Presenter(s)
G. Kavak Eren1, M. Atak2, K. Bir Yücel2, E. Gurlek1, Y. Barel1, Ö. B. Çakmak Öksüzoglu2, and Y. Yukselen Guney1; 1Etlik City Hospital, Department of Radiation Oncology, Ankara, Turkey, 2Etlik City Hospital, Department of Medical Oncology, Ankara, Turkey
Purpose/Objective(s): Glioblastoma (GB) is an primary brain tumor with poor outcomes despite multimodal therapy. Frailty has been associated with inferior treatment tolerance and outcomes in oncologic populations; however, its impact on progression-free survival (PFS) in patients with GB remains unclear. This study aimed to evaluate the association between frailty, assessed using the 5-item modified frailty index (mFI-5) and an age-adjusted frailty score and PFS in patients with GB.
Materials/Methods: This retrospective, single-center study included patients with histologically confirmed GB. Frailty was assessed using the mFI-5, composed of five variables (hypertension, diabetes mellitus, congestive heart failure, chronic obstructive pulmonary disease, and Karnofsky Performance Status =60), each scored as one point, and patients were categorized as prefrail (0–1), frail (2), or severely frail (=3). An age-adjusted frailty score (range 0–3) was calculated by assigning 0, 1, and 2 points to prefrail, frail, and severely frail status, respectively, with an additional point for age =65 years. PFS was estimated using the Kaplan–Meier method and compared using the log-rank test. Univariable and multivariable Cox proportional hazards regression analyses were performed to identify prognostic factors associated with PFS.
Results: A total of 135 patients were analyzed. Median PFS did not significantly differ according to age adjusted frailty score (median PFS: 9.1, 12.0, 10.4, and 6.7 months for scores 0–3, respectively; p = 0.69) or mFI-5–based frailty categories (prefrail, frail, and severely frail: 9.4, 10.3, and 7.0 months, respectively; p = 0.76). In univariable analyses, age adjusted frailty scores and extent of resection (subtotal vs total) were not associated with PFS. Non-lobar (multifocal and deep central) tumor location (HR 2.72; p = 0.001) and fewer (<6) adjuvant temozolomide cycles (HR 2.56; p < 0.001) were significantly associated with shorter PFS. In multivariable analyses, non-lobar tumor location (adjusted HR 2.59; p < 0.003) and fewer (<6) adjuvant temozolomide cycles (adjusted HR 2.85; p < 0.001) remained independent adverse prognostic factors. Age adjusted frailty score was not independently associated with PFS.
Conclusion: Frailty was not found to be independently associated with PFS in patients with GB, suggesting that PFS may be more strongly influenced by tumor-related factors and treatment intensity. Further prospective studies are warranted to clarify the role of frailty-adapted treatment strategies in this population.
Table 1: Multivariable Cox regression analysis for PFS| Adjusted HR (95% CI) | p | |
| Age adjusted frailty score (per 1-point increase) | 0.87 (0.61 – 1.25) | 0.467 |
| Tumor location (Non-lobar vs Lobar) | 2.59 (1.39 – 4.84) | 0.003 |
| Adjuvant TMZ cycles (<6 vs 6) | 2.85 (1.68 – 4.85) | <0.001 |
| Extent of resection (Subtotal vs Total) | 1.20 (0.72 – 2.00) | 0.472 |