Abstract
BACKGROUND AND OBJECTIVES:
Aggressive resection for primary tumors of the spine are associated with a high rate of adverse events (AEs), but the impact of AEs on patient-reported outcomes (PROs) remains unknown and is critical to the shared decision-making. Our primary objective was to assess the impact of surgical AEs on PROs using an international registry. Assessing the impact on clinical outcomes and identifying risk factors for AEs were our secondary objectives.
METHODS:
Patients who underwent surgery for a primary spinal tumor were selected through the Primary Tumor Research and Outcomes Network. Our primary outcome was the impact of AEs on PROs at 3 and 12 months after surgery (measured with Spinal Oncology Study Group Outcomes Questionnaire, Short-Form 36, and EuroQol 5 Dimension). We also assessed the impact on clinical outcomes (local control, surgical margins, readmission, reoperation, and mortality). We stratified our results according to severity of AEs, histology, and type of resection.
RESULTS:
374 patients met inclusion criteria (219 males/155 females). The mean age of the cohort was 48.7 years. The most frequent histology was chordoma (37.3%) followed by chondrosarcoma (8.8%). Sixty-seven patients (17.9%) experienced at least 1 intraoperative AE and 117 patients (31.3%) had at least 1 postoperative AE within 3 months. Overall, 159 patients (42.5%) experienced AEs. The readmission rate was significantly higher in patients who experienced AEs (Any AE: 10.1% vs no AE: 1.9% within 3 months; P = <0.001). PROs were not significantly affected by AEs in most questionnaires. Local control, risk of reoperation, mortality, and achieving preplanned margins were similar between AE groups.
CONCLUSION:
The rate of surgical AEs is considerable in this population. Surgical AEs seem to be associated with a higher number of readmissions, but do not seem to result in significant differences in PROs or in a higher risk of reoperation, mortality, and failure to achieve preplanned margins.
KEY WORDS: Primary spinal tumors, Adverse events, Complications, Surgery, Spine
ABBREVIATIONS:
- AEs
adverse events
- EQ-5D
EuroQol 5D
- PROs
patient-reported outcomes
- PTRON
Primary Tumors Research and Outcomes Network
- SAVES
Spinal AdVerse Events Severity
- SF-36
Short-Form 36
- SOSGOQ
Spine Oncology Study Group Outcomes Questionnaire.
Primary tumors of the spine are relatively rare entities when compared with spinal metastasis.1,2 The principles behind the surgical treatment of these tumors are based on the Enneking classification of musculoskeletal tumors, which mandates wide or marginal surgical resection to achieve negative margins for malignant tumors.3,4 Although invasive, aggressive surgeries such as en bloc resections are associated with less local recurrence and improved survival.5
The complex anatomic relationships of the spine make resection of primary spine tumors challenging and associated with a high risk of complications.6 Previous single-center experience reported adverse event (AE) rate as high as 79%.7 They vary considerably according to the area of the spine involved, extent and/or histology of the tumor, and experience of the surgical team.8 Increased operative time, likely as a surrogate to case complexity, has also been identified as an important factor associated with higher risk of perioperative AEs.7
Limitations of single-center studies include heterogenous patient cohorts as well as variations in surveillance and reporting of AEs.6,7 In addition, little is known about the impact of AEs on clinical and patient-reported outcomes (PROs) in this population. It would be of great value for both surgeons and patients to be informed and able to discuss the impact of AEs, especially considering the complexity of the procedures and the life and death consequences that are a significant component of the preoperative counseling and informed consent. Rather than a crude complication rate, it may be more relevant to patients to discuss the impact of AEs on their quality of life in a setting of heightened local recurrence and uncertain survival. The primary objective of this study was to assess the impact of AEs on PROs. Assessing the impact on clinical outcomes was our secondary objective.
METHODS
Design
The Primary Tumor Research and Outcomes Network (PTRON) is a multicenter international registry with prospectively collected data from patients with primary spine tumors. Fifteen centers with expertise in spine oncology participated and received approval from their local ethics board. All participating surgeons had uniform experience, a clinical focus in spine oncology, and technical expertise in primary spine tumor resection. Informed consent was obtained from all patients enrolled in the study. Available data from inception to January 2022 were analyzed.
Patient Selection
Adult patients (18 years or older) who underwent surgical treatment after enrollment in PTRON and with available follow-up data at 3 months after surgery were included. The same patients in the 3-month cohort were also included in the 12-month cohort if they had adequate follow-up data at that time point. Patients with revision surgery were also included.
Outcomes
The primary outcome was the impact of AEs on PROs at 3 and 12 months measured by three validated questionnaires: the Short-Form 36 (SF-36v2) (Mental and Physical), the EuroQol 5 Dimension (EQ-5D), and the Spine Oncology Study Group Outcomes Questionnaire (SOSGOQv1.0).9-11 Secondary outcomes included reoperation, readmission, and mortality within 3 and 12 months after surgery. Finally, we analyzed the relation between an intraoperative AEs and a compromised surgical margin. Surgeon's preoperative planned margin (intralesional, marginal, wide) was compared with the pathologist margin assessment. Success was defined as the pathologist margin being as good or better than preoperative planned margin.
Adverse Events
The Spine AdVerse Events Severity (SAVES) system version 2 was used to record AEs. SAVES-V2 is a validated tool to capture AEs in spine surgery patients and is categorized into intraoperative and postoperative AEs.12,13 Severity grades from 1 (no impact) to 6 (causing death) were used to categorize AEs into minor (1-2) and major (3-6). In case where severity grading was missing, two members of the team independently assigned a category (minor vs major) to the AEs based on previous work by Glassman et al.14 The logistics of collecting AEs varied across sites as to the people responsible for it and the exact timing. It was the same for PROs and other outcomes.
