patients receiving treatment for MF-related cytopenias) will be enrolled at 200–250 sites. Patients with MDS/MPN overlap syndromes are also eligible. Patients who have a suspected or proven juvenile myelomonocytic leukemia diagnosis or are currently enrolled in any interventional clinical trial where the investigational product cannot be identified are not eligible. <h3>Main Outcome Measures</h3> All diagnoses, treatments, and laboratory testing are at the discretion of the treating physician, in accordance with standard clinical practice at each site. Health status, clinical response (by MFSAF, spleen size, transfusion burden, and bone marrow biopsy), overall survival, adverse drug reactions, serious adverse events (AEs), and protocol-defined AEs of interest will be collected. PRO data will be assessed using the MFSAF V.4, FACT-An, and EQ-5D-3L questionnaires. Patients may consent to an optional biomarker tissue sub-study. Patient data will be reported at baseline and quarterly for ≤5 years or until early termination, withdrawal, or death. <h3>Conclusions</h3> Data collected in the MF cohort of the Registry will increase understanding of the clinical effectiveness, safety, and PRO of current treatment strategies for patients with MF. This is a BMS-sponsored study.

Poster: MPN-390: Study Design and Objectives for a New Cohort of Patients with Myelofibrosis (MF) Enrolled in the Ongoing Connect® Myeloid Disease Registry

Poster: MPN-390: Study Design and Objectives for a New Cohort of Patients with Myelofibrosis (MF) Enrolled in the Ongoing Connect® Myeloid Disease Registry

Creation of mortality risk calculator using a I-123 mIBG-based machine learning model: differential prediction of arrhythmic death and heart-failure death

Abstract Funding Acknowledgements Type of funding sources: None. Background Although I-123 meta-iodobenzylguanidine (mIBG) has been applied to patients with chronic heart failure (CHF), a diagnostic tool for differential prediction of fatal arrhythmic events (ArE) and heart-failure death (HFD) has been pursued. Purpose The aim of this study was to create a calculator of mortality risk for differentiating mode of cardiac death using a machine learning (ML) method, and to test the accuracy in a new cohort of patients with CHF. Methods A total of 529 patients with CHF was used as the training database for ML. The ArE group consisted of patients with arrhythmic death, sudden cardiac death and appropriate therapy by implantable cardioverter defibrillator. A heart-to-mediastinum ratio (H/M) standardized to the medium-energy collimator condition was calculated with a planar anterior mIBG scintigram. The best classifier models for predicting HFD and ArE were determined by four-fold cross validation. Input variables included age, sex, New York Heart Association (NYHA) functional class, left ventricular ejection fraction, ischemic etiology, mIBG H/M and washout rate, and b-type natriuretic peptide (BNP) or NT Pro BNP, estimated glomerular filtration rate, hemoglobin, and complications such as diabetes and hypertension. After creating the ML-based model, the constructed classifier functions for ArE, HFD, and survival were exported for subsequent use. A new cohort of patients (n = 312, age 67 ± 13 years, 2015 or later) was used to test the ML-based model. Results The training database included 141 events (27%) with ArE (7%) and HFD (20%). Receiver-operating characteristic analysis by four-fold validation showed area under the curve value of 0.90 for HFD and 0.73 for ArE. Among various ML methods, the logistic regression method demonstrated the most stable calculation of the probability of ArE followed by random forest and gradient boosted tree methods. Therefore, the logistic-regression method was used for calculating both HFD and ArE probabilities. In the test cohort, patients with a high HFD probability &amp;gt;8% resulted in 6.3-fold higher HFD than those with low probability (≤ 8%). Patients with high ArE probability &amp;gt;8% showed 2.5-fold higher ArE than those with low probability (≤ 8%). Conclusion The ML-based mortality risk calculator could be used for stratifying patients at high and low risks, which might be useful for estimating appropriate treatment strategy.

