A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed Glioblastoma
BackgroundGlioblastoma is the most common primary malignant brain tumor. Recent studies have shown that hematological biomarkers have become a powerful tool for predicting the prognosis of patients with cancer. However, most studies have only investigated the prognostic value of unilateral hematolog...
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| Format: | Article |
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Frontiers Media S.A.
2020-12-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2020.591352/full |
| _version_ | 1818664320789118976 |
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| author | Chao Zhao Long-Qing Li Feng-Dong Yang Ruo-Lun Wei Min-Kai Wang Di-Xiang Song Xiao-Yue Guo Wei Du Xin-Ting Wei |
| author_facet | Chao Zhao Long-Qing Li Feng-Dong Yang Ruo-Lun Wei Min-Kai Wang Di-Xiang Song Xiao-Yue Guo Wei Du Xin-Ting Wei |
| author_sort | Chao Zhao |
| collection | DOAJ |
| description | BackgroundGlioblastoma is the most common primary malignant brain tumor. Recent studies have shown that hematological biomarkers have become a powerful tool for predicting the prognosis of patients with cancer. However, most studies have only investigated the prognostic value of unilateral hematological markers. Therefore, we aimed to establish a comprehensive prognostic scoring system containing hematological markers to improve the prognostic prediction in patients with glioblastoma.Patients and MethodsA total of 326 patients with glioblastoma were randomly divided into a training set and external validation set to develop and validate a hematological-related prognostic scoring system (HRPSS). The least absolute shrinkage and selection operator Cox proportional hazards regression analysis was used to determine the optimal covariates that constructed the scoring system. Furthermore, a quantitative survival-predicting nomogram was constructed based on the hematological risk score (HRS) derived from the HRPSS. The results of the nomogram were validated using bootstrap resampling and the external validation set. Finally, we further explored the relationship between the HRS and clinical prognostic factors.ResultsThe optimal cutoff value for the HRS was 0.839. The patients were successfully classified into different prognostic groups based on their HRSs (P < 0.001). The areas under the curve (AUCs) of the HRS were 0.67, 0.73, and 0.78 at 0.5, 1, and 2 years, respectively. Additionally, the 0.5-, 1-y, and 2-y AUCs of the HRS were 0.51, 0.70, and 0.79, respectively, which validated the robust prognostic performance of the HRS in the external validation set. Based on both univariate and multivariate analyses, the HRS possessed a strong ability to predict overall survival in both the training set and validation set. The nomogram based on the HRS displayed good discrimination with a C-index of 0.81 and good calibration. In the validation cohort, a high C-index value of 0.82 could still be achieved. In all the data, the HRS showed specific correlations with age, first presenting symptoms, isocitrate dehydrogenase mutation status and tumor location, and successfully stratified them into different risk subgroups.ConclusionsThe HRPSS is a powerful tool for accurate prognostic prediction in patients with newly diagnosed glioblastoma. |
| first_indexed | 2024-12-17T05:30:52Z |
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| id | doaj.art-068bbb586ad047239f7654c2adf657ca |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-17T05:30:52Z |
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| series | Frontiers in Oncology |
| spelling | doaj.art-068bbb586ad047239f7654c2adf657ca2022-12-21T22:01:44ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2020-12-011010.3389/fonc.2020.591352591352A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed GlioblastomaChao Zhao0Long-Qing Li1Feng-Dong Yang2Ruo-Lun Wei3Min-Kai Wang4Di-Xiang Song5Xiao-Yue Guo6Wei Du7Xin-Ting Wei8Department of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Orthopedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaDepartment of Neurosurgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, ChinaBackgroundGlioblastoma is the most common primary malignant brain tumor. Recent studies have shown that hematological biomarkers have become a powerful tool for predicting the prognosis of patients with cancer. However, most studies have only investigated the prognostic value of unilateral hematological markers. Therefore, we aimed to establish a comprehensive prognostic scoring system containing hematological markers to improve the prognostic prediction in patients with glioblastoma.Patients and MethodsA total of 326 patients with glioblastoma were randomly divided into a training set and external validation set to develop and validate a hematological-related prognostic scoring system (HRPSS). The least absolute shrinkage and selection operator Cox proportional hazards regression analysis was used to determine the optimal covariates that constructed the scoring system. Furthermore, a quantitative survival-predicting nomogram was constructed based on the hematological risk score (HRS) derived from the HRPSS. The results of the nomogram were validated using bootstrap resampling and the external validation set. Finally, we further explored the relationship between the HRS and clinical prognostic factors.ResultsThe optimal cutoff value for the HRS was 0.839. The patients were successfully classified into different prognostic groups based on their HRSs (P < 0.001). The areas under the curve (AUCs) of the HRS were 0.67, 0.73, and 0.78 at 0.5, 1, and 2 years, respectively. Additionally, the 0.5-, 1-y, and 2-y AUCs of the HRS were 0.51, 0.70, and 0.79, respectively, which validated the robust prognostic performance of the HRS in the external validation set. Based on both univariate and multivariate analyses, the HRS possessed a strong ability to predict overall survival in both the training set and validation set. The nomogram based on the HRS displayed good discrimination with a C-index of 0.81 and good calibration. In the validation cohort, a high C-index value of 0.82 could still be achieved. In all the data, the HRS showed specific correlations with age, first presenting symptoms, isocitrate dehydrogenase mutation status and tumor location, and successfully stratified them into different risk subgroups.ConclusionsThe HRPSS is a powerful tool for accurate prognostic prediction in patients with newly diagnosed glioblastoma.https://www.frontiersin.org/articles/10.3389/fonc.2020.591352/fullglioblastomahematological markerprognostic scoring systemprognosisinflammationnutrition |
| spellingShingle | Chao Zhao Long-Qing Li Feng-Dong Yang Ruo-Lun Wei Min-Kai Wang Di-Xiang Song Xiao-Yue Guo Wei Du Xin-Ting Wei A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed Glioblastoma Frontiers in Oncology glioblastoma hematological marker prognostic scoring system prognosis inflammation nutrition |
| title | A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed Glioblastoma |
| title_full | A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed Glioblastoma |
| title_fullStr | A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed Glioblastoma |
| title_full_unstemmed | A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed Glioblastoma |
| title_short | A Hematological-Related Prognostic Scoring System for Patients With Newly Diagnosed Glioblastoma |
| title_sort | hematological related prognostic scoring system for patients with newly diagnosed glioblastoma |
| topic | glioblastoma hematological marker prognostic scoring system prognosis inflammation nutrition |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2020.591352/full |
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