Impact of intraoperative imaging on decision-making during spine surgery: a survey among spine surgeons using simulated intraoperative images.

PURPOSE: To assess whether the intention to intraoperatively reposition pedicle screws differs when spine surgeons evaluate the same screws with 2D imaging or 3D imaging. METHODS: In this online survey study, 21 spine surgeons evaluated eight pedicle screws from patients who had undergone posterior spinal fixation. In a simulated intraoperative setting, surgeons had to decide if they would reposition a marked pedicle screw based on its position in the provided radiologic imaging. The eight assessed pedicle screws varied in radiologic position, including two screws positioned within the pedicle, two breaching the pedicle cortex < 2 mm, two breaching the pedicle cortex 2-4 mm, and two positioned completely outside the pedicle. Surgeons assessed each pedicle screw twice without knowing and in random order: once with a scrollable three-dimensional (3D) image and once with two oblique fluoroscopic two-dimensional (2D) images. RESULTS: Almost all surgeons (19/21) intended to reposition more pedicle screws based on 3D imaging than on 2D imaging, with a mean number of pedicle screws to be repositioned of, respectively, 4.1 (± 1.3) and 2.0 (± 1.3; p < 0.001). Surgeons intended to reposition two screws placed completely outside the pedicle, one breaching 2-4mm, and one breaching < 2 mm more often based on 3D imaging. CONCLUSION: When provided with 3D imaging, spine surgeons not only intend to intraoperatively reposition pedicle screws at risk of causing postoperative complications more often but also screws with acceptable positions. This study highlights the potential of intraoperative 3D imaging as well as the need for consensus on how to act on intraoperative 3D information.

Patient Expectations About Palliative Treatment for Symptomatic Spinal Metastases: A Qualitative Study.

OBJECTIVES: Patients with spinal metastases often receive palliative surgery or radiation therapy to maintain or improve health-related quality of life. Patients with unrealistic expectations regarding treatment outcomes have been shown to be less satisfied with their post-treatment health status. This study evaluated expectations of patients with spinal metastases scheduled for surgery and/or radiation therapy. METHODS: Individual semistructured interviews were conducted with patients with symptomatic spinal metastases before and 6 weeks after surgery and/or radiation therapy. Expectations regarding treatment outcomes were discussed before treatment, and level of fulfillment of these pretreatment expectations was discussed after treatment. Interviews were recorded, transcribed and analyzed according to the thematic analysis method to identify themes. RESULTS: Before treatment, patients thought they were not, or minimally, informed about (expected) treatment outcomes, but they felt well informed about treatment procedures and possible complications. Although patients expected pain relief and improvement in daily functioning, they found it difficult to describe any recovery timeline or the impact of these expected improvements on their daily life. Patients generally understood that treatment was not curative, but lacked insight into the impact of treatment on life expectancy given that this was hardly discussed by their surgeon and/or radiation oncologist. Pretreatment expectations regarding pain and daily functioning were only partially met in most patients post-treatment. CONCLUSIONS: Patients thought they were not, or only minimally, informed about expected outcomes after surgery and/or radiation therapy for symptomatic spinal metastases. Improvements in patient-physician communication and counseling could help guide patients toward realistic pretreatment expectations.

Does the Presence of Missing Data Affect the Performance of the SORG Machine-learning Algorithm for Patients With Spinal Metastasis? Development of an Internet Application Algorithm.

BACKGROUND: The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA) was developed to predict the survival of patients with spinal metastasis. The algorithm was successfully tested in five international institutions using 1101 patients from different continents. The incorporation of 18 prognostic factors strengthens its predictive ability but limits its clinical utility because some prognostic factors might not be clinically available when a clinician wishes to make a prediction. QUESTIONS/PURPOSES: We performed this study to (1) evaluate the SORG-MLA's performance with data and (2) develop an internet-based application to impute the missing data. METHODS: A total of 2768 patients were included in this study. The data of 617 patients who were treated surgically were intentionally erased, and the data of the other 2151 patients who were treated with radiotherapy and medical treatment were used to impute the artificially missing data. Compared with those who were treated nonsurgically, patients undergoing surgery were younger (median 59 years [IQR 51 to 67 years] versus median 62 years [IQR 53 to 71 years]) and had a higher proportion of patients with at least three spinal metastatic levels (77% [474 of 617] versus 72% [1547 of 2151]), more neurologic deficit (normal American Spinal Injury Association [E] 68% [301 of 443] versus 79% [1227 of 1561]), higher BMI (23 kg/m2 [IQR 20 to 25 kg/m2] versus 22 kg/m2 [IQR 20 to 25 kg/m2]), higher platelet count (240 × 103/µL [IQR 173 to 327 × 103/µL] versus 227 × 103/µL [IQR 165 to 302 × 103/µL], higher lymphocyte count (15 × 103/µL [IQR 9 to 21× 103/µL] versus 14 × 103/µL [IQR 8 to 21 × 103/µL]), lower serum creatinine level (0.7 mg/dL [IQR 0.6 to 0.9 mg/dL] versus 0.8 mg/dL [IQR 0.6 to 1.0 mg/dL]), less previous systemic therapy (19% [115 of 617] versus 24% [526 of 2151]), fewer Charlson comorbidities other than cancer (28% [170 of 617] versus 36% [770 of 2151]), and longer median survival. The two patient groups did not differ in other regards. These findings aligned with our institutional philosophy of selecting patients for surgical intervention based on their level of favorable prognostic factors such as BMI or lymphocyte counts and lower levels of unfavorable prognostic factors such as white blood cell counts or serum creatinine level, as well as the degree of spinal instability and severity of neurologic deficits. This approach aims to identify patients with better survival outcomes and prioritize their surgical intervention accordingly. Seven factors (serum albumin and alkaline phosphatase levels, international normalized ratio, lymphocyte and neutrophil counts, and the presence of visceral or brain metastases) were considered possible missing items based on five previous validation studies and clinical experience. Artificially missing data were imputed using the missForest imputation technique, which was previously applied and successfully tested to fit the SORG-MLA in validation studies. Discrimination, calibration, overall performance, and decision curve analysis were applied to evaluate the SORG-MLA's performance. The discrimination ability was measured with an area under the receiver operating characteristic curve. It ranges from 0.5 to 1.0, with 0.5 indicating the worst discrimination and 1.0 indicating perfect discrimination. An area under the curve of 0.7 is considered clinically acceptable discrimination. Calibration refers to the agreement between the predicted outcomes and actual outcomes. An ideal calibration model will yield predicted survival rates that are congruent with the observed survival rates. The Brier score measures the squared difference between the actual outcome and predicted probability, which captures calibration and discrimination ability simultaneously. A Brier score of 0 indicates perfect prediction, whereas a Brier score of 1 indicates the poorest prediction. A decision curve analysis was performed for the 6-week, 90-day, and 1-year prediction models to evaluate their net benefit across different threshold probabilities. Using the results from our analysis, we developed an internet-based application that facilitates real-time data imputation for clinical decision-making at the point of care. This tool allows healthcare professionals to efficiently and effectively address missing data, ensuring that patient care remains optimal at all times. RESULTS: Generally, the SORG-MLA demonstrated good discriminatory ability, with areas under the curve greater than 0.7 in most cases, and good overall performance, with up to 25% improvement in Brier scores in the presence of one to three missing items. The only exceptions were albumin level and lymphocyte count, because the SORG-MLA's performance was reduced when these two items were missing, indicating that the SORG-MLA might be unreliable without these values. The model tended to underestimate the patient survival rate. As the number of missing items increased, the model's discriminatory ability was progressively impaired, and a marked underestimation of patient survival rates was observed. Specifically, when three items were missing, the number of actual survivors was up to 1.3 times greater than the number of expected survivors, while only 10% discrepancy was observed when only one item was missing. When either two or three items were omitted, the decision curves exhibited substantial overlap, indicating a lack of consistent disparities in performance. This finding suggests that the SORG-MLA consistently generates accurate predictions, regardless of the two or three items that are omitted. We developed an internet application (https://sorg-spine-mets-missing-data-imputation.azurewebsites.net/) that allows the use of SORG-MLA with up to three missing items. CONCLUSION: The SORG-MLA generally performed well in the presence of one to three missing items, except for serum albumin level and lymphocyte count (which are essential for adequate predictions, even using our modified version of the SORG-MLA). We recommend that future studies should develop prediction models that allow for their use when there are missing data, or provide a means to impute those missing data, because some data are not available at the time a clinical decision must be made. CLINICAL RELEVANCE: The results suggested the algorithm could be helpful when a radiologic evaluation owing to a lengthy waiting period cannot be performed in time, especially in situations when an early operation could be beneficial. It could help orthopaedic surgeons to decide whether to intervene palliatively or extensively, even when the surgical indication is clear.

The Skeletal Oncology Research Group Machine Learning Algorithm (SORG-MLA) for predicting prolonged postoperative opioid prescription after total knee arthroplasty: an international validation study using 3,495 patients from a Taiwanese cohort.

BACKGROUND: Preoperative prediction of prolonged postoperative opioid use (PPOU) after total knee arthroplasty (TKA) could identify high-risk patients for increased surveillance. The Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) has been tested internally while lacking external support to assess its generalizability. The aims of this study were to externally validate this algorithm in an Asian cohort and to identify other potential independent factors for PPOU. METHODS: In a tertiary center in Taiwan, 3,495 patients receiving TKA from 2010-2018 were included. Baseline characteristics were compared between the external validation cohort and the original developmental cohorts. Discrimination (area under receiver operating characteristic curve [AUROC] and precision-recall curve [AUPRC]), calibration, overall performance (Brier score), and decision curve analysis (DCA) were applied to assess the model performance. A multivariable logistic regression was used to evaluate other potential prognostic factors. RESULTS: There were notable differences in baseline characteristics between the validation and the development cohort. Despite these variations, the SORG-MLA ( https://sorg-apps.shinyapps.io/tjaopioid/ ) remained its good discriminatory ability (AUROC, 0.75; AUPRC, 0.34) and good overall performance (Brier score, 0.029; null model Brier score, 0.032). The algorithm could bring clinical benefit in DCA while somewhat overestimating the probability of prolonged opioid use. Preoperative acetaminophen use was an independent factor to predict PPOU (odds ratio, 2.05). CONCLUSIONS: The SORG-MLA retained its discriminatory ability and good overall performance despite the different pharmaceutical regulations. The algorithm could be used to identify high-risk patients and tailor personalized prevention policy.

Diffuse idiopathic skeletal hyperostosis is associated with incident stroke in patients with increased cardiovascular risk.

OBJECTIVES: Earlier retrospective studies have suggested a relation between DISH and cardiovascular disease, including myocardial infarction. The present study assessed the association between DISH and incidence of cardiovascular events and mortality in patients with high cardiovascular risk. METHODS: In this prospective cohort study, we included 4624 patients (mean age 58.4 years, 69.6% male) from the Second Manifestations of ARTerial disease cohort. The main end point was major cardiovascular events (MACE: stroke, myocardial infarction and vascular death). Secondary endpoints included all-cause mortality and separate vascular events. Cause-specific proportional hazard models were used to evaluate the risk of DISH on all outcomes, and subdistribution hazard models were used to evaluate the effect of DISH on the cumulative incidence. All models were adjusted for age, sex, body mass index, blood pressure, diabetes, non-HDL cholesterol, packyears, renal function and C-reactive protein. RESULTS: DISH was present in 435 (9.4%) patients. After a median follow-up of 8.7 (IQR 5.0-12.0) years, 864 patients had died and 728 patients developed a MACE event. DISH was associated with an increased cumulative incidence of ischaemic stroke. After adjustment in cause-specific modelling, DISH remained significantly associated with ischaemic stroke (HR 1.55; 95% CI: 1.01, 2.38), but not with MACE (HR 0.99; 95% CI: 0.79, 1.24), myocardial infarction (HR 0.88; 95% CI: 0.59, 1.31), vascular death (HR 0.94; 95% CI: 0.68, 1.27) or all-cause mortality (HR 0.94; 95% CI: 0.77, 1.16). CONCLUSION: The presence of DISH is independently associated with an increased incidence and risk for ischaemic stroke, but not with MACE, myocardial infarction, vascular death or all-cause mortality.

The preoperative machine learning algorithm for extremity metastatic disease can predict 90-day and 1-year survival: An external validation study.

BACKGROUND: The prediction of survival is valuable to optimize treatment of metastatic long-bone disease. The Skeletal Oncology Research Group (SORG) machine-learning (ML) algorithm has been previously developed and internally validated. The purpose of this study was to determine if the SORG ML algorithm accurately predicts 90-day and 1-year survival in an external metastatic long-bone disease patient cohort. METHODS: A retrospective review of 264 patients who underwent surgery for long-bone metastases between 2003 and 2019 was performed. Variables used in the stochastic gradient boosting SORG algorithm were age, sex, primary tumor type, visceral/brain metastases, systemic therapy, and 10 preoperative laboratory values. Model performance was calculated by discrimination, calibration, and overall performance. RESULTS: The SORG ML algorithms retained good discriminative ability (area under the cure [AUC]: 0.83; 95% confidence interval [CI]: 0.76-0.88 for 90-day mortality and AUC: 0.84; 95% CI: 0.79-0.88 for 1-year mortality), calibration, overall performance, and decision curve analysis. CONCLUSION: The previously developed ML algorithms demonstrated good performance in the current study, thereby providing external validation. The models were incorporated into an accessible application (https://sorg-apps.shinyapps.io/extremitymetssurvival/) that may be freely utilized by clinicians in helping predict survival for individual patients and assist in informative decision-making discussion before operative management of long bone metastatic lesions.

International Validation of the SORG Machine-learning Algorithm for Predicting the Survival of Patients with Extremity Metastases Undergoing Surgical Treatment.

BACKGROUND: The Skeletal Oncology Research Group machine-learning algorithms (SORG-MLAs) estimate 90-day and 1-year survival in patients with long-bone metastases undergoing surgical treatment and have demonstrated good discriminatory ability on internal validation. However, the performance of a prediction model could potentially vary by race or region, and the SORG-MLA must be externally validated in an Asian cohort. Furthermore, the authors of the original developmental study did not consider the Eastern Cooperative Oncology Group (ECOG) performance status, a survival prognosticator repeatedly validated in other studies, in their algorithms because of missing data. QUESTIONS/PURPOSES: (1) Is the SORG-MLA generalizable to Taiwanese patients for predicting 90-day and 1-year mortality? (2) Is the ECOG score an independent factor associated with 90-day and 1-year mortality while controlling for SORG-MLA predictions? METHODS: All 356 patients who underwent surgery for long-bone metastases between 2014 and 2019 at one tertiary care center in Taiwan were included. Ninety-eight percent (349 of 356) of patients were of Han Chinese descent. The median (range) patient age was 61 years (25 to 95), 52% (184 of 356) were women, and the median BMI was 23 kg/m2 (13 to 39 kg/m2). The most common primary tumors were lung cancer (33% [116 of 356]) and breast cancer (16% [58 of 356]). Fifty-five percent (195 of 356) of patients presented with a complete pathologic fracture. Intramedullary nailing was the most commonly performed type of surgery (59% [210 of 356]), followed by plate screw fixation (23% [81 of 356]) and endoprosthetic reconstruction (18% [65 of 356]). Six patients were lost to follow-up within 90 days; 30 were lost to follow-up within 1 year. Eighty-five percent (301 of 356) of patients were followed until death or for at least 2 years. Survival was 82% (287 of 350) at 90 days and 49% (159 of 326) at 1 year. The model's performance metrics included discrimination (concordance index [c-index]), calibration (intercept and slope), and Brier score. In general, a c-index of 0.5 indicates random guess and a c-index of 0.8 denotes excellent discrimination. Calibration refers to the agreement between the predicted outcomes and the actual outcomes, with a perfect calibration having an intercept of 0 and a slope of 1. The Brier score of a prediction model must be compared with and ideally should be smaller than the score of the null model. A decision curve analysis was then performed for the 90-day and 1-year prediction models to evaluate their net benefit across a range of different threshold probabilities. A multivariate logistic regression analysis was used to evaluate whether the ECOG score was an independent prognosticator while controlling for the SORG-MLA's predictions. We did not perform retraining/recalibration because we were not trying to update the SORG-MLA algorithm in this study. RESULTS: The SORG-MLA had good discriminatory ability at both timepoints, with a c-index of 0.80 (95% confidence interval 0.74 to 0.86) for 90-day survival prediction and a c-index of 0.84 (95% CI 0.80 to 0.89) for 1-year survival prediction. However, the calibration analysis showed that the SORG-MLAs tended to underestimate Taiwanese patients' survival (90-day survival prediction: calibration intercept 0.78 [95% CI 0.46 to 1.10], calibration slope 0.74 [95% CI 0.53 to 0.96]; 1-year survival prediction: calibration intercept 0.75 [95% CI 0.49 to 1.00], calibration slope 1.22 [95% CI 0.95 to 1.49]). The Brier score of the 90-day and 1-year SORG-MLA prediction models was lower than their respective null model (0.12 versus 0.16 for 90-day prediction; 0.16 versus 0.25 for 1-year prediction), indicating good overall performance of SORG-MLAs at these two timepoints. Decision curve analysis showed SORG-MLAs provided net benefits when threshold probabilities ranged from 0.40 to 0.95 for 90-day survival prediction and from 0.15 to 1.0 for 1-year prediction. The ECOG score was an independent factor associated with 90-day mortality (odds ratio 1.94 [95% CI 1.01 to 3.73]) but not 1-year mortality (OR 1.07 [95% CI 0.53 to 2.17]) after controlling for SORG-MLA predictions for 90-day and 1-year survival, respectively. CONCLUSION: SORG-MLAs retained good discriminatory ability in Taiwanese patients with long-bone metastases, although their actual survival time was slightly underestimated. More international validation and incremental value studies that address factors such as the ECOG score are warranted to refine the algorithms, which can be freely accessed online at https://sorg-apps.shinyapps.io/extremitymetssurvival/. LEVEL OF EVIDENCE: Level III, therapeutic study.

Translation and validation of the Dutch Spine Oncology Study Group Outcomes Questionnaire (SOSGOQ2.0) to evaluate health-related quality of life in patients with symptomatic spinal metastases.

BACKGROUND: The primary goal of palliative treatment of spinal metastases is to maintain or improve health-related quality of life (HRQOL). We translated and validated a Dutch version of The Spine Oncology Study Group Outcome Questionnaire (SOSGOQ2.0), a valid and reliable 20-item questionnaire to evaluate HRQOL in patients with spinal metastases. METHODS: After cross-cultural translation and adaptation, the questionnaire was pre-tested in fifteen patients referred for spine surgery and/or radiotherapy. This resulted in a final questionnaire that was sent to patients for assessment of internal consistency, construct (i.e., convergent and divergent) validity, discriminative power and test-retest reliability. RESULTS: Overall, 147 patients (mean age 65.6 years, SD = 10.4) completed the questionnaire after a median time of 45.4 months (IQR = 18.9-72.9) after spine surgery and/or radiotherapy. Internal consistency was good for the Physical function, Pain, and Mental health domains (α = 0.87, 0.86, 0.72), but not for Social function (α = 0.04). Good convergent validity was demonstrated except for Social function (rs = 0.37 95%CI = 0.21-0.51). Discriminative power between patients with ECOG performance scores of 0-1 and 2-4 was found on all domains and Neurological function items. Test-retest reliability was acceptable for Physical function, Pain and Mental health (ICC = 0.89 95%CI = 0.81-0.94, ICC = 0.88 95%CI = 0.78-0.93, ICC = 0.68 95%CI = 0.48-0.81), whereas ICC = 0.45 (95%CI = 0.17-0.66) for Social function was below threshold. After removing item 20 from the Social function domain, internal consistency improved, and convergent validity and test-retest reliability were good. CONCLUSION: The Dutch version of the SOSGOQ2.0 questionnaire is a reliable and valid tool to measure HRQOL in patients with spinal metastases. Item 20 was removed to retain psychometric properties.

Expectations of treatment outcomes in patients with spinal metastases; what do we tell our patients? A qualitative study.

BACKGROUND: Realistic pre-treatment expectations are important and have been associated with post-treatment health related quality of life (HRQOL). Patient expectations are greatly influenced by physicians, as they are the primary resource for information. This study aimed to explore the communication practices of physicians regarding treatment outcomes for patients with spinal metastases, and physician experiences with patients' pre-treatment expectations. METHODS: An international qualitative study using semi-structured interviews with physicians routinely involved in treating metastatic spine disease (spine surgeons, radiation and medical oncologists, and rehabilitation specialists) was conducted. Physicians were interviewed about the content and extent of information they provide to patients with spinal metastases regarding treatment options, risks and treatment outcomes. Interviews were transcribed verbatim and analyzed using a thematic coding network. RESULTS: After 22 interviews data saturation occurred. The majority of the physicians indicated that they currently do not establish patients' pre-treatment expectations, despite acknowledging the importance of these expectations. Spine surgeons often believe that patient expectations are disproportionate. Physicians expressed they manage expectations by detailing the most common risks and providing a broad but nonspecific overview of treatment outcomes. While the palliative intent seems clear to the physicians, their perception is that the implications of a palliative treatment remains elusive to most patients. CONCLUSION: This study highlights the current gap in patient-physician communication regarding expectations of treatment outcomes of patients with spinal metastases. These results warrant further research to improve communication practices and determine the effect of patient expectations on patient reported outcomes in this population.