Increasing sample diversity in psychiatric genetics – Introducing a new cohort of patients with schizophrenia and controls from Vietnam – Results from a pilot study

Objectives Genome-Wide Association Studies (GWAS) of Schizophrenia (SCZ) have provided new biological insights; however, most cohorts are of European ancestry. As a result, derived polygenic risk scores (PRS) show decreased predictive power when applied to populations of different ancestries. We aimed to assess the feasibility of a large-scale data collection in Hanoi, Vietnam, contribute to international efforts to diversify ancestry in SCZ genetic research and examine the transferability of SCZ-PRS to individuals of Vietnamese Kinh ancestry. Methods In a pilot study, 368 individuals (including 190 SCZ cases) were recruited at the Hanoi Medical University's associated psychiatric hospitals and outpatient facilities. Data collection included sociodemographic data, baseline clinical data, clinical interviews assessing symptom severity and genome-wide SNP genotyping. SCZ-PRS were generated using different training data sets: (i) European, (ii) East-Asian and (iii) trans-ancestry GWAS summary statistics from the latest SCZ GWAS meta-analysis. Results SCZ-PRS significantly predicted case status in Vietnamese individuals using mixed-ancestry (R2 liability = 4.9%, p = 6.83 × 10−8), East-Asian (R2 liability = 4.5%, p = 2.73 × 10−7) and European (R2 liability = 3.8%, p = 1.79 × 10−6) discovery samples. Discussion Our results corroborate previous findings of reduced PRS predictive power across populations, highlighting the importance of ancestral diversity in GWA studies.

Identification of Novel Mutations in CDC20: Expanding the Mutational Spectrum for Female Infertility.

Oocyte maturation and fertilization are fundamental processes for successful human reproduction, and abnormalities in these processes will cause infertility. Recently, we identified biallelic mutations in CDC20 that are responsible for human oocyte maturation arrest, fertilization failure, and early embryonic development arrest. In this study, we screened for further CDC20 mutations in a new cohort of patients with abnormalities in oocyte maturation, fertilization, and early embryonic development. Through whole-exome sequencing, we identified the four novel mutations c.887G > A (p. Arg296Gln), c.964C > T (p.Arg322∗), c.1155G > C (p.Trp385Cys), and c.330 + 1G > A (p. Glu111Ilefs∗36) and one previously reported mutation c.965G > A (p.Arg322Gln) in CDC20 in four infertile individuals from three independent families. The patients had different phenotypes of oocyte maturation arrest and fertilization failure resulting from the different mutations. This study confirms our previous research and expands the spectrum of known mutations in CDC20, providing new evidence supporting the function of CDC20 in the genetic etiology of female infertility characterized by oocyte maturation arrest and fertilization failure.

Biomarkers and key pathways in atrial fibrillation associated with mitral valve disease identified by multi-omics study.

BackgroundMitral valve disease (MVD)-associated atrial fibrillation (AF) is one of the most common arrhythmias with an increased risk of thromboembolic events. This study aimed to identify the molecular mechanisms and possible biomarkers for chronic AF in MVD by using multi-omics methods.MethodsThis prospective study enrolled patients with MVD (n=100) undergoing mitral valve replacement surgery. The patients were allocated into chronic AF and sinus rhythm (SR) groups. Plasma samples were collected preoperatively. Proteomics was performed with isobaric tags for relative and absolute quantitation (iTRAQ) to identify differential proteins (DPs) between the two groups. The selected DPs were then validated in a new cohort of patients by enzyme-linked immunosorbent assay (ELISA). A gas chromatography-mass spectrometer was used in the metabolomics study to identify differential metabolites (DMs). Bioinformatics analyses were performed to analyze the results.ResultsAmong the 447 plasma proteins and 322 metabolites detected, 57 proteins and 55 metabolites, including apolipoprotein A-I (ApoA-I), apolipoprotein A-II (ApoA-II), LIM domain only protein 7 (LMO7), and vitronectin (VN) were differentially expressed between AF and SR patients. Bioinformatics analyses identified enriched pathways related to AF, including peroxisome proliferator-activated receptor alpha (PPARα), the renin angiotensin aldosterone system (RAAS), galactose, biosynthesis of unsaturated fatty acids, and linoleic acid metabolism.ConclusionsUsing integrated multi-omics technologies in MVD-associated AF patients, the present study, for the first time, revealed important signaling pathways, such as PPARα, as well as possible roles of other signaling pathways, including the RAAS and galactose metabolism to understand the molecular mechanism of MVD-associated AF. It also identified a large number of DPs and DMs. Some identified proteins and metabolites, such as ApoA-I, ApoA-II, LMO7, and VN, may be further developed as biomarkers for MVD-associated AF.

Change-point joint model for identification of plateau of activity in early phase trials.

