Surgical treatment of spinal metastasis

Sammanfattning: The aim of this thesis was to study surgical treatment of spinal metastasis from several points of view, with a focus on predictive tools and survival after surgery. Study I includes 315 patients treated surgically at Uppsala University Hospital 2006-2012 due to spinal metastatic disease. Based on the data known at the time of surgery, predictive scores were calculated using four different scoring systems (Tokuhashi, revised Tokuhashi, Tomita and modified Bauer scores). The predictions were then compared with true survival data. All of the scores had a statistically significant correlation to survival but all of them tended to underestimate rather than overestimate survival. Study II focused on patients with an unknown primary tumour (UPT). We reviewed 393 cases treated at Uppsala University Hospital, where 122 (31%) had an unknown primary tumour at the time of surgery. A survival analysis showed that the patients with an UPT had a longer estimated survival compared to the group with a known primary tumour (KPT). The estimated median survival time in the UPT group was 15.6 months, compared to 7.4 months in the KPT group. The mean estimated survival time was 48.1 months in the UPT group and 21.6 months in the KPT group. The difference was statistically significant (p=0.001).Study III is a retrospective multi-registry study linking the Swedish spine surgery database Swespine with the Swedish Cause of Death (CoD) Register. The analysis included 1820 patients who underwent surgery due to spinal metastatic disease at 19 hospitals in Sweden 2006-2016. The study showed that both the mean and the median estimated survival time after surgery are well above the recommended three months threshold for surgery, suggesting that surgical treatment could be indicated in even more cases. In study IV, prognostic tools were revisited with a validation study of PathFx 3.0, an online open-source tool to estimate survival for patients with skeletal metastases. A cohort of 668 patients treated at Uppsala University Hospital and Karolinska University Hospital were included in the study and the results indicate that PathFx 3.0 could predict survival after treatment with good reliability, especially for patients with long expected survival. As PathFx can be updated to reflect advancements in oncological treatment, this type of tool is probably more useful than the rigid point-based scoring systems evaluated in study I.