Artificial intelligence improves risk stratification for breast cancer recurrence and mortality in women exposed to pesticides: a call for reassessment of stratification criteria - Scorecard - MDSpire
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Artificial intelligence improves risk stratification for breast cancer recurrence and mortality in women exposed to pesticides: a call for reassessment of stratification criteria
Clinical Scorecard: Machine Learning Enhances Risk Assessment for Breast Cancer Recurrence and Mortality in Women with Pesticide Exposure: A Proposal for Reevaluation of Stratification Standards
At a Glance
Category
Detail
Condition
Breast Cancer
Key Mechanisms
Incorporation of pesticide exposure as a risk factor in predictive models.
Target Population
Women with breast cancer, particularly those with occupational pesticide exposure.
Care Setting
Clinical settings in Brazil, particularly in rural areas.
Key Highlights
Machine learning models improved prediction of breast cancer recurrence and mortality by 24.12% when including pesticide exposure.
Pesticide exposure is not currently considered in the Brazilian Diagnostic and Therapeutic Guidelines for Breast Carcinoma.
Women exposed to pesticides showed higher rates of disease recurrence and aggressive tumor subtypes.
Guideline-Based Recommendations
Diagnosis
Consider pesticide exposure as a risk factor in breast cancer diagnosis.
Management
Re-evaluate treatment protocols to include risk stratification based on pesticide exposure.
Monitoring & Follow-up
Monitor breast cancer patients for recurrence and metastasis with consideration of pesticide exposure.
Risks
Increased likelihood of aggressive breast cancer and higher rates of metastasis in women exposed to pesticides.
Patient & Prescribing Data
Women with breast cancer, particularly those in agricultural settings.
Tailor treatment strategies based on the inclusion of pesticide exposure in risk assessments.
Clinical Best Practices
Utilize machine learning algorithms to enhance predictive accuracy in breast cancer outcomes.
Incorporate environmental risk factors, such as pesticide exposure, into clinical guidelines.
