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Updated: Feb 16, 2026

A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer
Published on: March 6, 2018
Predicting castration-resistant prostate cancer after combined androgen blockade
Miao He1, Haina Liu1, Jingyi Cao2
1Department of Nuclear Medicine, Xuzhou Cancer Hospital, Jiangsu Province, Xuzhou, China.
Early-stage castration resistance in prostate cancer (CRPC) with bone metastasis is predicted by longer times to reach the lowest prostate-specific antigen (PSA) value. Bone scans effectively diagnose and grade bone metastases in these patients.
Area of Science:
- Oncology
- Nuclear Medicine
- Urology
Background:
- Prostate cancer (PC) frequently metastasizes to bone.
- Castration resistance (CRPC) is a critical progression in advanced PC.
- Early identification of factors predicting CRPC is essential for treatment optimization.
Purpose of the Study:
- To analyze 99Tcm-MDP bone scans in patients with bone metastatic PC.
- To identify factors influencing early-stage castration resistance in PC patients with bone metastasis.
Main Methods:
- Retrospective analysis of clinical data from 92 patients with bone metastatic PC treated with maximal androgen blockade.
- 99Tcm-MDP bone scans for metastasis detection and grading.
- Regular monitoring of prostate-specific antigen (PSA) levels.
Main Results:
- A total of 464 bone metastases were detected initially, with 30.6% in the pelvis.
- Median time to CRPC occurrence was 23 months after treatment.
- Longer time to reach the lowest PSA value independently predicted early-onset CRPC (<1 year).
- Gleason score >8, higher post-treatment PSA, and shorter time to lowest PSA predicted poorer treatment response.
Conclusions:
- 99Tcm-MDP bone scans are valuable for diagnosing and grading prostate cancer bone metastasis.
- Predictive factors for early CRPC and poorer treatment response were identified.
- These findings aid in managing advanced prostate cancer with bone metastasis.
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Resistivity
Resistance

