Wang, Lijie, Zhang, Jinling, Wang, Jingtao, Xue, Hao, Deng, Lin, Che, Fengyuan, Heng, Xueyuan, Zheng, Xuejun, Lu, Zilong, Yang, Liuqing, Tan, Qihua, Xu, Yeping, Zhang, Yanchun ORCID: 0000-0002-5094-5980, Ji, Xiaokang, Li, Gang, Yang, Fan ORCID: 0000-0003-0717-5420 and Xue, Fuzhong (2023) Postoperative prognostic nomogram for adult grade II/III astrocytoma in the Chinese Han population. Health Information Science and Systems, 11 (1). ISSN 2047-2501

Abstract

Background: Prognostic models of glioma have been the focus of many studies. However, most of them are based on Western populations. Additionally, because of the complexity of healthcare data in China, it is important to select a suitable model based on existing clinical data. This study aimed to develop and independently validate a nomogram for predicting the overall survival (OS) with newly diagnosed grade II/III astrocytoma after surgery. Methods: Data of 472 patients with astrocytoma (grades II–III) were collected from Qilu Hospital as training cohort while data of 250 participants from Linyi People's Hospital were collected as validation cohort. Cox proportional hazards model was used to construct the nomogram and individually predicted 1-, 3-, and 5-year survival probabilities. Calibration ability, and discrimination ability were analyzed in both training and validation cohort. Results: Overall survival was negatively associated with histopathology, age, subtotal resection, multiple tumors, lower KPS and midline tumors. Internal validation and external validation showed good discrimination (The C-index for 1-, 3-, and 5-year survival were 0.791, 0.748, 0.733 in internal validation and 0.754, 0.735, 0.730 in external validation, respectively). The calibration curves showed good agreement between the predicted and actual 1-, 3-, and 5-year OS rates. Conclusion: This is the first nomogram study that integrates common clinicopathological factors to provide an individual probabilistic prognosis prediction for Chinese Han patients with astrocytoma (grades II–III). This model can serve as an easy-to-use tool to advise patients and establish optimized surveillance approaches after surgery.

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