Validation of Ten Osteoporosis Screening Tools in Rural Communities of Taiwan.

PURPOSE: Patients with osteoporosis are at risk of fractures, which can lead to immobility and reduced quality of life. Early diagnosis and treatment are crucial for preventing fractures, but many patients are not diagnosed until after a fracture has occurred. This study aimed to evaluate the performance of 10 osteoporosis screening tools (OSTs) in rural communities of Taiwan. In this prospective study, a total of 567 senior citizens from rural communities underwent bone mineral density (BMD) measurement using dual-energy X-ray absorptiometry (DXA) and ten OSTs were administered. Discrimination analysis was performed using the area under the receiver operating characteristic curve (AUROC). Primary outcomes included area under curve (AUC) value, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). The DXA examination revealed that 63.0% of females and 22.4% of males had osteoporosis. Among females, Osteoporosis Index of Risk (OSIRIS) and Osteoporosis Self-Assessment Tool for Asians (OSTA) presented the best AUC value with 0.71 (0.66-0.76) and 0.70 (0.66-0.75), respectively. Among males, BWC had the best AUC value of 0.77 (0.67-0.86), followed by OSTA, Simple Calculated Osteoporosis Risk Estimation (SCORE), and OSIRIS. OSTA and OSIRIS showed acceptable performance in both genders. The specificity of Fracture Risk Assessment Tool (FRAX-H), SCORE, National Osteoporosis Foundation Score, OSIRIS, Osteoporosis Risk Assessment Instrument, Age, Bulk, One or Never Estrogen (ABONE), and Body weight criteria increased in both genders after applying the optimum cut-off. Considering it high AUC and simplicity of use, OSTA appeared to be the recommended tool for seniors of both genders among the ten OSTs. This study provides a viable reference for future development of OSTs in Taiwan. Further adjustment according to epidemiological data and risk factors is recommended while applying OSTs to different cohorts.

Factors associated with skeletal-related events in patients with bone metastatic melanoma: A retrospective study of 481 patients.

OBJECTIVES: Metastatic bone disease is estimated to develop in up to 17% of patients with melanoma, compromising skeleton integrity resulting in skeletal-related events (SREs), which impair quality of life and reduce survival. The objective of the study was to investigate (1) the proportion of melanoma patients developing SREs following diagnosis of bone metastasis and (2) the predictors for SREs in this patient cohort. METHODS: Four hundred and eighty-one patients with bone metastatic melanoma from two tertiary centers in the United States from 2008 to 2018 were included. The primary outcome was 90-day and 1-year occurrence of a SRE, including pathological fractures of bones, cord compression, hypercalcemia, radiotherapy, and surgery. Fine-Gray regression analysis was performed for overall SREs and pathological fracture, with death as a competing risk. RESULTS: By 1-year, 52% (258/481) of patients experienced SREs, and 28% (137/481) had a pathological fracture. At 90-day, lytic lesions, bone pain, elevated calcium and absolute lymphocyte, and decreased albumin and hemoglobin were associated with higher SRE risk. The same factors, except for decreased hemoglobin, were shown to predict development of SREs at 1-year. CONCLUSION: The high incidence of SREs and pathological fractures warrants vigilance using the identified factors in this study and preventative measures during clinical oncological care.

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.

Are Current Survival Prediction Tools Useful When Treating Subsequent Skeletal-related Events From Bone Metastases?

