8 research outputs found
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Alignment of parent- and child-reported outcomes and histology in eosinophilic esophagitis across multiple CEGIR sites.
BACKGROUND: Patient-reported outcome metrics for eosinophilic esophagitis (EoE) have been developed and validated but not used in a multicenter pediatric population or systematically aligned with histology. OBJECTIVE: We sought to understand (1) the potential of caregiver report to predict patient self-reported symptoms and (2) the correlation of patient-reported outcome domains with histology. METHODS: Patients with EoE (n = 310) and their parents participating in the Consortium of Gastrointestinal Eosinophilic Disease Researchers (CEGIR) observational clinical trial were queried for baseline patient symptoms and quality of life (QOL) by using the Pediatric Eosinophilic Esophagitis Symptom Score, version 2 (PEESSv2.0), and the Pediatric QOL EoE module (PedsQL-EoE), and biopsy specimens were analyzed by using the EoE Histology Scoring System. RESULTS: PEESSv2.0 parental and child reports aligned across all domains (r = 0.68-0.73, P < .001). PedsQL-EoE reports correlated between parents and children across ages and multiple domains (r = 0.48-0.79, P < .001). There was a tight correlation between symptoms on PEESSv2.0 and their effects on QOL both on self-report and parental report (P < .001). Self-reported symptoms on PEESSv2.0 (positively) and PedsQL-EoE (inversely) showed a weak correlation with proximal, but not distal, peak eosinophil counts and features and architectural tissue changes on the EoE Histology Scoring System (P < .05). CONCLUSIONS: Parents of children with EoE aged 3 to 18 years accurately reflected their childrens disease symptoms and QOL. Self- and parent-reported symptoms correlate with proximal esophageal histology. Our data suggest that parental report in young children can function as an adequate marker for self-reported symptoms and that self-reported symptoms can reflect changes in tissue histology in the proximal esophagus. These findings should be considered during clinical trials for drug development
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Alignment of parent- and child-reported outcomes and histology in eosinophilic esophagitis across multiple CEGIR sites.
BACKGROUND:Patient-reported outcome metrics for eosinophilic esophagitis (EoE) have been developed and validated but not used in a multicenter pediatric population or systematically aligned with histology. OBJECTIVE:We sought to understand (1) the potential of caregiver report to predict patient self-reported symptoms and (2) the correlation of patient-reported outcome domains with histology. METHODS:Patients with EoE (n = 310) and their parents participating in the Consortium of Gastrointestinal Eosinophilic Disease Researchers (CEGIR) observational clinical trial were queried for baseline patient symptoms and quality of life (QOL) by using the Pediatric Eosinophilic Esophagitis Symptom Score, version 2 (PEESSv2.0), and the Pediatric QOL EoE module (PedsQL-EoE), and biopsy specimens were analyzed by using the EoE Histology Scoring System. RESULTS:PEESSv2.0 parental and child reports aligned across all domains (r = 0.68-0.73, P < .001). PedsQL-EoE reports correlated between parents and children across ages and multiple domains (r = 0.48-0.79, P < .001). There was a tight correlation between symptoms on PEESSv2.0 and their effects on QOL both on self-report and parental report (P < .001). Self-reported symptoms on PEESSv2.0 (positively) and PedsQL-EoE (inversely) showed a weak correlation with proximal, but not distal, peak eosinophil counts and features and architectural tissue changes on the EoE Histology Scoring System (P < .05). CONCLUSIONS:Parents of children with EoE aged 3 to 18 years accurately reflected their children's disease symptoms and QOL. Self- and parent-reported symptoms correlate with proximal esophageal histology. Our data suggest that parental report in young children can function as an adequate marker for self-reported symptoms and that self-reported symptoms can reflect changes in tissue histology in the proximal esophagus. These findings should be considered during clinical trials for drug development
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Alignment of parent- and child-reported outcomes and histology in eosinophilic esophagitis across multiple CEGIR sites.
