Validity of Brain Metastasis Risk Predictive Model in Hormone Positive Breast Cancer Patients
NCT ID: NCT06729099
Last Updated: 2024-12-11
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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NOT_YET_RECRUITING
128 participants
OBSERVATIONAL
2025-01-31
2027-06-30
Brief Summary
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Detailed Description
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Age at BC diagnosis, tumor size, axillary adenopathy, clinical stage, HER2 status, Ki67 proliferation index and the modified Scarff-Bloom-Richardson grade of differentiation.
2. Analysis Plan:
Continuous variables as means and standard deviation (SD) if they follow a normal distribution; if not, as medians and IQR (interquartile range). Numbers and percentages display categorical variables.
3. Model validation:
The association between covariates and the diagnosis of brain metastases by performing logistic regression analyses; odds ratio (OR), 95 % confidence intervals (CI), and p-value will be estimated. Variables with a p-value \< 0.05 in the univariate logistic regression analysis will be further assessed in a multivariate logistic regression analysis.
For the clinical use of the model, we will use a score to each variable as that designed by Cacho-Díaz B. et. al. then, we will categorize patients into three risk groups according to the sum of the scores. We will employe a Cox regression analysis to assess each group's risk of developing brain metastases. Adjusted hazard ratios (aHRs), 95 % CIs, and p values will be evaluated.
Conditions
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Keywords
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Study Design
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COHORT
OTHER
Study Groups
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Low-risk group
Brain metastasis risk prediction model score 0-4 points.
No interventions assigned to this group
Medium-risk group
Brain metastasis risk prediction model score 5-10 points.
No interventions assigned to this group
High-risk group
Brain metastasis risk prediction model score \>10 points.
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
2. Bilateral breast cancer.
3. Synchronic cancer (i.e., lung cancer, melanoma).
4. Paitents presenting neurologic symptoms without follow-up or lacking a contrast-enhanced magnetic resonance image (cMRI).
5. Incomplete clinicopathological information at the time of diagnosis.
18 Years
FEMALE
No
Sponsors
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Assiut University
OTHER
Responsible Party
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Moheb Ibrahim Melek
Clinical oncology specialist
Central Contacts
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Moheb I Moheb Ibrahim Melek, MSc in clinical oncology
Role: CONTACT
Phone: +201092655523
Email: [email protected]
Other Identifiers
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Predictive model
Identifier Type: -
Identifier Source: org_study_id