ENT COBRA (Consortium for Brachytherapy Data Analysis): interdisciplinary standardized data collection system for head and neck patients treated with interventional radiotherapy (brachytherapy)

Abstract

Purpose: Aim of the COBRA (Consortium for Brachytherapy Data Analysis) project is to create a multicenter group (consortium) and a web-based system for standardized data collection.

Material and methods: GEC-ESTRO (Groupe Européen de Curiethérapie - European Society for Radiotherapy & Oncology) Head and Neck (H&N) Working Group participated in the project and in the implementation of the consortium agreement, the ontology (data-set) and the necessary COBRA software services as well as the peer reviewing of the general anatomic site-specific COBRA protocol. The ontology was defined by a multicenter task-group.

Results: Eleven centers from 6 countries signed an agreement and the consortium approved the ontology. We identified 3 tiers for the data set: Registry (epidemiology analysis), Procedures (prediction models and DSS), and Research (radiomics). The COBRA-Storage System (C-SS) is not time-consuming as, thanks to the use of "brokers", data can be extracted directly from the single center's storage systems through a connection with "structured query language database" (SQL-DB), Microsoft Access(®), FileMaker Pro(®), or Microsoft Excel(®). The system is also structured to perform automatic archiving directly from the treatment planning system or afterloading machine. The architecture is based on the concept of "on-purpose data projection". The C-SS architecture is privacy protecting because it will never make visible data that could identify an individual patient. This C-SS can also benefit from the so called "distributed learning" approaches, in which data never leave the collecting institution, while learning algorithms and proposed predictive models are commonly shared.

Conclusions: Setting up a consortium is a feasible and practicable tool in the creation of an international and multi-system data sharing system. COBRA C-SS seems to be well accepted by all involved parties, primarily because it does not influence the center's own data storing technologies, procedures, and habits. Furthermore, the method preserves the privacy of all patients.

Keywords: ENT-COBRA; consortium; data collection; head and neck cancer.

Fig. 1

BOA physically separates privacy relevant information from registry level data splitting this two pieces of information into two databases: “Local Patient Index Archive” and “Pathology Archive”. It sends only clinical data to Cloud Large Database, destroying the inverse mapping, HUB extracts and harmonizes legacy data while making them available for BOA, Local Research Proxy makes local queries on its own pathology database, Cloud Research Proxy run queries on the cloud large database and computes outcomes for each consortium member to use

Fig. 2

BOA physically separates privacy relevant information from registry level data splitting this two pieces of information into two databases: “Local Patient Index Archive” and “Pathology Archive”. It sends only clinical data to Cloud Large Database, destroying the inverse mapping, HUB (optional module of BOA) extracts and harmonizes legacy data while making them available for BOA, Local Research Proxy (optional module of BOA) makes local queries on its own pathology database. Learning Analyzer Proxy (module of BOA only in distributed mode) sends algorithms directly to Local Research Proxies, taking back from them only the results of each iteration step, with no need to work with shared data in the Cloud anymore. In this mode, Local Research Proxies do not move data around: they only apply iterative algorithms that the Supervisor will use to build consensus and estimate the model's parameters