External Validation of PATHFx Version 3.0 in Patients Treated Surgically and Nonsurgically for Symptomatic Skeletal Metastases

What Factors Are Associated With Implant Revision in the Treatment of Pathologic Subtrochanteric Femur Fractures?

BACKGROUND

Limiting reoperation or revision after operative stabilization or endoprosthetic reconstruction of a pathologic subtrochanteric femur fracture reduces morbidity, but how best to achieve this remains controversial. Endoprosthetic reconstruction offers durable mechanical stability but may not be most appropriate in patients who are frail or who are not expected to survive more than a few months. For that reason, cumulative incidence survival (looking at the endpoint of reoperation or revision with death as a competing risk) and factors associated with revision after surgical stabilization or reconstruction-both of which remain poorly characterized to date-would help surgeons make better decisions on behalf of these patients.

QUESTIONS/PURPOSES

We analyzed patients who were operatively treated for pathologic subtrochanteric femur fracture, and we asked: (1) What is the cumulative incidence of reoperation and revision at 3 months, 1 year, and 2 years after surgery for pathologic subtrochanteric femur fracture in patients undergoing each treatment type with death as a competing risk? (2) What are the factors associated with implant revision after operative treatment of pathologic subtrochanteric femur fracture? (3) What is the overall survival of patients in this population after surgery? (4) How do clinical and surgical factors along with the frequency of complications compare in this population by operative treatment?

METHODS

Between January 2000 and December 2020, 422 patients underwent surgery for completed proximal femur pathologic fractures. After excluding patients with non-subtrochanteric femur fractures (71% [301]), fractures caused by primary tumors of bone (< 1% [2]), and insufficient data (1% [6]), we included 113 patients who underwent operative treatment of completed pathologic subtrochanteric femur fractures. Our study period spanned 20 years because although implant trends may have shifted, the overall operative objective for pathologic subtrochanteric femur fractures-restoring function and alleviating pain, regardless of the extent of bony union-have remained relatively unchanged during this period. Median follow-up time was 6 months (range 1 month to 20.6 years). Intramedullary nailing (IMN) was performed in 68% (77) of patients, proximal femur replacement (PFR) was performed in 19% (22), and open reduction and internal fixation (ORIF) was performed in 12% (14) of patients. IMN was performed in patients with a poor prognosis but in whom fracture stabilization was felt to be advantageous. In instances of complex fractures in which adequate reduction could not be achieved, ORIF was generally performed. PFR was generally performed in patients with a better prognosis in which long-term implant survival and patient function were prioritized. We found a higher proportion of women in the IMN group (73% versus 32% in PFR and 50% in ORIF; p = 0.001). Rapid growth tumors (Katagiri classification) were found in 25% of patients with IMN, 27% with PFR, and 43% with ORIF. The primary outcome was the cumulative incidence of reoperation or revision surgery after initial stabilization. Competing risk analysis with death as a competing event was performed to estimate the cumulative incidence for reoperation and revision. Factors associated with revision surgery were identified using the Cox proportional hazards model, which rendered HRs. All analyses were adjusted to control for potential confounders.

RESULTS

The cumulative incidence for reoperation at 2 years was 5% (95% confidence interval [CI] 4% to 6%) for IMN, 15% (95% CI 9% to 22%) for PFR, and 32% (95% CI 15% to 50%) for ORIF (p = 0.03). The cumulative incidence for revision at 2 years was 4% (95% CI 3% to 4%) for IMN, 4% (95% CI 2% to 6%) for PFR, and 33% (95% CI 15% to 51%) for ORIF (p = 0.01). Factors associated with revision surgery were radioresistant tumor histology (HR 8.5 [95% CI 1.2 to 58.9]; p = 0.03) and ORIF (HR 6.3 [95% CI 1.5 to 27.0]; p = 0.01). The 3-month, 1-year, and 2-year overall survival was 80% (95% CI 71% to 87%), 35% (95% CI 26% to 45%), and 28% (95% CI 19% to 36%), respectively. Thirty-day postoperative complications did not differ by fixation type, but 90-day readmission was highest after ORIF (3 of 14 versus 4 of 22 in PFR and 4% [3 of 77] in IMN; p = 0.03) Periprosthetic joint infection (PJI) was more common after salvage PFR (2 of 6) than primary PFR (1 of 22) (p = 0.04).

CONCLUSION

Primary PFR may be preferred for pathologic subtrochanteric femur fractures arising from radioresistant tumor types, as the cumulative incidence of revision was no different than for IMN while restoring function, alleviating pain, and offering local tumor control, and it less commonly develops PJI than salvage PFR. In complex fractures not amenable to IMN, surgeons should consider performing a PFR over ORIF because of the lower risk of revision and the added benefit of replacing the pathologic fracture altogether and offering immediate mechanical stability with a cemented endoprosthesis. Future studies might evaluate the extent of bone loss from local tumor burden, and this could be quantified and analyzed in future studies as a covariate as it may clarify when PFR is advantageous in this population.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Management of metastatic bone disease of the pelvis: current concepts

PURPOSE

Metastatic disease of the pelvis is frequently associated with severe pain and impaired ambulatory function. Depending on the patient's characteristics, primary tumor, and metastatic pelvic disease, the treatment choice may be varied. This study aims to report on the current management options of metastatic pelvic disease.

METHODS

We comprehensively researched multiple databases and evaluated essential studies about current concepts of managing a metastatic bone disease of the pelvis, focusing on specific indications as well as on the result of treatment.

RESULTS

Pelvic metastases not in the periacetabular region can be managed with modification of weight-bearing, analgesics, bisphosphonates, chemotherapy and/or radiotherapy. Minimally invasive approaches include radiofrequency ablation, cryoablation, embolization, percutaneous osteoplasty, and percutaneous screw placement. Pathological or impending periacetabular fracture, excessive periacetabular bone defect, radioresistant tumor, and persistent debilitating pain despite non-surgical treatment and/or minimally invasive procedures can be managed with different surgical techniques. Overall, treatment can be divided into nonoperative, minimally invasive, and operative based on specific indications, the expectations of the patient and the lesion.

CONCLUSION

Different treatment modalities exist to manage metastatic pelvic bone disease. Decision-making for the most appropriate treatment should be made with a multidisciplinary approach based on a case-by-case basis.

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.

Machine Learning-Assisted Decision Making in Orthopaedic Oncology

» Artificial intelligence is an umbrella term for computational calculations that are designed to mimic human intelligence and problem-solving capabilities, although in the future, this may become an incomplete definition. Machine learning (ML) encompasses the development of algorithms or predictive models that generate outputs without explicit instructions, assisting in clinical predictions based on large data sets. Deep learning is a subset of ML that utilizes layers of networks that use various inter-relational connections to define and generalize data.» ML algorithms can enhance radiomics techniques for improved image evaluation and diagnosis. While ML shows promise with the advent of radiomics, there are still obstacles to overcome.» Several calculators leveraging ML algorithms have been developed to predict survival in primary sarcomas and metastatic bone disease utilizing patient-specific data. While these models often report exceptionally accurate performance, it is crucial to evaluate their robustness using standardized guidelines.» While increased computing power suggests continuous improvement of ML algorithms, these advancements must be balanced against challenges such as diversifying data, addressing ethical concerns, and enhancing model interpretability.

Life Expectancy After Treatment of Metastatic Bone Disease: An International Trend Analysis

INTRODUCTION

The decision to treat metastatic bone disease (MBD) surgically depends in part on patient life expectancy. We are unaware of an international analysis of how life expectancy among these patients has changed over time. Therefore, we asked (1) how has the life expectancy for patients treated for MBD changed over time, and (2) which, if any, of the common primary cancer types are associated with longer survival after treatment of MBD?

METHODS

We reviewed data collected from 2000 to 2022 in an international MBD database, as well as data used for survival model validation. We included 3,353 adults who underwent surgery and/or radiation. No patients were excluded. Patients were grouped by treatment date into period 1 (2000 to 2009), period 2 (2010 to 2019), and period 3 (2020 to 2022). Cumulative survival was portrayed using Kaplan-Meier curves; log-rank tests were used to determine significance at P < 0.05. Subgroup analyses by primary cancer diagnosis were performed.

RESULTS

Median survival in period 2 was longer than in period 1 ( P < 0.001). Median survival (at which point 50% of patients survived) had not been reached for period 3. Median survival was longer in period 2 for all cancer types ( P < 0.001) except thyroid. Only lung cancer reached median survival in period 3, which was longer compared with periods 1 and 2 ( P < 0.001). Slow-growth, moderate-growth, and rapid-growth tumors all demonstrated longer median survival from period 1 to period 2; only rapid-growth tumors reached median survival for period 3, which was longer compared with periods 1 and 2 ( P < 0.001).

DISCUSSION

Median duration of survival after treatment of MBD has increased, which was a consistent finding in nearly all cancer types. Longer survival is likely attributable to improvements in both medical and surgical treatments. As life expectancy for patients with MBD increases, surgical methods should be selected with this in mind.

LEVEL OF EVIDENCE

VI.

Reoperation after surgery for bone metastasis of renal cell carcinoma

BACKGROUND AND OBJECTIVE

The prognosis of metastatic renal cell carcinoma (RCC) has markedly improved with the advent of molecular targeted therapies and immune checkpoint inhibitors. However, the therapeutic response in patients with bone metastasis remains low; therefore, surgery still plays a significant role in treatment of bone metastasis. It is important to maintain quality of life for patients with bone metastasis from RCC and avoid reoperation after surgery for bone metastasis. Therefore, we investigated the risk factors for reoperation after surgery in patients with bone metastasis from RCC.

METHODS

We retrospectively studied 103 bones of 97 patients who underwent surgery for bone metastasis of RCC from 2001 to 2023 at our institutions.

RESULTS

Reoperation was performed in 10 (9.7%) of 103 bones. There was no correlation between reoperation-free survival and any of the following variables: preoperative and postoperative radiotherapy, site of bone metastasis, indication for surgery (solitary bone metastasis or impending or pathologic fractures), surgical method (intramedullary nailing fixation, curettage, or en bloc resection), preoperative embolization, or survival.

CONCLUSION

The risk of reoperation for bone metastasis of RCC does not appear to be based on the surgical method.

Artificial Intelligence in Bone Metastasis Imaging: Recent Progresses from Diagnosis to Treatment - A Narrative Review

The introduction of artificial intelligence (AI) represents an actual revolution in the radiological field, including bone lesion imaging. Bone lesions are often detected both in healthy and oncological patients and the differential diagnosis can be challenging but decisive, because it affects the diagnostic and therapeutic process, especially in case of metastases. Several studies have already demonstrated how the integration of AI-based tools in the current clinical workflow could bring benefits to patients and to healthcare workers. AI technologies could help radiologists in early bone metastases detection, increasing the diagnostic accuracy and reducing the overdiagnosis and the number of unnecessary deeper investigations. In addition, radiomics and radiogenomics approaches could go beyond the qualitative features, visible to the human eyes, extrapolating cancer genomic and behavior information from imaging, in order to plan a targeted and personalized treatment. In this article, we want to provide a comprehensive summary of the most promising AI applications in bone metastasis imaging and their role from diagnosis to treatment and prognosis, including the analysis of future challenges and new perspectives.

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/m 2 [IQR 20 to 25 kg/m 2 ] versus 22 kg/m 2 [IQR 20 to 25 kg/m 2 ]), higher platelet count (240 × 10 3 /µL [IQR 173 to 327 × 10 3 /µL] versus 227 × 10 3 /µL [IQR 165 to 302 × 10 3 /µL], higher lymphocyte count (15 × 10 3 /µL [IQR 9 to 21× 10 3 /µL] versus 14 × 10 3 /µL [IQR 8 to 21 × 10 3 /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.

Prognostic factors and real-life applicability of prognostic models for patients with bone metastases of carcinoma

OBJECTIVE

This study aimed to investigate the factors affecting the survival of patients with bone carcinoma metastases and assess the clinical applicability of existing prognostic models.

METHODS

We retrospectively evaluated 247 patients who presented to our hospital between 2011 and 2021 diagnosed with bone carcinoma metastasis. Demographic data, general health status, primary diagnoses, laboratory and radiological findings, pathological fracture status, treatment methods, and survival times of the patients were recorded, and the effects of these variables on survival time were evaluated. Previously developed Katagiri, Janssen, 2013-Spring, PathFX, and SORG prognostic models were applied, and the predictive performances of these models were evaluated by comparing the predicted survival time with the actual survival time of our patients.

RESULTS

After the multivariate analysis, the following factors were shown to be significantly associated with the survival time of patients: blood hemoglobin and leukocyte levels, lactate dehydrogenase concentration, prognostic nutritional index, body mass index, performance status, medium and fast-growing groups of primary tumors, presence of extraspinal and visceral or brain metastases, and pathological fractures. According to receiver operating characteristics and Brier scores, SORG had the overall highest performance scores, while the Janssen nomogram had the lowest.

CONCLUSION

Our report showed that all prognostic models were clinically applicable, but their performances varied. Among them, the SORG predictive model had the best performance scores overall and is the model the authors suggested for survival prediction among patients with carcinoma bone metastases.

LEVEL OF EVIDENCE

Level IV, Prognostic Study.

Poor adherence to national guidance in the management of patients with metastatic bone disease

Cite this article: Bone Joint J 2024;106-B(1):6–8.

The Importance of Awaiting Biopsy Results in Solitary Pathological Proximal Femoral Fractures : Do We Need to Biopsy Solitary Pathological Fractures?

BACKGROUND

The optimal surgical treatment for patients presenting with (impending and complete) pathological proximal femoral fractures is predicated on prognosis. Guidelines recommend a preoperative biopsy to exclude sarcomas, however no evidence confirms a benefit.

OBJECTIVE

This study aimed to describe the diagnostic accuracy, morbidity and sarcoma incidence of biopsy results in these patients.

MATERIAL AND METHODS

All patients (n = 153) presenting with pathological proximal femoral fractures between 2000 and 2019 were retrospectively evaluated. Patients after inadvertent surgery (n = 25) were excluded. Descriptive statistics were used to evaluate the accuracy and morbidity of diagnostic biopsies.

RESULTS

Of 112/128 patients who underwent biopsy, nine (8%) biopsies were unreliable either due to being inconclusive (n = 5) or because the diagnosis changed after resection (n = 4). Of impending fractures, 32% fractured following needle core biopsy. Median time from diagnosis to surgery was 30 days (interquartile range 21-46). The overall biopsy positive predictive value (PPV) to differentiate between sarcoma and non-sarcoma was 1.00 (95% confidence interval [CI] 0.88-1.00). In patients with a previous malignancy (n = 24), biopsy (n = 23) identified the diagnosis in 83% (PPV 0.91, 95% CI 0.71-0.99), of whom five (24%) patients had a new diagnosis. In patients without a history of cancer (n = 61), final diagnosis included carcinomas (n = 24, 39.3%), sarcomas (n = 24, 39.3%), or hematological malignancies (n = 13, 21.3%). Biopsy (n = 58) correctly identified the diagnosis in 66% of patients (PPV 0.80, 95% CI 0.67-0.90).

CONCLUSION

This study confirms the importance of a preoperative biopsy in solitary pathological proximal femoral fractures due to the risk of sarcoma in patients with and without a history of cancer. However, biopsy delays the time to definite surgery, results can be inconclusive or false, and it risks completion of impending fractures.

Functional outcomes after open reconstruction or nonoperative management of 81 pathologic acetabular fractures from metastatic bone disease

Background

Pathologic acetabular fracture secondary to skeletal metastasis may result in debilitating pain, inability to ambulate, and impaired quality of life, which may mark the first period of dependent care in cancer patients. Acetabular reconstruction may involve morbid procedures with increased complication rates. This study aimed to evaluate the evolution of pain, performance status, and ambulation following nonoperative management or open reconstruction of pathologic acetabular fractures.

Methods

A retrospective cohort of 2630 adult patients with osseous metastatic disease treated at a high-volume cancer center between 2005 and 2021 was screened for pathologic fractures of the acetabulum. The study outcomes were pain, performance status, and the ability to ambulate. We identified 78 patients (median age, 60 years; 37 female patients [46%]) with 81 fractures. Of these, treatment consisted of open reconstruction (n = 34) or nonoperative management alone (n = 47). The mean follow-up in surviving patients was 3.4 years.

Results

Open reconstruction was performed more frequently for displaced fractures (P < 0.01), Harrington class III or IV acetabula (P < 0.01), and patients with a performance status ≥3 at hospitalization (P = 0.00). Open reconstruction was associated with clinically meaningful improvements in pain (adjusted odds ratio [aOR], 8.3; 95% CI, 1.4-50.6; P = 0.02) and performance status (aOR, 10.9; 95% CI, 1.7-71.0; P = 0.01) at discharge and a restoration of ambulation (aOR, 7.5; 95% CI, 1.9-29.8; P < 0.01) at final follow-up.

Conclusions

In patients with pathologic acetabular fracture due to osseous metastatic disease, functional improvements in pain, performance status, and ambulation were observed following open acetabular reconstruction in carefully selected patients, with no impact on survival, while noninferior improvements were observed in patients receiving nonoperative management when considering their larger clinical context.

Level of evidence

Level III, therapeutic study.

Bone Mass Changes Following Percutaneous Radiofrequency Ablation, Osteoplasty, Reinforcement, and Internal Fixation of Periacetabular Osteolytic Metastases

BACKGROUND

The success of orthopedic interventions for periacetabular osteolytic metastases depends on the progression or regression of cancer-induced bone loss.

PURPOSE

To characterize relative bone mass changes following percutaneous radiofrequency ablation, osteoplasty, cement reinforcement, and internal screw fixation (AORIF).

METHODS

Of 70 patients who underwent AORIF at a single institution, 21 patients (22 periacetabular sites; average follow-up of 18.5 ± 12.3 months) had high-resolution pelvic bone CT scans, with at least one scan within 3 months following their operation (baseline) and a comparative scan at least 6 months post-operatively. In total, 73 CT scans were measured for bone mass changes using Hounsfield Units (HU). A region of interest was defined for the periacetabular area in the coronal, axial, and sagittal reformation planes for all CT scans. For 6-month and 1-year scans, the coronal and sagittal HU were combined to create a weight-bearing HU (wbHU). Three-dimensional volumetric analysis was performed on the baseline and longest available CT scans. Cohort survival was compared to predicted PathFx 3.0 survival.

RESULTS

HU increased from baseline post-operative (1.2 ± 1.1 months) to most recent follow-up (20.2 ± 12.1 months) on coronal (124.0 ± 112.3), axial (140.3 ± 153.0), and sagittal (151.9 ± 162.4), p < 0.05. Grayscale volumetric measurements increased by 173.4 ± 166.4 (p < 0.05). AORIF median survival was 27.7 months (6.0 months PathFx3.0 predicted; p < 0.05). At 12 months, patients with >10% increase in wbHU demonstrated superior median survival of 36.5 months (vs. 26.4 months, p < 0.05).

CONCLUSION

Percutaneous stabilization leads to improvements in bone mass and may allow for delays in extensive open reconstruction procedures.

What are the indications and survivorship of tumor endoprosthetic reconstructions for patients with extremity metastatic bone disease?

BACKGROUND AND OBJECTIVES

Given advances in therapies, endoprosthetic reconstruction (EPR) in metastatic bone disease (MBD) may be increasingly indicated. The objectives were to review the indications, and implant and patient survivorship in patients undergoing EPR for MBD.

METHODS

A review of patients undergoing EPR for extremity MBD between 1992 and 2022 at two centers was performed. Surgical data, implant survival, patient survival, and implant failure modes were examined.

RESULTS

One hundred fifteen patients were included with a median follow-up of 14.9 months (95% confidence interval [CI]: 9.2-19.3) and survival of 19.4 months (95% CI: 13.6-26.1). The most common diagnosis was renal cell carcinoma (34/115, 29.6%) and the most common location was proximal femur (43/115, 37.4%). Indications included: actualized fracture (58/115, 50.4%), impending fracture (30/115, 26.1%), and failed fixation (27/115, 23.5%). Implant failure was uncommon (10/115, 8.7%). Patients undergoing EPR for failed fixation were more likely to have renal or lung cancer (p = 0.006).

CONCLUSIONS

EPRs were performed most frequently for renal cell carcinoma and in patients with a relatively favorable survival. EPR was indicated for failed previous fixation in 23.5% of cases, emphasizing the importance of predictive survival modeling. EPR can be a reliable and durable surgical option for patients with MBD.

Is the association of electrochemotherapy and bone fixation rational in patients with bone metastasis?

BACKGROUND

Bone metastases are frequent in patients with cancer. Electrochemotherapy (ECT) is a minimally invasive treatment based on a high-voltage electric pulse combined with an anticancer drug. Preclinical and clinical studies supported the use of ECT in patients with metastatic bone disease, demonstrating that it does not damage the mineral structure of the bone and its regenerative capacity, and that is feasible and efficient for the treatment of bone metastases. Year 2014 saw the start of a registry of patients with bone metastases treated with ECT, whose data are recorded in a shared database.

QUESTIONS/PURPOSES

(1) Among patients who underwent ECT and internal fixation for bone metastasis, how many experienced a reduction of pain? (2) How many cases showed a radiological response? (3) How many patients presented local or systemic complication after ECT and fixation?

PATIENTS AND METHODS

Patients were treated in Bologna at Rizzoli Orthopaedic Institute between March 2014 and February 2022 and recorded in the REINBONE registry (a shared database protected by security passwords): clinical and radiological information, ECT session, adverse events, response, quality of life indicators, and duration of follow-up were registered. We consider only cases treated with ECT and intramedullary nail during the same surgical session. Patients included in the analysis were 32: 15 males and 17 females, mean age 65 ± 13 years (median 66, range 38-88 years), mean time since diagnosis of primary tumor 6.2 ± 7.0 years (median 2.9, range 0-22 years). Nail was indicated in 13 cases for a pathological fracture in, 19 for an impending fracture. Follow-up was available for 29 patients, as 2 patients were lost to follow-up and 1 was unable to return to controls. Mean follow-up time was 7.7 ± 6.5 months (median 5, range 1-24), and 16 patients (50%) had a follow-up longer than 6 months.

RESULTS

A significant decrease in pain intensity was observed at the mean Visual Numeric Scale after treatment. Bone recovery was observed in 13 patients. The other 16 patients remained without changes, and one presented disease progression. One patient presented a fracture occurrence during the ECT procedure. Among all patients, bone recovery was observed in 13 patients: complete recovery in 1 patient (3%) and partial recovery in 12 patients (41%). The other 16 patients remained without changes, and one presented disease progression. One patient presented a fracture occurrence during the ECT procedure. However, healing was possible with normal fracture callus quality and healing time. No other local or systemic complications were observed.

CONCLUSION

We found that pain levels decreased after treatment in 23 of the 29 cases for a pain relief rate of 79% at final follow-up. Pain is one of the most important indicators of quality of life in patients that undergo palliative treatments. Even if conventional external body radiotherapy is considered a noninvasive treatment, it presents a dose-dependent toxicity. ECT provides a chemical necrosis preserving osteogenic activity and structural integrity of bone trabeculae; this is a crucial difference with other local treatments and allows bone healing in case of pathological fracture. The risk of local progression in our patient population was small, and 44% experienced bone recovery while 53% of the cases remained unchanged. We observe intraoperative fracture in one case. This technique, in selected patients, improves outcome in bone metastatic patients combing both the efficacy of the ECT in the local control of the disease and the mechanical stability with the bone fixation to synergize their benefits. Moreover, the risk of complication is very low. Although encouraging data, comparative studies are required to quantify the real efficacy of the technique. Level of Evidence Level I, therapeutic study.

Percutaneous Ablation, Osteoplasty, Reinforcement, and Internal Fixation for Pain and Ambulatory Function in Periacetabular Osteolytic Malignancies

Background Osteolytic neoplasms to periacetabular bone frequently cause pain and fractures. Immediate recovery is integral to lifesaving ambulatory oncologic care and maintaining quality of life. Yet, open acetabular reconstructive surgeries are associated with numerous complications that delay cancer treatments. Purpose To determine the effectiveness for short- and long-term pain and ambulatory function following percutaneous ablation, osteoplasty, reinforcement, and internal fixation (AORIF) for periacetabular osteolytic neoplasm. Materials and Methods This retrospective observational study evaluated clinical data from 50 patients (mean age, 65 years ± 14 [SD]; 25 men, 25 women) with osteolytic periacetabular metastases or myeloma. The primary outcome of combined pain and ambulatory function index score (range, 1 [bedbound] through 10 [normal ambulation]) was assessed before and after AORIF at 2 weeks and then every 3 months up to 40 months (overall median follow-up, 11 months [IQR, 4-14 months]). Secondary outcomes included Eastern Cooperative Oncology Group (ECOG) score, infection, transfusion, 30-day readmission, mortality, and conversion hip arthroplasty. Serial radiographs and CT images were obtained to assess the hip joint integrity. The paired t test or Wilcoxon signed-rank test and Kaplan-Meier analysis were used to analyze data. Results Mean combined pain and ambulatory function index scores improved from 4.5 ± 2.4 to 7.8 ± 2.1 (P < .001) and median ECOG scores from 3 (IQR, 2-4) to 1 (IQR, 1-2) (P < .001) at the first 2 weeks after AORIF. Of 22 nonambulatory patients, 19 became ambulatory on their first post-AORIF visit. Pain and functional improvement were retained beyond 1 year, up to 40 months after AORIF in surviving patients. No hardware failures, surgical site infections, readmissions, or delays in care were identified following AORIF. Of 12 patients with protrusio acetabuli, one patient required a conversion hemiarthroplasty at 24 months. Conclusion The ablation, osteoplasty, reinforcement, and internal fixation, or AORIF, technique was effective for short- and long-term improvement of pain and ambulatory function in patients with periacetabular osteolytic neoplasm. © RSNA, 2023.

Operative management of metastatic disease of the acetabulum: review of the literature and prevailing concepts

Metastatic disease of the periacetabular region is a common problem in orthopaedic oncology, associated with severe pain, decreased mobility, and substantial decline of the quality of life. Conservative management includes optimisation of pain management, activity modification, and radiation therapy. However, patients with destructive lesions affecting the weight-bearing portion of the acetabulum often require reconstructive surgery to decrease pain and restore mobility. The goal of surgery is to provide an immediately stable and durable construct, allowing immediate postoperative weight-bearing and maintaining functional independence for the remaining lifetime of the patient. A variety of surgical techniques have been reported, most of which are based upon cemented total hip arthroplasty, but also include porous tantalum implants and percutaneous cementoplasty. This review discusses the various reconstructive concepts and options, including their respective indications and outcome. A reconstructive algorithm incorporating different techniques and strategies based upon location and quality of remaining bone is also presented.

Age, sex, primary tumor type and site are associated with mortality after pathological fractures: an observational study of 1453 patients from the Swedish Fracture Register

BACKGROUND

Pathological fractures are challenging in orthopedic surgery and oncology, with implications for the patient's quality of life, mobility and mortality. The efficacy of oncological treatment on life expectancy for cancer patients has improved, but the metastatic pattern for bone metastases and survival is diverse for different tumor types. This study aimed to evaluate survival in relation to age, sex, primary tumor and site of the pathological fractures.

METHODS

All pathological fractures due to cancer between 1 September 2014 and 31 December 2021 were included in this observational study from the Swedish Fracture Register (SFR). Data on age, sex, tumor type, fracture site and mortality were collected.

RESULTS

A total of 1453 patients with pathological fractures were included (48% women, median age 73, range 18-100 years). Unknown primary tumors were the most common primary site (n = 308). The lower extremities were the most common site of pathological fractures. Lung cancer had the shortest median survival of 78 days (range 54-102), and multiple myeloma had the longest median survival of 432 days (range 232-629). The site at the lower extremity had the shortest (187 days, range 162-212), and the spine had the longest survival (386 days, range 211-561). Age, sex, primary type and site of the pathological fractures were all associated with mortality.

INTERPRETATION

Age, sex, primary tumor type and site of pathological fractures were associated with survival. Survival time is short and correlated with primary tumor type, with lung cancer as the strongest negative predictor of survival.

A machine learning-Based model to predict early death among bone metastatic breast cancer patients: A large cohort of 16,189 patients

Purpose: This study aims to develop a prediction model to categorize the risk of early death among breast cancer patients with bone metastases using machine learning models. Methods: This study examined 16,189 bone metastatic breast cancer patients between 2010 and 2019 from a large oncological database in the United States. The patients were divided into two groups at random in a 90:10 ratio. The majority of patients (n = 14,582, 90%) were served as the training group to train and optimize prediction models, whereas patients in the validation group (n = 1,607, 10%) were utilized to validate the prediction models. Four models were introduced in the study: the logistic regression model, gradient boosting tree model, decision tree model, and random forest model. Results: Early death accounted for 17.4% of all included patients. Multivariate analysis demonstrated that older age; a separated, divorced, or widowed marital status; nonmetropolitan counties; brain metastasis; liver metastasis; lung metastasis; and histologic type of unspecified neoplasms were significantly associated with more early death, whereas a lower grade, a positive estrogen receptor (ER) status, cancer-directed surgery, radiation, and chemotherapy were significantly the protective factors. For the purpose of developing prediction models, the 12 variables were used. Among all the four models, the gradient boosting tree had the greatest AUC [0.829, 95% confident interval (CI): 0.802-0.856], and the random forest (0.828, 95% CI: 0.801-0.855) and logistic regression (0.819, 95% CI: 0.791-0.847) models came in second and third, respectively. The discrimination slopes for the three models were 0.258, 0.223, and 0.240, respectively, and the corresponding accuracy rates were 0.801, 0.770, and 0.762, respectively. The Brier score of gradient boosting tree was the lowest (0.109), followed by the random forest (0.111) and logistic regression (0.112) models. Risk stratification showed that patients in the high-risk group (46.31%) had a greater six-fold chance of early death than those in the low-risk group (7.50%). Conclusion: The gradient boosting tree model demonstrates promising performance with favorable discrimination and calibration in the study, and this model can stratify the risk probability of early death among bone metastatic breast cancer patients.

Management of Long Bones Metastatic Disease: Concepts That We All Know but Not Always Remember

Bones are the third most common site of metastatic disease. Treatment is rarely curative; rather, it seeks to control disease progression and palliate symptoms. Imaging evaluation of a patient with symptoms of metastatic bone disease should begin with plain X-rays. Further imaging consists of a combination of (PET)-CT scan and bone scintigraphy. We recommend performing a biopsy after imaging workup has been conducted. Metastatic bone disease is managed with a combination of systemic treatment, radiotherapy (RT), and surgery. External beam RT (EBRT) is used for pain control and postoperatively after fracture stabilization. Single-fraction and multiple-fractions schemes are equally effective achieving pain control. Adequate assessment of fracture risk should guide the decision to stabilize an impending fracture. Despite low specificity, plain X-rays are the first tool to determine risk of impending fractures. CT scan offers a higher positive predictive value and can add diagnostic value. Surgical management depends on the patient's characteristics, tumor type, and location of fracture/bone stock. Fixation options include plate and screw fixation, intramedullary (IM) nailing, and endoprostheses. Despite widespread use, the need for prophylactic stabilization of the entire femur should be individually analyzed in each patient due to higher complication rates of long stems.

Predicting survival of patients with spinal metastatic disease using PathFx 3.0 - A validation study of 668 patients in Sweden

Introduction

PathFx is a computer-based prediction model for estimating survival of patients with bone metastasis. The model has been validated in several studies, but this is the first validation using exclusively patients with spinal metastases.

Research question

Is PathFx 3.0 a tool useful for predicting survival for patients with spinal metastatic disease?

Material and methods

668 patients (67% male, median age 67 years) presenting with spinal metastases at two university hospitals in Sweden 1991-2014 were included. Of those, the majority (82%, n ​= ​551) underwent surgery. Data on all patients was analyzed with PathFx version 3.0, generating a probability of survival at 1, 3, 6, 12, 18 and 24 months. The predictions were compared to real survival data and the precision in estimation was evaluated with Receiver-Operating Characteristic curve (ROC) analysis where the Area Under Curve (AUC) was calculated. Brier score and decision curve analyses were also assessed.

Results

The AUC for 1-, 3-, 6- and 12 months survival predictions were 0.64 (95% CI 0.5-0.71), 0.71 (95% CI 0.67-0.75), 0.70 (95% CI 0.66-0.77) and 0.74 (95% CI 0.70-0.78). For 18- and 24 months survival the AUC were 0.74 (95% CI 0.69-0.78) and 0.76 (95% CI 0.72-0.81). The Brier scores were all 0.23 or lower depending on the estimated survival time.

Discussion and conclusion

PathFx 3.0 is a reasonably reliable tool for predicting survival in patients with spinal metastatic disease. As the PathFx computer model can be updated to reflect advancements in oncology, we suggest this type of model, rather than rigid point-based scoring systems, to be used for estimating survival in patients with metastatic spinal disease in the future.

External Validation of a Machine Learning Algorithm for Predicting Clinically Meaningful Functional Improvement After Arthroscopic Hip Preservation Surgery

BACKGROUND

Individualized risk prediction has become possible with machine learning (ML), which may have important implications in enhancing clinical decision making. We previously developed an ML algorithm to predict propensity for clinically meaningful outcome improvement after hip arthroscopy for femoroacetabular impingement syndrome. External validity of prognostic models is critical to determine generalizability, although it is rarely performed.

PURPOSE

To assess the external validity of an ML algorithm for predicting clinically meaningful improvement after hip arthroscopy.

STUDY DESIGN

Cohort study; Level of evidence, 3.

METHODS

An independent hip preservation registry at a tertiary academic medical center was queried for consecutive patients/athletes who underwent hip arthroscopy for femoroacetabular impingement syndrome between 2015 and 2017. By assuming a minimal clinically important difference (MCID) outcome/event proportion of 75% based on the original study, a minimum sample of 132 patients was required. In total, 154 patients were included. Age, body mass index, alpha angle on anteroposterior pelvic radiographs, Tönnis grade and angle, and preoperative Hip Outcome Score-Sports Subscale were used as model inputs to predict the MCID for the Hip Outcome Score-Sports Subscale 2 years postoperatively. Performance was assessed using identical metrics to the internal validation study and included discrimination, calibration, Brier score, and decision curve analysis.

RESULTS

The concordance statistic in the validation cohort was 0.80 (95% CI, 0.71 to 0.87), suggesting good to excellent discrimination. The calibration slope was 1.16 (95% CI, 0.74 to 1.61) and the calibration intercept 0.13 (95% CI, -0.26 to 0.53). The Brier score was 0.15 (95% CI, 0.12 to 0.18). The null model Brier score was 0.20. Decision curve analysis revealed favorable net treatment benefit for patients with use of the algorithm as compared with interventional changes made for all and no patients.

CONCLUSION

The performance of this algorithm in an independent patient population in the northeast region of the United States demonstrated superior discrimination and comparable calibration to that of the derivation cohort. The external validation of this algorithm suggests that it is a reliable method to predict propensity for clinically meaningful improvement after hip arthroscopy and is an essential step forward toward introducing initial use in clinical practice. Potential uses include integration into electronic medical records for automated prediction, enhanced shared decision making, and more informed allocation of resources to optimize patient outcomes.

Fifty years of bone tumors

There have been enormous advances in the treatment of bone tumors over the past half-century. The most notable of these has been the transition from amputation as the standard of care to limb salvage surgery. This transition is the result of advances in imaging techniques, accurate diagnosis, systemic therapies (including chemotherapy), and prosthetic design for the reconstruction of musculoskeletal defects. Advances have also been made in the management of benign and metastatic bone tumors.

Can a Bayesian belief network for survival prediction in patients with extremity metastases (PATHFx) be externally validated in an Asian cohort of 356 surgically treated patients?

BACKGROUND AND PURPOSE

Predicted survival may influence the treatment decision for patients with skeletal extremity metastasis, and PATHFx was designed to predict the likelihood of a patient dying in the next 24 months. However, the performance of prediction models could have ethnogeographical variations. We asked if PATHFx generalized well to our Taiwanese cohort consisting of 356 surgically treated patients with extremity metastasis.

PATIENTS AND METHODS

We included 356 patients who underwent surgery for skeletal extremity metastasis in a tertiary center in Taiwan between 2014 and 2019 to validate PATHFx's survival predictions at 6 different time points. Model performance was assessed by concordance index (c-index), calibration analysis, decision curve analysis (DCA), Brier score, and model consistency (MC).

RESULTS

The c-indexes for the 1-, 3-, 6-, 12-, 18-, and 24-month survival estimations were 0.71, 0.66, 0.65, 0.69, 0.68, and 0.67, respectively. The calibration analysis demonstrated positive calibration intercepts for survival predictions at all 6 timepoints, indicating PATHFx tended to underestimate the actual survival. The Brier scores for the 6 models were all less than their respective null model's. DCA demonstrated that only the 6-, 12-, 18-, and 24-month predictions appeared useful for clinical decision-making across a wide range of threshold probabilities. The MC was < 0.9 when the 6- and 12-month models were compared with the 12-month and 18-month models, respectively.

INTERPRETATION

In this Asian cohort, PATHFx's performance was not as encouraging as those of prior validation studies. Clinicians should be cognizant of the potential decline in validity of any tools designed using data outside their particular patient population. Developers of survival prediction tools such as PATHFx might refine their algorithms using data from diverse, contemporary patients that is more reflective of the world's population.

Functional and Survival Outcomes of Patients following the Harrington Procedure for Complex Acetabular Metastatic Lesions

Background: The Harrington surgical technique makes it possible to manage complex, extensive bone lesions using pins and cement to consolidate bone for acetabular cup positioning. However, it may be associated with a high reoperation rate, and the functional results of this surgery are not precisely described in the literature. Methods: In a monocentric retrospective study including all patients operated on using the Harrington procedure associated with THA between 2005 and 2020, we aimed to assess preoperative and postoperative function, reoperation-free survival, and overall survival. Results: Functional improvement was significant for Parker scores (preoperative: 3.6 ± 2.0; 6-month follow-up: 6.6 ± 3.2; 12-month follow-up: 7.6 ± 2.1) and Musculoskeletal Tumor Society (MSTS) scores (preoperative: 31.1 ± 16.2%; 6-month follow-up: 67.7 ± 30.6%; 12-month follow-up: 82.4 ± 24.0%). Of the 21 patients included, the reoperation-free survival rate was 76.1% [CI 95%: 58.1–99.7] at six and twelve months, with the main complications being pin migration (50.0%) and infection (25%). The patient overall survival rate was 76.2% [95% CI: 59.9–96.7] at six months and 61.9% [95% CI: 59.9–96.7] at 12 months. Discussion: These results underlined significant functional improvements following a conventional Harrington procedure, with acceptable reoperation rates.

The Prediction of Survival after Surgical Management of Bone Metastases of the Extremities—A Comparison of Prognostic Models

Individualized survival prognostic models for symptomatic patients with appendicular metastatic bone disease are key to guiding clinical decision-making for the orthopedic surgeon. Several prognostic models have been developed in recent years; however, most orthopedic surgeons have not incorporated these models into routine practice. This is possibly due to uncertainty concerning their accuracy and the lack of comparison publications and recommendations. Our aim was to conduct a review and quality assessment of these models. A computerized literature search in MEDLINE, EMBASE and PubMed up to February 2022 was done, using keywords: “Bone metastasis”, “survival”, “extremity” and “prognosis”. We evaluated each model’s performance, assessing the estimated discriminative power and calibration accuracy for the analyzed patients. We included 11 studies out of the 1779 citations initially retrieved. The 11 studies included seven different models for estimating survival. Among externally validated survival prediction scores, PATHFx 3.0, 2013-SPRING and potentially Optimodel were found to be the best models in terms of performance. Currently, it is still a challenge to recommend any of the models as the standard for predicting survival for these patients. However, some models show better performance status and other quality characteristics. We recommend future, large, multicenter, prospective studies to compare between PATHfx 3.0, SPRING 2013 and OptiModel using the same external validation dataset.

Quantitative preoperative patient assessments are related to survival and procedure outcome for osseous metastases

Aims

Our objective was to determine if preoperative patient-reported assessments are associated with survival after surgery for stabilization of skeletal metastases.

Patients and Methods

All patients with metastatic cancer to bone and indications for skeletal stabilization surgery were approached to participate in a prospective cohort study at a tertiary care center from 2012 to 2017. Of the 208 patients who were eligible, 195 (94%) completed the 36-item Short Form Health Survey (SF-36) preoperatively and underwent surgical treatment of skeletal metastases with complete or impending fractures; the sample encompassed a range of cancer diagnoses and included cases of both internal fixation and endoprosthetic replacement. Cox proportional hazards models were used to identify associations between SF-36 scores and survival.

Results

In a model adjusted for clinical factors, patients' mental and physical SF-36 component summary scores were significantly associated with survival, as was their SF-36 composite score (P = 0.004, P = 0.015, and P < 0.001, respectively). Scores in the general health, vitality, and mental health domains were each strongly associated with survival (P < 0.001).

Conclusions

Patients' preoperative assessments of their health status are associated with their survival after surgery for skeletal metastases. Patient-reported assessments have the potential to contribute unique information to models that estimate patient survival, as part of efforts to provide optimal, individualized care and make informed decisions about the type and magnitude of surgery for metastatic bone disease that will last the patient's lifetime.

What Factors Are Associated With Local Metastatic Lesion Progression After Intramedullary Nail Stabilization?

BACKGROUND

Pathologic fracture of the long bones is a common complication of bone metastases. Intramedullary nail stabilization can be used prophylactically (for impending fractures) or therapeutically (for completed fractures) to preserve mobility and quality of life. However, local disease progression may occur after such treatment, and there is concern that surgical instrumentation and the intramedullary nail itself may seed tumor cells along the intramedullary tract, ultimately leading to loss of structural integrity of the construct. Identifying factors associated with local disease progression after intramedullary nail stabilization would help surgeons predict which patients may benefit from alternative surgical strategies.

QUESTIONS/PURPOSES

(1) Among patients who underwent intramedullary nail stabilization for impending or completed pathologic fractures of the long bones, what is the risk of local progression, including progression of the existing lesion and development of a new lesion around the nail? (2) Among patients who experience local progression, what proportion undergo reoperation? (3) What patient characteristics and treatment factors are associated with postoperative local progression? (4) What is the difference in survival rates between patients who experienced local progression and those with stable local disease?

METHODS

Between January 2013 and December 2019, 177 patients at our institution were treated with an intramedullary nail for an impending or completed pathologic fracture. We excluded patients who did not have a pathologic diagnosis of metastasis before fixation, who were younger than 18 years of age, who presented with a primary soft tissue mass that eroded into bone, and who experienced nonunion from radiation osteitis or an avulsion fracture rather than from metastasis. Overall, 122 patients met the criteria for our study. Three fellowship-trained orthopaedic oncology surgeons involved in the care of these patients treated an impending or pathologic fracture with an intramedullary nail when a long bone lesion either fractured or was deemed to be of at least 35% risk of fracture within 3 months, and in patients with an anticipated duration of overall survival of at least 6 weeks (fractured) or 3 months (impending) to yield palliative benefit during their lifetime. The most common primary malignancy was multiple myeloma (25% [31 of 122]), followed by lung carcinoma (16% [20 of 122]), breast carcinoma (15% [18 of 122]), and renal cell carcinoma (12% [15 of 122]). The most commonly involved bone was the femur (68% [83 of 122]), followed by the humerus (27% [33 of 122]) and the tibia (5% [6 of 122]). A competing risk analysis was used to determine the risk of progression in our patients at 1 month, 3 months, 6 months, and 12 months after surgery. A proportion of patients who ultimately underwent reoperation due to progression was calculated. A univariate analysis was performed to determine whether lesion progression was associated with various factors, including the age and sex of the patient, use of adjuvant therapies (radiation therapy at the site of the lesion, systemic therapy, and antiresorptive therapy), histologic tumor type, location of the lesion, and fracture type (impending or complete). Patient survival was assessed with a Kaplan-Meier curve. A p value < 0.05 was considered significant.

RESULTS

The cumulative incidence of local tumor progression (with death as a competing risk) at 1 month, 3 months, 6 months, and 12 months after surgery was 1.9% (95% confidence interval 0.3% to 6.1%), 2.9% (95% CI 0.8% to 7.5%), 3.9% (95% CI 1.3% to 8.9%), and 4.9% (95% CI 1.8% to 10.3%), respectively. Of 122 patients, 6% (7) had disease progression around the intramedullary nail and 0.8% (1) had new lesions at the end of the intramedullary nail. Two percent (3 of 122) of patients ultimately underwent reoperation because of local progression. The only factors associated with progression were a primary tumor of renal cell carcinoma (odds ratio 5.1 [95% CI 0.69 to 29]; p = 0.03) and patient age (difference in mean age 7.7 years [95% CI 1.2 to 14]; p = 0.02). We found no associations between local disease progression and the presence of visceral metastases, other skeletal metastases, radiation therapy, systemic therapy, use of bisphosphonate or receptor activator of nuclear factor kappa-B ligand inhibitor, type of fracture, or the direction of nail insertion. There was no difference in survivorship curves between those with disease progression and those with stable local disease (= 0.36; p = 0.54).

CONCLUSION

Our analysis suggests that for this population of patients with metastatic bone disease who have a fracture or impeding fracture and an anticipated survival of at least 6 weeks (completed fracture) or 3 months (impending fracture), the risk of experiencing local progression of tumor growth and reoperations after intramedullary nail stabilization seems to be low. Lesion progression was not associated with the duration of survival, although this conclusion is limited by the small number of patients in the current study and the competing risks of survival and local progression. Based on our data, patients who present with renal cell carcinoma should be cautioned against undergoing intramedullary nailing because of the risk of postoperative lesion progression.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Machine learning algorithms to estimate 10-Year survival in patients with bone metastases due to prostate cancer: toward a disease-specific survival estimation tool

BACKGROUND

Prognostic indicators, treatments, and survival estimates vary by cancer type. Therefore, disease-specific models are needed to estimate patient survival. Our primary aim was to develop models to estimate survival duration after treatment for skeletal-related events (SREs) (symptomatic bone metastasis, including impending or actual pathologic fractures) in men with metastatic bone disease due to prostate cancer. Such disease-specific models could be added to the PATHFx clinical-decision support tool, which is available worldwide, free of charge. Our secondary aim was to determine disease-specific factors that should be included in an international cancer registry.

METHODS

We analyzed records of 438 men with metastatic prostate cancer who sustained SREs that required treatment with radiotherapy or surgery from 1989-2017. We developed and validated 6 models for 1-, 2-, 3-, 4-, 5-, and 10-year survival after treatment. Model performance was evaluated using calibration analysis, Brier scores, area under the receiver operator characteristic curve (AUC), and decision curve analysis to determine the models' clinical utility. We characterized the magnitude and direction of model features.

RESULTS

The models exhibited acceptable calibration, accuracy (Brier scores < 0.20), and classification ability (AUCs > 0.73). Decision curve analysis determined that all 6 models were suitable for clinical use. The order of feature importance was distinct for each model. In all models, 3 factors were positively associated with survival duration: younger age at metastasis diagnosis, proximal prostate-specific antigen (PSA) < 10 ng/mL, and slow-rising alkaline phosphatase velocity (APV).

CONCLUSIONS

We developed models that estimate survival duration in patients with metastatic bone disease due to prostate cancer. These models require external validation but should meanwhile be included in the PATHFx tool. PSA and APV data should be recorded in an international cancer registry.

Prognosis by cancer type and incidence of zoledronic acid-related osteonecrosis of the jaw: a single-center retrospective study

PURPOSE

Survival time after bisphosphonate use has been increasingly recognized to be associated with the incidence of medication-related osteonecrosis of the jaw (MRONJ); however, this has not been elucidated sufficiently in the literature. This study aimed to clarify the incidence of MRONJ and the corresponding survival rate of patients treated with zoledronic acid (ZA) for each type of cancer and obtain useful information for the oral/dental supportive care of cancer patients.

METHODS

We evaluated 988 patients who were administered ZA at our hospital; among them, 862 patients with metastatic bone tumors or myeloma were included.

RESULTS

The median survival time (MST) after ZA initiation was 35, 34, 8, 41, 12, and 6 months for patients with breast, prostrate, lung, myeloma, renal, and other cancers, respectively. Patients with cancers that had a short survival time (lung and other cancers [MST = 8 and 6 months, respectively] and cancers with MST < 10 months) did not develop MRONJ; this could be attributed to the shorter duration of ZA administration. The cumulative incidence of MRONJ in breast cancer, prostate cancer, and multiple myeloma was related to the frequency of anti-resorptive drug use and the increased risk over time. In renal cancer, the cumulative incidence of MRONJ increased early, although the MST was 12 months.

CONCLUSION

For the dentists in charge of dental management, it is essential to be aware of prognosis-related factors, predict MRONJ risk for each cancer treatment, and use risk prediction in dental management planning, particularly for cancers with non-poor prognosis.

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.

Artificial intelligence applied to musculoskeletal oncology: a systematic review

Developments in artificial intelligence have the potential to improve the care of patients with musculoskeletal tumors. We performed a systematic review of the published scientific literature to identify the current state of the art of artificial intelligence applied to musculoskeletal oncology, including both primary and metastatic tumors, and across the radiology, nuclear medicine, pathology, clinical research, and molecular biology literature. Through this search, we identified 252 primary research articles, of which 58 used deep learning and 194 used other machine learning techniques. Articles involving deep learning have mostly involved bone scintigraphy, histopathology, and radiologic imaging. Articles involving other machine learning techniques have mostly involved transcriptomic analyses, radiomics, and clinical outcome prediction models using medical records. These articles predominantly present proof-of-concept work, other than the automated bone scan index for bone metastasis quantification, which has translated to clinical workflows in some regions. We systematically review and discuss this literature, highlight opportunities for multidisciplinary collaboration, and identify potentially clinically useful topics with a relative paucity of research attention. Musculoskeletal oncology is an inherently multidisciplinary field, and future research will need to integrate and synthesize noisy siloed data from across clinical, imaging, and molecular datasets. Building the data infrastructure for collaboration will help to accelerate progress towards making artificial intelligence truly useful in musculoskeletal oncology.

Does surgical technique influence the burden of lung metastases in patients with pathologic long bone fractures?

BACKGROUND

The aims of this study are to (1) determine whether fixation of metastatic long bone fractures with an intramedullary nail (IMN) influences the incidence of lung metastasis in comparison to arthroplasty or ORIF (Arthro/ORIF); and (2) assess this relationship in primary tumor types; and (3) to assess survival implications of lung metastasis after surgery.

METHODS

Retrospective cohort study investigating 184 patients (107 IMN, and 77 Arthro/ORIF) surgically treated for metastatic long bone fractures. Patients were required to have a single surgically treated impending or established pathologic fracture of a long bone, pre-operative lung imaging (lung radiograph or computed tomography) and post-operative lung imaging within 6 months of surgery. Primary cancer types included were breast (n = 70), lung (n = 43), prostate (n = 34), renal cell (n = 37). Statistical analyses were conducted using two-tailed Fisher's exact tests, and Kaplan-Meier survival analyses.

RESULTS

Patients treated with IMN and Arthro/ORIF developed new or progressive lung metastases following surgery at an incidence of 34 and 26%, respectively. Surgical method did not significantly influence lung metastasis (p = 0.33). Furthermore, an analysis of primary cancer subgroups did not yield any differences between IMN vs Arthro/ORIF. Median survival for the entire cohort was 11 months and 1-year overall survival was 42.7% (95% CI: 35.4-49.8). Regardless of fixation method, the presence of new or progressive lung metastatic disease at follow up imaging study was found to have a negative impact on patient survival (p < 0.001).

CONCLUSIONS

In this study, development or progression of metastatic lung disease was not affected by long bone stabilization strategy. IM manipulation of metastatic long bone fractures therefore may not result in a clinically relevant increase in metastatic lung burden. The results of this study also suggest that lung metastasis within 6 months of surgery for metastatic long bone lesions is negatively associated with patient survival.

LEVEL OF EVIDENCE

III, therapeutic study.

Comparison between different prognostic models to be used for metastatic bone disease on appendicular skeleton in a Chilean population

PURPOSE

Several preoperation prognosis models used on the treatment of metastatic bone disease on appendicular skeleton have been devised. The purpose of this study was to compare the performance of different survival prognostic models on patients with metastatic bone disease in long bones in a Chilean population.

METHODS

This is a multicentric retrospective study. We retrospectively reviewed the medical records of 136 patients who were confirmed with metastatic bone disease of the appendicular skeleton and who were treated surgically from 2016 to 2019. The minimum follow-up time was 12 months. All patients were assessed using four appendicular metastatic bone disease scoring systems. A preoperative predicted survival time for all 136 patients was retrospectively calculated making use of the revised Katagiri, PathFx, Optimodel and IOR score model.

RESULTS

The PathFx model demonstrated an accuracy at predicting 3 (area under the curve [AUC] = 0.61) and 6-month (AUC = 0.65) survival time after surgical management. IOR score model demonstrated an accuracy at predicting 12-month survival time (AUC = 0.64). The survival rate reached the 44% in a year. The median survival time to death or last follow-up time was 14.9 months (SD ± 15).

CONCLUSION

PathFx score model demonstrated the highest accuracy at predicting a survival time of 3 and 6 months. IOR score model was the most accurate measure at predicting a survival time of 12-months. To our knowledge, this is the first study reporting a comparative analysis of metastatic bone disease with predicting models in a country located in Latin America. PathFx's and IOR score models are the ones to be used in the Chilean population as the predictive models in metastatic bone disease of the appendicular skeleton.

What's new in the management of metastatic bone disease

Metastatic bone disease is a common complication of malignant tumours. As cancer treatment improves the overall survival of patients, the number of patients with bone metastases is expected to increase. The treatments for bone metastases include surgery, radiotherapy, and bone-modifying agents, with patients with a short expected prognosis requiring less invasive treatment. Patients with metastatic bone disease show greatly varying primary tumour histology, metastases sites and numbers, and comorbidities. Therefore, randomised clinical trials are indispensable to compare treatments for these patients. This editorial reviews recent findings on the diagnosis and prognosis prediction and discusses the current treatment of patients with metastatic bone disease.

Prognostic Factors Influencing Survival and a Treatment Pattern Analysis of Conventional Palliative Radiotherapy for Patients with Bone Metastases

BACKGROUND

Treatment indication for bone metastases is influenced by patient prognosis. Single-fraction radiotherapy (SFRT) was proven equally effective as multiple fractionation regimens (MFRT) but continues to be underused.

OBJECTIVE

Primary objectives: (a) to identify prognostic factors for overall survival and (b) to analyze treatment patterns of palliative radiotherapy (proportion of SFRT indication and predictive factors of radiotherapy regimen) for bone metastases.

METHODS

582 patients with bone metastases who underwent conventional radiotherapy between January 1st 2014-31 December 2017 were analyzed. The Cox proportional hazard model was used to identify predictors of overall survival. For the treatment pattern analysis, 677 radiotherapy courses were evaluated. The logistic regression model was used to identify potential predictors of radiotherapy regimen.

RESULTS

The 3-year overall survival was 15%. Prognostic factors associated with poor overall survival were multiple bone metastases [hazard ratio (HR = 5.4)], poor performance status (HR = 1.5) and brain metastases (HR = 1.37). SFRT prescription increased from 41% in 2017 to 51% in 2017. Predictors of SFRT prescription were a poor performance status [odds ratio (OR = 0.55)], lung (OR = 0.49) and urologic primaries (OR = 0.33) and the half-body lower site of irradiation (OR = 0.59). Spinal metastases were more likely to receive MFRT (OR = 2.09).

CONCLUSIONS

Based on the prognostic factors we identified, a selection protocol for patients candidates for palliative radiotherapy to bone metastases could be established, in order to further increase SFRT prescription in our institution.

Current Overview of Treatment for Metastatic Bone Disease

The number of patients with bone metastasis increases as medical management and surgery improve the overall survival of patients with cancer. Bone metastasis can cause skeletal complications, including bone pain, pathological fractures, spinal cord or nerve root compression, and hypercalcemia. Before initiation of treatment for bone metastasis, it is important to exclude primary bone malignancy, which would require a completely different therapeutic approach. It is essential to select surgical methods considering the patient’s prognosis, quality of life, postoperative function, and risk of postoperative complications. Therefore, bone metastasis treatment requires a multidisciplinary team approach, including radiologists, oncologists, and orthopedic surgeons. Recently, many novel palliative treatment options have emerged for bone metastases, such as stereotactic body radiation therapy, radiopharmaceuticals, vertebroplasty, minimally invasive spine stabilization with percutaneous pedicle screws, acetabuloplasty, embolization, thermal ablation techniques, electrochemotherapy, and high-intensity focused ultrasound. These techniques are beneficial for patients who may not benefit from surgery or radiotherapy.

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.

Fracture Risk of Long Bone Metastases: A Review of Current and New Decision-Making Tools for Prophylactic Surgery

Simple Summary

Long bone metastases are frequently a pivotal point in the oncological history of patients. Weakening of the bone results in pathologic fractures that not only compromise patient function but also their survival. Therefore, the main issue for tumor boards remains timely assessment of the risk of fracture, as this is a key consideration in providing preventive surgery while also avoiding overtreatment. As the Mirels scoring system takes into account both the radiological and the clinical criteria, it has been used worldwide since the 1990s. However, due to increasing concern regarding the lack of accuracy, new thresholds have been defined for the identification of impending fractures that require prophylactic surgery, on the basis of axial cortical involvement and biomechanical models involving quantitative computed tomography. The aim of this review is to establish a state-of-the-art of the risk assessment of long bone metastases fractures, from simple radiologic scores to more complex multidimensional bone models, in order to define new decision-making tools.

Abstract

Long bone pathological fractures very much reflect bone metastases morbidity in many types of cancer. Bearing in mind that they not only compromise patient function but also survival, identifying impending fractures before the actual event is one of the main concerns for tumor boards. Indeed, timely prophylactic surgery has been demonstrated to increase patient quality of life as well as survival. However, early surgery for long bone metastases remains controversial as the current fracture risk assessment tools lack accuracy. This review first focuses on the gold standard Mirels rating system. It then explores other unique imaging thresholds such as axial or circumferential cortical involvement and the merits of nuclear imaging tools. To overcome the lack of specificity, other fracture prediction strategies have focused on biomechanical models based on quantitative computed tomography (CT): computed tomography rigidity analysis (CT-RA) and finite element analysis (CT-FEA). Despite their higher specificities in impending fracture assessment, their limited availability, along with a need for standardization, have limited their use in everyday practice. Currently, the prediction of long bone pathologic fractures is a multifactorial process. In this regard, machine learning could potentially be of value by taking into account clinical survival prediction as well as clinical and improved CT-RA/FEA data.

Prosthesis or osteosynthesis for the treatment of a pathological hip fracture? A nationwide registry-based cohort study

Aims

How endoprosthetic replacement compares to osteosynthesis in the treatment of pathologic hip fractures as far as functional outcome and use of healthcare resources is concerned remains largely unknown. We aimed to investigate this in a nationwide registry.

Methods

We analyzed the functional outcome after surgery for a pathological fracture of the hip in terms of post-operative pain and ambulatory capacity. The preferred surgical method depending on the level of the treating unit was also examined. Furthermore, we documented the length of hospital stay and the patterns of discharge and compared them between these two methods.

Results

Patients operated with an endoprosthesis reported significantly lower pain at follow-up. Both methods (endoprosthetic replacement and osteosynthesis) were equally effective in restoring the ambulatory capacity and demanded a similar length of stay in hospital. Orthopaedic surgeons working in hospitals with dedicated sarcoma teams were more likely to use a prosthesis rather than osteosynthesis, when compared to surgeons working at other university hospitals or emergency hospitals.

Conclusion

Endoprosthetic replacement results in a better functional outcome in terms of post-operative pain without consuming more healthcare resources. Orthopaedic surgeons working in hospitals with sarcoma centers are more likely to use prostheses as compared to surgeons working at hospitals where dedicated musculoskeletal oncology teams are not available.

Can Machine-learning Algorithms Predict Early Revision TKA in the Danish Knee Arthroplasty Registry?

BACKGROUND

Revision TKA is a serious adverse event with substantial consequences for the patient. As the demand for TKA rises, reducing the risk of revision TKA is becoming increasingly important. Predictive tools based on machine-learning algorithms could reform clinical practice. Few attempts have been made to combine machine-learning algorithms with data from nationwide arthroplasty registries and, to the authors' knowledge, none have tried to predict the likelihood of early revision TKA.

QUESTION/PURPOSES

We used the Danish Knee Arthroplasty Registry to build models to predict the likelihood of revision TKA within 2 years of primary TKA and asked: (1) Which preoperative factors were the most important features behind these models' predictions of revision? (2) Can a clinically meaningful model be built on the preoperative factors included in the Danish Knee Arthroplasty Registry?

METHODS

The Danish Knee Arthroplasty Registry collects patients' characteristics and surgical information from all arthroplasties conducted in Denmark and thus provides a large nationwide cohort of patients undergoing TKA. As training dataset, we retrieved all preoperative variables of 25,104 primary TKAs from 2012 to 2015. The same variables were retrieved from 6170 TKAs conducted in 2016, which were used as a hold-out year for temporal external validation. If a patient received bilateral TKA, only the first knee to receive surgery was included. All patients were followed for 2 years, with removal, exchange, or addition of an implant defined as TKA revision. We created four different predictive models to find the best performing model, including a regression-based model using logistic regression with least shrinkage and selection operator (LASSO), two classification tree models (random forest and gradient boosting model) and a supervised neural network. For comparison, we created a noninformative model predicting that all observations were unrevised. The four machine learning models were trained using 10-fold cross-validation on the training dataset after adjusting for the low percentage of revisions by over-sampling revised observations and undersampling unrevised observations. In the validation dataset, the models' performance was evaluated and compared by density plot, calibration plot, accuracy, Brier score, receiver operator characteristic (ROC) curve and area under the curve (AUC). The density plot depicts the distribution of probabilities and the calibration plot graphically depicts whether the predicted probability resembled the observed probability. The accuracy indicates how often the models' predictions were correct and the Brier score is the mean distance from the predicted probability to the observed outcome. The ROC curve is a graphical output of the models' sensitivity and specificity from which the AUC is calculated. The AUC can be interpreted as the likelihood that a model correctly classified an observation and thus, a priori, an AUC of 0.7 was chosen as threshold for a clinically meaningful model.

RESULTS

Based the model training, age, postfracture osteoarthritis and weight were deemed as important preoperative factors within the machine learning models. During validation, the models' performance was not different from the noninformative models, and with AUCs ranging from 0.57 to 0.60, no models reached the predetermined AUC threshold for a clinical useful discriminative capacity.

CONCLUSION

Although several well-known presurgical risk factors for revision were coupled with four different machine learning methods, we could not develop a clinically useful model capable of predicting early TKA revisions in the Danish Knee Arthroplasty Registry based on preoperative data.

CLINICAL RELEVANCE

The inability to predict early TKA revision highlights that predicting revision based on preoperative information alone is difficult. Future models might benefit from including medical comorbidities and an anonymous surgeon identifier variable or may attempt to build a postoperative predictive model including intra- and postoperative factors as these may have a stronger association with early TKA revisions.