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Big Data and Text-mining Technologies Applied for Breast Cancer Medical Data Analysis (SENOMETRY)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT02810093
Recruitment Status : Unknown
Verified June 2016 by University Hospital, Strasbourg, France.
Recruitment status was:  Recruiting
First Posted : June 22, 2016
Last Update Posted : June 22, 2016
Information provided by (Responsible Party):
University Hospital, Strasbourg, France

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

Condition or disease Intervention/treatment
Breast Cancer Other: retrospective medical records analyze

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Study Type : Observational
Estimated Enrollment : 10000 participants
Observational Model: Cohort
Time Perspective: Retrospective
Official Title: SENOMETRY : Big Data and Text-mining Technologies Applied for Breast Cancer Medical Data Analysis
Study Start Date : May 2016
Estimated Primary Completion Date : November 2016
Estimated Study Completion Date : December 2016

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Breast Cancer

Group/Cohort Intervention/treatment
Breast cancer patients between 2000 and 2016
Patients treated for a breast cancer between 2000 and 2016 in the Hospital of Strasbourg (France).
Other: retrospective medical records analyze
Ten thousand medical records (between years 2000 and 2016) will be analyzed

Primary Outcome Measures :
  1. Validate the reliability of a computer-based, automatic information retrieval method specific to medical records from breast cancer multidisciplinary meetings [ Time Frame: 6 months ]

Secondary Outcome Measures :
  1. Breast cancer recurrence rate after some therapeutic procedures [ Time Frame: 6 months ]
    Study of the recurrence rate of different subgroups of patients where various procedures were performed

Information from the National Library of Medicine

Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies.

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Ages Eligible for Study:   18 Years and older   (Adult, Older Adult)
Sexes Eligible for Study:   Female
Accepts Healthy Volunteers:   No
Sampling Method:   Probability Sample
Study Population
Patients (men and women) suffering from an in situ or invasive cancer treated at Hôpitaux Universitaires de Strasbourg between years 2000 and 2016.

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

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT02810093

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Contact: Anne Laudamy +33 3 88 11 66 88
Contact: anatta Razafimanantsoa + 33 3 88 11 54 14

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University Strasbourg Hospital Recruiting
Strasbourg, France, 67091
Contact: Carole Mathelin, MD    03 88 12 78 34   
Contact: Karl Neuberger   
Sponsors and Collaborators
University Hospital, Strasbourg, France
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Principal Investigator: Carole Mathelin, MD Strasbourg's University Hospitals

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Responsible Party: University Hospital, Strasbourg, France Identifier: NCT02810093    
Other Study ID Numbers: 6373
First Posted: June 22, 2016    Key Record Dates
Last Update Posted: June 22, 2016
Last Verified: June 2016
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No
Keywords provided by University Hospital, Strasbourg, France:
Breast cancer
Text mining
Big Data
Machine Learning
Additional relevant MeSH terms:
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Breast Neoplasms
Neoplasms by Site
Breast Diseases
Skin Diseases