Evidence map›Paper›PMID 39217259›Full record

ArticleDiscover oncology2024

A nomogram to predict cancer-specific mortality in adult patients with malignant meningioma: a competing risk analysis.

Hongfu Zhang, Jing Li, Xin Wan, Zhuoyi Liu

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Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

Hongfu Zhang *Department of Neurosurgery, Henan Provincial People's Hospital, Zhengzhou University People's Hospital; Henan University People's Hospital, Zhengzhou, 450003, Henan, China.
Jing Li *Department of Rehabilitation, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China.
Xin WanDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China. 403677@csu.edu.cn.
Zhuoyi LiuNational Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China. zhuoyiliu@csu.edu.cn.

Funding

Youth Natural Science Foundation of Changsha City kq2202379
6 · The paper itself

Abstract

backgroundComprehensive investigations of the prognosis factors and treatment strategies with adjustment of competing causes of death for patients with malignant meningioma (MM) is still lacking. PATIENT AND

methodThe surveillance, Epidemiology, and End Results (SEER) database were used to include adult patients with this rare disease between 2004 and 2018. The probability of MM-caused mortality (MMCM) and non-MM-caused mortality (non-MMCM) were presented by cumulative incidence function curves. Then, the association between variates with non-MMCM was evaluated by the cox proportional hazard model, and the prognostic factors of MMCM were identified by Fine-Gray competing risk regression model. Furthermore, a nomogram was developed to predict the 1-year, 2-year, and 5-year MMCM and the performance was tested by a time-dependent area under the receiver operating characteristic (ROC) curve and calibration.

result577 patients were included, with a median age of 62 (18-100) years old and a median overall survival time of 36 (0-176) months. The percentage of non-MMCM was 15.4% (n = 89) in the entire population and 21.7% (n = 54) in elderly patients. The multivariable Cox proportional hazard regression model revealed that older age and other tumor(s) before or after MM had an independently significant association with higher non-MMCM. After adjustment of competing causes of death, the multivariable Fine-gray regression model identified age group ≥ 65 year, tumor size > 5.3 cm, recurrent MM, and histologic type 9530/3 (Meningioma, malignant) had an independently significant association with higher MMCM. Compared with gross total (GTR) of tumor, subtotal resection of tumor (HR 1.66, 95%CI 1.08-2.56, P = 0.02), partial resection of lobe (HR 2.26, 95%CI 1.32-3.87, P = 0.003), and gross total resection of lobe (HR 1.69, 95%CI 1.12-2.51, P = 0.01) had an independently significant association with higher MMCM.

conclusionThe competing risk nomogram including age group, tumor size, initial status, histologic type, and extent of resection is discriminative and clinically useful. This study emphasized the importance of the GTR of tumor in the treatment of MM patients, which had a significantly lower incidence of MMCM compared with biopsy, STR of tumor, partial resection of lobe, and GTR of lobe.

Indexed as

Competing risksGross total resectionMalignant meningiomaNomogramSEER

Identifiers

PMID39217259
PMCPMC11365918

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