The Assisi Think Tank Meeting Breast Large Database for Standardized Data Collection in Breast Cancer-ATTM.BLADE

Abstract

Background: During the 2016 Assisi Think Tank Meeting (ATTM) on breast cancer, the panel of experts proposed developing a validated system, based on rapid learning health care (RLHC) principles, to standardize inter-center data collection and promote personalized treatments for breast cancer. Material and Methods: The seven-step Breast LArge DatabasE (BLADE) project included data collection, analysis, application, and evaluation on a data-sharing platform. The multidisciplinary team developed a consensus-based ontology of validated variables with over 80% agreement. This English-language ontology constituted a breast cancer library with seven knowledge domains: baseline, primary systemic therapy, surgery, adjuvant systemic therapies, radiation therapy, follow-up, and toxicity. The library was uploaded to the BLADE domain. The safety of data encryption and preservation was tested according to General Data Protection Regulation (GDPR) guidelines on data from 15 clinical charts. The system was validated on 64 patients who had undergone post-mastectomy radiation therapy. In October 2018, the BLADE system was approved by the Ethical Committee of Fondazione Policlinico Gemelli IRCCS, Rome, Italy (Protocol No. 0043996/18). Results: From June 2016 to July 2019, the multidisciplinary team completed the work plan. An ontology of 218 validated variables was uploaded to the BLADE domain. The GDPR safety test confirmed encryption and data preservation (on 5000 random cases). All validation benchmarks were met. Conclusion:BLADE is a support system for follow-up and assessment of breast cancer care. To successfully develop and validate it as the first standardized data collection system, multidisciplinary collaboration was crucial in selecting its ontology and knowledge domains. BLADE is suitable for multi-center uploading of retrospective and prospective clinical data, as it ensures anonymity and data privacy.

Keywords: breast cancer; large database; networks; standardized data collection.

Figure 1

General beyond awareness ontology (BOA) architecture, with both the BOA.Local and BOA.Cloud servers. An infinite number of external institutions without a BOA.Local installation can be added at needed to this infrastructure. Double-line arrows represent non-anonymized patient data, dashed arrows represent anonymized patient data, and dotted arrows represent aggregate data.

Figure 2

Timeline framework for ATTM.BLADE project.

Figure 3

Underlying BOA data model visualized through an entity–relationship model that highlights all relationships between the different objects in the database. As an example (and using imaginary values), the archive named BLADE would contain a patient named John Doe, affected by a pathology of breast cancer, for which he was treated through a treatment of first treatment. This treatment would have a compiled version of the case report form (CRF) radiotherapy linked to the phase called neoadjuvant, and an answer of prone, to the question of radiotherapy treatment position present in the previously mentioned CRF.

Figure 4

Example of a CRF configuration file. The columns represent various mandatory configuration settings for BOA and are to be interpreted as follows: The ID column represents an internal identifier and is generated automatically when the CRF is first uploaded. CRF_NAME refers to the name by which the CRF is to be visualized in the UI. QUESTION_NUMBER can either be automatically assigned or manually set, and refers to the ordering of the various questions inside the CRF, with SECTION_NAME and SECTION_LABEL working as visual dividers when the questions are displayed in the interface, with the former being the name to be used in the UI code, and the latter being the name to be displayed. ITEM_NAME and DESCRIPTION_LABEL work in a similar manner, with the former being the identifier in the underlying code and the latter being the name of the text to be displayed with the question in the UI.