RESUMEN
BACKGROUND: Image-defined risk factors (IDRFs) were promulgated for predicting the feasibility and safety of complete primary tumor resection in children with neuroblastoma (NB). There is limited understanding of the impact of individual IDRFs on resectability of the primary tumor or patient outcomes. A multicenter database of patients with high-risk NB was interrogated to answer this question. DESIGN/METHODS: Patients with high-risk NB (age <20 years) were eligible if cross-sectional imaging was performed at least twice prior to resection. IDRFs and primary tumor measurements were recorded for each imaging study. Extent of resection was determined from operative reports. RESULTS: There were 211 of 229 patients with IDRFs at diagnosis, and 171 patients with IDRFs present pre-surgery. A ≥90% resection was significantly more likely in the absence of tumor invading or encasing the porta hepatis, hepatoduodenal ligament, superior mesenteric artery (SMA), renal pedicles, abdominal aorta/inferior vena cava (IVC), iliac vessels, and/or diaphragm at diagnosis or an overlapping subset of IDRFs (except diaphragm) at pre-surgery. There were no significant differences in event-free survival (EFS) and overall survival (OS) when patients were stratified by the presence versus absence of any IDRF either at diagnosis or pre-surgery. CONCLUSION: Two distinct but overlapping subsets of IDRFs present either at diagnosis or after induction chemotherapy significantly influence the probability of a complete resection in children with high-risk NB. The presence of IDRFs was not associated with significant differences in OS or EFS in this cohort.
Asunto(s)
Neuroblastoma , Humanos , Neuroblastoma/cirugía , Neuroblastoma/patología , Neuroblastoma/mortalidad , Neuroblastoma/diagnóstico por imagen , Masculino , Femenino , Preescolar , Niño , Lactante , Factores de Riesgo , Adolescente , Tasa de Supervivencia , Pronóstico , Estudios de Seguimiento , Recién Nacido , Estudios RetrospectivosRESUMEN
Automated analysis of electronic health record (EHR) data is a complementary tool for public health surveillance. Analyzing and presenting these data, however, demands new methods of data communication optimized to the detail, flexibility, and timeliness of EHR data.RiskScape is an open-source, interactive, Web-based, user-friendly data aggregation and visualization platform for public health surveillance using EHR data. RiskScape displays near-real-time surveillance data and enables clinical practices and health departments to review, analyze, map, and trend aggregate data on chronic conditions and infectious diseases. Data presentations include heat maps of prevalence by zip code, time series with statistics for trends, and care cascades for conditions such as HIV and HCV. The platform's flexibility enables it to be modified to incorporate new conditions quickly-such as COVID-19.The Massachusetts Department of Public Health (MDPH) uses RiskScape to monitor conditions of interest using data that are updated monthly from clinical practice groups that cover approximately 20% of the state population. RiskScape serves an essential role in demonstrating need and burden for MDPH's applications for funding, particularly through the identification of inequitably burdened populations.
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COVID-19/epidemiología , Registros Electrónicos de Salud/estadística & datos numéricos , Informática en Salud Pública/instrumentación , Vigilancia en Salud Pública/métodos , Humanos , MassachusettsRESUMEN
Electronic medical record (EMR) systems have rich potential to improve integration between primary care and the public health system at the point of care. EMRs make it possible for clinicians to contribute timely, clinically detailed surveillance data to public health practitioners without changing their existing workflows or incurring extra work. New surveillance systems can extract raw data from providers' EMRs, analyze them for conditions of public health interest, and automatically communicate results to health departments. We describe a model EMR-based public health surveillance platform called Electronic Medical Record Support for Public Health (ESP). The ESP platform provides live, automated surveillance for notifiable diseases, influenza-like illness, and diabetes prevalence, care, and complications. Results are automatically transmitted to state health departments.
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Algoritmos , Prestación Integrada de Atención de Salud/organización & administración , Registros Electrónicos de Salud , Vigilancia de la Población/métodos , Diabetes Mellitus/epidemiología , Notificación de Enfermedades/métodos , Humanos , Atención Primaria de Salud , Estados Unidos/epidemiologíaRESUMEN
In this report, we describe the Automated Epidemiological Geotemporal Integrated Surveillance system (AEGIS), developed for real-time population health monitoring in the state of Massachusetts. AEGIS provides public health personnel with automated near-real-time situational awareness of utilization patterns at participating healthcare institutions, supporting surveillance of bioterrorism and naturally occurring outbreaks. As real-time public health surveillance systems become integrated into regional and national surveillance initiatives, the challenges of scalability, robustness, and data security become increasingly prominent. A modular and fault tolerant design helps AEGIS achieve scalability and robustness, while a distributed storage model with local autonomy helps to minimize risk of unauthorized disclosure. The report includes a description of the evolution of the design over time in response to the challenges of a regional and national integration environment.
