Glioblastoma: Emerging Treatments and Novel Trial Designs
Abstract
:Simple Summary
Abstract
1. Introduction
2. Therapeutic Targets on GBM
3. Newly Diagnosed GBM
4. Recurrent GBM
5. Problematic Issues on Interventional Trials: The Glioblastoma Paradox
Improving Interventional Clinical Trials Design on GBM
6. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Trial Name | Phase | Experimental Compounds | Setting |
---|---|---|---|
NCT02386826 | I | Capmatinib and bevacizumab | Newly diagnosed and recurrent GBM |
NCT04077866 | I/II | B7-HR CAR-T | Glioblastoma cells expressing B7-H3 |
NCT04741984 DEMAND | I | Pp65CMV antigen monocytes | Newly diagnosed MGMT unmethylated GBM |
NCT04047706 | I | BMS-986205 + Nivolumab | Newly diagnosed GBM |
NCT03294486 ONCOVIRAC | I/II | Combination of TG002 and 5-flucytosine | Recurrent GBM |
NCT03714334 | I | DNX-2440 | Recurrent GBM |
NCT02062827 | I | M032-HSV1 | Newly diagnosed GBM or recurrent GBM. |
NCT03663725 StrateGlio | III | Intensified TMZ protocol | Newly diagnosed GBM |
NCT03899857 PERGOLA | II | Pembrolizumab | Newly diagnosed GBM |
NCT04396860 | II/III | Ipilimumab + nivolumab | Newly diagnosed GBM-MGMT unmethylated |
NCT03776071 | III | Enzastaurin | Newly diagnosed GBM |
NCT04704154 | II | Regorafenib + nivolumab | Recurrent GBM |
NCT04277221 | III | Autologous Dendritic Cell/Tumor antigen | Recurrent GBM |
Challenges of Clinical Trials Design on GBM | Innovation Proposed |
---|---|
A small number of patients benefit from inclusion in clinical trials | The inclusion of patients should be encouraged through the development of inter-center networks and improvement of organizational phases. Investments in trial planning and facilities for patients enrolled in clinical trials can increase the number of patients in clinical trials [88,89,90]. |
Reduced reliability from phase II study | Inclusion of comparator arm in this setting and also randomization in phase II studies [91]. |
A large number of patients are required for randomization in an early setting | Bayesian models with flexible and adaptive trial designs offer to test more compounds at the same time (comparing them to a shared comparator arm) with a reduced number of patients [92]. |
A long time from the trial start to the final result | (1) Bayesian adaptive randomized (AR) studies [93,94,95] (2) Use of different endpoints such as a composed PFS-OS endpoint or ORR through assessment of learning algorithms [96]. |
A large number of novel compounds in pre-clinical phases | Phase 0 trials [97]. |
Molecular heterogeneity of the disease | Umbrella trial in which treatment arm allocation is driven by the molecular composition of the disease [98]. |
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Di Nunno, V.; Franceschi, E.; Tosoni, A.; Gatto, L.; Lodi, R.; Bartolini, S.; Brandes, A.A. Glioblastoma: Emerging Treatments and Novel Trial Designs. Cancers 2021, 13, 3750. https://doi.org/10.3390/cancers13153750
Di Nunno V, Franceschi E, Tosoni A, Gatto L, Lodi R, Bartolini S, Brandes AA. Glioblastoma: Emerging Treatments and Novel Trial Designs. Cancers. 2021; 13(15):3750. https://doi.org/10.3390/cancers13153750
Chicago/Turabian StyleDi Nunno, Vincenzo, Enrico Franceschi, Alicia Tosoni, Lidia Gatto, Raffaele Lodi, Stefania Bartolini, and Alba Ariela Brandes. 2021. "Glioblastoma: Emerging Treatments and Novel Trial Designs" Cancers 13, no. 15: 3750. https://doi.org/10.3390/cancers13153750
APA StyleDi Nunno, V., Franceschi, E., Tosoni, A., Gatto, L., Lodi, R., Bartolini, S., & Brandes, A. A. (2021). Glioblastoma: Emerging Treatments and Novel Trial Designs. Cancers, 13(15), 3750. https://doi.org/10.3390/cancers13153750