This article presents a phase I/II trial design for targeted therapies and immunotherapies, with the objective of identifying the optimal dose (OD). We employ a joint modeling technique for discrete time-to-event toxicity data and repeated and continuous biomarker measurements. For the biomarker measurements, we implement a change point linear mixed effects skeleton model. This model can accommodate both plateauing and nonplateauing dose-activity relationships. For each new cohort of patients, we estimate the maximum tolerated dose (MTD) taking toxicity as a cumulative endpoint, over six treatment cycles. Then, we select the OD using two different criteria. The OD is a dose that is equally active to the MTD or a dose located on the beginning of the plateau of the dose-activity relationship. Joint modeling allows us to take into account informative censoring due to toxicities or lack of activity and we also consider consent withdrawal and intermittent missing responses. Model estimation relies on likelihood inference.

New Cohort of Patients With CEDNIK Syndrome Expands the Phenotypic and Genotypic Spectra.

ObjectiveTo report 6 new patients with cerebral dysgenesis, neuropathy, ichthyosis, and keratoderma (CEDNIK) syndrome.MethodsClinical exome or targeted sequencing were performed to elucidate the molecular genetic cause in patients with neurocognitive abnormalities and brain imaging findings.ResultsCEDNIK syndrome is a rare genetic condition caused by biallelic pathogenic loss-of-function variants in synaptosomal-associated protein 29 (SNAP29), which encodes a vesicular membrane fusion protein. Clinical manifestations include significant developmental delay/intellectual disability (DD/ID), brain abnormalities, failure to thrive, and skin abnormalities. To date, 19 patients from 10 unrelated families with CEDNIK syndrome have been reported. We report 5 additional patients with homozygous predicted loss-of-function variants in SNAP29 and one with compound heterozygous variants: a frameshift SNAP29 variant and a 370 kb deletion on 22q11.2. All patients exhibit DD/ID, ichthyosis and/or palmoplantar keratoderma, and hypotonia. Four of 6 subjects had hypomyelinated white matter on MRI, 2 of 6 had early puberty, and 4 of 6 had strabismus, which were previously rarely reported. Other phenotypes were variably present, including dysmorphic features, feeding difficulties, and recurrent respiratory infections. The cohort includes 2 siblings with a c.2T>C variant who have a relatively milder phenotype, a patient with the most C-terminal variant yet described (c.622G>T), and 3 patients with previously described variants (c.354dupG, c.487dupA).ConclusionsThis cohort of 6 additional patients expands the genotypic and phenotypic spectrum of CEDNIK syndrome, highlighting previously under-recognized features such as hypomyelination, seizures, and early puberty. Owing to reduced penetrance of the skin phenotype, cerebral dysgenesis, and neuropathy, we propose renaming this syndrome SNAP29-related disorder.

Increased frequency of canine distemper virus-specific antibodies in multiple sclerosis.

Background and purposeCanine distemper virus (CDV) is a candidate agent in the etiology of multiple sclerosis (MS). Elevated anti‐CDV levels were previously found in the sera from MS patients compared with controls. We now investigated whether there was an age‐related association with the presence of antibodies specific to CDV‐hemagglutinin (H) protein in MS.MethodsSera from patients with MS, other neurological diseases, and inflammatory and/or autoimmune diseases, and healthy individuals were screened for anti‐CDV in an ELISA using linear peptides of the CDV‐H protein as antigen. Antibody levels to measles and varicella‐zoster virus were measured and served as controls.ResultsAnalysis of the new cohort of MS patients and controls confirmed our initial finding of elevated anti‐CDV‐H levels in MS patients. An increase in measles but not varicella‐zoster virus antibody levels was found in MS patients compared with healthy controls. Data from the new cohort of patients and controls were combined with data from the original study and analyzed with respect to age distribution of anti‐CDV IgG. Mean CDV antibody levels were significantly elevated in each decade from 20 to 50 years of age in MS compared with healthy and disease controls. Antibody levels to measles virus were not consistently elevated during this age span. A striking relationship (p < .0001, odds ratio = 5.0) was observed between elevated anti‐CDV‐H levels and diagnosis of MS.ConclusionsThe finding that anti‐CDV levels are elevated in MS patients of all ages provides substantial evidence of a strong association between elevated anti‐CDV and MS.

