Clinical trial · Observational
Big Data and Text-mining Technologies Applied for Breast Cancer Medical Data Analysis
SENOMETRY : Big Data and Text-mining Technologies Applied for Breast Cancer Medical Data Analysis
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Breast Cancer | Malignant Breast Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| retrospective medical records analyze | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Breast cancer patients between 2000 and 2016
- description
- Patients treated for a breast cancer between 2000 and 2016 in the Hospital of Strasbourg (France).
- interventionNames
- Other: retrospective medical records analyze
Primary outcomes (1)
- measure
- Validate the reliability of a computer-based, automatic information retrieval method specific to medical records from breast cancer multidisciplinary meetings
- timeFrame
- 6 months
Secondary outcomes (1)
- measure
- Breast cancer recurrence rate after some therapeutic procedures
- timeFrame
- 6 months
- description
- Study of the recurrence rate of different subgroups of patients where various procedures were performed
Eligibility
Eligibility (as posted)
- Sex
- Female
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Majority (age \> 18) * Malignant breast tumors * signed informed consent Exclusion Criteria: * Benign breast pathology * Patients not initially treated at the Hôpitaux Universitaires de Strasbourg
References
Publications (1)
- DERIVEDSimoulin 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 37453367