Department of Radiation Oncology, University Medical Center Utrecht, The Netherlands.
Int J Radiat Oncol Biol Phys. 2011 Nov 1;81(3):737-44. doi: 10.1016/j.ijrobp.2010.06.009. Epub 2010 Oct 1.
Acute urinary retention (AUR) after iodine-125 (I-125) prostate brachytherapy negatively influences long-term quality of life and therefore should be prevented. We aimed to develop a nomogram to preoperatively predict the risk of AUR.
Using the preoperative data of 714 consecutive patients who underwent I-125 prostate brachytherapy between 2005 and 2008 at our department, we modeled the probability of AUR. Multivariate logistic regression analysis was used to assess the predictive ability of a set of pretreatment predictors and the additional value of a new risk factor (the extent of prostate protrusion into the bladder). The performance of the final model was assessed with calibration and discrimination measures.
Of the 714 patients, 57 patients (8.0%) developed AUR after implantation. Multivariate analysis showed that the combination of prostate volume, IPSS score, neoadjuvant hormonal treatment and the extent of prostate protrusion contribute to the prediction of AUR. The discriminative value (receiver operator characteristic area, ROC) of the basic model (including prostate volume, International Prostate Symptom Score, and neoadjuvant hormonal treatment) to predict the development of AUR was 0.70. The addition of prostate protrusion significantly increased the discriminative power of the model (ROC 0.82). Calibration of this final model was good. The nomogram showed that among patients with a low sum score (<18 points), the risk of AUR was only 0%-5%. However, in patients with a high sum score (>35 points), the risk of AUR was more than 20%.
This nomogram is a useful tool for physicians to predict the risk of AUR after I-125 prostate brachytherapy. The nomogram can aid in individualized treatment decision-making and patient counseling.
碘-125(I-125)前列腺近距离放射治疗后发生急性尿潴留(AUR)会对长期生活质量产生负面影响,因此应予以预防。我们旨在开发一种列线图来预测 AUR 的风险。
利用 2005 年至 2008 年我科 714 例连续接受 I-125 前列腺近距离放射治疗患者的术前资料,建立 AUR 发生概率模型。采用多变量 logistic 回归分析评估一组预处理预测因子的预测能力和新危险因素(前列腺突入膀胱的程度)的附加价值。通过校准和区分度评估最终模型的性能。
714 例患者中,57 例(8.0%)在植入后发生 AUR。多变量分析显示,前列腺体积、IPSS 评分、新辅助激素治疗和前列腺突出程度的组合有助于预测 AUR。基本模型(包括前列腺体积、国际前列腺症状评分和新辅助激素治疗)预测 AUR 发展的判别值(ROC 曲线下面积,ROC)为 0.70。前列腺突出程度的增加显著提高了模型的判别能力(ROC 0.82)。该最终模型的校准良好。列线图显示,在低总分(<18 分)的患者中,AUR 的风险仅为 0%-5%。然而,在总分较高(>35 分)的患者中,AUR 的风险超过 20%。
该列线图是医生预测 I-125 前列腺近距离放射治疗后 AUR 风险的有用工具。该列线图可辅助个体化治疗决策和患者咨询。