Med Check: Zuralone and Depressive Disorder; Rimegepant and Migrane; Neflamapimod and Dementia; FDA Warning About Diphenhydramine

Back to table of contents Previous article Next article Med CheckFull AccessMed Check: Zuralone and Depressive Disorder; Rimegepant and Migrane; Neflamapimod and Dementia; FDA Warning About DiphenhydramineTerri D’ArrigoTerri D’ArrigoSearch for more papers by this authorPublished Online:17 Nov 2020https://doi.org/10.1176/appi.pn.2020.11b4Zuranolone Shows Promise for Major Depressive DisorderThe investigational medication zuranolone may reduce depressive symptoms in people with major depressive disorder, suggest the results of a phase 3 open-label trial. Sage Therapeutics, manufacturer of zuranolone, announced the results in October.The SHORELINE study followed adults with major depressive disorder—defined as a Hamilton Rating Scale for Depression-17 (HAMD-17) score of equal to or greater than 20—for up to one year. The trial initially included treatment with only 30 mg of zuranolone. However, patients who initially started treatment at that dose and were retreated after May started receiving zuranolone 50 mg rather than 30 mg. A new cohort of patients who started treatment with 50 mg also joined the study in May.At the beginning of the trial, 725 patients were treated with 30 mg of zuranolone a day for 14 days. Of those, 143 did not respond to the medication and left the study. Among patients who did respond to the medication and who received only 30 mg of zuranolone throughout their participation in the study, HAMD-17 scores dropped a mean of 15 points by day 15. Among patients who joined the study in May and who took only 50 mg, HAMD-17 scores dropped a mean of 16 points by day 15.Side effects in both the 30 mg cohort and the 50 mg cohort included sleepiness, sedation, headache, and tremor. However, these side effects occurred more frequently in the 50 mg cohort.FDA Reviews Rimegepant for Migraine PreventionIn October the U.S. Food and Drug Administration accepted for review Biohaven’s supplemental New Drug Application for rimegepant (Nurtec ODT) for the prevention of migraines. The medication is already available for the acute treatment of migraine.In a phase 2/3 study, 695 adults with migraine were randomized to either 75 mg rimegepant every other day or placebo for 12 weeks. In the final four weeks of the study, patients in the rimegepant group experienced a 4.3-day reduction from baseline in monthly migraine days, compared with a 3.5-day reduction in the placebo group. Roughly half of patients in the rimegepant group had at least a 50% reduction from baseline in the mean number of moderate to severe migraine days per month compared with 41.5% in the placebo group.The most common side effect, as shown previously in a study about rimegepant’s safety and tolerability, was nausea, which occurred in less than 2% of patients who took the medication.Neflamapimod May Improve Cognition in Dementia with Lewy BodiesEIP Pharma Inc. in October announced the results of its phase 2 AscenD-LB study of neflamapimod for improving cognition in patients with mild to moderate dementia with Lewy bodies.In the trial, 91 patients were randomized to receive 40 mg neflamapimod capsules or placebo for 16 weeks. The dosing regimen was based on weight, with study participants weighing less than 80 kg receiving capsules twice per day and those weighing at least 80 kg receiving capsules three times per day.The primary objective was to evaluate the effect of neflamapimod on cognition as assessed in a study-specific Neuropsychological Test Battery (NTB). Patients in the neflamapimod group who took the medication three times per day experienced significant improvement on the NTB compared with those who received either placebo or neflamapimod twice daily.FDA Warns Against High Doses of DiphenhydramineIn September the FDA issued a drug safety communication warning that taking higher than recommended doses of diphenhydramine (Benadryl) can lead to heart problems, seizures, coma, or death. The warning follows reports of adolescents visiting hospital emergency departments or dying after participating in the “Benadryl Challenge,” which encourages people to take large doses of the antihistamine to cause hallucinations.“Health care professionals should be aware that the ‘Benadryl Challenge’ is occurring among teens and alert their caregivers about it. Encourage teens and caregivers to read and follow the Drug Facts label,” the drug safety communication states. “In the event of an overdose, health care professionals should attempt to determine whether a patient with a suspected overdose took diphenhydramine.” ■ ISSUES NewArchived

A Prospective Validation of the NUT CRACKER Diagnostic Algorithm for Walnut and Pecan Allergy with Prediction of Severity

