Development and Evaluation of Prognostic Nomogram Model for Adult Ventricle Glioma Patients
目的 探究成人脑室胶质瘤（adult ventricle glioma, AVG）患者的预后因素，进一步构建和评价预后列线图模型，为该类患者的临床管理提供一定的参考。 方法 本研究纳入SEER数据库（1973–2016）中经组织学明确诊断的AVG患者，用随机数字表法按2∶1比例分为训练集和验证集进行分析。使用Kaplan-Meier进行生存分析，Cox回归分析确定总生存（OS）和癌症特异性生存（CSS）的独立预后因素，结合患者基本特征，分别构建训练集中针对OS率和CSS率的生存相关列线图预测模型，再依次通过训练集和验证集进行模型的内部交叉验证和外部验证。C指数（C-index）用来评估列线图模型的真实性和可靠性，校准图用来评估训练集和验证集中预测值和观察值之间的一致性。 结果 本研究共纳入369例AVG患者，其中男性218例，女性151例，所有患者中位年龄为53岁。根据WHO分级，66例（17.9%）为Ⅱ级胶质瘤，73例（19.8%）为Ⅲ级胶质瘤，230例（62.3%）为Ⅳ级胶质瘤。根据手术切除程度，59 例（16.0%）为肿瘤全切，145例（39.3%）为次全切或部分切除。所有患者中，167例（45.3%）术后接受了放疗，143例（38.8%）术后接受了化疗。患者随机分为训练集 （n=246） 和验证集（n=123），训练集和验证集之间的基本临床特征的差异均无统计学意义（P>0.05）。训练集中Cox回归分析显示，年龄≥65岁、肿瘤分级III级和Ⅳ级、未接受放疗均是OS和CSS的独立预后因素。在训练集中，使用5个变量（年龄、性别、WHO 分级、手术和放疗）分别构建用于预测术后6个月、1年和2年OS率和CSS率的列线图模型。训练集内部交叉验证结果显示，OS率和CSS率的C指数分别为0.758和0.765；验证集外部验证结果显示，OS率和CSS率的C指数分别为0.733和0.719。训练集中6个月、1年和2年OS率的校准图均表现出良好的一致性，而在验证集中一致性相对较低。6个月、1年和2年CSS率的校准图与OS率校准图具有相似的结果。 结论 OS率和CSS率的列线图预测模型具有中等可靠的预测效能，可为临床医生简易评估AVG患者的生存概率提供参考。Abstract: Objective To explore the prognostic factors of adult ventricle glioma (AVG) and to construct and evaluate a survival-related prognostic nomogram model, which could provide further reference for the clinical management of AVG patients. Methods The patients covered in the study were selected from the Surveillance Epidemiology and End Results (SEER) database (1973–2016). They all had definite histological diagnosis of AVG. They were assigned randomly to the training cohort and the validation cohort by random number table at a 2/1 ratio. Survival analysis was performed by Kaplan-Meier analysis. Cox regression analysis was employed to determine the independent prognostic factors for overall survival (OS) and cancer-specific survival (CSS). Then, integrating the basic characteristics of patients, the survival-related nomogram predictive model for OS and CSS in the training cohort was constructed, respectively. After that, internal cross validation and external validation of the model were carried out with the training cohort and the validation cohort in succession. The authenticity and reliability of the nomogram model were evaluated by calculating the concordance index (C-index). Calibration plots were constructed to assess the agreement between the predicted values and the observed values in the training cohort and the validation cohort. Results A total of 369 AVG patients, including 218 males and 151 females, were included. The median age of the patients was 53. According to the WHO classification of gliomas, 66 (17.9%) patients had grade Ⅱ gliomas, 73 (19.8%) had grade Ⅲ gliomas, and 230 (62.3%) had grade Ⅳ gliomas. Regarding the extent of resection (EOR), 59 (16.0%) had gross total resection (GTR) and 145 (39.3%) had subtotal resection (STR) or partial resection (PR). Of all the patients, 167 (45.3%) received postoperative radiotherapy and 143 (38.8%) received postoperative chemotherapy. Patients were randomized into the training cohort (n=246) and the validation cohort (n=123), and there was no significant difference (P>0.05) in the basic clinical characteristics between the training cohort and the validation cohort. In the training cohort, Cox regression analysis revealed that the independent prognostic factors for OS and CSS included age≥65, grades Ⅲ and Ⅳ according to the WHO classification of gliomas, and not receiving radiotherapy. Furthermore, 5 variables, including age, gender, WHO grades, surgery, and radiotherapy, were used to construct the nomogram model for predicting 6-month, 1-year, and 2-year OS and CSS. The results of internal cross validation in the training cohort showed that the C-indexes of OS and CSS were 0.758 and 0.765, respectively. The external validation results of the validation cohort showed that the C-indexes of OS and CSS were 0.733 and 0.719, respectively. Calibration plots for 6-month, 1-year, and 2-year OS in the training cohort showed relatively good agreement, while in the validation cohort the agreement was relatively low. The 6-month, 1-year, and 2-year CSS calibration plots had results similar to the calibration plots of OS. Conclusion This nomogram predictive model of OS and CSS showed moderately reliable predictive performance, providing helpful reference information for clinicians to make quick and simple assessment of the survival probability of AVG patients.
