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Radiological assessment schedule for high-grade glioma patients during the surveillance period using parametric modeling

Authors :
Yong Hwy Kim
Tae Min Kim
Seung Hong Choi
Joo Ho Lee
Jin Wook Kim
Jongjin Lee
So Young Ji
Yongdai Kim
Chul-Kee Park
Jae Kyung Won
Sung Hye Park
Soon-Tae Lee
Source :
Neuro Oncol
Publication Year :
2020
Publisher :
Oxford University Press (OUP), 2020.

Abstract

Background An optimal radiological surveillance plan is crucial for high-grade glioma (HGG) patients, which is determined arbitrarily in daily clinical practice. We propose the radiological assessment schedule using a parametric model of standardized progression-free survival (PFS) curves. Methods A total of 277 HGG patients (178 glioblastoma [GBM] and 99 anaplastic astrocytoma [AA]) from a single institute who completed the standard treatment protocol were enrolled in this cohort study and retrospectively analyzed. The patients were stratified into each layered risk group by genetic signatures and residual mass or through recursive partitioning analysis. PFS curves were estimated using the piecewise exponential survival model. The criterion of a 10% progression rate among the remaining patients at each observation period was used to determine the optimal radiological assessment time point. Results The optimal follow-up intervals for MRI evaluations of isocitrate dehydrogenase (IDH) wild-type GBM was every 7.4 weeks until 120 weeks after the end of standard treatment, followed by a 22-week inflection period and every 27.6 weeks thereafter. For the IDH mutated GBM, scans every 13.2 weeks until 151 weeks are recommended. The optimal follow-up intervals were every 22.8 weeks for IDH wild-type AA, and 41.2 weeks for IDH mutated AA until 241 weeks. Tailored radiological assessment schedules were suggested for each layered risk group of the GBM and the AA patients. Conclusions The optimal schedule of radiological assessments for each layered risk group of patients with HGG could be determined from the parametric model of PFS.

Details

ISSN :
15235866 and 15228517
Volume :
23
Database :
OpenAIRE
Journal :
Neuro-Oncology
Accession number :
edsair.doi.dedup.....592491c82931bfc42a460bf133448ca6
Full Text :
https://doi.org/10.1093/neuonc/noaa250