Statistical Analyses
Dependent on the sample size and the number of groups, a Fischer's exact test or the χ2 test was used to identify if experiencing AEs was associated with secondary outcomes. The changes of the PRO scores from baseline to 3 and 12 months between groups (AEs status) were analyzed using a t-test. Furthermore, the relationship between AEs within 12 months and local control was investigated using Kaplan–Meier curves. Survival curves between groups (AE status) were compared using the log-rank test and the P-value was provided. We also conducted post hoc stratification of our PROs and clinical outcome results by histology and surgical plan.
Multivariable logistic relative risk models were produced to analyze the association between specific covariates and the occurrence of AEs. The following covariates were investigated: age, operating time, Eastern Cooperative Oncology Group Performance Status, Enneking staging, previous treatment status (surgery, radiotherapy, chemotherapy), tumor location, tumor dimension, and surgical approach. Feature selection was conducted using bootstrapping with backward selection based on the Akaike information criterion. In this approach, 1000 bootstrap samples were drawn from the original data set and backward selection used to determine variables associated with the outcome interest in each sample. Only variables present in 70% or more of the bootstrap samples were included in the final models. P-values were not adjusted for multiple comparisons. Model performance was assessed using the area under the receiver operating characteristic curve with 95% confidence interval.
Furthermore, generalized linear models analyzed the relationship between specific covariates and PROs. Covariates of interest were incidence of postoperative AEs, PRO at baseline, time to PRO, age, operating time, Eastern Cooperative Oncology Group, Enneking staging, previous treatment status, tumor location, tumor dimension, and surgical approach. The first two variables were included in all the models. For the other covariates, we used the same method as described above.
RESULTS
Patient Selection
Of the 970 patients enrolled in PTRON, 374 (38.6%) were included for the 3-month analyses and 296 (30.5%) were included for the 12-month analyses. The main reasons for exclusion were absence of prospective surgical treatment (n = 150) and lost to follow-up (n = 184 and 347 for 3 and 12 months, respectively). Also, a significant proportion of patients with incomplete follow-up data were excluded (n = 169 and 84 for 3 and 12 months, respectively) (Figure 1).
FIGURE 1.
The cohort consisted of 374 patients for the 3-month analysis and 296 patients for the 12-month analysis. PTRON, Primary Tumor Research and Outcomes Network.
Patient Characteristics
Clinical and demographic details of the patients with a 3-month follow-up are shown in Tables 1 and 2. The mean age was 48.7 years and the majority were male (58.6%) and Caucasian (86.9%). The total number of patients with available pathology report was 308. The most frequent benign histology was schwannoma (8.8%) followed by giant cell tumor (6.8%), and the most common malignant tumor was chordoma (37.3%) followed by chondrosarcoma (8.8%). The thoracic and lumbar spine (T3-L5) was the most common main tumor location (54.8%). Most of the patients were enrolled before their first surgery; however, a significant number of patients already had surgery for their pathology at the time of enrollment (36.9%).
TABLE 1.
Patients Demographics From the 3-Month Follow-up Cohort (n = 374)
| Age, years (mean ± SD) | 48.7 ± 17.1 |
| Male, n (%) | 219 (58.6) |
| Female, n (%) | 155 (41.4) |
| Ethnicity, n (%) | |
| Caucasian | 325 (86.9) |
| Black | 4 (1.1) |
| Asian | 14 (3.7) |
| Aboriginal | 0 (0.0) |
| Hispanic | 22 (5.9) |
| Caribbean | 2 (0.5) |
| East Indian | 3 (0.8) |
| Other/mixed | 1 (0.3) |
| Unknown | 3 (0.8) |
| Charlson Comorbidity Index (mean ± SD) (n = 363) | 2.1 ± 1.2 |
| Smoking status, n (%) | |
| Active | 26 (7.0) |
| Ancient | 36 (9.6) |
| Previous surgical status (n = 372), n (%) | |
| First surgery (virgin) | 234 (62.9) |
| Revision surgery | 138 (37.1) |
| Main tumor location (reclassified), n (%) | |
| C0-C2 | 31 (8.3) |
| C3-C6 | 15 (4.0) |
| C7-T2 | 30 (8.1) |
| T3-L5 | 205 (54.8) |
| S1-S5/coccyx | 93 (24.9) |
| ECOG performance status (n = 362), n (%) | |
| 0 | 130 (35.9) |
| 1 | 166 (45.9) |
| 2 | 43 (11.9) |
| 3 | 18 (5.0) |
| 4 | 5 (1.4) |
| 5 | 0 (0.0) |
ECOG, Eastern Cooperative Oncology Group.
TABLE 2.