图 5 训练集中6个月、1年和2年OS率和CSS率的列线图预测模型
Figure 5. Nomogram prediction model🦂 of 6-month,𓃲 1-year, and 2-year OS rates and CSS rates in the training cohortA: Nomogram model of 6-month,1-year, and 2-year OS rates in the training cohort; B: Nomogram model of 6-month, 1-year, and 2-year CSS rates in the training cohort.
图 6 训练集和验证集中6个月、1年和2年OS率的校准图
Figure 6. ᩚᩚᩚᩚᩚᩚᩚᩚᩚ𒀱ᩚᩚᩚ Calibration plots of 6-month, 1-year, and 2-year OS rate in the training cohort and validation cohortA-C: Calibration plots of 6-month, 1-year, and 2-year OS rates in the training cohort. D-F: Calibration plots of 6-month, 1-year, and 2-year OS rates in the validation cohort. The grey curve is the ideal curve, the blue curve is the actual curve, and the black line indicates the error margin.
图 7 训练集和验证集中6个月、1年和2年CSS率的校准图
Figure 7. Calibration plots 🤡of 6-month, 1- year, and 2-year CSS rates✅ in the training cohort and validation cohortA-C: Calibration plots of 6-month, 1-year, and 2-year CSS rates in the training cohort; D-F: Calibration plots of 6-month, 1-year, and 2-year CSS rates in the validation cohort. The grey curve is the ideal curve, the blue curve is the actual curve, and the black line means the error margin.
表 1 AVG患者的临床病理特征和治疗情况
Table 1. Summ🍌ary of clinicopathologic features and treatments of in patients with AVG
Variable All (n=369) Training cohort (n=246) Validation cohort (n=123) Age at diagnosis Mean/yr. 51.44±17.53 51.73±17.55 50.88±17.54 Median/yr. 53 53 52 18-<65 yr./case 272 182 90 ≥65 yr./case 97 64 33 Sex/case Male 218 147 71 Female 151 99 52 Race/case White 313 206 107 Black 24 13 11 Other 32 27 5 Year at diagnosis 1973–1999 143 105 38 2000–2009 124 75 49 2010–2016 102 66 36 Marital status/case Single or divorced 124 79 45 Married 233 158 75 Unknown 12 9 3 Insurance/case Insured 117 76 41 Medicaid 22 13 9 No/unknown 230 157 73 WHO grade/case Ⅱ 66 44 22 Ⅲ 73 51 22 Ⅳ 230 151 79 Tumor diameter/mm $ \bar x \pm s $ 39.93±16.03 39.90±16.56 40.00±15.10 Median 40.00 40.00 40 Surgery/case GTR 59 43 16 PR/STR 145 90 55 No 88 57 31 Surgery, NOS 77 56 21 Radiotherapy/case Yes 167 115 52 No/unknown 202 131 71 Chemotherapy/case Yes 143 96 47 No/unknown 226 150 76 OS/month Median 8.0 8.0 7.0 GTR: Gross total resection; STR: Subtotal resection; PR: Partial resection; NOS: Not otherwise specified.
表 2 训练集中OS和CSS的多变量Cox回归分析（n=246）
Table 2. Multivariate Cox regression analysis of OS and CSS in the training cohort (n=246)
Variable OS CSS HR 95% CI P HR 95% CI P Age at diagnosis 18-<65 yr. 1 Ref 1 Ref ≥65 yr. 1.529 1.075-2.177 0.018 1.309 0.886-1.934 0.176 WHO grade Ⅱ 1 Ref 1 Ref Ⅲ 5.166 2.339-11.412 <0.001 4.667 1.908-11.417 0.001 Ⅳ 12.208 5.662-26.323 <0.001 13.339 5.725-31.077 <0.001 Surgery No 1 Ref 1 Ref PR/STR 1.004 0.628-1.605 0.986 1.255 0.766-2.056 0.367 GTR 1.021 0.577-1.805 0.944 1.176 0.634-2.181 0.607 Radiotherapy No 1 Ref 1 Ref Yes 0.328 0.213-0.506 <0.001 0.295 0.189-0.461 <0.001 HR: Hadds ratio; CI: Confidence interval; OS: Overall survival; CSS: Cancer-specific survival.
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