We previously devised an algorithm using skin prick tests (SPT), basophil activation tests (BAT), and co-allergy status to reduce the need for oral food challenges (OFCs) in 63 patients with suspected walnut/pecan allergies. To validate prospectively the NUT CRACKER (Nut Co-Reactivity-Acquiring Knowledge for Elimination Recommendations) diagnostic algorithm in a new cohort of patients (n= 120) and to study the utility of SPT and BAT in predicting walnut-pecan allergy severity in both groups (n=183). Patients (n= 183) aged 8 (6-11) years, median (interquartile range), with suspected tree nut allergy were studied. SPT used ground nut extract (10 mg/mL), and BAT assessed allergen-induced basophil CD63 expression. Allergy was determined based on a recent reaction or a positive OFC, and tolerance was defined by regular consumption or a negative OFC. Walnut BAT was significantly higher in walnut/pecan dual compared with single walnut allergy (P= .003) and predicted the need for epinephrine during positive walnut OFCs (P= .009). Results of walnut and pecan BAT correlated with the corresponding nut eliciting dose (P= .014 and P<.001, respectively). Receiver operating curves for walnut and pecan allergy in the prospective cohort yielded area under the curves ranging from 0.87 to 0.93 for SPT and BAT. Concordant with the original study, pecan-allergic patients were all co-allergic for walnut. The algorithm decreased the need for OFCs by 78.8 % with 6 of 240 (2.5%) falsely positives and no false negatives. The algorithm was validated prospectively and awaits broader testing across other populations. The use of BAT further associates with severity in walnut/pecan allergy.

SC344 - The asymptomatic, high-grade refluxing male. ciinical follow up of a new cohort of patients derived from prenatal diagnosis

SC344 - The asymptomatic, high-grade refluxing male. ciinical follow up of a new cohort of patients derived from prenatal diagnosis

Protein biomarkers and risk scores in pulmonary arterial hypertension associated with ventricular septal defect: integration of multi-omics and validation.

The molecular mechanisms underlying pulmonary arterial hypertension (PAH) in congenital ventricular septal defects (VSD) are unclear. We aimed to reveal molecular pathways and potential biomarkers by multi-omics analysis in VSD-PAH. Plasma from 160 children, including 120 VSD patients with/without PAH and 40 healthy children was studied by integrated proteomics, metabolomics, and bioinformatics analyses. Proteomics identified 107 differential proteins (DPs) between patients with/without PAH including significantly increased adiponectin (ADIPO), dopamine β-hydroxylase (DBH), alanyl membrane aminopeptidase (ANPEP), transferrin receptor 1, and glycoprotein Ib platelet α-subunit and decreased guanine nucleotide-binding protein Gs in VSD-PAH. Metabolomics discovered 191 differential metabolites between patients with/without PAH, including elevation of serotonin, taurine, creatine, sarcosine, and 2-oxobutanoate, and decrease of vanillylmandelic acid, 3,4-dihydroxymandelate, 15-keto-prostaglandin F2α, fructose 6-phosphate, l-glutamine, dehydroascorbate, hydroxypyruvate, threonine, l-cystine, and 1-aminocyclopropane-1-carboxylate. The DPs were validated in a new cohort of patients (n = 80). Integrated analyses identified key pathways, including cAMP, ECM receptor interaction, AMPK, hypoxia-inducible factor 1, PI3K-Akt signaling pathways, and amino acid metabolisms. Increased plasma protein levels of DBH, ADIPO, and ANPEP were found to be independently associated with the occurrence of PAH, with a new total risk score from these three proteins developed for clinical diagnosis. In this integrated multi-omics analysis in VSD-PAH patients, we have, for the first time, found that VSD-PAH patients present important differential proteins, metabolites, and key pathways. We have developed a total risk score (based on the plasma concentration of DBH, ANPEP, and ADIPO) as a predictor of development of PAH in CHD-VSD patients. Therefore, these proteins may be used as biomarkers, and the new total risk score has significant clinical implications in the diagnosis of PAH.

Preoperative Stratification of Liver Transplant Recipients: Validation of the LTRS.

The liver transplant risk score (LTRS) was developed to stratify 90-day mortality of patients referred for liver transplantation (LT). We aimed to validate the LTRS using a new cohort of patients. The LTRS stratifies the risk of 90-day mortality of LT recipients based on their age, body mass index, diabetes, model for end-stage liver disease (MELD) score, and need for dialysis. We assessed the performance of the LTRS using a new cohort of patients transplanted in the United States between July 2013 and June 2017. Exclusion criteria were age <18 years, ABO incompatibility, redo or multivisceral transplants, partial grafts, malignancies other than hepatocellular carcinoma and fulminant hepatitis. We found a linear correlation between the number of points of the LTRS and 90-day mortality. Among 18 635 recipients, 90-day mortality was 2.7%, 3.8%, 5.2%, 4.8%, 6.7%, and 9.3% for recipients with 0, 1, 2, 3, 4, and ≥5 points (P < 0.001). The LTRS also stratified 1-year mortality that was 5.5%, 7.7%, 9.9%, 9.3%, 10.8%, and 15.4% for 0, 1, 2, 3, 4, and ≥5 points (P < 0.001). An inverse correlation was found between the LTRS and 4-year survival that was 82%, 79%, 78%, 82%, 78%, and 66% for patients with 0, 1, 2, 3, 4, and ≥5 points (P < 0.001). The LTRS remained an independent predictor after accounting for recipient sex, ethnicity, cause of liver disease, donor age, cold ischemia time, and waiting time. The LTRS can stratify the short- and long-term outcomes of LT recipients at the time of their evaluations irrespective of their gender, ethnicity, and primary cause of liver disease.

Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study.

Metastasis development represents an important threat for melanoma patients, even when diagnosed at early stages and upon removal of the primary tumor. In this scenario, determination of prognostic biomarkers would be of great interest. Serum contains information about the general status of the organism and therefore represents a valuable source for biomarkers. Thus, we aimed to define serological biomarkers that could be used along with clinical and histopathological features of the disease to predict metastatic events on the early‐stage population of patients. We previously demonstrated that in stage II melanoma patients, serum levels of dermcidin (DCD) were associated with metastatic progression. Based on the relevance of the immune response on the cancer progression and the recent association of DCD with local and systemic immune response against cancer cells, serum DCD was analyzed in a new cohort of patients along with interleukin 4 (IL‐4), IL‐6, IL‐10, IL‐17A, interferon γ (IFN‐γ), transforming growth factor‐β (TGF‐ β), and granulocyte–macrophage colony‐stimulating factor (GM‐CSF). We initially recruited 448 melanoma patients, 323 of whom were diagnosed as stages I‐II according to AJCC. Levels of selected cytokines were determined by ELISA and Luminex, and obtained data were analyzed employing machine learning and Kaplan–Meier techniques to define an algorithm capable of accurately classifying early‐stage melanoma patients with a high and low risk of developing metastasis. The results show that in early‐stage melanoma patients, serum levels of the cytokines IL‐4, GM‐CSF, and DCD together with the Breslow thickness are those that best predict melanoma metastasis. Moreover, resulting algorithm represents a new tool to discriminate subjects with good prognosis from those with high risk for a future metastasis.

Confirmation of multiple endotypes in atopic dermatitis based on serum biomarkers

Atopic dermatitis (AD) is a highly heterogeneous disease, both clinically and biologically, whereas patients are still being treated according to a "one-size-fits-all" approach. Stratification of patients into biomarker-based endotypes is important for future development of personalized therapies. Our aim was to confirm previously defined serum biomarker-based patient clusters in a new cohort of patients with AD. A panel of 143 biomarkers was measured by using Luminex technology in serum samples from 146 patients with severe AD (median Eczema Area and Severity Index= 28.3; interquartile range= 25.2-35.3). Principal components analysis followed by unsupervised k-means cluster analysis of the biomarker data was used to identify patient clusters. Aprediction model was built on the basis of a previous cohort to predict the 1 of the 4 previously identified clusters to which the patients of our new cohort would belong. Cluster analysis identified 4 serum biomarker-based clusters, 3 of which (clusters B, C, and D) were comparable to the previously identified clusters. Cluster A(33.6%) could be distinguished from the other clusters as being a "skin-homing chemokines/IL-1R1-dominant" cluster, whereas cluster B (18.5%) was a "TH1/TH2/TH17-dominant" cluster, cluster C (18.5%) was a "TH2/TH22/PARC-dominant" cluster, and cluster D (29.5%) was a "TH2/eosinophil-inferior" cluster. Additionally, by using a prediction model based on our previous cohort we accurately assigned the new cohort to the 4 previously identified clusters by including only 10 selected serum biomarkers. We confirmed that AD is heterogeneous at the immunopathologic level and identified 4 distinct biomarker-based clusters, 3 of which were comparable with previously identified clusters. Cluster membership could be predicted with a model including 10 serum biomarkers.

Identification of distinct clinical phenotypes in mechanically ventilated patients with acute brain dysfunction using cluster analysis.

