Risk factors and risk prediction model for recurrence in medulloblastoma

Area of Science:

• Pediatric Oncology
• Cancer Genomics
• Immunology

Background:

• Established treatment protocols for recurrent medulloblastoma are lacking.
• Accurate pre-treatment risk assessment is crucial for tailoring medulloblastoma treatment intensity.
• A predictive model for medulloblastoma recurrence is needed for clinical decision-making.

Purpose of the Study:

• To develop an enhanced risk prediction model for medulloblastoma relapse.
• To integrate molecular subtyping and neutrophil-to-lymphocyte ratio (NLR) into a nomogram for improved prediction.
• To aid clinical decision-making in medulloblastoma management.

Main Methods:

• Retrospective analysis of 273 medulloblastoma patient records.
• Calculation of pre-radiotherapy neutrophil-to-lymphocyte ratio (NLR).
• Utilized Kaplan-Meier, Cox regression, and nomogram construction for prognostic factor identification and validation.

Main Results:

• Independent prognostic factors for progression-free survival (PFS) included age, residual tumor volume, NLR > 4.5, dissemination, and Group 3 molecular subtype.
• The nomogram achieved a C-index of 0.749 (training) and 0.736 (validation).
• The nomogram demonstrated significant stratification of low-risk versus high-risk groups (P<0.001).

Conclusions:

• Pre-treatment NLR is an independent prognostic marker for medulloblastoma recurrence and metastasis.
• The developed nomogram integrating NLR and clinical variables can predict PFS post-radiotherapy.
• This nomogram facilitates accurate risk stratification and personalized treatment for medulloblastoma patients.