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He Q, Luo Z, Zou H, Ye B, Wu L, Deng Y, Yang M, Wang D, Wang Q, Zhang K. A prognostic nomogram that includes MPV in esophageal squamous cell carcinoma. Cancer Med 2023; 12:20266-20276. [PMID: 37807972 PMCID: PMC10652314 DOI: 10.1002/cam4.6551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 08/13/2023] [Accepted: 09/08/2023] [Indexed: 10/10/2023] Open
Abstract
BACKGROUND Mean platelet volume (MPV), as a marker of platelet activity, has been shown to be an efficient prognostic biomarker in several types of cancer. Using MPV, this study aimed to create and validate a prognostic nomogram to the overall survival in esophageal squamous cell carcinoma (ESCC) patients. METHODS The nomogram was constructed and tested using data from a retrospective study of 1893 patients who were randomly assigned to the training and testing cohorts with a 7:3 randomization. In order to screen out the optimal predictors for overall survival (OS), we conducted the LASSO-cox regression, univariate, and multivariate cox regression analyses. Subsequently, the predictive accuracy of the nomogram was validated in both the training and the testing cohorts. Finally, decision curve analysis (DCA) was used to confirm clinical validity. RESULTS Age, MPV, nerve invasion, T stage, and N stage were found as independent prognostic variables for OS and were further developed into a nomogram. The nomogram's prediction accuracy for 1-, 3-, and 5-year OS was 0.736, 0.749, 0.774, and 0.724, 0.719, 0.704 in the training and testing cohorts, respectively. Furthermore, DCA results indicated that nomograms outperformed the AJCC 8th and conventional T, N staging systems in both the training and testing cohorts. CONCLUSIONS The nomogram, in conjunction with MPV and standard clinicopathological markers, could improve the accuracy of prediction of OS in ESCC patients.
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Affiliation(s)
- Qiao He
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Zhenglian Luo
- Department of Transfusion Medicine, West China HospitalSichuan UniversityChengduChina
| | - Haiming Zou
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Bo Ye
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Lichun Wu
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Yao Deng
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Mu Yang
- Centre for Translational Research in CancerSichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Dongsheng Wang
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Qifeng Wang
- Department of Radiation OncologySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
| | - Kaijiong Zhang
- Department of Clinical LaboratorySichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of ChinaChengduChina
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Yuan S, Wei C, Wang M, Deng W, Zhang C, Li N, Luo S. Prognostic impact of examined lymph-node count for patients with esophageal cancer: development and validation prediction model. Sci Rep 2023; 13:476. [PMID: 36627338 PMCID: PMC9831985 DOI: 10.1038/s41598-022-27150-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 12/27/2022] [Indexed: 01/11/2023] Open
Abstract
Esophageal cancer (EC) is a malignant tumor with high mortality. We aimed to find the optimal examined lymph node (ELN) count threshold and develop a model to predict survival of patients after radical esophagectomy. Two cohorts were analyzed: the training cohort which included 734 EC patients from the Chinese registry and the external testing cohort which included 3208 EC patients from the Surveillance, Epidemiology, and End Results (SEER) registry. Cox proportional hazards regression analysis was used to determine the prognostic value of ELNs. The cut-off point of the ELNs count was determined using R-statistical software. The prediction model was developed using random survival forest (RSF) algorithm. Higher ELNs count was significantly associated with better survival in both cohorts (training cohort: HR = 0.98, CI = 0.97-0.99, P < 0.01; testing cohort: HR = 0.98, CI = 0.98-0.99, P < 0.01) and the cut-off point was 18 (training cohort: P < 0.01; testing cohort: P < 0.01). We developed the RSF model with high prediction accuracy (AUC: training cohort: 87.5; testing cohort: 79.3) and low Brier Score (training cohort: 0.122; testing cohort: 0.152). The ELNs count beyond 18 is associated with better overall survival. The RSF model has preferable clinical capability in terms of individual prognosis assessment in patients after radical esophagectomy.
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Affiliation(s)
- Shasha Yuan
- grid.414008.90000 0004 1799 4638Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008 Henan People’s Republic of China
| | - Chen Wei
- grid.414008.90000 0004 1799 4638Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008 Henan People’s Republic of China
| | - Mengyu Wang
- grid.493088.e0000 0004 1757 7279Department of Radiotherapy, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan People’s Republic of China
| | - Wenying Deng
- grid.414008.90000 0004 1799 4638Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008 Henan People’s Republic of China
| | - Chi Zhang
- grid.414008.90000 0004 1799 4638Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008 Henan People’s Republic of China
| | - Ning Li
- Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, People's Republic of China.
| | - Suxia Luo
- Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, People's Republic of China.
