Spinal Metastasis Surgery: A Proposal for a Predictive Model of Morbidity and Mortality*

BackgroundTherapeutic decision-making regarding surgical treatment of spinal metastasis is supported by clinical characteristics that are potentially predictive of postoperative events. The predictive power of total lymphocyte count (TLC) in peripheral blood has not been elucidated for this type of surgery. Therefore, the aim of this study was to assess the capacity of TLC to predict 30-day morbidity and mortality following surgery for spinal metastases. MethodsThis is a level III prognostic study, which consists of a retrospective review of records from a cancer referral hospital. Consecutive patients who underwent open surgery for spinal metastatic disease were studied. Outcomes of interest were 30-day post-op mortality and complications. The patients were divided into three groups based on preoperative TLC: low, moderate, and high risk for surgery, according to a discriminatory power analysis. The predictive power of TLC was compared to that of other known predictors, i.e., older age, tumor aggressiveness, and presence of comorbidities. Odds ratios (ORs) and 95% confidence intervals were calculated using bivariate and multivariate analyses. ResultsIn total, 205 patients underwent surgery. Thirty-day mortality and occurrence of complications were 17% and 31%, respectively. The discriminatory power of TLC was 71% and 68% for 30-day survival and complications, respectively. In multivariate analysis, the strongest relationship between predictors and postoperative morbidity and mortality concerned TLC < 800 cells/µL, which was associated with decreased likelihood of 30-day survival (OR 3.17) and increased likelihood of complications (OR 3.93). Incidence of 30-day mortality and complications by risk group was, respectively: 4% and 13% for low risk (TLC > 1857 cells/µL); 22% and 34% for moderate risk (TLC 800-1857 cells/µL); and 35% and 56% for high risk (TLC < 800 cells/µL). ConclusionsTLC is a strong predictor of 30-day morbidity and mortality following spinal metastasis surgery. It may be useful for improving patient care and planning personalized treatments.

Assessing the utility of a clinical prediction score regarding 30-day morbidity and mortality following metastatic spinal surgery: the New England Spinal Metastasis Score (NESMS)

Predictive factors of the 30-day mortality after surgery for spinal metastasis: Analysis of a nationwide database

Patients presenting with neurological deficits and/or pain due to spinal metastasis usually require immediate or subacute surgical treatment. Nevertheless, it is unclear whether or not side effects of primary cancer location might influence postoperative complication rate. We therefore analyzed our spinal database to identify factors influencing early postoperative complications after surgery for symptomatic spinal metastases. From 2013 to 2017, 163 consecutive patients suffering from symptomatic spinal metastases were treated at our department. Early postoperative complications were defined as any postoperative event requiring additional medical or surgical treatment within 30days of spinal surgery. A multivariate regression analysis was performed to identify independent predictors for postoperative complications after surgery for spinal metastasis. Overall, 39 of 163 patients who underwent spinal surgery for spinal metastasis developed early postoperative complications throughout the treatment course (24%). Preoperative ASA score ≥ 3 (p = 0.003), preoperative C-reactive protein level > 10mg/l (p = 0.008), preoperative Karnofsky Performance Score < 60% (p = 0.03), radiation treatment within 2months of surgery (p = 0.01), presence of diabetes mellitus (p = 0.008), and preoperative complete neurological impairment (p = 0.04) were significant and independent predictors for early postoperative complications in patients with surgery for spinal metastasis. The ability to preoperatively predict postoperative complication risk is valuable to select critically ill patients at higher risk requiring special attention. Therefore, the present study identified several significant and independent risk factors for the development of early postoperative complication in patients who underwent surgery for spinal metastasis.

