Clinical characteristics and disease-specific prognostic nomogram for primary gliosarcoma: a SEER population-based...

Area of Science:

• Neuro-oncology
• Cancer epidemiology
• Biostatistics

Background:

• Gliosarcoma (GSM) is a rare brain tumor with limited understanding due to small patient populations.
• Accurate prognosis prediction is crucial for effective treatment planning in GSM patients.

Purpose of the Study:

• To identify clinical characteristics and independent prognostic factors for GSM patients.
• To develop a predictive nomogram for GSM patient prognosis following craniotomy.

Main Methods:

• Utilized data from 498 primary GSM patients (2004-2015) from the SEER database.
• Employed Cox proportional hazards and decision tree models to determine prognostic factors.
• Developed and internally validated a nomogram using the rms package in R.

Main Results:

• Median disease-specific survival (DSS) was 12.0 months; 3-year DSS rate was 9.8%.
• Independent prognostic factors identified: age, tumor size, metastasis, and adjuvant chemotherapy (CT).
• The nomogram achieved a C-index of 0.67 for DSS prediction with good calibration.

Conclusions:

• This study presents the first disease-specific nomogram for predicting GSM prognosis post-craniotomy.
• The nomogram aids clinicians in accurate and immediate prognosis prediction.
• Findings can guide further treatment strategies for gliosarcoma patients.