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嗜铬细胞瘤和副神经节瘤早期死亡的预测列线图

A Predictive Nomogram for Early Death in Pheochromocytoma and Paraganglioma.

作者信息

Li Huiyang, Abbas Kirellos Said, Abdelazeem Basel, Xu Yao, Lin Yile, Wu Haixiao, Chekhonin Vladimir P, Peltzer Karl, Zhang Chao

机构信息

Department of Obstetrics & Gynecology, Tianjin Medical University General Hospital, Tianjin, China.

Tianjin Key Laboratory of Female Reproductive Health and Eugenics, Tianjin, China.

出版信息

Front Oncol. 2022 Feb 25;12:770958. doi: 10.3389/fonc.2022.770958. eCollection 2022.

DOI:10.3389/fonc.2022.770958
PMID:35280784
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8913719/
Abstract

BACKGROUND

Pheochromocytoma (PHEO) and paraganglioma (PGL) are relatively rare neuroendocrine tumors. The factors affecting patients with early death remain poorly defined. We aimed to study the demographic and clinicopathologic pattern and to develop and validate a prediction model for PHEO/PGL patients with early death.

METHODS

Data of 800 participants were collected from the Surveillance Epidemiology and End Results (SEER) database as a construction cohort, while data of 340 participants were selected as a validation cohort. Risk factors considered included the year of diagnosis, age at diagnosis, gender, marital status, race, insurance status, tumor type, primary location, laterality, the presence of distant metastasis. Univariate and multivariate logistic regressions were performed to determine the risk factors. R software was used to generate the nomogram. Calibration ability, discrimination ability, and decision curve analysis were analyzed in both construction and validation cohorts.

RESULTS

PHEO and PGL patients accounted for 54.3% (N=434) and 45.7% (N=366), respectively. More than half of tumors (N=401, 50.1%) occurred in the adrenal gland, while 16.9% (N=135) were in aortic/carotid bodies. For the entire cohort, the median overall survival (OS) was 116.0 (95% CI: 101.5-130.5) months. The multivariate analysis revealed that older age ( age between 31 and 60: OR=2.03, 95% CI: 1.03-4.03, ; age older than 60: OR=5.46, 95% CI: 2.68-11.12, ), female gender ( OR=0.59, 95% CI: 0.41-0.87, ), tumor located in aortic/carotid bodies ( OR=0.49, 95% CI: 0.27-0.87, ) and the presence of distant metastasis ( OR=4.80, 95% CI: 3.18-7.23, ) were independent risk factors of early death. The predictive nomogram included variables: age at diagnosis, gender, primary tumor location, and distant metastasis. The model had satisfactory discrimination and calibration performance: Harrell's C statistics of the prediction model were 0.733 in the construction cohort and 0.716 in the validation cohort. The calibration analysis showed acceptable coherence between predicted probabilities and observed probabilities.

CONCLUSIONS

We developed and validated a predictive nomogram utilizing data from the SEER database with satisfactory discrimination and calibration capability which can be used for early death prediction for PHEO/PGL patients.

摘要

背景

嗜铬细胞瘤(PHEO)和副神经节瘤(PGL)是相对罕见的神经内分泌肿瘤。影响患者早期死亡的因素仍未明确。我们旨在研究人口统计学和临床病理模式,并开发和验证PHEO/PGL早期死亡患者的预测模型。

方法

从监测、流行病学和最终结果(SEER)数据库收集800名参与者的数据作为构建队列,同时选择340名参与者的数据作为验证队列。考虑的风险因素包括诊断年份、诊断时年龄、性别、婚姻状况、种族、保险状况、肿瘤类型、原发部位、侧别、远处转移情况。进行单因素和多因素逻辑回归以确定风险因素。使用R软件生成列线图。在构建队列和验证队列中分析校准能力、鉴别能力和决策曲线分析。

结果

PHEO和PGL患者分别占54.3%(N = 434)和45.7%(N = 366)。超过一半的肿瘤(N = 401,50.1%)发生在肾上腺,而16.9%(N = 135)位于主动脉/颈动脉体。对于整个队列,中位总生存期(OS)为116.0(95%CI:101.5 - 130.5)个月。多因素分析显示,年龄较大(31至60岁:OR = 2.03,95%CI:1.03 - 4.03;年龄大于60岁:OR = 5.46,95%CI:2.68 - 11.12)、女性(OR = 0.59,95%CI:0.41 - 0.87)、肿瘤位于主动脉/颈动脉体(OR = 0.49,95%CI:0.27 - 0.87)和存在远处转移(OR = 4.80,95%CI:3.18 - 7.23)是早期死亡的独立危险因素。预测列线图包括变量:诊断时年龄、性别、原发肿瘤部位和远处转移。该模型具有令人满意的鉴别和校准性能:预测模型的Harrell's C统计量在构建队列中为0.733,在验证队列中为0.716。校准分析显示预测概率与观察概率之间具有可接受的一致性。

结论

我们利用SEER数据库的数据开发并验证了一个预测列线图,其具有令人满意的鉴别和校准能力,可用于PHEO/PGL患者的早期死亡预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/85027a49fe69/fonc-12-770958-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/459ec8c80e9a/fonc-12-770958-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/ef93ab8c93d1/fonc-12-770958-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/5f08e1aa8ac9/fonc-12-770958-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/9274fcb01efd/fonc-12-770958-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/85027a49fe69/fonc-12-770958-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/459ec8c80e9a/fonc-12-770958-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/ef93ab8c93d1/fonc-12-770958-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/5f08e1aa8ac9/fonc-12-770958-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/9274fcb01efd/fonc-12-770958-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa56/8913719/85027a49fe69/fonc-12-770958-g005.jpg

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