Dataset Information

Mapping child and adolescent self-reported symptom data to clinician-reported adverse event grading to improve pediatric oncology care and research.

ABSTRACT: BACKGROUND:Clinicians are the standard source for adverse event (AE) reporting in oncology trials, despite the subjective nature of symptomatic AEs. The authors designed a pediatric patient-reported outcome (PRO) instrument for symptomatic AEs to support the National Cancer Institute's Common Terminology Criteria for Adverse Events (CTCAE) (the Pediatric PRO-CTCAE). The current study developed a standardized algorithm that maps all possible Pediatric PRO-CTCAE response patterns to recommended CTCAE grades to improve the accuracy of AE reporting in pediatric oncology trials. METHODS:Two rounds of surveys were administered to experienced cancer clinicians across 9 pediatric hospitals. In round 1, pediatric oncologists assigned CTCAE grades to all 101 possible Pediatric PRO-CTCAE response patterns. The authors evaluated clinician agreement of CTCAE grades across response patterns and categorized each response pattern as having high or low agreement. In round 2, a survey was sent to a larger clinician group to examine clinician agreement among a select set of Pediatric PRO-CTCAE response patterns, and the authors examined how clinical context influenced grade assignment. RESULTS:A total of 10 pediatric oncologists participated in round 1. Of the 101 possible patterns, 89 (88%) had high agreement. The Light weighted kappa was averaged across the 10 oncologists (Light kappa = 0.73; 95% CI, 0.66-0.81). A total of 139 clinicians participated in round 2. High clinician agreement remained for the majority of generic response patterns and the clinical context did not typically change grades but rather improved agreement. CONCLUSIONS:The current study provides a framework for integrating child self-reported symptom data directly into mandated AE reporting in oncology trials. Translating Pediatric PRO-CTCAE responses into clinically meaningful metrics will guide future cancer care and toxicity grading.

SUBMITTER: McFatrich M

PROVIDER: S-EPMC6906242 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mapping child and adolescent self-reported symptom data to clinician-reported adverse event grading to improve pediatric oncology care and research.

McFatrich Molly M Brondon Jennifer J Lucas Nicole R NR Hinds Pamela S PS Maurer Scott H SH Mack Jennifer W JW Freyer David R DR Jacobs Shana S SS Baker Justin N JN Mowbray Catriona C Wang Mian M Castellino Sharon M SM Barz Leahy Allison A Reeve Bryce B BB

Cancer 20190925 1

<h4>Background</h4>Clinicians are the standard source for adverse event (AE) reporting in oncology trials, despite the subjective nature of symptomatic AEs. The authors designed a pediatric patient-reported outcome (PRO) instrument for symptomatic AEs to support the National Cancer Institute's Common Terminology Criteria for Adverse Events (CTCAE) (the Pediatric PRO-CTCAE). The current study developed a standardized algorithm that maps all possible Pediatric PRO-CTCAE response patterns to recomm ...[more]

PMID: 31553494

Similar Datasets

Project description:Oncology-associated adverse drug/device reactions can be fatal. Some clinicians who treat single patients with severe oncology-associated toxicities have researched case series and published this information. We investigated motivations and experiences of select individuals leading such efforts. Clinicians treating individual patients who developed oncology-associated serious adverse drug events were asked to participate. Inclusion criteria included having index patient information, reporting case series, and being collaborative with investigators from two National Institutes of Health funded pharmacovigilance networks. Thirty-minute interviews addressed investigational motivation, feedback from pharmaceutical manufacturers, FDA personnel, and academic leadership, and recommendations for improving pharmacovigilance. Responses were analyzed using constant comparative methods of qualitative analysis. Overall, 18 clinicians met inclusion criteria and 14 interviewees are included. Primary motivations were scientific curiosity, expressed by six clinicians. A less common theme was public health related (three clinicians). Six clinicians received feedback characterized as supportive from academic leaders, while four clinicians received feedback characterized as negative. Three clinicians reported that following the case series publication they were invited to speak at academic institutions worldwide. Responses from pharmaceutical manufacturers were characterized as negative by 12 clinicians. One clinician's wife called the post-reporting time the "Maalox month," while another clinician reported that the manufacturer collaboratively offered to identify additional cases of the toxicity. Responses from FDA employees were characterized as collaborative for two clinicians, neutral for five clinicians, unresponsive for negative by six clinicians. Three clinicians endorsed developing improved reporting mechanisms for individual physicians, while 11 clinicians endorsed safety activities that should be undertaken by persons other than a motivated clinician who personally treats a patient with a severe adverse drug/device reaction. Our study provides some of the first reports of clinician motivations and experiences with reporting serious or potentially fatal oncology-associated adverse drug or device reactions. Overall, it appears that negative feedback from pharmaceutical manufacturers and mixed feedback from the academic community and/or the FDA were reported. Big data, registries, Data Safety Monitoring Boards, and pharmacogenetic studies may facilitate improved pharmacovigilance efforts for oncology-associated adverse drug reactions. These initiatives overcome concerns related to complacency, indifference, ignorance, and system-level problems as barriers to documenting and reporting adverse drug events- barriers that have been previously reported for clinician reporting of serious adverse drug reactions.

