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

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.