Tumor Histology and Enneking Classification (3-Month Follow-up Cohort)
| Tumor histology (pathologist report), n (%) | N = 308 |
|---|---|
| Chordoma | 115 (37.3) |
| Chondrosarcoma | 27 (8.8) |
| Osteosarcoma | 5 (1.6) |
| Ewing's sarcoma | 11 (3.6) |
| Hemangiopericytoma | 2 (0.6) |
| Giant cell tumor | 21 (6.8) |
| Osteoid osteoma | 16 (5.2) |
| Osteoblastoma | 17 (5.5) |
| Hemangioma | 11 (3.6) |
| Osteochondroma | 2 (0.6) |
| Aneurysmal bone cyst | 3 (1.0) |
| Fibrous dysplasia | 4 (1.3) |
| Chondroblastoma | 1 (0.3) |
| Schwannoma | 27 (8.8) |
| Neurofibroma | 2 (0.6) |
| Meningioma | 4 (1.3) |
| Malignant peripheral nerve sheath tumor (MPNST) | 1 (0.3) |
| Other malignant bone tumor | 9 (2.9) |
| Other benign bone tumor | 4 (1.3) |
| Other malignant soft tissue tumor | 20 (6.5) |
| Other benign soft tissue tumor | 6 (1.9) |
| Enneking classification, n (%) | N = 308 |
|---|---|
| Benign—S1 | 13 (4.2) |
| Benign—S2 | 34 (11.0) |
| Benign—S3 | 67 (21.8) |
| Malignant—Ia | 11 (3.6) |
| Malignant—Ib | 105 (34.1) |
| Malignant—IIa | 20 (6.5) |
| Malignant—IIb | 46 (14.9) |
| Malignant—IIIa | 6 (1.9) |
| Malignant—IIIb | 6 (1.9) |
Adverse Events
Overall, 67 patients (17.9%) experienced at least 1 intraoperative AE for the 3-month follow-up cohort. The number of patients who suffered postoperative AEs was higher with 117 (31.3%, n = 374) of them within 3 months and 106 (35.8%, n = 296) within 12 months. A total of 159 patients (42.5%) experienced at least 1 surgical AE within 3 months after the first surgical treatment. From these, 80 patients (21.4%) had AEs categorized as minor, 74 (19.8%) as major, and 5 (1.3%) could not be categorized. The most frequent intraoperative AE was dural tear (n = 36), while wound-related complications were the most common in the postoperative period. Frequency of AEs can be seen in Tables 3 and 4.
TABLE 3.
Intraoperative AEs (3-Month Follow-up Cohort) (n = 374)
| List of intraop AE with frequency, n (%) | |
|---|---|
| Allergic reaction | — |
| Anesthesia-related | — |
| Bone implant failure requiring revision | 1 (0.3) |
| Cardiac | — |
| Cord injury | 2 (0.5) |
| Dural tear | 36 (9.6) |
| Hardware malposition requiring revision | 7 (1.9) |
| Hypotension (<85 mm Hg SBP for 15 min) | 2 (0.5) |
| Massive blood loss (>5 L in 24 h or >2 L in 3 h) | 8 (2.1) |
| Nerve root injury | 3 (0.8) |
| Pressure sores | 1 (0.3) |
| Vascular injury | 5 (1.3) |
| Ventilation/airway | 2 (0.5) |
| Visceral injury | 7 (1.9) |
| Others | 4 (1.1) |
| No. of patients with at least 1 intraoperative AE, n (%) | 67 (17.9) |
AE, adverse events; SBP, systolic blood pressure.
TABLE 4.
Postoperative AEs
| List of postoperative AEs with frequency, n (%) | 3 months (n = 374) | 12 months (n = 296) |
|---|---|---|
| Cardiac arrest/failure/arrythmia | 10 (2.7) | 6 (2.0) |
| Construct failure with loss of correction | 2 (0.5) | 1 (0.3) |
| Construct failure without loss of correction | 2 (0.5) | 1 (0.3) |
| CSF leak/pseudomeningocele | 12 (0.5) | 8 (2.7) |
| Deep vein thrombosis | 10 (2.7) | 7 (2.4) |
| Deep wound infection | 21 (5.6) | 16 (5.4) |
| Delirium | 7 (1.9) | 6 (2.0) |
| Dysphagia | 7 (1.9) | 6 (2.0) |
| Dysphonia | 5 (1.3) | 5 (1.7) |
| Gastrointestinal bleeding | 2 (0.5) | 2 (0.7) |
| Hematoma | 7 (1.9) | 7 (2.4) |
| Myocardial infarction | — | — |
| Neurological deterioration (≥ 1 motor grade in ASIA motor scale) | 10 (2.7) | 9 (3.0) |
| Nonunion | — | 1 (0.3) |
| Pneumonia | 17 (4.5) | 15 5.1) |
| Postoperative neuropathic pain | 10 (2.7) | 7 (2.4) |
| Pressure sores | — | — |
| Pulmonary embolism | 14 (3.7) | 12 (4.1) |
| Superficial wound infection | 12 (3.2) | 11 (3.7) |
| Systemic infection | 6 (1.6) | 7 (2.4) |
| Urinary tract infection | 7 (1.9) | 7 (2.4) |
| Wound dehiscence | 19 (5.1) | 16 (5.4) |
| Others | 98 (26.2) | 89 (30.1) |
| Number of patients with at least 1 postoperative AE, n (%) | 117 (31.3) | 106 (35.8) |
| No. of patients with at least 1 AE (any), n (%) | 159 (42.5) | 137 (46.3) |
AE, adverse events; ASIA, American Spinal Injury Association; CSF, cerebrospinal fluid.
Multivariable logistic relative risk regression models were used to identify factors that had an influence on AEs (Table 5). The area under the receiver operating characteristic curve for all models ranged between 0.66 and 0.77. A longer operative time was constantly associated with a higher risk of AEs. Older age was also significantly associated with a higher risk of AEs in 2 of 6 models. Finally, a posterior approach only was associated with a lower risk of intraoperative AEs compared with combined anterior/posterior approach.
TABLE 5.
Multivariate (Logistic) Regression Models Assessing the Effect of Covariates on the Risk of AE (Relative Risk With 95% CI)
| Covariates | Model #1 (any AE at 3 mo) AUROC (95% CI): 0.73 (0.68-0.79) |
Model #2 (postoperative AE at 3 mo) AUROC (95% CI): 0.73 (0.67-0.79) |
Model #3 (intraoperative AE at 3 mo) AUROC (95% CI): 0.66 (0.59-0.73) |
Model #4 (any AE at 12 mo) AUROC (95% CI): 0.77 (0.71-0.82) |
Model #5 (postoperative AE at 12 mo) AUROC (95% CI): 0.75 (0.69-0.82) |
Model #6 (intraoperative AE at 12 mo) AUROC (95% CI): 0.71 (0.63-0.78) |
|---|---|---|---|---|---|---|
| Age [y] | 1.0106 [1.0031-1.0181] | — | — | 1.0163 [1.0083-1.0244] | — | — |
| Operating time [min] | 1.0009 [1.0007-1.0011] | 1.0012 [1.0010-1.0015] | 1.0010 [1.0005-1.0014] | 1.0008 [1.0006-1.0011] | 1.0012 [1.0009-1.0014] | 1.0010 [1.0006-1.0014] |
| ECOG 2 | — | — | — | — | — | — |
| ECOG 3-4-5 | — | — | — | — | — | — |
| Posterior approach | — | — | — | — | — | 0.4724 [0.2928-0.7621] |
| Anterior approach | — | — | — | — | — | 0.5581 [0.2481-1.2557] |
AE, adverse event; AUROC, area under the receiver operating characteristic curve; ECOG, Eastern Cooperative Oncology Group.
