4.5 Article

Development of a novel model for predicting survival of patients with spine metastasis from colorectal cancer

期刊

EUROPEAN SPINE JOURNAL
卷 28, 期 6, 页码 1491-1501

出版社

SPRINGER
DOI: 10.1007/s00586-019-05879-5

关键词

Colorectal cancer; Spine metastasis; Nomogram; Prognostic factor

资金

  1. National Key Research and Development Project of China [2016YFC0902100]
  2. National Natural Science Foundation of China [81702888]
  3. Shanghai Youth doctor assistance program [QNYS09]

向作者/读者索取更多资源

ObjectiveTo develop a novel nomogram for predicting survival of patients with spine metastasis from colorectal cancer (SMCRC) based on the clinical characteristics and prognostic factors.MethodsIncluded in this study were 93 SMCRC patients who received treatments in our institute between 2006 and 2017, whose clinical data were analyzed retrospectively by univariate and multivariate analysis to identify independent variables that could predict prognosis. A nomogram for survival prediction was established on the basis of preoperative independent factors, and then subjected to bootstrap re-samples for internal validation. The discrimination was measured by concordance index (C-index). We used ROC analysis with the corresponding AUROC to compare the prediction accuracy of Changzheng Nomogram with three existing prognostic systems (Tomita, Tokuhashi and Bauer).ResultsThe high and median degrees of primary tumor differentiation, primary tumor surgery, carcinoembryonic antigen5ng/ml, no visceral metastases and ECOG-PS (0-2) were favorable prognostic factors for CRC metastases in the spine. These five preoperative independent factors were identified and entered into the nomogram with the C-index of 0.786 (0.739-0.833). The calibration curves for probability of 12- and 24-month overall survival (OS) showed good agreement between the predictive risk and the actual risk, and calibration was assessed. Compared with the previous prognostic systems, Changzheng Nomogram reported in this study showed higher accuracy in predicting OS of patients with SMCRC spinal metastases (p<0.05). ConclusionBy using this novel predictive model, clinicians could more precisely estimate the survival outcome of individual patients by evaluating clinical characteristics and identify subgroups of patients who are in need of a specific individual treatment strategy.

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