• Satoshi Kato, Hideki Murakami, Satoru Demura, Katsuhito Yoshioka, Noriaki Yokogawa, Noritaka Yonezawa, Takaki Shimizu, Norihiro Oku, Ryo Kitagawa, and Hiroyuki Tsuchiya.
• Department of Orthopaedic Surgery, Graduate School of Medical Sciences, Kanazawa University, Kanazawa, Japan. Electronic address: skato323@gmail.com.
• World Neurosurg. 2019 Feb 1; 122: e1305-e1311.

BackgroundSpinal metastases (SMs) from kidney and thyroid cancers have several common features suggesting that excisional surgery for isolated and removable SMs can improve survival. We propose a simple treatment algorithm for SMs from these cancers. Our study aimed to evaluate the efficacy of the algorithm.MethodsWe performed a retrospective analysis of the data of 69 consecutive patients (48 with kidney and 21 with thyroid cancers) who underwent excisional surgery for SMs between 1995 and 2014. The patients were retrospectively classified into an indicated group for excisional SM surgery and a nonindicated group according to our algorithm, and the Tokuhashi and Tomita scoring systems. Patients in the indicated group were expected to survive ≥2 years postoperatively, whereas those in the nonindicated group were not. The positive predictive value and negative predictive value (NPV) were calculated using the predicted versus actual survival times of the patients. Survival was defined as the time from the first excisional surgery for the spinal lesion to death or the last follow-up of ≥2 years.ResultsFor patients with kidney cancer, the 2- and 5-year survival rates were 85.4% and 60.4%, respectively. For patients with thyroid cancer, the 2- and 5-year survival rates were 100% and 83.8%, respectively. Our algorithm had a compatible high positive predictive value (95.5%) and NPV (100%), whereas the Tokuhashi and Tomita scoring systems had low NPVs of 15.8% and 13.3%, respectively.ConclusionsOur treatment algorithm of SMs from kidney and thyroid cancers is useful for determining an adequate treatment including excisional surgery.Copyright © 2018 Elsevier Inc. All rights reserved.

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