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| ZHENG Bowen,ZOU Mingxiang,LIU Fusheng.Significance of tumor-stroma ratio and tumor-stroma ratio combined with immunescore in predicting the survival and prognosis of spinal chordoma patients[J].Chinese Journal of Spine and Spinal Cord,2021,(2):134-144. |
| Significance of tumor-stroma ratio and tumor-stroma ratio combined with immunescore in predicting the survival and prognosis of spinal chordoma patients |
| Received:August 20, 2020 Revised:November 04, 2020 |
| English Keywords:Chordoma Tumor-stroma ratio Survival analysis Prognostic biomarker Immunescore |
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| 【Abstract】 Objectives: By analyzing the relationship between tumor-stroma ratio(TSR), immunescore(IS), and patient prognosis in spinal chordoma, we aimed to determine the clinical significance of TSR and further investigate the predictive ability of TSR combined with IS. Methods: The clinical data of 77 patients with spinal chordoma were retrospectively analyzed, including 54 men and 23 women. All the spinal cord tumor cases fell into the class of classic pathology. TSR was evaluated on pathology slides by 2 independent pathologists, the local relapse-free survival(LRFS) and overall survival(OS) point with the smallest log rank P-value was obtained using X-tile software, and then the patients were divided it into high TSR and low TSR groups. Immunohistochemistry was applied to 77 tumor specimens for CD3+ and CD8+ tumor-infiltrating lymphocytes subset(TILs), automated image analysis was performed to derive IS, and the patients were classified into two groups: high and low on the basis of IS. A univariate Kaplan-Meier curve by log-rank test was used to explore the relationship between clinicopathological factors and patient outcomes. A multivariate Cox proportional hazards model was used to assess independent prognostic factors of LRFS and OS after adjusting for other clinical predictors that were significant in our univariate survival analysis. Pearson′s correlation test was used to observe the relationship between two continuous variables. Receiver operating characteristic(ROC) curves were used to compare the predictive power of TSR in combination with IS or TSR or IS alone. And Bland-Altman consistency analysis was used to assess the consistency of TSR measures between two assessors. All tests were two-sided, and P<0.05 was considered to be statistically significant. Results: There was a strong correlation between the two assessors for TSR assessment(r=0.924, P<0.001); Bland-Altman confirmed a small mean difference in TSR data between the two assessors with good agreement(P=0.292). Univariate analysis showed that TSR, IS, age, surrounding muscle invasion, type of surgery were correlated with LRFS(P<0.05). TSR, IS, surrounding muscle invasion, tumor stage, and type of surgerywere related to OS(P<0.05). TSR was positively correlated with IS(P<0.05), high IS indicated a good clinical prognosis, patients with low TSR combined with low IS had the lowest survival rates. Multivariate Cox analysis of LRFS showed that surrounding muscle invasion, TSR, and IS could independently predict prognosis(P<0.05), and multivariate Cox analysis of OS shows that TSR was the only predictor of OS(P=0.011). ROC analysis showed that incorporating TSR into the IS system improved the accuracy of the IS in predicting disease recurrence and survival. Conclusions: TSR is associated with patient survival and is a predictor of LRFS and OS. Inclusion of TSR in survival analysis improves its ability to predict prognosis, and inclusion of TSR in the IS system improves the accuracy of IS in predicting disease recurrence and survival. |
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