PDF(Pubmed)
Abstract：
UNASSIGNED: To explore the predictive factors and predictive model construction for the progression of prostate cancer bone metastasis to castration resistance.
UNASSIGNED: Clinical data of 286 patients diagnosed with prostate cancer with bone metastasis, initially treated with endocrine therapy, and progressing to metastatic castration resistant prostate cancer (mCRPC) were collected. By comparing the differences in various factors between different groups with fast and slow occurrence of castration-resistant prostate cancer (CRPC). Kaplan-Meier survival analysis and COX multivariate risk proportional regression model were used to compare the differences in the time to progression to CRPC in different groups. The COX multivariate risk proportional regression model was used to evaluate the impact of candidate factors on the time to progression to CRPC and establish a predictive model. The accuracy of the model was then tested using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).
UNASSIGNED: The median time for 286 mCRPC patients to progress to CRPC was 17 (9.5-28.0) months. Multivariate analysis showed that the lowest value of PSA (PSA nadir), the time when PSA dropped to its lowest value (timePSA), and the number of BM, and LDH were independent risk factors for rapid progression to CRPC. Based on the four independent risk factors mentioned above, a prediction model was established, with the optimal prediction model being a random forest with area under curve (AUC) of 0.946[95% CI: 0.901-0.991] and 0.927[95% CI: 0.864-0.990] in the training and validation cohort, respectively.
UNASSIGNED: After endocrine therapy, the PSA nadir, timePSA, the number of BM, and LDH are the main risk factors for rapid progression to mCRPC in patients with prostate cancer bone metastases. Establishing a CRPC prediction model is helpful for early clinical intervention decision-making.
UNASSIGNED: Clinical data of 286 patients diagnosed with prostate cancer with bone metastasis, initially treated with endocrine therapy, and progressing to metastatic castration resistant prostate cancer (mCRPC) were collected. By comparing the differences in various factors between different groups with fast and slow occurrence of castration-resistant prostate cancer (CRPC). Kaplan-Meier survival analysis and COX multivariate risk proportional regression model were used to compare the differences in the time to progression to CRPC in different groups. The COX multivariate risk proportional regression model was used to evaluate the impact of candidate factors on the time to progression to CRPC and establish a predictive model. The accuracy of the model was then tested using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).
UNASSIGNED: The median time for 286 mCRPC patients to progress to CRPC was 17 (9.5-28.0) months. Multivariate analysis showed that the lowest value of PSA (PSA nadir), the time when PSA dropped to its lowest value (timePSA), and the number of BM, and LDH were independent risk factors for rapid progression to CRPC. Based on the four independent risk factors mentioned above, a prediction model was established, with the optimal prediction model being a random forest with area under curve (AUC) of 0.946[95% CI: 0.901-0.991] and 0.927[95% CI: 0.864-0.990] in the training and validation cohort, respectively.
UNASSIGNED: After endocrine therapy, the PSA nadir, timePSA, the number of BM, and LDH are the main risk factors for rapid progression to mCRPC in patients with prostate cancer bone metastases. Establishing a CRPC prediction model is helpful for early clinical intervention decision-making.
摘要：
■探讨前列腺癌骨转移进展为去势抵抗的预测因素及预测模型构建
■286例前列腺癌骨转移患者的临床资料,最初接受内分泌治疗，并收集进展为转移性去势耐药前列腺癌（mCRPC）。通过比较各种因素在去势抵抗性前列腺癌(CRPC)发生快、慢不同人群之间的差异。采用Kaplan-Meier生存分析和COX多因素风险比例回归模型比较不同组患者进展至CRPC时间的差异。采用COX多因素风险比例回归模型评价候选因素对进展至CRPC时间的影响,建立预测模型。然后使用受试者工作特性(ROC)曲线和决策曲线分析(DCA)测试模型的准确性。
■286名mCRPC患者进展为CRPC的中位时间为17（9.5-28.0）个月。多因素分析显示,PSA最低值(PSA最低点),PSA下降到最低值的时间(timePSA)，和BM的数量，LDH是CRPC快速进展的独立危险因素。根据上述四个独立风险因素，建立了预测模型，在训练和验证队列中，最佳预测模型是曲线下面积（AUC）为0.946[95％CI：0.901-0.991]和0.927[95％CI：0.864-0.990]的随机森林，分别。
■内分泌治疗后，PSA最低点,timePSA,BM的数量，和LDH是前列腺癌骨转移患者快速进展为mCRPC的主要危险因素。建立CRPC预测模型有助于早期临床干预决策。
■286例前列腺癌骨转移患者的临床资料,最初接受内分泌治疗，并收集进展为转移性去势耐药前列腺癌（mCRPC）。通过比较各种因素在去势抵抗性前列腺癌(CRPC)发生快、慢不同人群之间的差异。采用Kaplan-Meier生存分析和COX多因素风险比例回归模型比较不同组患者进展至CRPC时间的差异。采用COX多因素风险比例回归模型评价候选因素对进展至CRPC时间的影响,建立预测模型。然后使用受试者工作特性(ROC)曲线和决策曲线分析(DCA)测试模型的准确性。
■286名mCRPC患者进展为CRPC的中位时间为17（9.5-28.0）个月。多因素分析显示,PSA最低值(PSA最低点),PSA下降到最低值的时间(timePSA)，和BM的数量，LDH是CRPC快速进展的独立危险因素。根据上述四个独立风险因素，建立了预测模型，在训练和验证队列中，最佳预测模型是曲线下面积（AUC）为0.946[95％CI：0.901-0.991]和0.927[95％CI：0.864-0.990]的随机森林，分别。
■内分泌治疗后，PSA最低点,timePSA,BM的数量，和LDH是前列腺癌骨转移患者快速进展为mCRPC的主要危险因素。建立CRPC预测模型有助于早期临床干预决策。