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Zhang Q, Liu Z, Liu S, Wang M, Li X, Xun J, Wang X, Yang Q, Wang X, Zhang D. A novel nomogram for adult primary perihilar cholangiocarcinoma and considerations concerning lymph node dissection. Front Surg 2023; 9:965401. [PMID: 36684342 PMCID: PMC9852046 DOI: 10.3389/fsurg.2022.965401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 11/03/2022] [Indexed: 01/07/2023] Open
Abstract
Objective To construct a reliable nomogram available online to predict the postoperative survival of patients with perihilar cholangiocarcinoma. Methods Data from 1808 patients diagnosed with perihilar cholangiocarcinoma between 2004 and 2015 were extracted from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database. They were randomly divided into training and validation sets. The nomogram was established by machine learning and Cox model. The discriminant ability and prediction accuracy of the nomogram were evaluated by concordance index (C-index), receiver operator characteristic (ROC) curve and calibration curve. Kaplan-Meier curves show the prognostic value of the associated risk factors and classification system. Results Machine learning and multivariate Cox risk regression model showed that sex, age, tumor differentiation, primary tumor stage(T), lymph node metastasis(N), TNM stage, surgery, radiation, chemotherapy, lymph node dissection were associated with the prognosis of perihilar cholangiocarcinoma patients relevant factors (P < 0.05). A novel nomogram was established. The calibration plots, C-index and ROC curve for predictions of the 1-, 3-, and 5-year OS were in excellent agreement. In patients with stage T1 and N0 perihilar cholangiocarcinoma, the prognosis of ≥4 lymph nodes dissected was better than that of 1- 3 lymph nodes dissected (P < 0.01). Conclusion The nomogram prognostic prediction model can provide a reference for evaluating the prognosis and survival rate of patients with perihilar cholangiocarcinoma. Patients with stage T1 and N0 perihilar cholangiocarcinoma have more benefits by increasing the number of lymph node dissection.
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Affiliation(s)
- Qi Zhang
- Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Tianjin Nankai Hospital, Tianjin Medical University, Tianjin, China,Integrated Chinese and Western Medicine Hospital, Tianjin University, Tianjin, China
| | - Zehan Liu
- Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Tianjin Nankai Hospital, Tianjin Medical University, Tianjin, China,Department of General Surgery, The Third People’s Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University & The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu, China
| | - Shuangqing Liu
- Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Tianjin Nankai Hospital, Tianjin Medical University, Tianjin, China
| | - Ming Wang
- Department of General Surgery, The Third People’s Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University & The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu, China
| | - Xinye Li
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jing Xun
- Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Tianjin Nankai Hospital, Tianjin Medical University, Tianjin, China,Integrated Chinese and Western Medicine Hospital, Tianjin University, Tianjin, China
| | - Xiangyu Wang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Qin Yang
- Department of General Surgery, The Third People’s Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University & The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu, China
| | - Ximo Wang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China,Correspondence: Dapeng Zhang Ximo Wang
| | - Dapeng Zhang
- Tianjin Key Laboratory of Acute Abdomen Disease Associated Organ Injury and ITCWM Repair, Tianjin Nankai Hospital, Tianjin Medical University, Tianjin, China,Integrated Chinese and Western Medicine Hospital, Tianjin University, Tianjin, China,Correspondence: Dapeng Zhang Ximo Wang
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Liu T, Li M, Cheng W, Yao Q, Xue Y, Wang X, Jin H. A clinical prognostic model for patients with esophageal squamous cell carcinoma based on circulating tumor DNA mutation features. Front Oncol 2023; 12:1025284. [PMID: 36686833 PMCID: PMC9850098 DOI: 10.3389/fonc.2022.1025284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 12/14/2022] [Indexed: 01/07/2023] Open
Abstract