Results with a P-value <.05 are highlighted in bold.
(—) means the covariate was not included in the model because it was not present in ≥70% of 1000 model simulations.
Patient-Reported Outcomes
Overall, the mean PRO scores evolved in the same direction across time for all four questionnaires and AE status (Table 6). For all PROs and groups, the mean score at 12 months was higher than baseline. This evolution in time is shown in Figure 2. The t-test was conducted to detect statistically significant differences in the mean change from baseline scores for patients with and without AE. The mean change measured with the EQ-5D from baseline to 12 months was 0.05 in the group with AE compared with 0.13 in the group without AE, and this was statistically significant (P = .047). Mean changes from baseline to 12 months for SF-36 Physical (2.34 vs 0.29; P = .353), SF-36 Mental (6.46 vs 5.69; P = .778), and SOSGOQ (0.10 vs 0.05; P = .194) did not reach statistical significance.
TABLE 6.
PROs Stratified by AE Status
| Questionnaire | AE status | Baseline | 3 months | 12 months |
|---|---|---|---|---|
| EQ-5D Mean (SD) |
No AE | 0.61 (0.20) | 0.67 (0.13) | 0.73 (0.12) |
| Any AE | 0.61 (0.19) | 0.63 (0.14) | 0.67 (0.16) | |
| SF36 Physical Mean (SD) |
No AE | 40.26 (11.46) | 39.44 (9.55) | 44.65 (10.22) |
| Any AE | 37.73 (12.61) | 35.96 (10.02) | 39.29 (11.85) | |
| SF36 Mental Mean (SD) |
No AE | 45.48 (13.03) | 49.53 (11.28) | 50.78 (11.07) |
| Any AE | 44.96 (12.94) | 48.41 (11.05) | 50.33 (12.07) | |
| SOSGOQ Mean (SD) |
No AE | 0.72 (0.18) | 0.72 (0.16) | 0.80 (0.13) |
| Any AE | 0.68 (0.19) | 0.67 (0.18) | 0.73 (0.18) |
AE, adverse event; EQ-5D, EuroQol 5D; SF-36, Short-Form 36; SOSGOQ, Spine Oncology Study Group Outcomes Questionnaire.
Change from baseline was significantly different according to the AE status with results highlighted in bold (any AE = 0.05 vs no AE = 0.13) (P = .047).
Baseline and 12-month data refer to cohort with follow-up up to 12 months. Three-month data refer to patients with a follow-up up to 3 months.
FIGURE 2.
PRO evolution in time from the 12-month cohort data. AE, adverse event; EQ5D, EuroQol 5D; PROs, patient-reported outcomes; SF36 Me, Short-Form 36 Mental Component Summary; SF36 Ph, Short-Form 36 Physical Component Summary; SOSGOQ, Spinal Oncology Study Group Outcomes Questionnaire.
After stratifying for histology, no significant differences were seen in change from baseline at 12 months in any histological subgroup across all PROs (Table 7). Similarly, there were no significant differences when stratifying for surgical plan, except for the EQ-5D at 3 months in patients with intralesional resection (Table 8).
TABLE 7.
PROs Stratified by Histology
| Questionnaires | Histology | AE status | Baseline | 3 months | 12 months |
|---|---|---|---|---|---|
| EQ-5D | Malignant | No AE | 0.64 (0.19) | 0.65 (0.12) | 0.73 (0.10) |
| Mean (SD) | Any AE | 0.59 (0.19) | 0.60 (0.17) | 0.66 (0.14) | |
| Benign | No AE | 0.57 (0.20) | 0.71 (0.12) | 0.76 (0.11) | |
| Any AE | 0.72 (0.15) | 0.66 (0.15) | 0.76 (0.11) | ||
| Intradural | No AE | 0.64 (0.19) | 0.71 (0.16) | 0.68 (0.17) | |
| Any AE | 0.55 (0.20) | 0.40 (0.21) | 0.85 (—) | ||
| SF36 physical | Malignant | No AE | 41.35 (12.62) | 36.17 (9.91) | 42.89 (9.14) |
| Mean (SD) | Any AE | 36.99 (12.93) | 33.98 (7.59) | 37.61 (11.72) | |
| Benign | No AE | 38.16 (10.31) | 44.70 (7.18) | 45.95 (8.65) | |
| Any AE | 40.80 (12.27) | 37.52 (14.07) | 47.97 (11.02) | ||
| Intradural | No AE | 41.66 (11.57) | 42.55 (8.30) | 45.90 (10.76) | |
| Any AE | 38.12 (15.16) | 32.91 (18.60) | — | ||
| SF36 mental | Malignant | No AE | 45.29 (13.78) | 47.30 (11.06) | 49.51 (11.34) |
| Mean (SD) | Any AE | 46.10 (12.81) | 48.97 (11.21) | 51.26 (10.92) | |
| Benign | No AE | 45.48 (12.49) | 52.41 (11.74) | 51.92 (11.92) | |
| Any AE | 43.33 (11.92) | 49.37 (10.93) | 51.25 (13.65) | ||
| Intradural | No AE | 48.15 (13.09) | 50.21 (11.92) | 53.44 (7.19) | |
| Any AE | 50.19 (13.80) | 30.76 (19.79) | — | ||
| SOSGOQ | Malignant | No AE | 0.74 (0.20) | 0.69 (0.16) | 0.76 (0.12) |
| Mean (SD) | Any AE | 0.67 (0.19) | 0.67 (0.15) | 0.71 (0.18) | |
| Benign | No AE | 0.72 (0.17) | 0.81 (0.14) | 0.87 (0.09) | |
| Any AE | 0.74 (0.17) | 0.67 (0.24) | 0.83 (0.18) | ||
| Intradural | No AE | 0.73 (0.15) | 0.79 (0.17) | 0.87 (0.13) | |
| Any AE | 0.75 (0.18) | 0.45 (0.24) | — |
AE, adverse event; EQ-5D, EuroQol 5D; SF-36, Short-Form 36; SOSGOQ, Spine Oncology Study Group Outcomes Questionnaire.
