Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Ave, Box 0628, Room M-372, San Francisco, CA 94143-0628, USA.
Radiology. 2011 Nov;261(2):477-86. doi: 10.1148/radiol.11110457. Epub 2011 Aug 24.
To determine whether magnetic resonance (MR) imaging and MR spectroscopic imaging findings can improve predictions made with the Kattan nomogram for radiation therapy.
The institutional review board approved this retrospective HIPAA-compliant study. Ninety-nine men who underwent endorectal MR and MR spectroscopy before external-beam radiation therapy for prostate cancer (January 1998 to June 2007) were included. Linear predictors were calculated with input variables from the study sample and the Kattan original coefficients. The linear predictor is a single weighted value that combines information of all predictor variables in a model, where the weight of each value is its association with the outcome. Two radiologists independently reviewed all MR images to determine extent of disease; a third independent reader resolved discrepancies. Biochemical failure was defined as a serum prostate-specific antigen level of 2 ng/mL (2 μg/L) or more above nadir. Cox proportional hazard models were used to determine the probabilities of treatment failure (biochemical failure) in 5 years. One model included only the Kattan nomogram data; the other also incorporated imaging findings. The discrimination performance of all models was determined with receiver operating characteristics (ROC) curve analyses. These analyses were followed by an assessment of net risk reclassification.
The areas under the ROC curve for the Kattan nomogram and the model incorporating MR imaging findings were 61.1% (95% confidence interval: 58.1%, 64.0%) and 78.0% (95% confidence interval: 75.7%, 80.4%), respectively. Comparison of performance showed that the model with imaging findings performed significantly better than did the model with clinical variables alone (P < .001). Overall, the addition of imaging findings led to an improvement in risk classification of about 28%, ranging from approximately a minimum of 16% to a maximum of 39%, depending on the risk change considered important.
MR imaging data improve the prediction of biochemical failure with the Kattan nomogram after external-beam radiation therapy for prostate cancer. The number needed to image to improve the prediction of biochemical failure in one patient ranged from three to six.
确定磁共振（MR）成像和 MR 波谱成像结果是否可以改善 Kattan 列线图在放射治疗中的预测。
本研究经机构审查委员会批准，为符合 HIPAA 规定的回顾性研究。共纳入 99 例前列腺癌患者，这些患者在接受外照射放射治疗前均接受了直肠内 MR 和 MR 波谱检查（1998 年 1 月至 2007 年 6 月）。研究样本的输入变量用于计算线性预测值，同时采用 Kattan 原始系数。线性预测值是一个单一的加权值，它结合了模型中所有预测变量的信息，每个值的权重与其与结果的相关性有关。两位放射科医生独立审查所有 MR 图像以确定疾病范围，第三位独立读者解决差异。生化失败定义为血清前列腺特异性抗原水平比最低点升高 2ng/mL（2μg/L）或更高。Cox 比例风险模型用于确定 5 年内治疗失败（生化失败）的概率。一个模型仅包含 Kattan 列线图数据，另一个模型还包含影像学发现。所有模型的判别性能均通过接收者操作特征（ROC）曲线分析确定。随后进行了净风险再分类评估。
Kattan 列线图和包含 MR 成像结果的模型的 ROC 曲线下面积分别为 61.1%（95%置信区间：58.1%，64.0%）和 78.0%（95%置信区间：75.7%，80.4%）。性能比较表明，包含影像学发现的模型明显优于仅包含临床变量的模型（P<0.001）。总体而言，影像学发现的加入导致风险分类的改善约为 28%，具体取决于认为重要的风险变化，范围从最小约 16%到最大约 39%。
MR 成像数据可改善 Kattan 列线图在前列腺癌外照射放射治疗后的生化失败预测。为改善一名患者的生化失败预测而需要进行的成像数量为 3 至 6 次。