Acute brain dysfunction (ABD) is a frequent and severe syndrome occurring in critically ill patients and early identification of high-risk patients is paramount. In the present analysis, we propose a clinically applicable model for early phenotype identification of ABD at the bedside in mechanically ventilated patients, improving the recognition of patients with prolonged ABD.Prospective cohort with 629 mechanically ventilated patients in two medical-surgical intensive care units at academic centers. We applied cluster analysis to identify phenotypes using clinical and biological data. We then tested the association of phenotypes and its respective clinical outcomes. We performed a validation on a new cohort of patients select on subsequent patients admitted to the participants intensive care units.A model with 3 phenotypes best described the study population. A 4-variable model including medical admission, sepsis diagnosis, simplified acute physiologic score II and basal serum C-reactive protein (CRP) accurately classified each phenotype (area under curve 0.82; 95% CI, 0.79-0.86). Phenotype A had the shorter duration of ABD (median, 1 day), while phenotypes B and C had progressively longer duration of ABD (median, 3 and 6 days, respectively; P < .0001). There was an association between the duration of ABD and the baseline CRP levels and simplified acute physiology score II score (sensitivity and specificity of 80%). To increase the sensitivity of the model, we added CRP kinetics. By day 1, a CRP < 1.0 times the initial level was associated with a shorter duration of ABD (specificity 0.98).A model based on widely available clinical variables could provide phenotypes associated with the duration of ABD. Phenotypes with longer duration of ABD (phenotypes B and C) are characterized by more severe inflammation and by significantly worse clinical outcomes.

Predicting Hearing Loss for Cancer Patients Before Treatment

Most of us will have a loved one hear the devastating words, “You have cancer.” As he or she processes this news, quick treatment decisions must be made. Cancer treatment side effects, such as hearing loss, often come with uncertainties. Our team sought to provide clarity to patients with head and neck cancer on their expected hearing loss before treatment.shutterstock/Iurii Motov, Health care, hearing loss, cancer.Figure 1: The standard model (post-treatment data) is as accurate as the predictive model (pretreatment data). Health care, hearing loss, cancer.Figure 2: Screenshot of the web-based app. Health care, hearing loss, cancer.Each year, more than half a million people develop head and neck cancer, and more than a quarter million die from it.1 Treatment options include surgery, radiation therapy, and chemotherapy (cisplatin). These therapies can cause permanent hearing loss and other side effects, including kidney damage (nephropathy), extreme dry mouth (xerostomia), and loss of healthy tissue (radiation necrosis).2-8 Despite the negative impact of hearing loss on patients’ quality of life, it can be overlooked.9 In 2014, our division of adult audiology at Washington University School of Medicine in St. Louis began providing care for head and neck cancer patients in collaboration with otolaryngology physicians. One of our team members attended a weekly multidisciplinary tumor board to better understand a patient's treatment journey and their challenges in streamlining the process for our patients. We were able to provide audiological care within existing structures to avoid disruptions by reaching out to our multidisciplinary partners. Working with the radiation oncology department, we built standard referral patterns to increase patient follow-up while reducing patient burden through same-day appointments. Baseline audiological testing was incorporated into our department's Head & Neck Cancer Multi-Disciplinary Clinic launched in 2016. The clinic allowed patients to see multiple medical professionals—a radiation oncologist, a medical oncologist, a head and neck cancer surgeon, a speech therapist, and an audiologist—all on the same day. This was appreciated by patients since they could complete their pre-treatment cancer appointments in one morning instead of a month. At these appointments, many patients often asked about what to expect of their hearing after treatment, which made us realize a gap: We could only provide general information about the effects of ototoxic medications, but couldn't address our patients’ needs. As a result, our team decided to explore options for how we could predict post-treatment hearing loss before treatment to provide better counseling. PREDICTING HEARING LOSS A literature review only revealed options that could predict hearing loss after treatment because they relied on final treatment doses. After identifying this gap in information, our team decided to create a new resource for patients. We studied 242 patients using an internal database and data from Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine in St. Louis, the Washington University Oncology Data Services Cancer Registry, Varian (a radiation oncology treatment planning software), and AudBase (a clinical audiometric database). We collected demographic information, tobacco and alcohol use, tumor characteristics (stage, histology, and proximity to the cochlea), and treatment methods (surgery, surgery with clean margins, cisplatin treatment regimen, total cumulative cisplatin dose, and mean cochlear radiotherapy dose) for each patient. Next, we analyzed the data to determine if they could be used to predict post-treatment hearing (pure-tone average [PTA] of 1, 2, 4 kHz) and help counsel patients on their hearing before treatment. We built two key models: one that used proxy measures available before treatment (location of the tumor and planned chemotherapy treatment regimen) and another that relied on final treatment doses. The results were identical: Using pre-treatment measures was as accurate as using post-treatment measures (Fig. 1). The pretreatment factors that we found predicted hearing loss were age, pre-treatment hearing, location of the tumor, and planned treatment chemotherapy dose. Using these factors, our model explained 80 percent of a patient's post-treatment hearing (1, 2, 4 kHz PTA), had a sensitivity of 80 percent and a specificity of 75 percent for predicting post-treatment hearing loss greater or less than 35 dB HL. To our knowledge, we created the first model capable of accurately predicting post-treatment hearing loss before treatment. Our team converted the model into a user-friendly internet-based tool. To use the tool, an audiologist inputs the predictive factors into a web-based application at the baseline hearing test (Fig. 2). The audiologist can then use this information to counsel his or her patient on realistic expectations regarding the patient's post-treatment hearing; however, the model is not yet ready for widespread implementation. We are working to validate it in a new cohort of patients with head and neck cancer.10 Once completed, we plan to publish the data and share our findings to support patients across the country. Each patient we see is someone's loved one. We hope our tool makes their journey a little easier.

