van Rossum Peter S N, Fried David V, Zhang Lifei, Hofstetter Wayne L, van Vulpen Marco, Meijer Gert J, Court Laurence E, Lin Steven H
Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, The Netherlands.
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas The University of Texas Graduate School of Biomedical Sciences at Houston, Houston, Texas; and.
J Nucl Med. 2016 May;57(5):691-700. doi: 10.2967/jnumed.115.163766. Epub 2016 Jan 21.
A reliable prediction of a pathologic complete response (pathCR) to chemoradiotherapy before surgery for esophageal cancer would enable investigators to study the feasibility and outcome of an organ-preserving strategy after chemoradiotherapy. So far no clinical parameters or diagnostic studies are able to accurately predict which patients will achieve a pathCR. The aim of this study was to determine whether subjective and quantitative assessment of baseline and postchemoradiation (18)F-FDG PET can improve the accuracy of predicting pathCR to preoperative chemoradiotherapy in esophageal cancer beyond clinical predictors.
This retrospective study was approved by the institutional review board, and the need for written informed consent was waived. Clinical parameters along with subjective and quantitative parameters from baseline and postchemoradiation (18)F-FDG PET were derived from 217 esophageal adenocarcinoma patients who underwent chemoradiotherapy followed by surgery. The associations between these parameters and pathCR were studied in univariable and multivariable logistic regression analysis. Four prediction models were constructed and internally validated using bootstrapping to study the incremental predictive values of subjective assessment of (18)F-FDG PET, conventional quantitative metabolic features, and comprehensive (18)F-FDG PET texture/geometry features, respectively. The clinical benefit of (18)F-FDG PET was determined using decision-curve analysis.
A pathCR was found in 59 (27%) patients. A clinical prediction model (corrected c-index, 0.67) was improved by adding (18)F-FDG PET-based subjective assessment of response (corrected c-index, 0.72). This latter model was slightly improved by the addition of 1 conventional quantitative metabolic feature only (i.e., postchemoradiation total lesion glycolysis; corrected c-index, 0.73), and even more by subsequently adding 4 comprehensive (18)F-FDG PET texture/geometry features (corrected c-index, 0.77). However, at a decision threshold of 0.9 or higher, representing a clinically relevant predictive value for pathCR at which one may be willing to omit surgery, there was no clear incremental value.
Subjective and quantitative assessment of (18)F-FDG PET provides statistical incremental value for predicting pathCR after preoperative chemoradiotherapy in esophageal cancer. However, the discriminatory improvement beyond clinical predictors does not translate into a clinically relevant benefit that could change decision making.
在食管癌手术前对放化疗的病理完全缓解(pathCR)进行可靠预测,将使研究人员能够研究放化疗后保留器官策略的可行性和结果。到目前为止,尚无临床参数或诊断研究能够准确预测哪些患者会实现病理完全缓解。本研究的目的是确定对基线和放化疗后(18)F-FDG PET进行主观和定量评估是否能在临床预测指标之外提高预测食管癌术前放化疗病理完全缓解的准确性。
本回顾性研究经机构审查委员会批准,无需书面知情同意。临床参数以及来自基线和放化疗后(18)F-FDG PET的主观和定量参数来自217例接受放化疗后手术的食管腺癌患者。在单变量和多变量逻辑回归分析中研究这些参数与病理完全缓解之间的关联。构建了四个预测模型,并使用自抽样法进行内部验证,以分别研究(18)F-FDG PET主观评估、传统定量代谢特征和综合(18)F-FDG PET纹理/几何特征的增量预测价值。使用决策曲线分析确定(18)F-FDG PET的临床益处。
59例(27%)患者实现了病理完全缓解。通过添加基于(18)F-FDG PET的主观反应评估(校正c指数,0.72),临床预测模型(校正c指数,0.67)得到了改善。仅添加1个传统定量代谢特征(即放化疗后总病变糖酵解;校正c指数,0.73)后,后一种模型略有改善,随后添加4个综合(18)F-FDG PET纹理/几何特征后改善更大(校正c指数,0.77)。然而,在决策阈值为0.9或更高时,这代表了对病理完全缓解具有临床相关预测价值,此时可能愿意省略手术,没有明显的增量价值。
对(18)F-FDG PET进行主观和定量评估为预测食管癌术前放化疗后的病理完全缓解提供了统计学上的增量价值。然而,超出临床预测指标的鉴别改善并未转化为可改变决策的临床相关益处。