Results with a P-value <.05 are highlighted in bold.
TABLE 8.
PROs Stratified by Surgical Plan
| Questionnaires | Surgical plan | AE status | Baseline | 3 months | 12 months |
|---|---|---|---|---|---|
| EQ-5D | Intralesional | No AE | 0.55 (0.21) | 0.72 (0.10) | 0.74 (0.09) |
| Mean (SD) | Any AE | 0.57 (0.23) | 0.66 (0.18) | 0.67 (0.17) | |
| En bloc | No AE | 0.64 (0.19) | 0.64 (0.14) | 0.73 (0.13) | |
| Any AE | 0.62 (0.18) | 0.60 (0.16) | 0.66 (0.15) | ||
| SF36 physical | Intralesional | No AE | 37.53 (11.10) | 41.90 (8.98) | 45.12 (11.33) |
| Mean (SD) | Any AE | 33.14 (11.29) | 38.04 (12.55) | 38.39 (10.07) | |
| En bloc | No AE | 41.95 (11.38) | 38.48 (9.89) | 44.58 (9.87) | |
| Any AE | 39.42 (12.71) | 34.40 (9.07) | 39.60 (12.51) | ||
| SF36 Mental | Intralesional | No AE | 45,48 (13.02) | 54.11 (8.53) | 56.25 (9.84) |
| Mean (SD) | Any AE | 40.54 (13.75) | 48.65 (10.59) | 50.25 (8.66) | |
| En bloc | No AE | 45.61 (13.10) | 47.56 (12.23) | 48.67 (10.71) | |
| Any AE | 46.59 (12.32) | 47.02 (12.75) | 50.36 (13.14) | ||
| SOSGOQ | Intralesional | No AE | 0.69 (0.18) | 0.78 (0.13) | 0.88 (0.10) |
| Mean (SD) | Any AE | 0.60 (0.25) | 0.71 (0.17) | 0.68 (0.22) | |
| En bloc | No AE | 0.74 (0.16) | 0.69 (0.17) | 0.77 (0.13) | |
| Any AE | 0.70 (0.17) | 0.65 (0.19) | 0.75 (0.17) |
AE, adverse event; EQ-5D, EuroQol 5D; SF-36, Short-Form 36; SOSGOQ, Spine Oncology Study Group Outcomes Questionnaire.
Results with a P-value <.05 are highlighted in bold.
Furthermore, generalized linear models were used to assess the influence of the covariates on the PRO scores at 3 and 12 months (Table 9). The baseline PRO score consistently had a significant unadjusted P-value in all four questionnaires at both 3 and 12 months. In addition, this analysis determined that AE severity had no impact on any of the four PROs.
TABLE 9.
Multivariable Generalized Linear Models of Factors Associated With PROs (exp (Estimate) With P Values)
| Covariates | Model #1 EQ-5D |
Model #2 SOSGOQ |
Model #3 SF36 physical |
Model #4 SF36 mental |
|---|---|---|---|---|
| 3 months follow-up cohort | ||||
| PRO at baseline | 1.5610 (P = .001) | 1.9749 (P < .0001) | 1.0089 (P < .0001) | 1.0087 (P < .0001) |
| Postoperative AE: minor | 0.9278 (P = .1217) | 0.9567 (P = .3969) | 0.9957 (P = 9460) | 0.9792 (P = .6695) |
| Postoperative AE: major | 0.9412 (P = .2773) | 0.9801 (P = .7294) | 0.9760 (P = .7654) | 1.0068 (P = .9028) |
| Operating time (min) | — | — | 0.9999 (P = .0501) | — |
| Time to PRO | — | — | — | 0.9971 (P = .0033) |
| Enneking S2/S3 | — | 0.9035 (P = .6202) | — | — |
| Enneking Ia/IB/IIa/IIb/IIIa/IIIb | — | 0.7946 (P = .2595) | — | — |
| Covariates | Model #5 EQ-5D |
Model #6 SOSGOQ |
Model #7 SF36 physical |
Model #8 SF36 Mental |
|---|---|---|---|---|
| 12 months follow-up cohort | ||||
| PRO at baseline | 1.2712 (P = .0134) | 1.8965 (P < .0001) | 1.0101 (P < .0007) | 1.0101 (P = .0001) |
| Postoperative AE: minor | 0.9231 (P = .0735) | 0.9608 (P = .5057) | 0.9900 (P = .8968) | 1.0618 (P = .2749) |
| Postoperative AE: major | 0.9704 (P = .6100) | 0.9048 (P = .1117) | 0.8869 (P = .0804) | 1.0408 (P = .5713) |
| Anterior approach | 0.8106 (P = .0069) | — | 0.8781 (P = .1611) | — |
| Posterior approach | 1.0513 (P = .4365) | — | 1.0725 (P = .3048) | — |
AE, adverse events; EQ-5D, EuroQol 5D; PRO, patient-reported outcomes; SF-36, Short-Form 36; SOSGOQ, Spine Oncology Study Group Outcomes Questionnaire.
