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Development and Validation of a Novel Survival Prediction Model in Patients With Spinal Metastasis From Non-small Cell Lung Cancer

Yang, Minglei, MD; Xu, Wei, MD; Liu, Tielong, MD; Yang, Xinghai, MD; Wang, Peng, MD; Wu, Sujia, MD; Wei, Haifeng, MD; Zhao, Jian, MD; Yang, Cheng, MD; Xiao, Jianru, MD

doi: 10.1097/BRS.0000000000002816
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Study Design. Retrospective study.

Objective. The aim of this study was to develop a model for predicting survival of patients with non-small cell lung cancer (NSCLC) spinal metastasis and compare its accuracy with the existing scoring systems.

Summary of Background Data. Spinal metastasis is commonly seen in advanced NSCLC and usually associated with poor survival prognosis.

Methods. A total of 376 patients with NSCLC spinal metastases admitted to our institution from January 2010 to October 2016 were enrolled. They were randomly assigned at a 3:1 ratio to a training cohort (n = 282) and a validation cohort (n = 94). A nomogram for survival prediction was established by identifying and integrating significant prognostic factors, and then subjected to bootstrap validation in both training and validation cohorts. The discrimination was measured by concordance index (C-index). Predictive accuracy was compared with three existing models by the receiver-operating characteristic curve (ROC) and area under ROC in both training and validation cohorts.

Results. Six independent prognostic factors including sex (P = 0.008), the presence of visceral metastasis (P = 0.008), the number of metastases in the vertebral body (P = 0.011), Frankel score (P < 0.001), d-dimer (P = 0.002), and sensitive epidermal growth factor receptor mutation (p < 0.001) were identified and entered into the nomogram. The calibration curves for probability of 3-, 6-, 12- and, 24-month overall survival showed good agreement between the predictive risk and the actual risk. The C-index of the nomogram was 0.708 (95% confidence interval [CI], 0.674–0.742) in the training cohort and 0.683 (95% CI, 0.619–0.747) in the validation cohort. Model comparison showed that this nomogram had better predictive accuracy than the Tomita et al, Tokuhashi et al, and Schwab et al scoring systems (P < 0.05 in the training cohort).

Conclusion. We established and validated a novel nomogram that could be used to predict the survival outcome of patients with NSCLC spinal metastasis, thus helping clinicians in decision making and individualized care planning of such patients.

Level of Evidence: 4

In this study, we developed and validated a model for predicting survival of patients with NSCLC spinal metastasis based on 376 patients. Model comparison showed that this nomogram had better predictive accuracy than the Tomita et al, Tokuhashi et al, and Schwab et al scoring systems.

Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, Shanghai, 200003, China

Department of Radiology, Changzheng Hospital, Second Military Medical University, Shanghai, 200003, China

Department of Orthopedic Oncology, Nanjing General Hospital of Nanjing Military Region, Nanjing, Jiangsu, 210002, China.

Address correspondence and reprint requests to Jianru Xiao, MD, Department of Orthopedic Oncology, Changzheng Hospital, Second Military Medical University, 415 Fengyang Road, Shanghai 200003, China; E-mail: jianruxiao83@163.com

Received 20 March, 2018

Revised 13 June, 2018

Accepted 26 June, 2018

M.Y. and W.X. are co-first authors.

The manuscript submitted does not contain information about medical device(s)/drug(s).

The National Key Research and Development Project of China (2016YFC0902100), National Natural Science Foundation of China (81702888), Shanghai technology innovation action plan (17411950300), and Shanghai Youth doctor assistance program funds were received in support of this work.

No relevant financial activities outside the submitted work.

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