Mei Jiang-Jun, Zhao Yun-Xin, Jiang Yi, Wang Jian, Yu Jia-Shun
Department of Ultrasound, Shanghai Punan Hospital of Pudong New District, Shanghai, People's Republic of China.
Department of Urology, Shanghai Punan Hospital of Pudong New District, Shanghai, People's Republic of China.
Cancer Manag Res. 2020 Jun 25;12:4959-4968. doi: 10.2147/CMAR.S250907. eCollection 2020.
Some patients with prostate cancer (PCa) will experience biochemical recurrence (BCR) after treatment. Current researches have identified the influencing factors of BCR, but these factors are difficult to quantify and hence unable to accurately predict the BCR in PCa patients.
To explore the value of contrast-enhanced ultrasound (CEUS) indicators in predicting the BCR after treatment by evaluating the association between them.
In a retrospective cohort study, 157 PCa patients were recruited and received prostate specific antigen (PSA) measurement, CEUS, pathological classification, and immunohistochemistry after puncture biopsy. PCa patients with BCR were included in the recurrence group, while the remaining patients were included in the non-recurrence group after a 5-year follow-up. The clinical characteristics and CEUS indicators were compared between the two groups, and the multivariable COX regression was used for screening the influencing factors of BCR. Receiver operating characteristic (ROC) curves were used to analyze the value of potential factors in predicting BCR. The effect of the combined prediction model was explored to improve the accuracy of the prediction.
Twelve patients are lost during the follow-up period and the final analysis included 145 patients. The 5-year BCR rate of PCa patients was 27%, with 43 patients in the recurrence group and 102 patients in the non-recurrence group. Multivariate analysis showed that lymph node metastasis (P<0.001), distant metastasis (P<0.001), Gleason score (P<0.001), pretreatment PSA (P<0.001), treatment method (P<0.001), peak intensity (PI) (P=0.001), and time to peak (TTP) (P=0.003) were independent influencing factors for BCR after treatment. ROC analysis showed that the AUCs of all indicators in predicting BCR were not high (all <0.9). The combination of lymph node metastasis, Gleason score, pretreatment PSA, and treatment method can improve the predictive accuracy (AUC = 0.85), but the AUC was still under 0.9. The combined prediction model including CEUS time-intensity curve (TIC) indicators (PI and TTP) could accurately predict the BCR after treatment (AUC=0.953). The sensitivity and specificity were 93.02% and 88.24%, respectively.
The prediction model including TIC indicators and common influencing factors can more accurately predict the BCR in PCa patients.
一些前列腺癌（PCa）患者在治疗后会出现生化复发（BCR）。目前的研究已经确定了BCR的影响因素，但这些因素难以量化，因此无法准确预测PCa患者的BCR。
通过评估对比增强超声（CEUS）指标之间的关联，探讨其在预测治疗后BCR中的价值。
在一项回顾性队列研究中，招募了157例PCa患者，在穿刺活检后接受前列腺特异性抗原（PSA）检测、CEUS、病理分类和免疫组化检查。随访5年后，发生BCR的PCa患者纳入复发组，其余患者纳入未复发组。比较两组患者的临床特征和CEUS指标，并采用多变量COX回归筛选BCR的影响因素。采用受试者操作特征（ROC）曲线分析各潜在因素预测BCR的价值。探索联合预测模型的效果以提高预测准确性。
随访期间有12例患者失访，最终纳入分析145例患者。PCa患者的5年BCR率为27%，复发组43例，未复发组102例。多因素分析显示，淋巴结转移（P<0.001）、远处转移（P<0.001）、Gleason评分（P<0.001）、治疗前PSA（P<0.001）、治疗方法（P<0.001）、峰值强度（PI）（P=0.001）和达峰时间（TTP）（P=0.003）是治疗后BCR的独立影响因素。ROC分析显示，各指标预测BCR的曲线下面积（AUC）均不高（均<0.9）。淋巴结转移、Gleason评分、治疗前PSA和治疗方法联合可提高预测准确性（AUC=0.85），但AUC仍低于0.9。包含CEUS时间-强度曲线（TIC）指标（PI和TTP）的联合预测模型能够准确预测治疗后的BCR（AUC=0.953），敏感性和特异性分别为93.02%和88.24%。
包含TIC指标和常见影响因素的预测模型能够更准确地预测PCa患者的BCR。
