A Retrospective/Prospective, Multicenter European Epidemiological Platform for Patients Diagnosed With Rare Anemia Disorders (RADs) With Clinical Significance.
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 32,564
- 试验地点
- 1
- 主要终点
- Estimation of Prevalence and Incidence of RADs
研究概览
简要总结
Rare Anaemia Disorders (RADs) is a group of rare diseases characterized for presenting anaemia as the main clinical manifestation. Different medical entities classified as RADs by ORPHA classification are most of them chronic life threating disorders with many unmet needs for their proper clinical management creating an impact on European health systems. RADs present diagnostic challenges and their appropriate management requires from specialised multidisciplinary teams in Centers of expertise.
Although there are some examples of well-established national registries on RADs in EU, the lack of recommendations for Rare disease registries implementation and the lack of standards for interoperability has led to the fragmentation or unavailability of data on prevalence, survival, main clinical manifestations or treatments in most of the European countries.
详细描述
The Rare Anaemia Disorders European Epidemiological Platform (RADeep) is an initiative endorsed by the European Reference Network on Rare Hematological Diseases (ERN-EuroBloodNet) under the frame of the European Blood Disorders Platform (ENROL), the ERN-EuroBloodNet umbrella platform officially endorsed by the European Hematology Association (EHA) for European patients' registries on rare haematological diseases. RADeep will share pseudonymised level data with ENROL.
RADeep supports the standardized collection of data of patients affected by any RADs at the European level, maximizing public benefit from data on RADs opened-up with the only restriction needed to guarantee patient rights and confidentiality, in agreement with the General Data Protection Regulation and applicable laws for cross-border sharing of personal data. RADeep has the following major objectives:
- To collect and describe the demographics, disease-management, and treatment outcomes of patients diagnosed with RADs
- To perform observational studies concerning research questions and to present outcomes in the fields of health related to organ damage and risk stratification for identification of trial cohorts for new drugs and/or development of research projects
- To promote harmonization and best practices in the prevention, diagnosis, treatment and follow-up of RADs patients by the dissemination of reliable Guidelines and the translation of research results into clinical practice.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 0 Years 至 100 Years（Child, Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients must meet all of the following criteria to be included in the RADeep Registry
- •Age from 0-100, both female and male
- •Diagnosed as RADs (SCD, THAL, PKD, and other RADs THAL according to ORPHANET classification)
- •Able and willing to provide written informed consent (patient or legal representative for minors)
排除标准
- •Patient or legal representative for minors unwilling or unable to give consent
- •Patients diagnosed with SCD or THAL (alpha-thalassaemia and beta-thalassaemia) traits or trait conditions for other recessive RADs
结局指标
主要结局
Estimation of Prevalence and Incidence of RADs
时间窗: 15 years
Demography and epidemiology To collect and to describe demographics and epidemiological data of any type of RADs: * Estimate the population frequency of each RAD disease group and disease survival * Estimate the diagnosis delay * Identify cohorts of patients for research/clinical trials * Estimate disease severity * Assess the use of specific treatments Descriptive analyses will be undertaken at the end of the follow-up period using standard statistical methods to examine the subjects' demographics, disease characteristics and management. Data is updated yearly in an electronic CRF form while assuring homogenization in categorization and units. Time-to-event analyses, namely Kaplan-Meier and Cox proportional hazard regression will be used to estimate overall survival. Multivariate Cox proportional hazards regression models will be used to identify variables that are important to correlate survival.
次要结局
未报告次要终点