Results with a P-value <.05 are highlighted in bold.
(—) means the covariate was not included in the final model because it was not present in ≥70% of 1000 model simulations.
Clinical Outcomes
The number of patients with a readmission was significantly higher in patients who suffered AEs compared with those who did not. This was observed at both 3 months (10.1 vs 1.9%, unadjusted P-value <.001) and 12 months (24.1 vs 6.9%, unadjusted P-value <.001) (Tables 10 and 11). However, for reoperation and mortality, no group dependency at either specific time points could be detected. When stratifying results between major and minor AEs, the risk of readmission was significantly higher in patients with major AEs at 3 months (12.2 vs 6.3%, unadjusted P-value <.001) and 12 months (28.2 vs 14.5%, unadjusted P-value <.001). As with the uncategorized AEs, the stratified AEs did not reach statistical significance for difference between groups for mortality and reoperation. Stratification by histology and surgical plan also only showed significant statistical differences between groups for readmission in en bloc resection as well as benign and intradural tumors (Tables 12 and 13). Finally, achieving preplanned margins was not affected by the presence of an intraoperative AE with a success rate of 68.6% in patients who did not suffer intraoperative AEs compared with 64.5% in patients who did (P = .538). Stratification of this outcome with minor vs major intraoperative AEs also did not show significant difference (P = .694). Local control was not affected by the presence of AEs within 12 months (P = .771) (Figure 3).
TABLE 10.
Clinical Outcomes Stratified by AE Status
| 3 months | Any AE (N = 159) | No AE (N = 215) |
|---|---|---|
| Readmission, n (%) | 16 (10.1) | 4 (1.9) |
| Reoperation, n (%) | 2 (1.3) | 2 (0.9) |
| Mortality, n (%) | 6 (3.8) | 4 (1.9) |
| 12 months | Any AE (n = 137) | No AE (n = 159) |
|---|---|---|
| Readmission, n (%) | 33 (24.1) | 11 (6.9) |
| Reoperation, n (%) | 7 (5.1) | 4 (2.5) |
| Mortality, n (%) | 16 (11.7) | 15 (9.4) |
AE, adverse event.
Results with a P-value <.05 are highlighted in bold.
TABLE 11.
Clinical Outcomes Stratified by AE Severity
| 3 months | No AE (N = 215) | Major AE (N = 74) | Minor AE (N = 80) |
|---|---|---|---|
| Readmission, n (%) | 4 (1.9) | 9 (12.2) | 5 (6.3) |
| Reoperation, n (%) | 2 (0.9) | 2 (2.7) | 0 (0.0) |
| Mortality, n (%) | 4 (1.9) | 5 (6.8) | 1 (1.3) |
| 12 months | No AE (N = 159) | Major AE (N = 78) | Minor AE (N = 55) |
|---|---|---|---|
| Readmission, n (%) | 11 (6.9) | 22 (28.2) | 8 (14.5) |
| Reoperation, n (%) | 4 (2.5) | 6 (7.7) | 1 (1.8) |
| Mortality, n (%) | 15 (9.4) | 11 (14.1) | 4 (7.3) |
AE, adverse event.
Results with a P-value <.05 are highlighted in bold.
TABLE 12.
Clinical Outcomes Stratified by Histology
| Malignant | Benign | Intradural | ||||
|---|---|---|---|---|---|---|
| Any AE | No AE | Any AE | No AE | Any AE | No AE | |
| 3 months | N = 104 | N = 89 | N = 28 | N = 58 | N = 6 | N = 28 |
| Readmission, n (%) | 9 (8.7) | 2 (2.2) | 2 (7.1) | 0 | 1 (16.7) | 1 (3.6) |
| Reoperation, n (%) | 1 (1.0) | 2 (2.2) | 0 | 0 | 0 | 0 |
| Mortality, n (%) | 4 (3.8) | 2 (2.2) | 1 (3.6) | 0 | 1 (16.7) | 0 |
| 12 months | N = 92 | N = 65 | N = 24 | N = 47 | N = 5 | N = 21 |
|---|---|---|---|---|---|---|
| Readmission, n (%) | 21 (22.8) | 7 (10.8) | 4 (16.7) | 1 (2.1) | 2 (40) | 2 (9.5) |
| Reoperation, n (%) | 3 (3.3) | 4 (6.2) | 2 (8.3) | 0 | 0 | 0 |
| Mortality, n (%) | 13 (14.1) | 10 (15.4) | 1 (4.2) | 0 | 1 (20) | 1 (4.8) |
AE, adverse event.
Results with a P-value <.05 are highlighted in bold.
TABLE 13.
Clinical Outcomes Stratified by Surgical Plan
| Intralesional | En bloc | |||
|---|---|---|---|---|
| Any AE | No AE | Any AE | No AE | |
| 3 months | N = 40 | N = 71 | N = 118 | N = 143 |
| Readmission, n (%) | 3 (7.5) | 2 (2.8) | 13 (11.0) | 2 (1.4) |
| Reoperation, n (%) | 1 (2.5) | 1 (1.4) | 1 (0.8) | 1 (0.7) |
| Mortality, n (%) | 2 (5.0) | 3 (4.2) | 4 (3.4) | 1 (0.7) |
| 12 months | N = 32 | N = 55 | N = 105 | N = 103 |
|---|---|---|---|---|
| Readmission, n (%) | 6 (18.8) | 4 (7.3) | 27 (25.7) | 7 (6.8) |
| Reoperation, n (%) | 4 (12.5) | 2 (3.6) | 3 (2.9) | 2 (1.9) |
| Mortality, n (%) | 5 (15.6) | 7 (12.7) | 11 (10.5) | 8 (7.8) |
AE, adverse event.