Inflammatory markers such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) have shown promise in predicting mortality in various types of cancer. The purpose of this study was to assess NLR, PLR, and SII in predicting 30-day mortality and overall survival (OS) among surgically treated patients with spinal metastasis. This was a retrospective study including 153 patients who underwent surgery for spinal metastasis between 2012 and 2022. Electronic medical records were manually reviewed, and NLR, PLR, and SII were calculated from preoperative neutrophil, platelet, and lymphocyte counts. Receiver operating characteristic curves with areas under the curve were generated to determine cutoff values. Logistic regression was used to determine the odds ratios (ORs) for 30-day mortality. The Kaplan-Meier method and Cox regression were used to determine the hazard ratio (HR) for OS limited to 5 years postoperatively. Preoperative cutoff values were as follows: NLR > 10.2, PLR > 260, and SII > 2900. Overall, 35.9% (55/153) of patients had elevated NLR, 45.7% (70/153) had elevated PLR, and 30.7% (47/153) had elevated SII. The overall 30-day mortality was 8.5% (13/153). After controlling for confounders such as performance status and primary tumor type, high NLR (OR 5.20, 95% CI 1.21-22.28; p = 0.026) and SII (OR 4.92, 95% CI 1.17-20.63; p = 0.029) were associated with increased odds of 30-day postoperative mortality. The median OS time in the study population was 26 months (95% CI 12-40 months). After controlling for confounders such as Eastern Cooperative Oncology Group status, primary tumor, and hypoalbuminemia, high NLR was associated with shorter OS (HR 2.23, 95% CI 1.48-3.97; p = 0.003). High preoperative NLR and SII were independently associated with 30-day postoperative mortality in this study. Elevated NLR was also found to be associated with shorter OS. The prognostic role of these metrics warrants further investigation.

40. Surgical Site Infection in Spinal Metastasis - Risk Factor and Countermeasure

Estimatedpostoperative survival is an important consideration during the decision-making process for patients with spinal metastases. Nutritional status has been associated with poor outcomes and limited survival in the general cancer population. The objective of this study was to evaluate the predictive utility of the prognostic nutritional index (PNI) for postoperative mortality after spinal metastasis surgery. A total of 139 patients who underwent oncologic surgery for spinal metastases between April 2012 and August 2022 and had a minimum 90-day follow-up were included. PNI was calculated using preoperative serum albumin and total lymphocyte count, with PNI < 40 defined as low. The mean PNI of our cohort was 43 (standard deviation: 7.7). The primary endpoint was 90-day mortality, and the secondary endpoint was 12-month mortality. Multivariate logistic regression analyses were performed. The 90-day mortality was 27% (37/139), and the 12-month mortality was 56% (51/91). After controlling for age, ECOG performance status, total psoas muscle cross-sectional area (TPA), and primary cancer site, thePNI was associated with 90-daymortality [odds ratio 0.86 (95% confidence interval 0.79-0.94); p = 0.001]. After controlling for ECOG performance status and primary cancer site, the PNI was associated with 12-month mortality [OR 0.89 (95% CI 0.82-0.97); p = 0.008]. Patients with a low PNI had a 50% mortality rate at 90days and an 84% mortality rate at 12months. The PNI was independently associated with 90-day and 12-month mortality after metastatic spinal tumor surgery, independent of performance status, TPA, and primary cancer site.

Updated external validation of the SORG machine learning algorithms for prediction of ninety-day and one-year mortality after surgery for spinal metastasis

Study DesignRetrospective study.PurposeTo investigate the incidence of symptomatic and asymptomatic implant failure in spinal metastasis surgery and identify potential risk factors.Overview of LiteratureSurgical stabilization with instrumentation is an established method for the treatment of spinal metastasis. However, very few studies have investigated the incidence and risk factors for implant failure after spinal instrumentation surgery for the treatment of spinal metastasis.MethodsThis study recruited 88 patients who received surgical stabilization with instrumentation for the treatment of spinal metastasis. Their medical records and postoperative X-rays were reviewed for evidence of implant failure. Statistical analysis with logistic regression was performed to assess nine potential risk factors for the development of implant failure, including patient’s age at operation, gender, survival, primary tumor, spinal level involved, construct length, decompression levels, fusion material utilization, and radiotherapy application either before or after surgery, to identify potential contributing risk factors.ResultsImplant failure was identified in nine out of 88 cases (10.2%) with two cases requiring implant removal: one case included a progressive kyphosis that resulted in nonhealing sore and the other involved a deep-seated wound infection that spread to the implants. Another case required wound debridement due to superficial wound infection. The remaining six cases were asymptomatic, despite postoperative X-rays demonstrating evidence of implant failure. No patient required implant revision. Logistic regression analysis demonstrated that patients who received radiotherapy either before or after surgery were less likely to develop implant failure.ConclusionsThe development of radiological implant failure following surgical treatment of spinal metastasis is common. However, symptomatic implant failure leading to revision surgery is uncommon. Our findings suggest that radiotherapy, either before or after spinal surgery, is not associated with the development of implant failure.

