Role of 3D volume growth rate for drug activity evaluation in meningioma clinical trials: the example of the CEVOREM study.
clinical trial
drug activity
meningioma
outcome
tumor growth rate
Journal
Neuro-oncology
ISSN: 1523-5866
Titre abrégé: Neuro Oncol
Pays: England
ID NLM: 100887420
Informations de publication
Date de publication:
01 07 2021
01 07 2021
Historique:
pubmed:
9
2
2021
medline:
5
8
2021
entrez:
8
2
2021
Statut:
ppublish
Résumé
We aimed to improve the assessment of the drug activity in meningioma clinical trials based on the study of the 3D volume growth rate (3DVGR) in a series of aggressive meningiomas. We secondarily aimed to correlate 3DVGR study with patient outcome. We performed a post hoc analysis based on volume data and 3DVGR extracted from CEVOREM study including 18 patients with 32 recurrent high-grade meningiomas and treated with everolimus and octreotide. The joint latent class model was used to classify tumor 3DVGR undertreatment. Class 1 includes lesions responding to treatment with decrease in volume in the first 3 months, and then a stabilization thereafter (9.5% of tumors) (mean pretreatment 3DVGR = 6.13%/month; mean undertreatment 3DVGR = -18.7%/month within 3 first months and -0.14%/month after the 3 first months). Class 2 includes lesions considered as stable or with a slight increase in volume undertreatment (65.5%) (mean pretreatment 3DVGR = 6.09%/month; undertreatment 3DVGR = -0.09% within the first 3 months). Class 3 includes lesions without 3DVGR decrease (25%) (mean pretreatment 3DVGR = 46.9%/month; mean undertreatment 3DVGR = 19.2%/month within the first 3 months). Patients with class 3 lesions had a significantly worse progression-free survival (PFS) rate than class 1 and 2 ones. Tumor 3DVGR could be helpful to detect early signal of drugs antitumoral activity or nonactivity. This volume response classification could help in the assessment of drug activity in tumors with mostly volume stabilization and rare response as aggressive meningiomas even with a low number of patients in complement to 6 months PFS.
Sections du résumé
BACKGROUND
We aimed to improve the assessment of the drug activity in meningioma clinical trials based on the study of the 3D volume growth rate (3DVGR) in a series of aggressive meningiomas. We secondarily aimed to correlate 3DVGR study with patient outcome.
METHODS
We performed a post hoc analysis based on volume data and 3DVGR extracted from CEVOREM study including 18 patients with 32 recurrent high-grade meningiomas and treated with everolimus and octreotide. The joint latent class model was used to classify tumor 3DVGR undertreatment.
RESULTS
Class 1 includes lesions responding to treatment with decrease in volume in the first 3 months, and then a stabilization thereafter (9.5% of tumors) (mean pretreatment 3DVGR = 6.13%/month; mean undertreatment 3DVGR = -18.7%/month within 3 first months and -0.14%/month after the 3 first months). Class 2 includes lesions considered as stable or with a slight increase in volume undertreatment (65.5%) (mean pretreatment 3DVGR = 6.09%/month; undertreatment 3DVGR = -0.09% within the first 3 months). Class 3 includes lesions without 3DVGR decrease (25%) (mean pretreatment 3DVGR = 46.9%/month; mean undertreatment 3DVGR = 19.2%/month within the first 3 months). Patients with class 3 lesions had a significantly worse progression-free survival (PFS) rate than class 1 and 2 ones.
CONCLUSIONS
Tumor 3DVGR could be helpful to detect early signal of drugs antitumoral activity or nonactivity. This volume response classification could help in the assessment of drug activity in tumors with mostly volume stabilization and rare response as aggressive meningiomas even with a low number of patients in complement to 6 months PFS.
Identifiants
pubmed: 33556177
pii: 6131353
doi: 10.1093/neuonc/noab019
pmc: PMC8661407
doi:
Substances chimiques
Pharmaceutical Preparations
0
Octreotide
RWM8CCW8GP
Types de publication
Clinical Trial
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1139-1147Informations de copyright
© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Références
Int J Neurosci. 2016 Nov;126(11):1002-6
pubmed: 26365467
Clin Cancer Res. 2014 Jan 1;20(1):246-52
pubmed: 24240109
Neuro Oncol. 2016 Mar;18(3):401-7
pubmed: 26354929
J Neurosurg. 2020 May 22;134(5):1377-1385
pubmed: 32442973
J Neurosurg. 2009 Apr;110(4):675-84
pubmed: 19061353
J Neurooncol. 2015 Aug;124(1):33-43
pubmed: 26015296
J Neurooncol. 2012 Aug;109(1):63-70
pubmed: 22535433
Stat Methods Med Res. 2014 Feb;23(1):74-90
pubmed: 22517270
Neuro Oncol. 2019 Jan 1;21(1):26-36
pubmed: 30137421
Eur Urol. 2014 Apr;65(4):713-20
pubmed: 23993162
Clin Cancer Res. 2020 Feb 1;26(3):552-557
pubmed: 31969329
Lancet Oncol. 2016 Sep;17(9):e383-91
pubmed: 27599143
J Neurooncol. 2015 May;123(1):151-60
pubmed: 25894596
Neuro Oncol. 2019 Feb 14;21(2):234-241
pubmed: 30085283
PLoS One. 2013;8(3):e59941
pubmed: 23555840
J Neurosurg. 2011 May;114(5):1250-6
pubmed: 21250802
Neuro Oncol. 2014 Jun;16(6):829-40
pubmed: 24500419
Bull Math Biol. 2015 Oct;77(10):1934-54
pubmed: 26481497
J Neurooncol. 2012 Aug;109(1):187-93
pubmed: 22544653