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DOI: 10.1055/s-0038-1651497
Integrating Multimodal Radiation Therapy Data into i2b2
Publication History
12 December 2017
07 April 2018
Publication Date:
30 May 2018 (online)
![](https://www.thieme-connect.de/media/10.1055-s-00035026/201802/lookinside/thumbnails/10-1055-s-0038-1651497_170210ra-1.jpg)
Abstract
Background Clinical data warehouses are now widely used to foster clinical and translational research and the Informatics for Integrating Biology and the Bedside (i2b2) platform has become a de facto standard for storing clinical data in many projects. However, to design predictive models and assist in personalized treatment planning in cancer or radiation oncology, all available patient data need to be integrated into i2b2, including radiation therapy data that are currently not addressed in many existing i2b2 sites.
Objective To use radiation therapy data in projects related to rectal cancer patients, we assessed the feasibility of integrating radiation oncology data into the i2b2 platform.
Methods The Georges Pompidou European Hospital, a hospital from the Assistance Publique – Hôpitaux de Paris group, has developed an i2b2-based clinical data warehouse of various structured and unstructured clinical data for research since 2008. To store and reuse various radiation therapy data—dose details, activities scheduling, and dose-volume histogram (DVH) curves—in this repository, we first extracted raw data by using some reverse engineering techniques and a vendor's application programming interface. Then, we implemented a hybrid storage approach by combining the standard i2b2 “Entity-Attribute-Value” storage mechanism with a “JavaScript Object Notation (JSON) document-based” storage mechanism without modifying the i2b2 core tables. Validation was performed using (1) the Business Objects framework for replicating vendor's application screens showing dose details and activities scheduling data and (2) the R software for displaying the DVH curves.
Results We developed a pipeline to integrate the radiation therapy data into the Georges Pompidou European Hospital i2b2 instance and evaluated it on a cohort of 262 patients. We were able to use the radiation therapy data on a preliminary use case by fetching the DVH curve data from the clinical data warehouse and displaying them in a R chart.
Conclusion By adding radiation therapy data into the clinical data warehouse, we were able to analyze radiation therapy response in cancer patients and we have leveraged the i2b2 platform to store radiation therapy data, including detailed information such as the DVH to create new ontology-based modules that provides research investigators with a wider spectrum of clinical data.
Protection of Human and Animal Subjects
This study from which the data were extracted was approved by the IRB and ethics committee CPP Ile-de-France II (IRB Committee # 00001072, study reference # CDW_2015_0024). Patients consent to participate to the study was implicit if refusal was not expressly stated. The HEGP CDW has been declared to the French CNIL regulatory commission for data privacy (# 1695855 v 0 ; 2013/08/28).
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References
- 1 Danciu I, Cowan JD, Basford M. , et al. Secondary use of clinical data: the Vanderbilt approach. J Biomed Inform 2014; 52: 28-35
- 2 Nalichowski R, Keogh D, Chueh HC, Murphy SN. Calculating the benefits of a Research Patient Data Repository. AMIA Annu Symp Proc 2006; 20 06: 1044
- 3 Degoulet P, Marin L, Lavril M. , et al. The HEGP component-based clinical information system. Int J Med Inform 2003; 69 (2-3): 115-126
- 4 Zapletal E, Rodon N, Grabar N, Degoulet P. Methodology of integration of a clinical data warehouse with a clinical information system: the HEGP case. Stud Health Technol Inform 2010; 160 (Pt 1): 193-197
- 5 Jannot A-S, Zapletal E, Avillach P, Mamzer M-F, Burgun A, Degoulet P. The Georges Pompidou University Hospital Clinical Data Warehouse: a 8-years follow-up experience. Int J Med Inform 2017; 102: 21-28
- 6 Rance B, Canuel V, Countouris H, Laurent-Puig P, Burgun A. Integrating heterogeneous biomedical data for cancer research: the CARPEM infrastructure. Appl Clin Inform 2016; 7 (02) 260-274
- 7 Kohane IS, Drazen JM, Campion EW. A glimpse of the next 100 years in medicine. N Engl J Med 2012; 367 (26) 2538-2539
- 8 Bibault J-E, Giraud P, Burgun A. Big Data and machine learning in radiation oncology: state of the art and future prospects. Cancer Lett 2016; 382 (01) 110-117
- 9 Meldolesi E, van Soest J, Damiani A. , et al. Standardized data collection to build prediction models in oncology: a prototype for rectal cancer. Future Oncol 2016; 12 (01) 119-136
- 10 Murphy SN, Mendis ME, Berkowitz DA, Kohane I, Chueh HC. Integration of clinical and genetic data in the i2b2 architecture. AMIA Annu Symp Proc 2006; 20 06: 1040
- 11 i2b2: Informatics for Integrating Biology & the Bedside. Available at: https://www.i2b2.org/work/i2b2_installations.html . Accessed September 5, 2017