Results with a P-value <.05 are highlighted in bold.
FIGURE 3.
Kaplan–Meier survival curves comparing local control between patients with and without at least 1 AE within 12 months postoperatively. y-axis is survival probability. x-axis is time (days). AE status: no = blue, yes = red. AE, adverse event.
DISCUSSION
The main goals of this study were to assess the impact of AEs on PROs and clinical outcomes up to 3 and 12 months postoperatively. The incidence of intraoperative and postoperative AEs was 17.9% and 31.3%, respectively, and 42.5% of patients experienced at least 1 AE within 3 months. Overall, patients in both groups overall had similar changes in PRO scores except for EQ-5D at 12 months where patients who had no AE reported bigger improvement from baseline. AEs were associated with a higher number of readmissions, but not a higher number of reoperation or mortality.
There is a high variability among reported rates of AEs in the spine oncology literature. AE rates vary from 45 to above 90%.7,15-18 This can be explained by heterogeneity in treated pathology, location (sacrum vs mobile spine), and the variability in reporting of AEs. Centers with a dedicated prospective AE collection mechanism will invariably have a higher rate of AEs.12,19 The reported rate of AEs in this study is toward the lower end of what has been published on the matter. This can likely be explained by the multicentric nature of this cohort. Although the same system was used across sites (SAVES-V2), there is variability in the method of collecting AEs (surgeon reporting, chart abstraction, and multidisciplinary meeting), which can explain a wide range of AEs rate.20,21 We should be cautious when it comes to the generalizability of our results since all our recruiting centers have an expertise in treating these complex pathologies.
Longer operative time and older age were both significantly associated with a higher risk of AEs in multiple regression models. Although this finding is intuitive and has a confirmatory value, it can also be quite relevant in a clinical setting when discussing an invasive tumor resection with an older patient.2 These results also support the idea that these patients should be referred to experienced surgical teams who can perform oncological resections in a reasonable amount of time.22 In one model (intraoperative AEs at 12 months), surgery with a posterior approach only was associated with a lower risk of AEs when compared with combined approaches. This result most likely is an indicator of the lesser complexity of the cases and should not be interpreted as a protective factor.
This analysis improves our understanding of the impact of AEs on patient health–related quality of life. Mean scores of PROs evolved in the same direction across all questionnaires, and although the magnitude was different depending on the AE status, only the change from baseline to 12 months in the EQ-5D had a significant unadjusted P-value. The difference in mean change between AE status detected for the EQ-5D at 12 months (0.05 vs 0.13) is above the minimal clinically important difference of 0.06, which has been used in previous spinal oncology publications.23,24 However, no significant difference was seen at 12 months across all questionnaires after stratifying for histology (malignant, benign, and intradural) and surgical plan, which adds to our impression that PROs were not significantly affected by AEs.
The number of readmissions was higher in the group of patients with AEs and even more with major AEs. Interestingly, although there was a trend toward higher number of reoperation in patients with AE, especially at 12 months (5.1 vs 2.5%), it did not reach statistical significance (P = .24) and was much smaller than the readmission difference. We can hypothesize that most readmissions were secondary to medical complications that did not require surgical treatment.
Although AEs had an impact on the EQ-5D and readmission, it did not have a significant impact on achievement of successful surgical margins. This shows that despite the consequences of intraoperative AEs, successful completion of the surgical plan can nevertheless be achieved.
This study adds to the literature being the largest sample of primary tumors from around the world. This added external validity palliates the numerous single-center reports in the literature. Moreover, it shows the impact of AEs on key clinical outcomes and PROs. This information is invaluable to shared decision-making process.
Limitations
The patients lost to follow-up and incomplete follow-up data can result in selection bias, and it is our biggest limitation. In our study, many centers recruited patients who came from abroad or lived remotely, and this has definitely affected our follow-up rate and completeness. In addition, PRO questionnaire translations that were not available was also an issue in our efforts to have the most complete follow-up data possible. The wide variety of centers in Europe and North America, while improving external validity of the results, can also represent a limitation not only by the variety of AEs collection systems, but also by the regional differences of health-related quality of life outcome scores across jurisdictions.25,26 Therefore, our results are at risk of information bias from under-reporting. Also, the wide variety of included pathologies, both benign and malignant, could limit the interpretability of some of the findings. We did try to capture some granularity by stratifying according to histology and surgical plan, but the cost was likely less statistical power. Multiple subgroup analyses also put us at risk of random positive findings.
CONCLUSION
In conclusion, the risk of surgical AEs in primary tumors of the spine is considerable. Patients without AEs overall seem to have comparable PRO scores, although they potentially benefit from a better improvement in health-related quality of life when assessed by a generic outcome tool. The number of readmissions is significantly higher in patients with AEs. However there is no difference in reoperations, mortality, local control and our capacity to achieve preplanned surgical margins. These results will help surgical teams discuss with patients and develop quality improvement strategies.
