Vos Maaike J, Berkhof Johannes, Postma Tjeerd J, Hoekstra Otto S, Barkhof Frederik, Heimans Jan J
Department of Neurology, VU University Medical Centre, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.
Eur J Nucl Med Mol Imaging. 2006 Feb;33(2):222-7. doi: 10.1007/s00259-005-1883-z. Epub 2005 Sep 29.
The aim of this study was to estimate 201Tl SPECT and CT-MRI cut-off values that lead to a validated prognostic classification for the end-point overall survival, in order to discriminate glioma patients with good and poor prognosis at an early stage during chemotherapeutic treatment.
We studied patients who underwent 201Tl SPECT and CT-MRI before and after two courses of chemotherapy. Cut-off values were retrieved from the Cox model. Patients were classified according to the computed cut-off values, creating subgroups of patients with different prognosis in terms of survival [tumour regression (TR); stable disease (SD); tumour progression (TP)]. The differences between the subgroups were assessed by Kaplan-Meier analyses. The predictive performance of the classification procedure was evaluated by a leave-one-out cross-validation method.
201Tl SPECT classified 41% of the patients as SD, 25% as TR and 34% as TP. CT-MRI classified 82% of the patients as SD, and only 4% and 14% as TR and TP, respectively. Of those patients with a relatively long overall survival (i.e. > or =16 months), cross-validation estimates of 201Tl SPECT classification rates were 50% TR and 50% SD, and cross-validation estimates of CT-MRI classification rates were 7% TR, 72% SD, and 21% TP.
We constructed a 201Tl SPECT model that makes it possible to identify glioma patients with a good or a poor prognosis at an early stage during chemotherapeutic treatment. With this model, accurate predictions can be made with regard to the expected duration of survival.
本研究旨在评估201Tl单光子发射计算机断层扫描(SPECT)及计算机断层扫描-磁共振成像(CT-MRI)的截断值,以得出针对总生存终点的有效预后分类,从而在化疗治疗早期区分预后良好和不良的胶质瘤患者。
我们研究了在两个化疗疗程前后接受201Tl SPECT及CT-MRI检查的患者。截断值通过Cox模型获取。根据计算出的截断值对患者进行分类,从而创建出在生存方面具有不同预后的患者亚组[肿瘤退缩(TR);疾病稳定(SD);肿瘤进展(TP)]。通过Kaplan-Meier分析评估亚组之间的差异。采用留一法交叉验证方法评估分类程序的预测性能。
201Tl SPECT将41%的患者分类为SD,25%为TR,34%为TP。CT-MRI将82%的患者分类为SD,分别仅有4%和14%为TR和TP。在那些总生存期相对较长(即≥16个月)的患者中,201Tl SPECT分类率的交叉验证估计为50% TR和50% SD,CT-MRI分类率的交叉验证估计为7% TR、72% SD和21% TP。
我们构建了一个201Tl SPECT模型,该模型能够在化疗治疗早期识别预后良好或不良的胶质瘤患者。借助该模型,可以对预期生存期做出准确预测。