Beyond survival: Longitudinal prognostication in glioblastoma using conditional survival—A population-based study.

2045 Background: Glioblastoma multiforme (GBM) carries a poor prognosis, and the initial survival projections provided at diagnosis do not accurately depict the evolving risk that exists for all GBM survivors. Conditional survival (CS), defined as the probability of surviving an additional period after having lived to a specific time point, provides a much more accurate way of defining prognosis for these patients. We evaluated conditional survival patterns in a large population-based cohort of patients with glioblastoma. Methods: Adult patients who were diagnosed with primary glioblastoma between 2000 and 2022 were identified from the SEER 17 Registries. The estimated overall survival (OS) was determined by using the Kaplan-Meier method. We also calculated one year and two-year conditional survival (CS) probabilities at multiple landmark times (0-24 months). In addition, we stratified the conditional survival by the status of surgical resection and whether or not the patient received radiation therapy. Results: There were 52,125 patients in our sample. As expected, the median OS was very poor, dropping from 37.3% at 12 months to 16.0% at 24 months. Nevertheless, the conditional survival was significantly better than overall survival. One-year CS increased from 40.4% at diagnosis to 57.2% among patients surviving 24 months, while two-year CS improved from 17.3% to 39.4% over the same landmarks. Patients who underwent surgical resection had higher early CS compared with biopsy or no surgery, though differences diminished at later landmarks. Similar trends were found in CS rates in patients who received radiation therapy, indicating survivorship selection over time as opposed to a decrease in the effectiveness of treatments. Conclusions: Conditional survival in glioblastoma improves markedly with increased time of survival. Therefore, it is essential to use CS in place of traditional survival statistics to provide more accurate prognoses for glioblastoma patients. Landmark Time (Months) Overall Survival 1-Year Conditional Survival 2-Year Conditional Survival 1-Year CS (Resection) 1-Year CS (No resection/Biopsy) 1-Year CS (RT Yes) 1-Year CS (RT No/Unknown) 0 92.4% 40.4% 17.3% 46.7% 17.1% 48.7% 14.1% 6 56.3% 42.0% 20.9% 43.2% 32.3% 42.5% 37.9% 12 37.3% 42.9% 24.5% 43.1% 40.7% 42.4% 47.9% 18 23.7% 49.8% 31.7% 49.9% 48.7% 49.2% 56.0% 24 16.0% 57.2% 39.4% 57.1% 57.2% 56.5% 63.2% RT: Radiotherapy.

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Publication Details

Journal
Journal of Clinical Oncology
Published
2026-05-27
DOI
https://doi.org/10.1200/jco.2026.44.16_suppl.2045
Primary Topic
Glioma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
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article

Beyond survival: Longitudinal prognostication in glioblastoma using conditional survival—A population-based study.

Owais Gul, Maria Khalid, Fawad Talat, Saqib Gul et al.
Journal of Clinical Oncology
Glioma Diagnosis and Treatment
article

Beyond survival: Longitudinal prognostication in glioblastoma using conditional survival—A population-based study.

Owais Gul, Maria Khalid, Fawad Talat, Saqib Gul, Obuli Srinivasan Gurunathan, Saagarika Sundaram Venkatesan, Yadhu Nandhan Gurunathan
article en

Abstract

2045 Background: Glioblastoma multiforme (GBM) carries a poor prognosis, and the initial survival projections provided at diagnosis do not accurately depict the evolving risk that exists for all GBM survivors. Conditional survival (CS), defined as the probability of surviving an additional period after having lived to a specific time point, provides a much more accurate way of defining prognosis for these patients. We evaluated conditional survival patterns in a large population-based cohort of patients with glioblastoma. Methods: Adult patients who were diagnosed with primary glioblastoma between 2000 and 2022 were identified from the SEER 17 Registries. The estimated overall survival (OS) was determined by using the Kaplan-Meier method. We also calculated one year and two-year conditional survival (CS) probabilities at multiple landmark times (0-24 months). In addition, we stratified the conditional survival by the status of surgical resection and whether or not the patient received radiation therapy. Results: There were 52,125 patients in our sample. As expected, the median OS was very poor, dropping from 37.3% at 12 months to 16.0% at 24 months. Nevertheless, the conditional survival was significantly better than overall survival. One-year CS increased from 40.4% at diagnosis to 57.2% among patients surviving 24 months, while two-year CS improved from 17.3% to 39.4% over the same landmarks. Patients who underwent surgical resection had higher early CS compared with biopsy or no surgery, though differences diminished at later landmarks. Similar trends were found in CS rates in patients who received radiation therapy, indicating survivorship selection over time as opposed to a decrease in the effectiveness of treatments. Conclusions: Conditional survival in glioblastoma improves markedly with increased time of survival. Therefore, it is essential to use CS in place of traditional survival statistics to provide more accurate prognoses for glioblastoma patients. Landmark Time (Months) Overall Survival 1-Year Conditional Survival 2-Year Conditional Survival 1-Year CS (Resection) 1-Year CS (No resection/Biopsy) 1-Year CS (RT Yes) 1-Year CS (RT No/Unknown) 0 92.4% 40.4% 17.3% 46.7% 17.1% 48.7% 14.1% 6 56.3% 42.0% 20.9% 43.2% 32.3% 42.5% 37.9% 12 37.3% 42.9% 24.5% 43.1% 40.7% 42.4% 47.9% 18 23.7% 49.8% 31.7% 49.9% 48.7% 49.2% 56.0% 24 16.0% 57.2% 39.4% 57.1% 57.2% 56.5% 63.2% RT: Radiotherapy.

Journal of Clinical OncologyVol. 44(16_suppl)
Hamdard University (PK), Chettinad Health City (IN), United Health Services (US), Saveetha University (IN)
No poverty
Openalex Percentile: Top 7%
Glioma Diagnosis and Treatment
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