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Bioterrorismo , Brotes de Enfermedades , Vigilancia de la Población/métodos , Informática en Salud Pública , Enfermedades Transmisibles , Sistemas de Computación , Humanos , MassachusettsRESUMEN
PURPOSE: The International Neuroblastoma Response Criteria (INRC) require serial measurements of primary tumors in three dimensions, whereas the Response Evaluation Criteria in Solid Tumors (RECIST) require measurement in one dimension. This study was conducted to identify the preferred method of primary tumor response assessment for use in revised INRC. PATIENTS AND METHODS: Patients younger than 20 years with high-risk neuroblastoma were eligible if they were diagnosed between 2000 and 2012 and if three primary tumor measurements (antero-posterior, width, cranio-caudal) were recorded at least twice before resection. Responses were defined as ≥ 30% reduction in longest dimension as per RECIST, ≥ 50% reduction in volume as per INRC, or ≥ 65% reduction in volume. RESULTS: Three-year event-free survival for all patients (N = 229) was 44% and overall survival was 58%. The sensitivity of both volume response measures (ability to detect responses in patients who survived) exceeded the sensitivity of the single dimension measure, but the specificity of all response measures (ability to identify lack of response in patients who later died) was low. In multivariable analyses, none of the response measures studied was predictive of outcome, and none was predictive of the extent of resection. CONCLUSION: None of the methods of primary tumor response assessment was predictive of outcome. Measurement of three dimensions followed by calculation of resultant volume is more complex than measurement of a single dimension. Primary tumor response in children with high-risk neuroblastoma should therefore be evaluated in accordance with RECIST criteria, using the single longest dimension.
Asunto(s)
Neoplasias Encefálicas/terapia , Neuroblastoma/terapia , Neoplasias Encefálicas/mortalidad , Neoplasias Encefálicas/patología , Niño , Preescolar , Femenino , Humanos , Lactante , Recién Nacido , Masculino , Neuroblastoma/mortalidad , Neuroblastoma/patología , Tasa de Supervivencia , Resultado del TratamientoRESUMEN
Clinical information, "-omic" datasets, and tissue samples are difficult to harmonize and manage for data mining. We have developed a platform for storing clinical research data while providing access to associated data from other information stores. Data on 34 metrics from 11,000 neuroblastoma patients were instantiated into a database. The Django web framework was used to create a model for rapid development of tools and views with a front-end interface for generating complex queries. Working with Nationwide Children's Hospital, we can now consume their tissue inventory data through an API. The end-user sees the number of patients who both match their search and have tissue available. Since initial implementation, the current tasks revolve around developing a governance structure and the necessary data use agreements. Efforts now are to (1) update the data with 5000 more patients, and (2) link to genomic data stores, facilitating disparate data acquisition for research studies.
RESUMEN
Electronic medical record (EMR) systems have rich potential to improve integration between primary care and the public health system at the point of care. EMRs make it possible for clinicians to contribute timely, clinically detailed surveillance data to public health practitioners without changing their existing workflows or incurring extra work. New surveillance systems can extract raw data from providers' EMRs, analyze them for conditions of public health interest, and automatically communicate results to health departments. The current paper describes a model EMR-based public health surveillance platform called Electronic Medical Record Support for Public Health (ESP). The ESP platform provides live, automated surveillance for notifiable diseases, influenza-like illness, and diabetes prevalence, care, and complications. Results are automatically transmitted to state health departments.
Asunto(s)
Algoritmos , Prestación Integrada de Atención de Salud/organización & administración , Registros Electrónicos de Salud , Vigilancia de la Población/métodos , Diabetes Mellitus/epidemiología , Notificación de Enfermedades/métodos , Humanos , Atención Primaria de Salud , Estados Unidos/epidemiologíaRESUMEN
Electronic medical record (EMR) systems are a rich potential source for detailed, timely, and efficient surveillance of large populations. We created the Electronic medical record Support for Public Health (ESP) system to facilitate and demonstrate the potential advantages of harnessing EMRs for public health surveillance. ESP organizes and analyzes EMR data for events of public health interest and transmits electronic case reports or aggregate population summaries to public health agencies as appropriate. It is designed to be compatible with any EMR system and can be customized to different states' messaging requirements. All ESP code is open source and freely available. ESP currently has modules for notifiable disease, influenza-like illness syndrome, and diabetes surveillance. An intelligent presentation system for ESP called the RiskScape is under development. The RiskScape displays surveillance data in an accessible and intelligible format by automatically mapping results by zip code, stratifying outcomes by demographic and clinical parameters, and enabling users to specify custom queries and stratifications. The goal of RiskScape is to provide public health practitioners with rich, up-to-date views of health measures that facilitate timely identification of health disparities and opportunities for targeted interventions. ESP installations are currently operational in Massachusetts and Ohio, providing live, automated surveillance on over 1 million patients. Additional installations are underway at two more large practices in Massachusetts.