BACKGROUND:Patient-reported outcome metrics for eosinophilic esophagitis (EoE) have been developed and validated but not used in a multicenter pediatric population or systematically aligned with histology. OBJECTIVE:We sought to understand (1) the potential of caregiver report to predict patient self-reported symptoms and (2) the correlation of patient-reported outcome domains with histology. METHODS:Patients with EoE (n = 310) and their parents participating in the Consortium of Gastrointestinal Eosinophilic Disease Researchers (CEGIR) observational clinical trial were queried for baseline patient symptoms and quality of life (QOL) by using the Pediatric Eosinophilic Esophagitis Symptom Score, version 2 (PEESSv2.0), and the Pediatric QOL EoE module (PedsQL-EoE), and biopsy specimens were analyzed by using the EoE Histology Scoring System. RESULTS:PEESSv2.0 parental and child reports aligned across all domains (r = 0.68-0.73, P < .001). PedsQL-EoE reports correlated between parents and children across ages and multiple domains (r = 0.48-0.79, P < .001). There was a tight correlation between symptoms on PEESSv2.0 and their effects on QOL both on self-report and parental report (P < .001). Self-reported symptoms on PEESSv2.0 (positively) and PedsQL-EoE (inversely) showed a weak correlation with proximal, but not distal, peak eosinophil counts and features and architectural tissue changes on the EoE Histology Scoring System (P < .05). CONCLUSIONS:Parents of children with EoE aged 3 to 18 years accurately reflected their children's disease symptoms and QOL. Self- and parent-reported symptoms correlate with proximal esophageal histology. Our data suggest that parental report in young children can function as an adequate marker for self-reported symptoms and that self-reported symptoms can reflect changes in tissue histology in the proximal esophagus. These findings should be considered during clinical trials for drug development
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Longitudinal Outcomes in Young Patients with Alpha-1-Antitrypsin Deficiency with Native Liver Reveal that Neonatal Cholestasis is a Poor Predictor of Future Portal Hypertension
ObjectivesTo identify predictors of portal hypertension, liver transplantation, and death in North American youth with alpha-1-antitrypsin (AAT) deficiency, and compare with patients with AAT deficiency elsewhere.Study designThe Childhood Liver Disease Research Network Longitudinal Observational Study of Genetic Causes of Intrahepatic Cholestasis is a prospective, cohort study of pediatric cholestatic liver diseases, including AAT deficiency, enrolling PIZZ and PISZ subjects 0-25 years of age seen since November 2007 at 17 tertiary care centers in the US and Canada. Data from standard-of-care baseline and annual follow-up visits were recorded from medical records, history, physical examination, and laboratory studies. Participants with portal hypertension were identified based on data collected.ResultsWe enrolled 350 participants (60% male) with a native liver; 278 (79%) entered the cohort without portal hypertension and 18 developed portal hypertension during follow-up. Thirty participants required liver transplantation; 2 patients died during 1077 person-years of follow-up. There was no difference in participants with or without preceding neonatal cholestasis progressing to transplantation or death during the study (12% vs 7%; P = .09), or in experiencing portal hypertension (28% vs 21%; P = .16); the hazard ratio for neonatal cholestasis leading to portal hypertension was P = .04. Development of portal hypertension was associated with a reduced height Z-score.ConclusionsPortal hypertension in youth with AAT deficiency impacts growth measures. Progression to liver transplantation is slow and death is rare, but the risk of complications and severe liver disease progression persists throughout childhood. A history of neonatal cholestasis is a weak predictor of severe disease
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Advancing patient care through the Consortium of Eosinophilic Gastrointestinal Disease Researchers (CEGIR)
Recent advances in rare disease research are accelerated by the work of consortia that have been supported by the National Institutes of Health. Development of such consortia rely on multidisciplinary relationships and engagement with patient advocacy groups, as well as the National Institutes of Health and industry and academic partners. In this rostrum we present the development of such a process that focuses on eosinophilic gastrointestinal diseases. Principal investigators, patient advocacy groups, research assistants, and trainees work together to perform natural history studies that promote clinical trial readiness tools, conduct clinical trials, train a new generation of investigators, and perform innovative pilot studies
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Serum biomarkers correlated with liver stiffness assessed in a multicenter study of pediatric cholestatic liver disease
Background and aimsDetailed investigation of the biological pathways leading to hepatic fibrosis and identification of liver fibrosis biomarkers may facilitate early interventions for pediatric cholestasis.Approach and resultsA targeted enzyme-linked immunosorbent assay-based panel of nine biomarkers (lysyl oxidase, tissue inhibitor matrix metalloproteinase (MMP) 1, connective tissue growth factor [CTGF], IL-8, endoglin, periostin, Mac-2-binding protein, MMP-3, and MMP-7) was examined in children with biliary atresia (BA; n =â187), alpha-1 antitrypsin deficiency (A1AT; n =â78), and Alagille syndrome (ALGS; n =â65) and correlated with liver stiffness (LSM) and biochemical measures of liver disease. Median age and LSM were 9âyears and 9.5âkPa. After adjusting for covariates, there were positive correlations among LSM and endoglin ( p =â0.04) and IL-8 ( p <â0.001) and MMP-7 ( p <â0.001) in participants with BA. The best prediction model for LSM in BA using clinical and lab measurements had an R2 =â0.437; adding IL-8 and MMP-7 improved R2 to 0.523 and 0.526 (both p <â0.0001). In participants with A1AT, CTGF and LSM were negatively correlated ( p =â0.004); adding CTGF to an LSM prediction model improved R2 from 0.524 to 0.577 ( p =â0.0033). Biomarkers did not correlate with LSM in ALGS. A significant number of biomarker/lab correlations were found in participants with BA but not those with A1AT or ALGS.ConclusionsEndoglin, IL-8, and MMP-7 significantly correlate with increased LSM in children with BA, whereas CTGF inversely correlates with LSM in participants with A1AT; these biomarkers appear to enhance prediction of LSM beyond clinical tests. Future disease-specific investigations of change in these biomarkers over time and as predictors of clinical outcomes will be important
A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study
Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions