Comparison of survival outcomes of patients with newly diagnosed glioblastoma treated with standard chemoradiation in and outside of clinical trials.

Authors

null

Rifaquat Rahman

Dana-Farber/Brigham and Women's Cancer Center, Boston, MA

Rifaquat Rahman , Gilbert Youssef , Steffen Ventz , Robert Redd , Jon McDunn , William Louv , Brian Michael Alexander , Patrick Y. Wen , Lorenzo Trippa

Organizations

Dana-Farber/Brigham and Women's Cancer Center, Boston, MA, Dana-Farber Cancer Institute, Boston, MA, Dana-Farber Cancer Institute, Brookline, MA, Project Data Sphere, Morrisville, NC, Project Data Sphere, Cary, NC, Dana-Farber Cancer Institute/Brigham and Women's Hospital, Boston, MA, Dana-Farber/Brigham and Women's Cancer Center, Harvard Medical School, Boston, MA, Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA

Research Funding

Other Foundation

Background: Randomized clinical trials use stringent eligibility criteria to select patients which can raise concerns about generalizability of study results. Recent interest in external controls and new trial designs has increasingly focused on the possible use of real-world data sources. We examined potential differences of survival outcomes in clinical trial and real-world datasets in newly diagnosed glioblastoma. Methods: Patient-level data from 4 independent datasets were analyzed. Non-trial data were derived from an institutional dataset of 453 patients with newly diagnosed glioblastoma treated outside of a clinical trial with standard radiation therapy with concurrent and adjuvant temozolomide at a large academic center. Trial patients included patients on the control arm of several multi-institutional trials (NCT00689221, n = 273; NCT00813943, n = 89; NCT00943826; n = 459) and patients treated on trial at our institution (n = 210). Non-trial patients were compared with each of the 4 clinical trial datasets in pairwise comparisons with Cox regression with adjustments for age, sex, extent of resection, KPS and MGMT status. Results: Patient-level data from 1,484 patients were analyzed. Non-trial patients were older compared to patients in the multi-institutional trials (mean 58.6 vs. 56.1 years (NCT00943826), 53.9 years (NCT00813943), 55.7 years (NCT00689221); p < = 0.001). The non-trial cohort had fewer women (43.5% vs. 35.9%, p = 0.02), greater proportion of lower KPS patients (47% KPS <90 vs. 31% KPS <90, p < 0.001) and greater proportion of MGMT methylated patients (49% vs. 33%, p < 0.001) compared to NCT00943826 patients. There were no other significant differences between patient characteristics of non-trial patients and the 4 trial datasets. Trial participation was not associated with improved survival in multivariable analysis after adjustments for clinical covariates (non-trial patients vs. each trial dataset; Table, P > 0.05). Conclusions: Glioblastoma patients treated on multi-institutional clinical trials that were included in our analysis did not have statistically significant differences in survival compared to patients treated outside of a clinical trial at a large academic center after adjustment for relevant variables. Our findings support the possible use of real-world data in the development of external control arms for future trials in newly diagnosed glioblastoma.

Hazard ratio of trial participation.

Dataset
Univariable analysis
Multivariable analysis

HR (95%CI)*
P-value
HR (95%CI)*
P-value
Non-trial (reference)
1

1

NCT00689221
1.39 (1.04-1.85)
0.026
1.32 (0.98-1.18)
0.07
NCT00813943
1.12 (0.87-1.43)
0.375
1.27 (0.98-1.66)
0.07
NCT00943826
1.40 (1.20-1.63)
<0.001
1.16 (0.97-1.40)
0.11
Institutional Trial Patients Dataset
1.04 (0.96-1.84)
0.704
0.90 (0.71-1.13)
0.35

*Compared to non-trial patients.

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Abstract Details

Meeting

2022 ASCO Annual Meeting

Session Type

Poster Session

Session Title

Central Nervous System Tumors

Track

Central Nervous System Tumors

Sub Track

Primary CNS Tumors–Glioma

Citation

J Clin Oncol 40, 2022 (suppl 16; abstr 2051)

DOI

10.1200/JCO.2022.40.16_suppl.2051

Abstract #

2051

Poster Bd #

389

Abstract Disclosures

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