A comprehensive model including preoperative peripheral blood inflammatory markers for prediction of the prognosis of diffuse spinal cord astrocytoma following surgery

Abstract

Purpose Due to the rarity of diffuse spinal cord astrocytoma, an effective model is still lacking to stratify their prognosis. Here, we aimed to establish a prognostic model through comprehensively evaluating clinicopathological features and preoperative peripheral blood inflammatory markers in 89 cases. Methods We performed univariate and multivariate Cox regression to identify prognosis factors. The Kaplan–Meier curves and ROC curves were employed to compare the prognostic value of selected factors. Results In addition to clinicopathological factors, we revealed the preoperative peripheral blood leukocyte count, neutrophils-to-lymphocytes ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were also significantly correlated with overall survival of spinal cord astrocytoma in univariate Cox regression, and NLR was still significant in multivariate Cox analysis. Further, we demonstrated that NLR ≤ 3.65 and preoperative McCormick score (MMS) ≤ 3 were independently correlated with better survival of WHO grade IV tumors. Meanwhile, Ki-67 < 10% and resection extent ≥ 90% were independent prognostic factors in WHO grade II/III tumors. Finally, we developed a prognostic model that had better predictive efficiencies than WHO grade and histological grade for 1-year (AUC = 76.6), 2- year (AUC = 80.9), and 3-year (AUC = 80.3) survival. This model could classify tumors into 4 classifications with increasingly poor prognosis: 1, WHO grade II/III, with Ki-67 < 10% and resection extent ≥ 90%; 2, WHO grade II/III, Ki-67 ≥ 10% or resection < 90%; 3, WHO grade IV, NLR ≤ 3.65 and MMS ≤ 3; 4, WHO grade IV, with NRL > 3.65 or MMS = 4. Conclusion We successfully constructed a comprehensive prognostic model including preoperative peripheral blood inflammatory markers, which can stratify diffuse spinal cord astrocytoma into 4 subgroups.

Advances in Molecular Pathology, Diagnosis and Treatment of Spinal Cord Astrocytomas

“… 22 – 26 According to the previous clinical research, the removed degree of tumor is the most significant prognostic factor for lower-grade SCA, and total resection can achieve effective control of SCA. 27 , 28 High-grade SCA cannot be completely removed by surgery for severe local infiltration. Positive surgical treatments are unable to extend the survival time of high-grade SCAs for tumor metastasis.…”

Multimodal-based machine learning strategy for accurate and non-invasive prediction of intramedullary glioma grade and mutation status of molecular markers: a retrospective study

“…Increasing evidence has revealed the feasibility of using MRI to predict the type of glioma and molecular biomarkers, such as IDH1, Ki67, and H3-K27M, via machine learning or deep learning method [ 6 – 8 ]. However, only a limited number of studies have attempted to predict markers and classification of IMGs based on MRI owing to the lack of sufficient training in such rare tumors [ 9 , 10 ].…”

Using complete blood count‐derived inflammatory markers to compare postoperative inflammation in dogs undergoing open or laparoscopic ovariectomy

“…In the field of human surgery, the preoperative and postoperative determinations of these blood inflammatory markers have been employed as prognostic factors for complications, outcome and survival in cardiac, 22 − 24 oncologic, 25 − 27 digestive 28 − 31 and orthopaedic surgery 32,33 . Furthermore, these markers have been used as a rapid and simple means to contrast postsurgical inflammation according to surgical methods.…”