Retrospective cohort study. This study aimed to develop machine-learning algorithms to predict ambulation outcomes following surgery for spinal metastasis. Postoperative ambulation status following spinal metastasis surgery is currently difficult to predict. The improved ability to predict this important postoperative outcome would facilitate management decision-making and help in determining realistic treatment goals. This retrospective study included patients who underwent spinal metastasis at a university-based medical center in Thailand between January 2009 and November 2021. Collected data included preoperative parameters and ambulatory status 90 and 180 days following surgery. Thirteen machine-learning algorithms, namely, artificial neural network, logistic regression, CatBoost classifier, linear discriminant analysis, extreme gradient boosting, extra trees classifier, random forest classifier, gradient boosting classifier, light gradient boosting machine, naïve Bayes, K-neighbor classifier, Ada boost classifier, and decision tree classifier were developed to predict ambulatory status 90 and 180 days following surgery. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and F1-score. In total, 167 patients were enrolled. The number of patients classified as ambulatory 90 and 180 days following surgery was 140 (81.9%) and 137 (82.0%), respectively. The extreme gradient boosting algorithm was found to most accurately predict 180-day ambulatory outcome (AUC, 0.85; F1-score, 0.90), and the decision tree algorithm most accurately predicted 90-day ambulatory outcome (AUC, 0.94; F1-score, 0.88). Machine-learning algorithms were effective in predicting ambulatory status following surgery for spinal metastasis. Based on our data, the extreme gradient boosting and decision tree best predicted postoperative ambulatory status 180 and 90 days after spinal metastasis surgery, respectively.

Retrospective study. This study aimed to evaluate the ability of the mortality and adverse events prediction following metastatic spinal surgery of MRI-based cross-sectional psoas muscle area (PMA). A retrospective chart review, 120 patients who had undergone metastatic spinal surgery were included. The cross-sectional area identified the PMA under MR-imaging at the L3 or L4 pedicle level, which was classified into 3 tertiles. We used univariate and multivariate cox proportional hazard regression to assess whether PMA was associated with 30-day, 90-day, 1-year, and overall mortality. The small psoas tertile group populations had a higher mortality rate than the large psoas tertile group. PMA in T1 and T2 had a probability of a higher 90-d mortality rate than PMA in T3 (T1 VS T3: P = .29 and T2 VS T3: P = .12). The median survival time was 7months, 9months, and 10months in PMA T1, T2, and T3, respectively. PMA in tertile 2 had a significantly higher mortality rate of 38% compared to PMA in tertile 3 (HR 1.38, 95% CI .83-2.32, P = .02). Considering PMA as a continuous variable, every 1mm2 increment of PMA resulted in the increase survivorship of 1% (HR .99 with 95% CI .99-1). The MRI-based cross-sectional PMA tends to predict the 90-d mortality rate and overall mortality rate in spinal metastasis patients who underwent spinal surgery. The PMA should be considered one of the prognostic factors in the treatment of metastatic spinal patients.

Spinal metastasis, common in advanced cancer cases, frequently require surgical intervention to improve quality of life by stabilizing the spine and alleviating neural compression. The perioperative transfusion strategies in this setting is under debate. Evidence specific to spinal metastasis surgery remains limited. This study aimed to evaluate the effects of liberal versus restrictive transfusion strategy on postoperative outcomes in patients undergoing surgery for spinal metastasis. A retrospective study was conducted with patients who underwent surgery for spinal metastasis. Using propensity score matching (PSM), patients were matched into restrictive and liberal transfusion groups, adjusting for baseline characteristics. Postoperative outcomes, including 30-day complications, hospital stay, and survival rates at 3 months and 1 year, were compared between the groups. Among 483 patients, 303 received at least one unit of red blood cells during hospitalization. Of these, 125 (41.3%) were in the restrictive transfusion group, and 178 (58.7%) in the liberal transfusion group. After PSM, 70 patients in each group were matched 1:1, ensuring comparable baseline characteristics. Post-matching analysis revealed no significant differences between the groups in key outcomes: 3-month survival (84% vs. 83%, P = 0.820), 1-year survival (46% vs. 51%, P = 0.499), 30-day postoperative complications (19% vs. 23%, P = 0.532), and median length of stay (15 [IQR, 11-18] days vs. 13 [IQR, 11-17] days, P = 0.316). Our study supports using a restrictive transfusion strategy with a target nadir Hb level of 7-8g/dL for spinal metastasis surgery. This approach ensures adequate oxygen delivery while minimizing unnecessary transfusions and associated risks. Future studies should validate these findings and further explore patient-centered outcomes to refine transfusion strategy in high-risk oncology patients. Not applicable.