- 12 pubmeddev. No items found - PubMed - NCBI. [cited 2017 Dec 11]. Available at: https://www.ncbi.nlm.nih.gov/pubmed/?term=i2b2+radiation+therapy
- 13 Katz A, Kang J. Stereotactic body radiation therapy for low- and intermediate-risk of prostate cancer: disease control and quality of life at 8 years. Int J Radiat Oncol 2015; 93 (3, Supplement): E187
- 14 Murphy SN, Herrick C, Wang Y. , et al. High throughput tools to access images from clinical archives for research. J Digit Imaging 2015; 28 (02) 194-204
- 15 SchemaSpy. Available at: http://schemaspy.sourceforge.net/ . Accessed April 10, 2017
- 16 Varian Developers Forum. CodePlex. Available at: https://variandeveloper.codeplex.com/Wikipage?ProjectName=variandeveloper . Accessed April 11, 2017
- 17 Talend Data Integration. ETL Software for Enterprise Data Integration. Talend Real-Time Open Source Data Integration Software. Available at: https://www.talend.com/products/data-integration/ . Accessed April 12, 2017
- 18 BI & Analytics Platform | SAP BusinessObjects. SAP. Available at: https://www.sap.com/product/analytics/bi-platform.html . Accessed April 10, 2017
- 19 R: The R Project for Statistical Computing. Available at: https://www.r-project.org/ . Accessed April 12, 2017
- 20 CRC_Design - CRC_Design.pdf-. Available at: https://www.i2b2.org/software/files/PDF/current/CRC_Design.pdf . Accessed April 14, 2017
- 21 SNOMED CT - Summary | NCBO BioPortal. Available at: https://bioportal.bioontology.org/ontologies/SNOMEDCT . Accessed April 28, 2017
- 22 National Cancer Institute Thesaurus - Summary | NCBO BioPortal. Available at: https://bioportal.bioontology.org/ontologies/NCIT . Accessed April 28, 2017
- 23 Common Terminology Criteria for Adverse Events - Summary | NCBO BioPortal. Available at: https://bioportal.bioontology.org/ontologies/CTCAE . Accessed April 28, 2017
- 24 UMLS Metathesaurus Fact Sheet. Available at: https://www.nlm.nih.gov/pubs/factsheets/umlsmeta.html . Accessed April 28, 2017
- 25 Radiation Oncology Ontology - Summary | NCBO BioPortal. Available at: http://bioportal.bioontology.org/ontologies/ROO . Accessed April 28, 2017
- 26 Grégoire V, Ang K, Budach W. , et al. Delineation of the neck node levels for head and neck tumors: a 2013 update. DAHANCA, EORTC, HKNPCSG, NCIC CTG, NCRI, RTOG, TROG consensus guidelines. Radiother Oncol 2014; 110 (01) 172-181
- 27 Rusch VW, Asamura H, Watanabe H, Giroux DJ, Rami-Porta R, Goldstraw P. The IASLC lung cancer staging project: a proposal for a new international lymph node map in the forthcoming seventh edition of the TNM classification for lung cancer. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer 2009; 4 (05) 568-577
- 28 Bibault J-E, Zapletal E, Rance B, Giraud P, Burgun A. Labeling for Big Data in radiation oncology: the Radiation Oncology Structures ontology. PLoS One 2018; 13 (01) e0191263
- 29 Deshmukh VG, Meystre SM, Mitchell JA. Evaluating the informatics for integrating biology and the bedside system for clinical research. BMC Med Res Methodol 2009; 9: 70
- 30 Haarbrandt B, Tute E, Marschollek M. Automated population of an i2b2 clinical data warehouse from an openEHR-based data repository. J Biomed Inform 2016; 63: 277-294
- 31 Modifiers in i2b2 Data Model - i2b2 Developer's Forum - i2b2 Community Wiki. Available at: https://community.i2b2.org/wiki/display/DevForum/Modifiers+in+i2b2+Data+Model . Accessed April 12, 2017
- 32 Modeling and Querying Data in MongoDB. Available at: http://www.ijser.org/paper/Modeling-and-Querying-Data-in-MongoDB.html . Accessed April 12, 2017
- 33 Apache CouchDB. Available at: http://couchdb.apache.org/ . Accessed April 27, 2017
- 34 Murphy SN, Avillach P, Bellazzi R. , et al. Combining clinical and genomics queries using i2b2 - three methods. PLoS One 2017; 12 (04) e0172187
- 35 Gabetta M, Limongelli I, Rizzo E, Riva A, Segagni D, Bellazzi R. BigQ: a NoSQL based framework to handle genomic variants in i2b2. BMC Bioinformatics 2015; 16: 415
- 36 Natter MD, Quan J, Ortiz DM. , et al. An i2b2-based, generalizable, open source, self-scaling chronic disease registry. J Am Med Inform Assoc 2013; 20 (01) 172-179
- 37 Segagni D, Ferrazzi F, Larizza C. , et al. R engine cell: integrating R into the i2b2 software infrastructure. J Am Med Inform Assoc 2011; 18 (03) 314-317
- 38 Segagni D, Tibollo V, Dagliati A. , et al. The ONCO-I2b2 project: integrating biobank information and clinical data to support translational research in oncology. Stud Health Technol Inform 2011; 169: 887-891
- 39 Web Client Plug-in Developers Guide - i2b2 Web Client - i2b2 Community Wiki. Available at: https://community.i2b2.org/wiki/display/webclient/Web+Client+Plug-in+Developers+Guide . Accessed February 1, 2018
- 40 Herzinger S, Gu W, Satagopam V. , et al; eTRIKS Consortium. SmartR: an open-source platform for interactive visual analytics for translational research data. Bioinformatics 2017; 33 (14) 2229-2231
- 41 Wilkinson MD, Dumontier M, Aalbersberg IJJ. , et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 2016; 3: 160018