Abstract
Purpose
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.
Methods
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.
Results
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. ≥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.
Conclusion
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.
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Acknowledgements
The authors would like to thank B.M.J. Uitdehaag for statistical assistence.
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Vos, M.J., Berkhof, J., Postma, T.J. et al. Thallium-201 SPECT: the optimal prediction of response in glioma therapy. Eur J Nucl Med Mol Imaging 33, 222–227 (2006). https://doi.org/10.1007/s00259-005-1883-z
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DOI: https://doi.org/10.1007/s00259-005-1883-z