Acknowledgments
The authors thank all the patients who accepted to participate in this study. The authors also thank all the research/support staff from the recruiting sites and at the AO Foundation. Author Contribution: Conception, design, and collection of data: Gasbarrini, Rhines, Lazary, Gokaslan, Reynolds, Luzzati, Disch, Chou, Clarke, Wei, Bettegowda, Rampersaud, Boriani, Shin, Lord, Sciubba, Laufer, Sahgal, Fisher, Dea; Analysis and interpretation of data: Laflamme, Dea; Drafting of the manuscript: Laflamme, Dea; Critically revising the manuscript: all authors; Reviewed submitted version of the manuscript: all authors. Author Contributions: Mathieu Laflamme, MD: Designing, Writing. Alessandro Gasbarrini, MD: Conducting, Laurence D. Rhines, MD: Designing, Conducting, Aron Lazary, MD, PhD: Designing, Conducting, Ziya L. Gokaslan, MD: Designing, Conducting, Jeremy J. Reynolds, MBChB: Designing, Conducting, Alessandro Luzzati, MD: Conducting, Alexander C. Disch, MD, PhD: Conducting, Dean Chou, MD: Conducting, Michelle J. Clarke, MD: Conducting, Feng Wei, MD: Conducting, Chetan Bettegowda, MD, PhD: Designing, Conducting, Y. Raja Rampersaud, MD: Conducting, Stefano Boriani, MD: Designing, Conducting, John H. Shin, MD: Conducting, Elizabeth Lord, MD: Conducting, Daniel M. Sciubba, MD: Conducting, Ilya Laufer, MD: Designing, Conducting, Arjun Sahgal, MD: Designing, Conducting, Charles G. Fisher, MD, MHSc: Designing, Conducting, Nicolas Dea, MD, MSc: Designing, Conducting, Writing.
Footnotes
Presented as an oral abstract at the Spine Summit in Miami, Florida, on March 19, 2023. Presented as an electronic poster at the Canadian Spine Society virtual annual meeting on April 13, 2022. Presented as an electronic poster at the Global Spine Congress in Las Vegas, Nevada, from June 1 to 4, 2022.
Contributor Information
Mathieu Laflamme, Email: mathieu.laflamme.2@ulaval.ca.
Alessandro Gasbarrini, Email: gasbarrini@me.com.
Laurence D. Rhines, Email: lrhines@mdanderson.org.
Aron Lazary, Email: lazary.aron@gmail.com.
Ziya L. Gokaslan, Email: ziya_gokaslan@brown.edu.
Jeremy J. Reynolds, Email: Jeremy.Reynolds@ouh.nhs.uk.
Alessandro Luzzati, Email: alessandroluzzati@gmail.com.
Alexander C. Disch, Email: Alexander.Disch@ukdd.de.
Dean Chou, Email: dc3658@cumc.columbia.edu.
Michelle J. Clarke, Email: Clarke.Michelle@mayo.edu.
Feng Wei, Email: weifeng@bjmu.edu.cn.
Chetan Bettegowda, Email: cbetteg1@jhmi.edu.
Y. Raja Rampersaud, Email: raja.rampersaud@uhn.ca.
Stefano Boriani, Email: stefanoboriani@gmail.com.
John H. Shin, Email: Shin.John@mgh.harvard.edu.
Elizabeth Lord, Email: Lord.elizabeth@gmail.com.
Daniel M. Sciubba, Email: DSciubba1@northwell.edu.
Ilya Laufer, Email: ilya.laufer@nyulangone.org.
Arjun Sahgal, Email: Arjun.Sahgal@sunnybrook.ca.
Charles G. Fisher, Email: charles.fisher@vch.ca.
Funding
This study was organized and funded by AO Spine through the AO Spine Knowledge Forum Tumor, a focused group of international spine tumor experts. AO Spine is a clinical division of the AO Foundation, which is an independent, medically guided, not-for-profit organization. Study support was provided directly through AO Network Clinical Research and the AO Innovation Translation Center, Clinical Evidence.
Disclosures
The authors have no personal, financial, or institutional interest in any of the drugs, materials, or devices described in this article. Dr Rhines receives payments from Styker, Icotec, and AO Spine. Dr Gokaslan is part of PTRON and MTRON registry, and receives research support for the collection of data from AOSpine Knowledge Forum. Dr Chou is a consultant for and receives royalties from Globus. Dr Bettegowda is a consultant for Depuy-Synthes, Bionaut Labs, Haystack Oncology, and Privo Technologies, and is a cofounder of OrisDx and Belay Diagnostics. Dr Rampersaud receives royalties from Medtronic. Dr Sciubba is a consultant for DePuy Synthes, Medtronic, Stryker, Baxter, Pacira, and Nuvasive. Dr Laufer is a consultant for DePuy Synthes and Iotec. Dr Fisher is a consultant for Medtronic and NuVasive, receives royalties from Medtronic, and receives fellowship support paid to an institution from Medtronic AO Spine and DePuy Synthes. Dr Dea is a consultant for Stryker and Medtronic, owns stock in Medtronic, and is on the speakers bureau for Baxter.
COMMENTS
The authors performed a retrospective review of patients undergoing surgery for primary spine tumors to determine the impact of adverse events (AEs) on patient-reported outcomes (PROs) and secondarily on clinical outcome and risk factors for AEs. A total of 374 patients were included with follow-up conducted at both 3 and 12 months. A total of 159 patients experienced an AE with the majority occurring during the 3-month postoperative period. The presence of an AE did not impact PROs or clinical outcomes but was correlated with a higher readmission rate. The authors conclude that this information will be useful when counseling patients who require surgery for primary spine tumors.
This work demonstrates the power of utilizing a multicenter prospective registry in order to accumulate data for uncommon pathologies. This work also benefits from the relatively consistent skill level among the participating centers and use of standardized measures to categorize the adverse events. As with any such work, limitations are present, the most significant being the potential for selection bias due to the significant loss to follow-up among their patient population. When considering these data, the reader needs to be aware that of available patients, data were not available from over 50% of patients.
Although some of the findings seem intuitive, such as an increased risk of adverse events with longer surgeries (presumably related to the complexity of surgery), this study provides data of reasonable strength to justify these assumptions. For this reason, the information contained in this manuscript may prove useful when counseling patients undergoing surgery for these relatively rare conditions.
Michael G. Kaiser
Ridgewood, New Jersey, USA
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