Evidence map›Paper›PMID 35341359›Full record

ArticleGlobal spine journal2023

Construction of a Tool to Predict Overall Survival of Patients With Primary Spinal Tumors After Surgical Resection: A Real-World Analysis Based on the Surveillance, Epidemiology, and End Results Database.

Zhangheng Huang, Yuexin Tong, Qingquan Kong

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Article in Global spine journal, 2023. 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

Authors and funding

3 authors.

Zhangheng HuangDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Yuexin TongDepartment of Orthopedics, China-Japan Union Hospital of Jilin University, Jilin, China.
Qingquan KongDepartment of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China.ORCID 0000-0002-4732-4948

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe aim to construct a practical clinical prediction model to accurately evaluate the overall survival (OS) of patients with primary spinal tumors after primary tumor resection, thereby aiding clinical decision-making.

methodsA total of 695 patients diagnosed with a primary spinal tumor, selected from the Surveillance, Epidemiology, and End Results (SEER) database, were included in this study. The Cox regression algorithm was applied to the training cohort to build the prognostic nomogram model. The nomogram's performance in terms of discrimination, calibration, and clinical usefulness was also assessed in the internal SEER validation cohort. The fitted prognostic nomogram was then used to create a web-based calculator.

resultsFour independent prognostic factors were identified to establish a nomogram model for patients with primary spinal tumors who had undergone surgical resection. The C-index (.757 for the training cohort and .681 for the validation cohort) and the area under the curve values over time (both >.68) showed that the model exhibited satisfactory discrimination in both the SEER cohort. The calibration curve revealed that the projected and actual survival rates are very similar. The decision curve analysis also revealed that the model is clinically valuable and capable of identifying high-risk patients.

conclusionsAfter developing a nomogram and a web-based calculator, we were able to reliably forecast the postoperative OS of patients with primary spinal tumors. These tools are expected to play an important role in clinical practice, informing clinicians in making decisions about patient care after surgery.

Indexed as

and end results databaseepidemiologynomogramoverall survivalprimary spinal tumorsprognosissurveillance

Identifiers

PMID35341359
PMCPMC10538349

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