Diffuse Idiopathic Skeletal Hyperostosis (DISH) and a Possible Inflammatory Component.

PURPOSE OF REVIEW: Diffuse Idiopathic Skeletal Hyperostosis (DISH) is considered a metabolic condition, characterized by new bone formation affecting mainly at entheseal sites. Enthesitis and enthesopathies occur not only in the axial skeleton but also at some peripheral sites, and they resemble to some extent the enthesitis that is a cardinal feature in spondyloarthritis (SpA), which is an inflammatory disease. RECENT FINDINGS: We review the possible non-metabolic mechanism such as inflammation that may also be involved at some stage and help promote new bone formation in DISH. We discuss supporting pathogenic mechanisms for a local inflammation at sites typically affected by this disease, and that is also supported by imaging studies that report some similarities between DISH and SpA. Local inflammation, either primary or secondary to metabolic derangements, may contribute to new bone formation in DISH. This new hypothesis is expected to stimulate further research in both the metabolic and inflammatory pathways in order to better understand the mechanisms that lead to new bone formation. This may lead to development of measures that will help in earlier detection and effective management before damage occurs.

Do Cohabitants Reliably Complete Questionnaires for Patients in a Terminal Cancer Stage when Assessing Quality of Life, Pain, Depression, and Anxiety?

BACKGROUND: Patients with bone metastases often are unable to complete quality of life (QoL) questionnaires, and cohabitants (such as spouses, domestic partners, offspring older than 18 years, or other people who live with the patient) could be a reliable alternative. However, the extent of reliability in this complicated patient population remains undefined, and the influence of the cohabitant's condition on their assessment of the patient's QoL is unknown. QUESTIONS/PURPOSES: (1) Do QoL scores, measured by the 5-level EuroQol-5D (EQ-5D-5L) version and the Patient-reported Outcomes Measurement Information System (PROMIS) version 1.0 in three domains (anxiety, pain interference, and depression), reported by patients differ markedly from scores as assessed by their cohabitants? (2) Do cohabitants' PROMIS-Depression scores correlate with differences in measured QoL results? METHODS: This cross-sectional study included patients and cohabitants older than 18 years of age. Patients included those with presence of histologically confirmed bone metastases (including lymphoma and multiple myeloma), and cohabitants must have been present at the clinic visit. Patients were eligible for inclusion in the study regardless of comorbidities, prognosis, prior surgery, or current treatment. Between June 1, 2016 and March 1, 2017 and between October 1, 2017 and February 26, 2018, all 96 eligible patients were approached, of whom 49% (47) met the selection criteria and were willing to participate. The included 47 patient-cohabitant pairs independently completed the EQ-5D-5L and the eight-item PROMIS for three domains (anxiety, pain, and depression) with respect to the patients' symptoms. The cohabitants also completed the four-item PROMIS-Depression survey with respect to their own symptoms. RESULTS: There were no clinically important differences between the scores of patients and their cohabitants for all questionnaires, and the agreement between patient and cohabitant scores was moderate to strong (Spearman correlation coefficients ranging from 0.52 to 0.72 on the four questionnaires; all p values < 0.05). However, despite the good agreement in QoL scores, an increased cohabitant's depression score was correlated with an overestimation of the patient's symptom burden for the anxiety and depression domains (weak Spearman correlation coefficient of 0.33 [95% confidence interval 0.08 to 0.58]; p = 0.01 and moderate Spearman correlation coefficient of 0.52 [95% CI 0.29 to 0.74]; p < 0.01, respectively). CONCLUSION: The present findings support that cohabitants might be reliable raters of the QoL of patients with bone metastases. However, if a patient's cohabitant has depression, the cohabitant may overestimate a patient's symptoms in emotional domains such as anxiety and depression, warranting further research that includes cohabitants with and without depression to elucidate the effect of depression on the level of agreement. For now, clinicians may want to reconsider using the cohabitant's judgement if depression is suspected. CLINICAL RELEVANCE: These findings suggest that a cohabitant's impressions of a patient's quality of life are, in most instances, accurate; this is potentially helpful in situations where the patient cannot weigh in. Future studies should employ longitudinal designs to see how or whether our findings change over time and with disease progression, and how specific interventions-like different chemotherapeutic regimens or surgery-may factor in.

Wide range of applications for machine-learning prediction models in orthopedic surgical outcome: a systematic review.

Background and purpose - Advancements in software and hardware have enabled the rise of clinical prediction models based on machine learning (ML) in orthopedic surgery. Given their growing popularity and their likely implementation in clinical practice we evaluated which outcomes these new models have focused on and what methodologies are being employed.Material and methods - We performed a systematic search in PubMed, Embase, and Cochrane Library for studies published up to June 18, 2020. Studies reporting on non-ML prediction models or non-orthopedic outcomes were excluded. After screening 7,138 studies, 59 studies reporting on 77 prediction models were included. We extracted data regarding outcome, study design, and reported performance metrics.Results - Of the 77 identified ML prediction models the most commonly reported outcome domain was medical management (17/77). Spinal surgery was the most commonly involved orthopedic subspecialty (28/77). The most frequently employed algorithm was neural networks (42/77). Median size of datasets was 5,507 (IQR 635-26,364). The median area under the curve (AUC) was 0.80 (IQR 0.73-0.86). Calibration was reported for 26 of the models and 14 provided decision-curve analysis.Interpretation - ML prediction models have been developed for a wide variety of topics in orthopedics. Topics regarding medical management were the most commonly studied. Heterogeneity between studies is based on study size, algorithm, and time-point of outcome. Calibration and decision-curve analysis were generally poorly reported.

Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review.

Background and purpose - External validation of machine learning (ML) prediction models is an essential step before clinical application. We assessed the proportion, performance, and transparent reporting of externally validated ML prediction models in orthopedic surgery, using the Transparent Reporting for Individual Prognosis or Diagnosis (TRIPOD) guidelines.Material and methods - We performed a systematic search using synonyms for every orthopedic specialty, ML, and external validation. The proportion was determined by using 59 ML prediction models with only internal validation in orthopedic surgical outcome published up until June 18, 2020, previously identified by our group. Model performance was evaluated using discrimination, calibration, and decision-curve analysis. The TRIPOD guidelines assessed transparent reporting.Results - We included 18 studies externally validating 10 different ML prediction models of the 59 available ML models after screening 4,682 studies. All external validations identified in this review retained good discrimination. Other key performance measures were provided in only 3 studies, rendering overall performance evaluation difficult. The overall median TRIPOD completeness was 61% (IQR 43-89), with 6 items being reported in less than 4/18 of the studies.Interpretation - Most current predictive ML models are not externally validated. The 18 available external validation studies were characterized by incomplete reporting of performance measures, limiting a transparent examination of model performance. Further prospective studies are needed to validate or refute the myriad of predictive ML models in orthopedics while adhering to existing guidelines. This ensures clinicians can take full advantage of validated and clinically implementable ML decision tools.

Clinical, radiological, and patient-reported outcomes 13 years after pedicle screw fixation with balloon-assisted endplate reduction and cement injection.

PURPOSE: In management of traumatic thoracolumbar burst fractures, short-segment pedicle screw fixation with balloon-assisted endplate reduction (BAER) and cement injection is a safe, feasible, and effective technique to maintain radiological alignment with minimum spinal segments involved. However, 20% of patients report daily discomfort despite good spinal alignment and fusion after this technique. This study provides clinical, radiological, and patient-reported outcomes after a minimum 13 years of follow-up. METHODS: Eighteen patients were invited at the outpatient clinic for clinical/radiological examinations. The cohort (originally 20 patients) was treated 13-14 years earlier with pedicle screw fixation, BAER, and cement injection for traumatic thoracolumbar burst fractures. Patient-reported outcome measures were obtained at time of examinations. Current data were compared with data obtained at 6 years of follow-up. RESULTS: Seventeen patients (median age 50; range 32-80) cooperated. No/minimal back pain was reported by 15 patients, and 12 patients returned to their previous heavy labor work. Median visual analog score of health (80%; 50-100%) was similar to results at 6 years (80%; 60-100% p = 0.259). An Oswestry Disability Index score of less than 20% (reflecting minimal disability) was reported by 14 patients, compared with 15 patients at 6 years of follow-up. No significant differences were found in wedge or Cobb angle between the time points. Intravertebral cement resorption was not observed. CONCLUSION: Results from this study suggest that, 13 years after pedicle screw fixation with BAER and cement injection for traumatic thoracolumbar burst fractures, functional performance, pain and radiological outcomes of the current cohort were stable or had slightly improved. These slides can be retrieved under Electronic Supplementary Material.

The importance of timely treatment for quality of life and survival in patients with symptomatic spinal metastases.

PURPOSE: A major challenge in metastatic spinal disease is timely identification of patients. Left untreated, spinal metastases may lead to gross mechanical instability and/or neurological deficits, often requiring extensive invasive surgical treatment. The aim of this cohort study was to assess the correlation between delayed treatment of patients with spinal metastases and functional performance, quality of life and survival. METHODS: All patients surgically treated for metastatic spinal disease at a tertiary care facility were included for analysis. Patients who underwent elective surgery were considered as timely treated, whereas patients requiring emergency surgery were considered to be treated in a delayed fashion. EQ-5D scores, KPS scores and mortality rates were compared between the two groups. RESULTS: A total of 317 patients (215 timely treated, 102 delayed) had survivorship data available and 202 patients (147 timely treated, 55 delayed) had clinical data available. Multivariate analyses showed delayed treatment was associated with lower EQ-5D and KPS scores and higher mortality rates, independent of confounders such as baseline EQ-5D/KPS scores, neurological status, tumor prognosis and patient age. CONCLUSIONS: The results from the present study show delayed treatment of patients with symptomatic spinal metastases has both direct and indirect adverse consequences for functional performance status, quality of life and survival. Optimization of referral pattern may accelerate the time to surgical treatment, potentially leading to better quality of life and survival.

Does Artificial Intelligence Outperform Natural Intelligence in Interpreting Musculoskeletal Radiological Studies? A Systematic Review.

