In:
Neuro-Oncology Advances, Oxford University Press (OUP), Vol. 5, No. 1 ( 2023-01-01)
Abstract:
Primary central nervous system lymphoma (PCNSL) is a highly aggressive non-Hodgkin’s B-cell lymphoma which normally treated by high-dose methotrexate (HD-MTX)-based chemotherapy. However, such treatment cannot always guarantee a good prognosis (GP) outcome while suffering several side effects. Thus, biomarkers or biomarker-based models that can predict PCNSL patient prognosis would be beneficial. Methods We first collected 48 patients with PCNSL and applied HPLC-MS/MS-based metabolomic analysis on such retrospective PCNSL patient samples. We then selected the highly dysregulated metabolites to build a logical regression model that can distinguish the survival time length by a scoring standard. Finally, we validated the logical regression model on a 33-patient prospective PCNSL cohort. Results Six metabolic features were selected from the cerebrospinal fluid (CSF) that can form a logical regression model to distinguish the patients with relatively GP (Z score ≤0.06) from the discovery cohort. We applied the metabolic marker-based model to a prospective recruited PCNSL patient cohort for further validation, and the model preformed nicely on such a validation cohort (AUC = 0.745). Conclusions We developed a logical regression model based on metabolic markers in CSF that can effectively predict PCNSL patient prognosis before the HD-MTX-based chemotherapy treatments.
Type of Medium:
Online Resource
ISSN:
2632-2498
DOI:
10.1093/noajnl/vdac181
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2023
detail.hit.zdb_id:
3009682-0
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