Background Few predictive models have included circulating tumor DNA (ctDNA) indicators to predict prognosis of esophageal squamous cell carcinoma (ESCC) patients. Here, we aimed to explore whether ctDNA can be used as a predictive biomarker in nomogram models to predict the prognosis of patients with ESCC. Methods We included 57 patients who underwent surgery and completed a 5-year follow-up. With next-generation sequencing, a 61-gene panel was used to evaluate plasma cell-free DNA and white blood cell genomic DNA from patients with ESCC. We analyzed the relationship between the mutation features of ctDNA and the prognosis of patients with ESCC, identified candidate risk predictors by Cox analysis, and developed nomogram models to predict the 2- and 5-year disease-free survival (DFS) and overall survival (OS). The area under the curve of the receiver operating characteristic (ROC) curve, concordance index (C-index), calibration plot, and integrated discrimination improvement (IDI) were used to evaluate the performance of the nomogram model. The model was compared with the traditional tumor-nodes-metastasis (TNM) staging system. Results The ROC curve showed that the average mutant allele frequency (MAF) of ctDNA variants and the number of ctDNA variants were potential biomarkers for predicting the prognosis of patients with ESCC. The predictors included in the models were common candidate predictors of ESCC, such as lymph node stage, angiolymphatic invasion, drinking history, and ctDNA characteristics. The calibration curve demonstrated consistency between the observed and predicted results. Moreover, our nomogram models showed clear prognostic superiority over the traditional TNM staging system (based on C-index, 2-year DFS: 0.82 vs. 0.64; 5-year DFS: 0.78 vs. 0.65; 2-year OS: 0.80 vs. 0.66; 5-year OS: 0.77 vs. 0.66; based on IDI, 2-year DFS: 0.33, p <0.001; 5-year DFS: 0.18, p = 0.04; 2-year OS: 0.28, p <0.001; 5-year OS: 0.15, p = 0.04). The comprehensive scores of the nomogram models could be used to stratify patients with ESCC. Conclusions The novel nomogram incorporating ctDNA features may help predict the prognosis of patients with resectable ESCC. This model can potentially be used to guide the postoperative management of ESCC patients in the future, such as adjuvant therapy and follow-up.
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Affiliation(s)
- Tao Liu
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Mengxing Li
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Wen Cheng
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Qianqian Yao
- Department of Medical Science, Shanghai AccuraGen Biotechnology Co., Ltd., Shanghai, China
| | - Yibo Xue
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Xiaowei Wang
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China,*Correspondence: Hai Jin, ; Xiaowei Wang,
| | - Hai Jin
- Department of Thoracic Surgery, Changhai Hospital, Second Military Medical University, Shanghai, China,*Correspondence: Hai Jin, ; Xiaowei Wang,
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Li L, Wang Y, He X, Li Z, Lu M, Gong T, Chang Q, Lin J, Liu C, Luo Y, Min L, Zhou Y, Tu C. Hematological Prognostic Scoring System Can Predict Overall Survival and Can Indicate Response to Immunotherapy in Patients With Osteosarcoma. Front Immunol 2022; 13:879560. [PMID: 35603156 PMCID: PMC9120642 DOI: 10.3389/fimmu.2022.879560] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 04/01/2022] [Indexed: 11/16/2022] Open
Abstract
Osteosarcoma is the most common primary malignant bone tumor with a high metastatic potential. Nowadays, there is a lack of new markers to identify prognosis of osteosarcoma patients with response to medical treatment. Recent studies have shown that hematological markers can reflect to some extent the microenvironment of an individual with the potential to predict patient prognosis. However, most of the previous studies have studied the prognostic value of a single hematological index, and it is difficult to comprehensively reflect the tumor microenvironment of patients. Here, we comprehensively collected 16 hematological markers and constructed a hematological prognostic scoring system (HPSS) using LASSO cox regression analysis. HPSS contains many indicators such as immunity, inflammation, coagulation and nutrition. Our results suggest that HPSS is an independent prognostic factor for overall survival in osteosarcoma patients and is an optimal addition to clinical characteristics and well suited to further identify high-risk patients from clinically low-risk patients. HPSS-based nomograms have good predictive ability. Finally, HPSS also has some hints for immunotherapy response in osteosarcoma patients.