BACKGROUND: Machine learning (ML) is a subdomain of artificial intelligence that enables computers to abstract patterns from data without explicit programming. A myriad of impactful ML applications already exists in orthopaedics ranging from predicting infections after surgery to diagnostic imaging. However, no systematic reviews that we know of have compared, in particular, the performance of ML models with that of clinicians in musculoskeletal imaging to provide an up-to-date summary regarding the extent of applying ML to imaging diagnoses. By doing so, this review delves into where current ML developments stand in aiding orthopaedists in assessing musculoskeletal images. QUESTIONS/PURPOSES: This systematic review aimed (1) to compare performance of ML models versus clinicians in detecting, differentiating, or classifying orthopaedic abnormalities on imaging by (A) accuracy, sensitivity, and specificity, (B) input features (for example, plain radiographs, MRI scans, ultrasound), (C) clinician specialties, and (2) to compare the performance of clinician-aided versus unaided ML models. METHODS: A systematic review was performed in PubMed, Embase, and the Cochrane Library for studies published up to October 1, 2019, using synonyms for machine learning and all potential orthopaedic specialties. We included all studies that compared ML models head-to-head against clinicians in the binary detection of abnormalities in musculoskeletal images. After screening 6531 studies, we ultimately included 12 studies. We conducted quality assessment using the Methodological Index for Non-randomized Studies (MINORS) checklist. All 12 studies were of comparable quality, and they all clearly included six of the eight critical appraisal items (study aim, input feature, ground truth, ML versus human comparison, performance metric, and ML model description). This justified summarizing the findings in a quantitative form by calculating the median absolute improvement of the ML models compared with clinicians for the following metrics of performance: accuracy, sensitivity, and specificity. RESULTS: ML models provided, in aggregate, only very slight improvements in diagnostic accuracy and sensitivity compared with clinicians working alone and were on par in specificity (3% (interquartile range [IQR] -2.0% to 7.5%), 0.06% (IQR -0.03 to 0.14), and 0.00 (IQR -0.048 to 0.048), respectively). Inputs used by the ML models were plain radiographs (n = 8), MRI scans (n = 3), and ultrasound examinations (n = 1). Overall, ML models outperformed clinicians more when interpreting plain radiographs than when interpreting MRIs (17 of 34 and 3 of 16 performance comparisons, respectively). Orthopaedists and radiologists performed similarly to ML models, while ML models mostly outperformed other clinicians (outperformance in 7 of 19, 7 of 23, and 6 of 10 performance comparisons, respectively). Two studies evaluated the performance of clinicians aided and unaided by ML models; both demonstrated considerable improvements in ML-aided clinician performance by reporting a 47% decrease of misinterpretation rate (95% confidence interval [CI] 37 to 54; p < 0.001) and a mean increase in specificity of 0.048 (95% CI 0.029 to 0.068; p < 0.001) in detecting abnormalities on musculoskeletal images. CONCLUSIONS: At present, ML models have comparable performance to clinicians in assessing musculoskeletal images. ML models may enhance the performance of clinicians as a technical supplement rather than as a replacement for clinical intelligence. Future ML-related studies should emphasize how ML models can complement clinicians, instead of determining the overall superiority of one versus the other. This can be accomplished by improving transparent reporting, diminishing bias, determining the feasibility of implantation in the clinical setting, and appropriately tempering conclusions. LEVEL OF EVIDENCE: Level III, diagnostic study.

How good are the outcomes of instrumented debulking operations for symptomatic spinal metastases and how long do they stand? A subgroup analysis in the global spine tumor study group database.

BACKGROUND: The benefits of surgery for symptomatic spinal metastases have been demonstrated, largely based on series of patients undergoing debulking and instrumentation operations. However, as cancer treatments improve and overall survival lengths increase, the incidence of recurrent spinal cord compression after debulking may increase. The aim of the current paper is to document the postoperative evolution of neurological function, pain, and quality of life following debulking and instrumentation in the Global Spine Tumor Study Group (GSTSG) database. METHODS: The GSTSG database is a prospective multicenter data repository of consecutive patients that underwent surgery for a symptomatic spinal metastasis. For the present analysis, patients were selected from the database that underwent decompressive debulking surgery with instrumentation. Preoperative tumor type, Tomita and Tokuhashi scores, EQ-5D, Frankel, Karnofsky, and postoperative complications, survival, EQ-5D, Frankel, Karnofsky, and pain numeric rating scores (NRS) at 3, 6, 12, and 24 months were analyzed. RESULTS: A total of 914 patients underwent decompressive debulking surgery with instrumentation and had documented follow-up until death or until 2 years post surgery. Median preoperative Karnofsky performance index was 70. A total of 656 patients (71.8%) had visceral metastases and 490 (53.6%) had extraspinal bone metastases. Tomita scores were evenly distributed above (49.1%) and below or equal to 5 (50.9%), and Tokuhashi scores almost evenly distributed below or equal to 8 (46.3%) and above 8 (53.7%). Overall, 12-month survival after surgery was 56.3%. The surgery resulted in EQ-5D health status improvement and NRS pain reduction that was maintained throughout follow-up. Frankel scores improved at first follow-up in 25.0% of patients, but by 12 months neurological deterioration was observed in 18.8%. CONCLUSION: We found that palliative debulking and instrumentation surgeries were performed throughout all Tomita and Tokuhashi categories. These surgeries reduced pain scores and improved quality of life up to 2 years after surgery. After initial improvement, a proportion of patients experienced neurological deterioration by 1 year, but the majority of patients remained stable.

Criteria for Early-Phase Diffuse Idiopathic Skeletal Hyperostosis: Development and Validation.

