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Establishment and validation of a novel survival prediction scoring algorithm for patients with non-small-cell lung cancer spinal metastasis

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Abstract

Background

This study was to develop an algorithm capable of predicting the survival of patients with NSCLC spinal metastasis for individualized therapy.

Methods

We identified 176 consecutive patients with NSCLC spinal metastasis between 2006 and 2017. Twenty-four features, including age, gender, smoking, KPS, paralysis, histological subtype, tumor stage, surgery, EGFR status, CEA, CA125, CA19-9, NSE, SCC, CYFRA21-1, calcium, AKP, albumin, the number of spinal, extra-spinal bone and visceral metastasis, time to metastasis, pathological fracture, and primary or secondary metastasis, were retrospectively analyzed. Features associated with survival in the multivariate analyses were included in a scoring model, which was prospectively validated in another 63 patients (NCT03363685).

Results

The median follow-up period was 12.00 months (interquartile range 6.00–23.40 months). One hundred forty-seven patients died during follow-up, with a median survival of 13.6 months being observed. Multivariate analysis revealed that the following features were associated with survival: age, smoking, CA125, SCC, KPS, and EGFR status. A scoring system based on these features was created to stratify patients into low-risk (0–3), intermediate-risk (4–6) and high-risk (7–10) groups, whose estimated median survival times 29.10, 10.40 and 3.90 months, respectively. The Harrell’s c-index was 0.72. Model validation supported this model’s validity and reproducibility.

Conclusions

In patients with NSCLC spinal metastasis, survival was associated with age, smoking, CA125, SCC, KPS, and EGFR status. A validated scoring system based on these features was devised that can predict the survival times of those patients. This scoring system provides a basis for applying the NOMS framework and for facilitating individual treatment.

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Acknowledgements

This research was supported by the Shanghai Science and Technology Committee (Grant No. 17411950300, 17411950303).

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Authors and Affiliations

  1. Department of Orthopedics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin er Road, Shanghai, China

    Shizhao Zang, Qin He, Qiyuan Bao, Yuhui Shen & Weibin Zhang

  2. Shanghai Institute of Traumatology and Orthopedics, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China

    Yuhui Shen & Weibin Zhang

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  1. Shizhao Zang
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  2. Qin He
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  3. Qiyuan Bao
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Correspondence to Yuhui Shen or Weibin Zhang.

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Zang, S., He, Q., Bao, Q. et al. Establishment and validation of a novel survival prediction scoring algorithm for patients with non-small-cell lung cancer spinal metastasis. Int J Clin Oncol 24, 1049–1060 (2019). https://doi.org/10.1007/s10147-019-01452-8

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