Big Data and Text-mining Technologies Applied for Breast Cancer Medical Data Analysis
SENOMETRY
SENOMETRY : Big Data and Text-mining Technologies Applied for Breast Cancer Medical Data Analysis
1 other identifier
observational
10,000
1 country
1
Brief Summary
Primary purpose : To develop a method to automatically extract and structure the information included in numerous medical records from breast cancer patients. Secondary purpose : With this procedure we can analyze the content of ten thousand anonymized textual medical records. This information should enable us to explore many subjects, such as:
- The impact of certain therapeutic procedures
- The characteristics of sub-groups of patients
- Pregnancy associated breast cancers
- Risk factors
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started May 2016
Shorter than P25 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
May 1, 2016
CompletedFirst Submitted
Initial submission to the registry
June 20, 2016
CompletedFirst Posted
Study publicly available on registry
June 22, 2016
CompletedPrimary Completion
Last participant's last visit for primary outcome
November 1, 2016
CompletedStudy Completion
Last participant's last visit for all outcomes
December 1, 2016
CompletedJune 22, 2016
June 1, 2016
6 months
June 20, 2016
June 20, 2016
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Validate the reliability of a computer-based, automatic information retrieval method specific to medical records from breast cancer multidisciplinary meetings
6 months
Secondary Outcomes (1)
Breast cancer recurrence rate after some therapeutic procedures
6 months
Study Arms (1)
Breast cancer patients between 2000 and 2016
Patients treated for a breast cancer between 2000 and 2016 in the Hospital of Strasbourg (France).
Interventions
Ten thousand medical records (between years 2000 and 2016) will be analyzed
Eligibility Criteria
Patients (men and women) suffering from an in situ or invasive cancer treated at Hôpitaux Universitaires de Strasbourg between years 2000 and 2016.
You may qualify if:
- Majority (age \> 18)
- Malignant breast tumors
- signed informed consent
You may not qualify if:
- Benign breast pathology
- Patients not initially treated at the Hôpitaux Universitaires de Strasbourg
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- University Hospital, Strasbourg, Francelead
- Quantmetrycollaborator
Study Sites (1)
University Strasbourg Hospital
Strasbourg, 67091, France
Related Publications (1)
Simoulin A, Thiebaut N, Neuberger K, Ibnouhsein I, Brunel N, Vine R, Bousquet N, Latapy J, Reix N, Moliere S, Lodi M, Mathelin C. From free-text electronic health records to structured cohorts: Onconum, an innovative methodology for real-world data mining in breast cancer. Comput Methods Programs Biomed. 2023 Oct;240:107693. doi: 10.1016/j.cmpb.2023.107693. Epub 2023 Jun 25.
PMID: 37453367DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Carole Mathelin, MD
Strasbourg's University Hospitals
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
June 20, 2016
First Posted
June 22, 2016
Study Start
May 1, 2016
Primary Completion
November 1, 2016
Study Completion
December 1, 2016
Last Updated
June 22, 2016
Record last verified: 2016-06
Data Sharing
- IPD Sharing
- Will not share