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Prediction of skeletal-related events in patients with non-small cell lung cancer
Hisaki Aiba1,2, Tomoki Kimura3, Takaya Yamagami4
1Department of Orthopaedic Surgery, Nagoya City University Graduate School of Medical Sciences, 1, Azakawasumi, Mizuho-cho, Mizuho-ku, Nagoya City, Aichi pref, 467-8601, Japan. hisakiaiba@yahoo.co.jp.
Purpose:
Advanced lung cancer frequently causes bone metastasis which can be associated with skeletal-related events (SREs) that may cause significant deterioration of the patient's quality of life (QoL). The Spinal Instability Neoplastic Score (SINS) can be used to assist in standardizing evaluations of neoplastic spinal instability between spinal and non-spine surgeons. This research investigated the association between SREs and SINS for patients with non-small cell lung cancer (NSCLC).
Methods:
Between 2009 and 2013, 47 patients with NSCLC who were diagnosed with bone metastasis were classified using SINS into either a stable group (SINS, 0-6 points) or unstable group (SINS, 7-18 points). The primary endpoint was time from diagnosis of metastasis to SREs. Secondary endpoints included tumor type and epidermal growth factor receptor (EGFR) mutational status. SREs were defined as spinal compression, pathologic fracture, spinal surgery, and hypercalcemia.
Results:
Patients included 37 cases of adenocarcinoma and 10 cases of squamous cell carcinoma. Mean follow-up time was 10.2 ± 13.7 months. SRE incidence was 15.0 % (3/20) in the stable group versus 44.4 % (12/27) in the unstable group (p = 0.048). A Cox regression model revealed that an EGFR-positive mutational status (hazard ratio [HR] = 0.15, 95 % CI, 0.030.71; p = 0.017) or good spinal stability (HR = 0.49; 0.08-0.99; p = 0.049) were favorable prognostic factors.
Conclusion:
The incidence of SREs was significantly lower in NSCLC patients with better spinal stability as determined by SINS, which was a good prediction tool for SREs from bone metastasis. The lower incidence of SREs in EGFR-positive patients suggests tumor biology should be considered when predicting SREs.
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