P137 Growing up on biologics: a case report of development of NMDAr encephalitis in a young person with JIA on abatacept

Abstract Background A 12-year-old female with JIA on biologic medication (IV abatacept every three weeks) presented with a first generalised tonic-clonic seizure on background of preceding headache and fatigue. The seizure self-terminated but disorientation and encephalopathy ensued. MRI brain demonstrated lesions with high signal intensity in the left periventricular and right occipital regions. The clinical picture and radiological imaging suggested a broad differential diagnosis including CNS infection, JC virus associated progressive multifocal leucoencephalomalacia (PML), acute disseminated encephalomyelitis (ADEM) and Anti-N-methyl-d-aspartate receptor (NMDAr) encephalitis. She was commenced on IV ceftriaxone, acyclovir and clarithromycin. All bloods including inflammatory markers and infection serology were unremarkable. CSF was acellular and JC virus PCR negative. NMDAr encephalitis was initially considered unlikely (pre-existing immunosuppression, abnormal MRI brain and no evidence of ovarian teratoma on abdominal MRI pelvis). However more classical clinical features developed including further seizures, significant movement disorder, cognitive dysfunction, sleep and speech dysfunction. Anti-NMDAr antibodies in both serum and CSF were positive. She made a good recovery following IV steroids, plasmapheresis and rituximab and was discharged home after a 10-week admission. NMDAr encephalitis developed three years after commencing abatacept treatment. Previous immune modulating treatment included methotrexate (since age 2 years), Etanercept (age 5-8 years) and Tocilizumab (aged 8-10 years). Flares of disease following a period of control necessitated the changes in therapy. Methods A literature review was conducted to explore the relationship between NMDAr encephalitis and biologic medication. A yellow card report and information request to abatacept manufacturer were also submitted. Results No previous cases of NMDAr encephalitis in patients on abatacept or paediatric cases related to biologic therapy are described. There are reports of adults developing NMDAr encephalitis on Adalumimab for Crohn’s disease and etanercept for rheumatoid arthritis. NMDAr encephalitis has also been described in patients on immune checkpoint inhibitors for malignant melanoma (nivolumab and ipilimumab). Known triggers of production of anti-NMDA receptor antibodies include tumours (ovarian teratoma; rarely associated in patients under 12 years) and viral infections. Developing autoimmune disorders on biologic medication is well reported, most notably psoriasis and inflammatory bowel disease. In relation to abatacept specifically, the development of anti-nuclear antibodies (ANA) and psoriasis have been described. However, patients with autoimmune disorders are known to be of increased risk for additional immune disease. A new cohort of patients are emerging who have received multiple biologic medications and the development of autoimmune conditions despite immunosuppression needs to be considered. Conclusion We describe the first case of NMDAr encephalitis occurring in a child on abatacept therapy, and the first case in JIA. We are unable to determine what contribution a history of autoimmune disease or immunomodulating therapy has made on its development in this case. Disclosures R. Close: None. P. Bale: None. K. Gallagher: None. G. Ambegaonkar: None. T. Rossor: None. N. Abbassi: None. K. Armon: None.