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Predictive factors for abiraterone withdrawal syndrome
S Almendros1, M A Berenguer-Francés2, F Ferrer-González2
1Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Barcelona, España; Servicio de Oncología Radioterápica, Institut Català d'Oncologia - L'Hospitalet, L'Hospitalet de Llobregat, Barcelona, España.
Abiraterone withdrawal syndrome (AWS) can occur after stopping abiraterone acetate (AA) treatment for metastatic castration-resistant prostate cancer. High PSA, ISUP grade 4, and stage IV at diagnosis predict AWS, potentially informing new treatment strategies.
Area of Science:
- Oncology
- Urology
Background:
- Abiraterone acetate (AA) is a treatment for metastatic castration-resistant prostate cancer (mCRPC).
- Abiraterone withdrawal syndrome (AWS) is a temporary PSA decrease after discontinuing AA.
- Predictive factors for AWS are not well-established.
Purpose of the Study:
- To identify predictive factors for AWS at the time of diagnosis in mCRPC patients.
Main Methods:
- Retrospective study of 70 mCRPC patients treated with AA.
- Analysis of patient data including PSA levels, ISUP grade, and stage at diagnosis.
- Statistical analysis to determine significant predictors of AWS.
Main Results:
- AWS occurred in 11 patients.
- Predictive factors for AWS included high PSA (p=.002), ISUP grade ≥4 (p=.002), and stage IV at diagnosis (p<.001).
- An AUC of 0.84 indicated good predictive accuracy.
Conclusions:
- AWS is not uncommon and can lead to prolonged responses after AA withdrawal.
- Identifying AWS predictors may influence future mCRPC treatment strategies.
- These findings suggest potential for novel treatment schemes in mCRPC management.
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