PurposeSpinal metastasis surgeries carry substantial risk of complications. PRF is among complications that significantly increase mortality rate and length of hospital stay. The risk factor of PRF after spinal metastasis surgery has not been investigated. This study aims to identify the predictors of postoperative respiratory failure (PRF) and in-hospital death after spinal metastasis surgery.MethodsWe retrospectively reviewed consecutive patients with spinal metastasis surgically treated between 2008 and 2018. PRF was defined as mechanical ventilator dependence > 48 h postoperatively (MVD) or unplanned postoperative intubation (UPI). Collected data include demographics, laboratory data, radiographic and operative data, and postoperative complications. Stepwise logistic regression analysis was used to determine predictors independently associated with PRFs and in-hospital death.ResultsThis study included 236 patients (average age 57 ± 14 years, 126 males). MVD and UPI occurred in 13 (5.5%) patients and 13 (5.5%) patients, respectively. During admission, 14 (5.9%) patients had died postoperatively. Multivariate logistic regression analysis revealed significant predictors of MVD included intraoperative blood loss > 2000 mL (odds ratio [OR] 12.28, 95% confidence interval [CI] 2.88–52.36), surgery involving cervical spine (OR 9.58, 95% CI 1.94–47.25), and ASA classification ≥ 4 (OR 6.59, 95% CI 1.85–23.42). The predictive factors of UPI included postoperative sepsis (OR 20.48, 95% CI 3.47–120.86), central nervous system (CNS) metastasis (OR 10.21, 95% CI 1.42–73.18), lung metastasis (OR 7.18, 95% CI 1.09–47.4), and postoperative pulmonary complications (OR 6.85, 95% CI 1.44–32.52). The predictive factors of in-hospital death included postoperative sepsis (OR 13.15, 95% CI 2.92–59.26), CNS metastasis (OR 10.55, 95% CI 1.54–72.05), and postoperative pulmonary complications (OR 9.87, 95% CI 2.35–41.45).ConclusionPRFs and in-hospital death are not uncommon after spinal metastasis surgery. Predictive factors for PRFs included preoperative comorbidities, intraoperative massive blood loss, and postoperative complications. Identification of risk factors may help guide therapeutic decision-making and patient counseling.

Changes in performance status and predictive factors for poor improvement following surgery for spinal metastasis: a nationwide multicenter prospective cohort study.

Surgery for spinal metastasis is a palliative treatment aimed at improving patient quality of life by alleviating pain and reversing or delaying neurologic dysfunction, but with a mean survival time of less than 1 year and significant complication rates, appropriate patient selection is crucial. To identify the most significant prognostic variables of survival after surgery for spinal metastasis. Chart review was performed on 200 surgically treated spinal metastasis patients at Stanford Hospital between 1999 and 2009. Survival analysis was performed and variables entered into a Cox proportional hazards model to determine their significance. Median overall survival was 8.0 months, with a 30-day mortality rate of 3.0% and a 30-day complication rate of 34.0%. A Cox proportional hazards model showed radiosensitivity of the tumor (hazard ratio: 2.557, P<.001), preoperative ambulatory status (hazard ratio: 2.355, P=.0001), and Charlson Comorbidity Index (hazard ratio: 2.955, P<.01) to be significant predictors of survival. Breast cancer had the best prognosis (median survival, 27.1 months), whereas gastrointestinal tumors had the worst (median survival, 2.66 months). We identified the Charlson Comorbidity Index score as one of the strongest predictors of survival after surgery for spinal metastasis. We confirmed previous findings that radiosensitivity of the tumor and ambulatory status are significant predictors of survival.