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Affiliation(s)
- Longqing Li
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Bone and Joint 3D-Printing and Biomechanical Laboratory, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
| | - Yang Wang
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Bone and Joint 3D-Printing and Biomechanical Laboratory, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
| | - Xuanhong He
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Bone and Joint 3D-Printing and Biomechanical Laboratory, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
| | - Zhuangzhuang Li
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Bone and Joint 3D-Printing and Biomechanical Laboratory, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
| | - Minxun Lu
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Bone and Joint 3D-Printing and Biomechanical Laboratory, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
| | - Taojun Gong
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Bone and Joint 3D-Printing and Biomechanical Laboratory, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
| | - Qing Chang
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Jingqi Lin
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
| | - Chuang Liu
- Institute of Jinan Yinfeng Medical Laboratory, Yinfeng Gene Technology Co Ltd, Jinan, China
| | - Yi Luo
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Bone and Joint 3D-Printing and Biomechanical Laboratory, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
| | - Li Min
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Bone and Joint 3D-Printing and Biomechanical Laboratory, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
| | - Yong Zhou
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Bone and Joint 3D-Printing and Biomechanical Laboratory, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Yong Zhou, ; Chongqi Tu,
| | - Chongqi Tu
- Department of Orthopedics, Orthopaedic Research Institute, West China Hospital, Sichuan University, Chengdu, China
- Bone and Joint 3D-Printing and Biomechanical Laboratory, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Yong Zhou, ; Chongqi Tu,
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Gao P, Kong T, Zhu X, Zhen Y, Li H, Chen D, Yuan S, Zhang D, Jiao H, Li X, Yan D. A Clinical Prognostic Model Based on Preoperative Hematological and Clinical Parameters Predicts the Progression of Primary WHO Grade II Meningioma. Front Oncol 2021; 11:748586. [PMID: 34707993 PMCID: PMC8542933 DOI: 10.3389/fonc.2021.748586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 09/15/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose The purpose was to explore the correlation between hematological parameters and the progression of WHO grade II meningioma, and establish a clinical prognostic model based on hematological parameters and clinical prognostic factors to predict the progression-free survival (PFS) of patients. Methods A total of 274 patients with WHO grade II meningiomas were included. Patients were randomly divided into a training cohort (192, 70%) and a test cohort (82, 30%). In the training cohort, the least absolute shrinkage and selection operator Cox regression analysis were used to screen for hematological parameters with prognostic value, and the hematological risk model (HRM) was constructed based on these parameters; univariate and multivariate Cox regression analyses were utilized to screen for clinical prognostic factors, and a clinical prognostic model was constructed based on clinical prognostic factors and HRM. The prognostic stability and accuracy of the HRM and clinical prognostic model were verified in the test cohort. Subgroup analysis was performed according to the patients' different clinical characteristics. Results Preoperative neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, albumin-to-globulin ratio, D-dimer, fibrinogen, and lactate dehydrogenase were associated with the PFS of patients. The areas under curve of the HRM were 0.773 (95% confidence interval [CI] 0.707-0.839) and 0.745 (95% CI 0.637-0.852) in the training cohort and test cohort, respectively. The progression risk was higher in the high-risk group than that in the low-risk group categorized by the optimal cutoff value (2.05) of hematological risk scores. The HRM, age, tumor location, tumor size, peritumoral edema, extent of resection, Ki-67 index, and postoperative radiotherapy were the prognostic factors for the progression of meningiomas. The corrected C-index of the clinical prognosis model was 0.79 in the training cohort. Clinical decision analysis showed that the clinical prognostic model could be used to obtain favorable clinical benefits. In the subgroup analysis, the HRM displayed excellent prognostic stability and general applicability in different subgroups. Conclusions Preoperative hematological parameters are associated with the postoperative progression of WHO grade II meningiomas. The clinical prognosis model constructed based on hematological parameters and clinical prognostic factors has favorable predictive accuracy and clinical benefits.
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Affiliation(s)
- Peng Gao
- Department of Neurosurgery, The First Affiliated Hospital of ZhengZhou University, Henan, China
| | - Tengxiao Kong
- Department of Neurosurgery, The First Affiliated Hospital of ZhengZhou University, Henan, China
| | - Xuqiang Zhu
- Department of Neurosurgery, The First Affiliated Hospital of ZhengZhou University, Henan, China
| | - Yingwei Zhen
- Department of Neurosurgery, The First Affiliated Hospital of ZhengZhou University, Henan, China
| | - Hongjiang Li
- Department of Neurosurgery, The First Affiliated Hospital of ZhengZhou University, Henan, China
| | - Di Chen
- Department of Neurosurgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shanpeng Yuan
- Department of Neurosurgery, The First Affiliated Hospital of ZhengZhou University, Henan, China
| | - Dongtao Zhang
- Department of Neurosurgery, The Second Affiliated Hospital of Zhengzhou University, Henan, China
| | - Henan Jiao
- Department of Neurosurgery, The First Affiliated Hospital of ZhengZhou University, Henan, China
| | - Xueyuan Li
- Department of Neurosurgery, The First Affiliated Hospital of ZhengZhou University, Henan, China
| | - Dongming Yan
- Department of Neurosurgery, The First Affiliated Hospital of ZhengZhou University, Henan, China
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