BACKGROUND: Bone metastasis in advanced cancer is challenging because of pain, functional issues, and reduced life expectancy. Treatment planning is complex, with consideration of factors such as location, symptoms, and prognosis. Prognostic models help guide treatment choices, with Skeletal Oncology Research Group machine-learning algorithms (SORG-MLAs) showing promise in predicting survival for initial spinal metastases and extremity metastases treated with surgery or radiotherapy. Improved therapies extend patient lifespans, increasing the risk of subsequent skeletal-related events (SREs). Patients experiencing subsequent SREs often suffer from disease progression, indicating a deteriorating condition. For these patients, a thorough evaluation, including accurate survival prediction, is essential to determine the most appropriate treatment and avoid aggressive surgical treatment for patients with a poor survival likelihood. Patients experiencing subsequent SREs often suffer from disease progression, indicating a deteriorating condition. However, some variables in the SORG prediction model, such as tumor histology, visceral metastasis, and previous systemic therapies, might remain consistent between initial and subsequent SREs. Given the prognostic difference between patients with and without a subsequent SRE, the efficacy of established prognostic models-originally designed for individuals with an initial SRE-in addressing a subsequent SRE remains uncertain. Therefore, it is crucial to verify the model's utility for subsequent SREs. QUESTION/PURPOSE: We aimed to evaluate the reliability of the SORG-MLAs for survival prediction in patients undergoing surgery or radiotherapy for a subsequent SRE for whom both the initial and subsequent SREs occurred in the spine or extremities. METHODS: We retrospectively included 738 patients who were 20 years or older who received surgery or radiotherapy for initial and subsequent SREs at a tertiary referral center and local hospital in Taiwan between 2010 and 2019. We excluded 74 patients whose initial SRE was in the spine and in whom the subsequent SRE occurred in the extremities and 37 patients whose initial SRE was in the extremities and the subsequent SRE was in the spine. The rationale was that different SORG-MLAs were exclusively designed for patients who had an initial spine metastasis and those who had an initial extremity metastasis, irrespective of whether they experienced metastatic events in other areas (for example, a patient experiencing an extremity SRE before his or her spinal SRE would also be regarded as a candidate for an initial spinal SRE). Because these patients were already validated in previous studies, we excluded them in case we overestimated our result. Five patients with malignant primary bone tumors and 38 patients in whom the metastasis's origin could not be identified were excluded, leaving 584 patients for analysis. The 584 included patients were categorized into two subgroups based on the location of initial and subsequent SREs: the spine group (68% [399]) and extremity group (32% [185]). No patients were lost to follow-up. Patient data at the time they presented with a subsequent SRE were collected, and survival predictions at this timepoint were calculated using the SORG-MLAs. Multiple imputation with the Missforest technique was conducted five times to impute the missing proportions of each predictor. The effectiveness of SORG-MLAs was gauged through several statistical measures, including discrimination (measured by the area under the receiver operating characteristic curve [AUC]), calibration, overall performance (Brier score), and decision curve analysis. Discrimination refers to the model's ability to differentiate between those with the event and those without the event. An AUC ranges from 0.5 to 1.0, with 0.5 indicating the worst discrimination and 1.0 indicating perfect discrimination. An AUC of 0.7 is considered clinically acceptable discrimination. Calibration is the comparison between the frequency of observed events and the predicted probabilities. In an ideal calibration, the observed and predicted survival rates should be congruent. The logarithm of observed-to-expected survival ratio [log(O:E)] offers insight into the model's overall calibration by considering the total number of observed (O) and expected (E) events. The Brier score measures the mean squared difference between the predicted probability of possible outcomes for each individual and the observed outcomes, ranging from 0 to 1, with 0 indicating perfect overall performance and 1 indicating the worst performance. Moreover, the prevalence of the outcome should be considered, so a null-model Brier score was also calculated by assigning a probability equal to the prevalence of the outcome (in this case, the actual survival rate) to each patient. The benefit of the prediction model is determined by comparing its Brier score with that of the null model. If a prediction model's Brier score is lower than the null model's Brier score, the prediction model is deemed as having good performance. A decision curve analysis was performed for models to evaluate the "net benefit," which weighs the true positive rate over the false positive rate against the "threshold probabilities," the ratio of risk over benefit after an intervention was derived based on a comprehensive clinical evaluation and a well-discussed shared-decision process. A good predictive model should yield a higher net benefit than default strategies (treating all patients and treating no patients) across a range of threshold probabilities. RESULTS: For the spine group, the algorithms displayed acceptable AUC results (median AUCs of 0.69 to 0.72) for 42-day, 90-day, and 1-year survival predictions after treatment for a subsequent SRE. In contrast, the extremity group showed median AUCs ranging from 0.65 to 0.73 for the corresponding survival periods. All Brier scores were lower than those of their null model, indicating the SORG-MLAs' good overall performances for both cohorts. The SORG-MLAs yielded a net benefit for both cohorts; however, they overestimated 1-year survival probabilities in patients with a subsequent SRE in the spine, with a median log(O:E) of -0.60 (95% confidence interval -0.77 to -0.42). CONCLUSION: The SORG-MLAs maintain satisfactory discriminatory capacity and offer considerable net benefits through decision curve analysis, indicating their continued viability as prediction tools in this clinical context. However, the algorithms overestimate 1-year survival rates for patients with a subsequent SRE of the spine, warranting consideration of specific patient groups. Clinicians and surgeons should exercise caution when using the SORG-MLAs for survival prediction in these patients and remain aware of potential mispredictions when tailoring treatment plans, with a preference for less invasive treatments. Ultimately, this study emphasizes the importance of enhancing prognostic algorithms and developing innovative tools for patients with subsequent SREs as the life expectancy in patients with bone metastases continues to improve and healthcare providers will encounter these patients more often in daily practice. LEVEL OF EVIDENCE: Level III, prognostic study.

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

BACKGROUND: Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. QUESTIONS/PURPOSES: (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? METHODS: Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. RESULTS: Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. CONCLUSION: Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. LEVEL OF EVIDENCE: Level III, diagnostic study.

Comparing long and intermediate-length plates for metastatic bone disease of the proximal humerus: A retrospective analysis.

AIMS: Managing proximal humerus pathologic fractures requires strategic planning to ensure optimal patient outcomes. Traditionally, fixation of the humerus using long devices has been considered the standard of care, but emerging evidence has challenged this approach. This study aimed to compare long plates (LPs) and intermediate-length plates (IPs) in this clinical context. METHODS: Forty-four patients with proximal humerus metastatic bone disease were retrospectively studied from 2013 to 2019, with 11 (25%) receiving long plates (LPs) and 33 (75%) intermediate-length plates (IPs). Outcomes included tumor progression, reoperation rates, postoperative anemia, blood loss, operation time, and hospitalization duration. Tumor progression was classified into three categories, with Type III progression (new metastatic lesions in the distal humerus) theoretically benefiting most from whole bone stabilization. RESULTS: Tumor progression occurred in three patients (7%), all of them was in IPs. No revision surgery was needed to address these tumor progressions, including one type III progression which occurred 34 months postoperatively after IP surgery. IP were associated with a reduced operation time compared with LP (median, 1.5 h [IQR, 1.2-1.9] vs. 2.4 [IQR, 1.7-2.5]; p = 0.004). No differences were found for the other perioperative outcomes. CONCLUSIONS: Our findings reveal a low incidence of tumor progression and low reoperation rates in both groups. The shortened operative time associated with IP use suggests its particular suitability for patients with limited life expectancy. Further research is needed to elucidate the ideal prosthesis length that best balances the risks and benefits when addressing proximal humerus metastatic disease.

Heterotopic Ossification of Bilateral Hips Post-COVID-19 and Prolonged Immobilization: A Case Report.

CASE: A 43-year-old healthy man developed hip pain post-coronavirus disease 2019 (COVID-19) immobilization. Imaging confirmed bilateral bridging heterotopic ossification (HO) of the hips, Brooker Class IV. Bilateral HO caused functional arthrodesis (45° flexion: -20° internal rotation). Bilateral HO resection resulted in almost full mobility at 1-year follow-up (90° flexion; 30° internal rotation). CONCLUSION: Many cases of HO after immobilization for COVID-19 have been reported, but as far as we know, this is the first case report describing surgical intervention as an adequate treatment option for severe restricted mobility caused by HO due to COVID-19-induced prolonged immobilization. Caution and preoperative 3D planning are recommended of HO formation near neurovascular structures.

Incidence, Risk Factors, and Survival of Bone Metastases and Skeletal-Related Events in Melanoma Patients: A Systematic Review and Quality Assessment of 29 Studies.

Background: Skeletal metastases make up 17% of all metastases from advanced-stage melanoma. Bone metastases are associated with increased morbidity and mortality and decreased quality of life due to their association with skeletal-related events (SREs), including pathological fracture, spinal cord compression, hypercalcemia, radiotherapy, and surgery. The study aimed to determine the incidence of bone metastases and SREs in melanoma, identify possible risk factors for the development of bone metastases and SREs, and investigate survival rates in this patient population. Methods: A computer-based literature search was conducted using Pubmed, Embase, and Cochrane Central Register of Controlled Trials up to July 2023. The Newcastle-Ottawa Quality Assessment Scale (NOS) was utilized for quality assessment. Study characteristics, patient information, risk factors for developing bone metastases and SREs, and characteristics for survival were recorded. Results: We included 29 studies. The average bone metastasis-free interval ranged from four to 72 months. Incidence of bone metastases varied from 2 % to 49 % across 14 studies. 69 % (20/29) of studies described the location of bone metastases, with 24 % (7/29) focusing solely on spinal metastases. In one study, 129 SREs were recorded in 71 % (59/83) of the patient cohort, with various manifestations. The use of bone-directed agents was independently associated with lower risk of SREs. Survival after detection of bone metastasis ranged from three to 13 months. Factors associated with survival included clinical, tumor-related, and treatment features. Conclusion: This review highlights the notable prevalence and risk factors of developing bone metastases and subsequent SREs in patients with melanoma. The surge in bone metastases poses a challenge in complication management, given the high prevalence of SREs. While this study offers a comprehensive overview of the incidence, risk factors, and outcomes associated with bone metastases and SREs in melanoma patients that may guide patient and physician decision-making, a notable gap lies in the limited availability of high-quality data and the heterogeneous design of the existing literature. Future research should address predictive factors for bone metastases and SREs in melanoma to facilitate patient and physician decision-making and ultimately improve outcomes in this patient population.

Survival in Patients With Spinal Metastatic Disease Treated Nonoperatively With Radiotherapy: Are the SORG-ML Algorithms Relevant?

SUMMARY OF BACKGROUND DATA: The SORG-ML algorithms for survival in spinal metastatic disease were developed in patients who underwent surgery and were externally validated for patients managed operatively. OBJECTIVE: To externally validate the SORG-ML algorithms for survival in spinal metastatic disease in patients managed nonoperatively with radiation. STUDY DESIGN: Retrospective cohort. METHODS: The performance of the SORG-ML algorithms was assessed by discrimination [receiver operating curves and area under the receiver operating curve (AUC)], calibration (calibration plots), decision curve analysis, and overall performance (Brier score). The primary outcomes were 90-day and 1-year mortality. RESULTS: Overall, 2074 adult patients underwent radiation for spinal metastatic disease and 29% (n=521) and 59% (n=917) had 90-day and 1-year mortality, respectively. On complete case analysis (n=415), the AUC was 0.76 (95% CI: 0.71-0.80) and 0.78 (95% CI: 0.73-0.83) for 90-day and 1-year mortality with fair calibration and positive net benefit confirmed by the decision curve analysis. With multiple imputation (n=2074), the AUC was 0.85 (95% CI: 0.83-0.87) and 0.87 (95% CI: 0.85-0.89) for 90-day and 1-year mortality with fair calibration and positive net benefit confirmed by the decision curve analysis. CONCLUSION: The SORG-ML algorithms for survival in spinal metastatic disease generalize well to patients managed nonoperatively with radiation.

Psoas muscle area is an independent survival prognosticator in patients undergoing surgery for long-bone metastases.

BACKGROUND: Predictive analytics is gaining popularity as an aid to treatment planning for patients with bone metastases, whose expected survival should be considered. Decreased psoas muscle area (PMA), a morphometric indicator of suboptimal nutritional status, has been associated with mortality in various cancers, but never been integrated into current survival prediction algorithms (SPA) for patients with skeletal metastases. This study investigates whether decreased PMA predicts worse survival in patients with extremity metastases and whether incorporating PMA into three modern SPAs (PATHFx, SORG-NG, and SORG-MLA) improves their performance. METHODS: One hundred eighty-five patients surgically treated for long-bone metastases between 2014 and 2019 were divided into three PMA tertiles (small, medium, and large) based on their psoas size on CT. Kaplan-Meier, multivariable regression, and Cox proportional hazards analyses were employed to compare survival between tertiles and examine factors associated with mortality. Logistic regression analysis was used to assess whether incorporating adjusted PMA values enhanced the three SPAs' discriminatory abilities. The clinical utility of incorporating PMA into these SPAs was evaluated by decision curve analysis (DCA). RESULTS: Patients with small PMA had worse 90-day and 1-year survival after surgery (log-rank test p < 0.001). Patients in the large PMA group had a higher chance of surviving 90 days (odds ratio, OR, 3.72, p = 0.02) and 1 year than those in the small PMA group (OR 3.28, p = 0.004). All three SPAs had increased AUC after incorporation of adjusted PMA. DCA indicated increased net benefits at threshold probabilities >0.5 after the addition of adjusted PMA to these SPAs. CONCLUSIONS: Decreased PMA on CT is associated with worse survival in surgically treated patients with extremity metastases, even after controlling for three contemporary SPAs. Physicians should consider the additional prognostic value of PMA on survival in patients undergoing consideration for operative management due to extremity metastases.

Opportunistic CT for Prediction of Adverse Postoperative Events in Patients with Spinal Metastases.

The purpose of this study was to assess the value of body composition measures obtained from opportunistic abdominal computed tomography (CT) in order to predict hospital length of stay (LOS), 30-day postoperative complications, and reoperations in patients undergoing surgery for spinal metastases. 196 patients underwent CT of the abdomen within three months of surgery for spinal metastases. Automated body composition segmentation and quantifications of the cross-sectional areas (CSA) of abdominal visceral and subcutaneous adipose tissue and abdominal skeletal muscle was performed. From this, 31% (61) of patients had postoperative complications within 30 days, and 16% (31) of patients underwent reoperation. Lower muscle CSA was associated with increased postoperative complications within 30 days (OR [95% CI] = 0.99 [0.98-0.99], p = 0.03). Through multivariate analysis, it was found that lower muscle CSA was also associated with an increased postoperative complication rate after controlling for the albumin, ASIA score, previous systemic therapy, and thoracic metastases (OR [95% CI] = 0.99 [0.98-0.99], p = 0.047). LOS and reoperations were not associated with any body composition measures. Low muscle mass may serve as a biomarker for the prediction of complications in patients with spinal metastases. The routine assessment of muscle mass on opportunistic CTs may help to predict outcomes in these patients.

Remineralization Rate of Lytic Lesions of the Spine in Multiple Myeloma Patients Undergoing Radiation Therapy.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: In general, Multiple Myeloma (MM) patients are treated with systemic therapy including chemotherapy. Radiation therapy can have an important supportive role in the palliative management of MM-related osteolytic lesions. Our study aims to investigate the degree of radiation-induced remineralization in MM patients to gain a better understanding of its potential impact on bone mineral density and, consequently, fracture prevention. Our primary outcome measure was percent change in bone mineral density measured in Hounsfield Units (Δ% HU) between pre- and post-radiation measurements, compared to non-targeted vertebrae. METHODS: We included 119 patients with MM who underwent radiotherapy of the spine between January 2010 and June 2021 and who had a CT scan of the spine at baseline and between 3-24 months after radiation. A linear mixed effect model tested any differences in remineralization rate per month (ßdifference) between targeted and non-targeted vertebrae. RESULTS: Analyses of CT scans yielded 565 unique vertebrae (366 targeted and 199 non-targeted vertebrae). In both targeted and non-targeted vertebrae, there was an increase in bone density per month (ßoverall = .04; P = .002) with the largest effect being between 9-18 months post-radiation. Radiation did not cause a greater increase in bone density per month compared to non-targeted vertebrae (ßdifference = .67; P = .118). CONCLUSION: Our results demonstrate that following radiation, bone density increased over time for both targeted and non-targeted vertebrae. However, no conclusive evidence was found that targeted vertebrae have a higher remineralization rate than non-targeted vertebrae in patients with MM.

Systematic review of machine-learning models in orthopaedic trauma.

Aims: Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool. Methods: A systematic search screening 3,252 studies identified 45 ML-based prediction models in orthopaedic trauma up to January 2023. The TRIPOD statement assessed transparent reporting and the PROBAST tool the risk of bias. Results: A total of 40 studies reported on training and internal validation; four studies performed both development and external validation, and one study performed only external validation. The most commonly reported outcomes were mortality (33%, 15/45) and length of hospital stay (9%, 4/45), and the majority of prediction models were developed in the hip fracture population (60%, 27/45). The overall median completeness for the TRIPOD statement was 62% (interquartile range 30 to 81%). The overall risk of bias in the PROBAST tool was low in 24% (11/45), high in 69% (31/45), and unclear in 7% (3/45) of the studies. High risk of bias was mainly due to analysis domain concerns including small datasets with low number of outcomes, complete-case analysis in case of missing data, and no reporting of performance measures. Conclusion: The results of this study showed that despite a myriad of potential clinically useful applications, a substantial part of ML studies in orthopaedic trauma lack transparent reporting, and are at high risk of bias. These problems must be resolved by following established guidelines to instil confidence in ML models among patients and clinicians. Otherwise, there will remain a sizeable gap between the development of ML prediction models and their clinical application in our day-to-day orthopaedic trauma practice.