Background Diffuse idiopathic skeletal hyperostosis (DISH) is a condition characterized by the formation of new bone along the anterolateral spinal column at four adjacent vertebral bodies. Purpose To propose and validate criteria for the early phase of DISH by using CT data from two large-scale retrospective cohorts, each with 5-year follow-up. Materials and Methods For this retrospective study, CT data at baseline and follow-up in 1367 patients (cohort I) from 2004 to 2011 were evaluated by two observers to define no DISH, early-stage DISH, and definite DISH on the basis of interval development of consecutive complete or incomplete bone bridges. An independent group of 2267 participants from the COPDGene cohort from 2008 to 2016 was used to validate the early DISH criteria (cohort II). The sensitivity and specificity of early DISH criteria were based on findings in the last CT study as the reference standard by using a nested case-control design. κ Values were calculated between seven readers and with a 3-month interval for one reader. Results Cohort I consisted of 100% men, with a mean age of 60.0 years ± 5.6 (standard deviation) and a mean time between baseline and follow-up CT of 5.0 years ± 1.1. Cohort II consisted of 51% men, with a mean age of 59.9 years ± 8.6 and a mean time between baseline and follow-up CT of 5.4 years ± 0.5. In the derivation cohort, 55 patients comprised the early DISH group. Early DISH was defined as the presence of a spinal segment with a complete bone bridge with an adjacent segment of at least a near-complete bone bridge and another adjacent segment with at least the presence of newly formed bone or when three or more adjacent segments were recorded as showing a near-complete bone bridge. In the validation cohort, sensitivity for early DISH (vs no DISH) was 96% (99 of 103 participants; 95% confidence interval [CI]: 90%, 99%). The corresponding specificity was 83% (1695 of 2034 participants; 95% CI: 82%, 85%). The Fleiss κ for interrater reliability was 0.78 (95% CI: 0.77, 0.78), and the κ for intrarater reliability was 0.89 (95% CI: 0.82, 0.96). Conclusion Early diffuse idiopathic skeletal hyperostosis (DISH) criteria had high sensitivity and specificity for predicting the development of DISH. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Block in this issue.

Simultaneous occurrence of ankylosing spondylitis and diffuse idiopathic skeletal hyperostosis: a systematic review.

Objectives: AS and DISH are both spinal ankylosing conditions with a 4-fold increased risk of spinal fractures. The most commonly used criteria for DISH were designed to exclude radiographic signs of spondyloarthritis. However, case reports describing the presence of both conditions exist. In this study, the co-occurrence of AS and DISH were reviewed in the literature to explore the potential need to revise the criteria for DISH. Methods: A search was conducted in Pubmed, Embase, Web of Science and the Cochrane library using the terms 'spondyloarthritis' and 'DISH' and their matching synonyms. Full-text articles describing the coexistence of both conditions in the same patient were included. A quality assessment was performed, and the case descriptions were extracted. Results: Twenty articles describing simultaneous occurrence of AS and DISH in 39 cases were retrieved. All articles were case reports or series of moderate quality. Back or neck pain was present in 97% of the patients (mean age 61.2 years, 90% male) and HLA-B27 was positive in 9/27 documented measurements. Radiographic abnormalities were described in the SI joint (82% AS, 13% DISH) and in the spine (49% AS, 100% DISH). Conclusion: Simultaneous occurrence of AS and DISH has been reported in the literature in at least 39 cases. AS and DISH should not be seen as mutually exclusive. If the results of the current study are confirmed in a large observational study, revision of the current criteria to include the co-existence of both conditions should be considered.

Prospective Evaluation of the Relationship Between Mechanical Stability and Response to Palliative Radiotherapy for Symptomatic Spinal Metastases.

BACKGROUND: A substantial number of patients with spinal metastases experience no treatment effect from palliative radiotherapy. Mechanical spinal instability, due to metastatic disease, could be associated with failed pain control following radiotherapy. This study investigates the relationship between the degree of spinal instability, as defined by the Spinal Instability Neoplastic Score (SINS), and response to radiotherapy in patients with symptomatic spinal metastases in a multi-institutional cohort. METHODS AND MATERIALS: The SINS of 155 patients with painful thoracic, lumbar, or lumbosacral metastases from two tertiary hospitals was calculated using images from radiotherapy planning CT scans. Patient-reported pain response, available for 124 patients, was prospectively assessed. Pain response was categorized, according to international guidelines, as complete, partial, indeterminate, or progression of pain. The association between SINS and pain response was estimated by multivariable logistic regression analysis, correcting for predetermined clinical variables. RESULTS: Of the 124 patients, 16 patients experienced a complete response and 65 patients experienced a partial response. Spinal Instability Neoplastic Score was associated with a complete pain response (adjusted odds-radio [ORadj] 0.78; 95% confidence interval [CI] 0.62-0.98), but not with an overall pain response (ORadj 0.94; 95% CI 0.81-1.10). CONCLUSIONS: A lower SINS, indicating spinal stability, is associated with a complete pain response to radiotherapy. This supports the hypothesis that pain resulting from mechanical spinal instability responds less well to radiotherapy compared with pain from local tumor activity. No association could be determined between SINS and an overall pain response, which might indicate that this referral tool is not yet optimal for prediction of treatment outcome. IMPLICATIONS FOR PRACTICE: Patients with stable painful spinal metastases, as indicated by a Spinal Instability Neoplastic Score (SINS) of 6 or lower, can effectively be treated with palliative external beam radiotherapy. The majority of patients with (impending) spinal instability, as indicated by a SINS score of 7 or higher, will achieve a (partial) response after palliative radiotherapy; however, some patients might require surgical intervention. Therefore, it is recommended to refer patients with a SINS score of 7 or higher to a spine surgeon to evaluate the need for surgical intervention.