前列腺癌碳离子放射治疗后急性尿毒性（AUT）的正常组织并发症概率（NTCP）模型。

Normal tissue complication probability (NTCP) models of acute urinary toxicity (AUT) following carbon ion radiotherapy (CIRT) for prostate cancer.

机构信息

Department of Medical Physics, Shanghai Proton and Heavy Ion Center, Shanghai 201321, China; Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai 201321, China.

Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai 201321, China; Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai 201321, China.

出版信息

Radiother Oncol. 2021 Mar;156:69-79. doi: 10.1016/j.radonc.2020.12.009. Epub 2020 Dec 11.

DOI:10.1016/j.radonc.2020.12.009

PMID:33309999

Abstract

PURPOSE

To estimate the Lyman Kutcher Burman (LKB) and multivariate NTCP models predicting the AUT of prostate cancer treated with CIRT.

MATERIALS AND METHODS

A cohort of 154 prostate adenocarcinoma patients were retrospectively analyzed. The AUT levels were graded according to CTCAE 4.03. Based on dosimetric parameters and/or clinical factors, a set of variables with best-fit values determined in the two models was validated by the area under the receiver operating characteristic curve (AUC) and used to correlate the predicted and observed NTCP rates for both levels and related endpoints.

RESULT

59 (38.3%) patients experienced AUT. For LKB model, the equivalent uniform doses (EUDs) were calculated to be 62.0 GyE (following V > 1.7%) and 61.2 GyE (following maximum dose > 63.0 GyE) with predicted NTCP rates of 37.0% (AUC: 0.71) and 15.6% (AUC: 0.65) for AUT G1&2 and G2 of bladder. While for the multivariate model, the predicted NTCP rates was 37.1% (AUC: 0.70) and 20.2% (AUC: 0.64) for AUT G1&2 and G2, associated with V and V, respectively. Nocturia was associated with bladder volume and maximum dose for G1&2, with patient's age and maximum bladder dose for G2. Other predictable endpoints were associated with V. The predicted NTCPs agree with the observed complication rates for bladder and its wall.

CONCLUSIONS

The LKB model successfully predicted the NTCP rates of both AUT levels and urgency urination. The multivariate model predicted well on both levels and nocturia. Decreasing high bladder dose volume may reduce the incidence of AUT.

摘要

目的

评估 Lyman Kutcher Burman（LKB）和多变量 NTCP 模型预测接受 CIRT 治疗的前列腺癌的自动全膀胱照射（AUT）。

材料与方法

回顾性分析了 154 例前列腺腺癌患者。根据 CTCAE 4.03 将 AUT 水平分级。基于剂量学参数和/或临床因素，通过接受者操作特征曲线（ROC）下面积（AUC）验证两个模型中最佳拟合值的一组变量，并将预测和观察到的 NTCP 率用于两种水平和相关终点的相关性。

结果

59 例（38.3%）患者出现 AUT。对于 LKB 模型，等效均匀剂量（EUD）分别为 62.0 GyE（V>1.7%）和 61.2 GyE（最大剂量>63.0 GyE），预测的 NTCP 率分别为 37.0%（AUC：0.71）和 15.6%（AUC：0.65），用于 AUT G1&2 和膀胱 G2。而对于多变量模型，预测的 NTCP 率分别为 37.1%（AUC：0.70）和 20.2%（AUC：0.64），用于 AUT G1&2 和 G2，分别与 V 和 V 相关。对于 G1&2，夜尿与膀胱体积和最大剂量相关，对于 G2，与患者年龄和最大膀胱剂量相关。其他可预测的终点与 V 相关。预测的 NTCP 与膀胱及其壁的观察到的并发症发生率相符。