Project description:BackgroundSerious cardiovascular adverse events (SCAEs) associated with intravenous sedatives remain poorly characterized.ObjectiveThe objective of this study was to compare SCAE incidence, types, and mortality between intravenous benzodiazepines (i.e., diazepam, lorazepam, and midazolam), dexmedetomidine, and propofol in the USA over 8 years regardless of the clinical setting where it was administered.MethodsThe Food and Drug Administration's MedWatch Adverse Event Reporting System was searched between 2004 and 2011 using the Evidex® platform from Advera Health Analytics, Inc. to identify all reports that included one or more of ten different SCAEs (package insert incidence???1%) and where an intravenous benzodiazepine, dexmedetomidine, or propofol was the primary suspected drug.ResultsAmong the 2326 Food and Drug Administration's MedWatch Adverse Event Reporting System cases reported, 394 (16.9%) were related to a SCAE. The presence of a SCAE (vs. a non-SCAE) is associated with higher mortality (34 vs. 8%, p?<?0.001). The percentage of cases with one or more SCAE, the case mortality rate (%), and the incidence of each SCAE (per 106 days of sedative exposure), respectively, were benzodiazepines (14, 26, 13) [diazepam (13, 23, 31); lorazepam (15, 43, 14); midazolam (14, 20, 11)]; dexmedetomidine (40, 15, 13); and propofol (17, 39, 7). Propofol (vs. either a benzodiazepine or dexmedetomidine) was associated with more total SCAEs (268 vs. 126, p?<?0.001) but a lower incidence (per 106 days of sedative exposure) of SCAE (7 vs. 13, p?=?0.0001) and cardiac arrest [6.3 (benzodiazepine) vs. 6.7 (dexmedetomidine) vs. 1.4 (propofol), p?<?0.0001].ConclusionsSerious cardiac adverse events account for nearly one-fifth of intravenous sedative Food and Drug Administration's MedWatch Adverse Event Reporting System reports. These SCAEs appear to be associated with greater mortality than non-cardiac serious adverse events. Serious cardiac events may be more prevalent with either benzodiazepines or dexmedetomidine than propofol.

Project description:BACKGROUND:Traditional concordance metrics have shortcomings based on dataset characteristics (e.g., multiple attributes rated, missing data); therefore it is necessary to explore supplemental approaches to quantifying agreement between independent assessments. The purpose of this methodological paper is to apply an Item Response Theory (IRT) -based framework to an existing dataset that included unidimensional clinician and multiple attribute patient ratings of symptomatic adverse events (AEs), and explore the utility of this method in patient-reported outcome (PRO) and health-related quality of life (HRQOL) research. METHODS:Data were derived from a National Cancer Institute-sponsored study examining the validity of a measurement system (PRO-CTCAE) for patient self-reporting of AEs in cancer patients receiving treatment (N?=?940). AEs included 13 multiple attribute patient-reported symptoms that had corresponding unidimensional clinician AE grades. A Bayesian IRT Model was fitted to calculate the latent grading thresholds between raters. The posterior mean values of the model-fitted item responses were calculated to represent model-based AE grades obtained from patients and clinicians. RESULTS:Model-based AE grades showed a general pattern of clinician underestimation relative to patient-graded AEs. However, the magnitude of clinician underestimation was associated with AE severity, such that clinicians' underestimation was more pronounced for moderate/very severe model-estimated AEs, and less so with mild AEs. CONCLUSIONS:The Bayesian IRT approach reconciles multiple symptom attributes and elaborates on the patterns of clinician-patient non-concordance beyond that provided by traditional metrics. This IRT-based technique may be used as a supplemental tool to detect and characterize nuanced differences in patient-, clinician-, and proxy-based ratings of HRQOL and patient-centered outcomes. TRIAL REGISTRATION:ClinicalTrials.gov NCT01031641 . Registered 1 December 2009.

Project description:BackgroundDislocation, periprosthetic fracture and infection are serious complications of total hip replacement (THR) and which negatively impact on patients' outcomes including satisfaction, quality of life, mental health and function. The accuracy with which patients report adverse events (AEs) after surgery varies. The impact of patient self-reporting of AEs on patient-reported outcome measures (PROMs) after THR is yet to be investigated. Our aim was to determine the effect of confirmed and perceived AEs on PROMs after primary THR.MethodsA prospective single-centre cohort study of patients undergoing primary THR, with one-year follow-up, was performed. Participants completed forms pre-operatively and 3, 6, 9 and 12?months post-operatively, including Work Productivity and Activity Impairment (WPAI), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), EuroQol-5D-3?L (EQ5D), Self-Administered Patient Satisfaction (SAPS) and AE reporting questionnaires. Results were reported in three groups: No AE, reported but not confirmed AE and confirmed AE. A generalised linear model was used to compare among groups using robust standard errors (SE).ResultsForty-one AEs were reported in a cohort of 417 patients (234 females), with 30 AEs reported by 3?months. Eleven (27 reported) infections, two (six reported) periprosthetic fractures and two (eight reported) dislocations were confirmed. Those in the no AE group reported significantly better outcomes that the reported AE group as measured by WOMAC Co-Eff 14.27 (p?=?0.01), EQ5D -?0.128 (p?=?0.02) and SAPS -?9.926 (p?=?0.036) and the combined reported and confirmed AE groups as measured by WOMAC Co-Eff 13.72 (p?=?0.002), EQ5D -?0.129 (p?=?0.036) and SAPS -?11.512 (p?=?0.004). No significant differences were seen in WPAI among groups.ConclusionsPatients who report AEs have worse outcomes than those who do not, regardless of whether the AEs can be confirmed by standard medical record review methods. The observed negative trends suggest that patient perception of AEs may influence patient outcome in a similar way to those with confirmed AEs.

Dataset Information

Mapping child and adolescent self-reported symptom data to clinician-reported adverse event grading to improve pediatric oncology care and research.

Publications

Mapping child and adolescent self-reported symptom data to clinician-reported adverse event grading to improve pediatric oncology care and research.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets