How do we estimate survival? External validation of a tool for survival estimation in patients with metastatic bone disease-decision analysis and comparison of three international patient populations

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.

Carbon vs. Titanium Nails in the Treatment of Impending and Pathological Fractures: A Literature Review

Background: Long bones are commonly affected by musculoskeletal tumors, but they also represent one of the most frequent locations for metastases. The treatment is based on pain management and the prevention or stabilization of pathological fractures by intramedullary nailing. While titanium nails are probably the most used, carbon-fiber-reinforced (CFR) nails have emerged as a new option for oncological patients. The aim of this review is to compare titanium and CFR nails according to current findings. Methods: Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) standards were followed: a total of 1004 articles were identified and 10 were included. Results: Traditionally, titanium implants are highly valued for their optimal biomechanical properties and ease of insertion, facilitated by their radiopacity. However, the use of titanium poses challenges in radiotherapy due to interference with radiation dosage and the creation of ferromagnetic artifacts. Conversely, CFR implants have emerged as a recommended option for intramedullary fixation, due to their biomechanical and structural properties and their benefits during radiotherapy and follow-up monitoring X-ray. Conclusions: CFR nailing represents a promising advancement in the surgical management of oncological patients with long bone metastases. However, further studies are needed to increase surgeons' confidence in their use.

Preoperative Albumin and Postoperative CRP/Albumin Ratio (CARS) are Independent Predictive Factors in Estimating 1-Year Mortality in Patients Operated for Proximal Femoral Metastasis with Endoprosthesis

Background

Proximal femur resection and prosthetic reconstruction are preferred in patients with extensive bone destruction, pathological fractures, tumours resistant to radiation therapy, and patients with more proximal metastatic lesions. There is increasing evidence that the CRP/albumin ratio (CAR) is an independent marker of inflammation in various primary organ cancers and maybe a more accurate prognostic factor. We aimed to evaluate whether preoperative and postoperative CAR values could be a factor in predicting mortality in these patients. We hypothesized that CAR could predict these patients' postoperative 90-day and 1-year mortality.

Methods

The patient's age and gender, primary tumour, number of bone metastases, and presence of visceral metastases were recorded using imaging techniques such as computed tomography and bone scan or positron emission tomography. The following laboratory data were analyzed before and after surgery.

Results

The mean age of the patients was 62.67 ± 14.8; 56.9% were female (n:29), and 43.1% were male (n:22). When the results of the ROC analysis of the parameters in predicting 1-year mortality were examined, and the cut-off value for preoperative albumin was taken as ≤ 3.75, the AUC value was found to be statistically significant as 0.745 (p:0.003). When the cut-off value for postoperative CAR was taken as ≥ 87.32, the AUC value was found to be 0.7 statistically significant (p:0.015).

Conclusion

Length of stay, preoperative albumin and postoperative CAR values can be used as independent predictive values in predicting 1-year mortality in patients undergoing endoprosthesis due to proximal femur metastasis.

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.

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.

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.

Intramedullary nailing vs modular megaprosthesis in extracapsular metastases of proximal femur: clinical outcomes and complication in a retrospective study

BACKGROUND

Extracapsular proximal femur metastasis could be treated by synthesis or resection and megaprosthesis. No universal accepted guidelines are present in the literature. The aim of our study is to analyze of patients with metastases in the trochanteric region of the femur treated by a single type of intramedullary nailing or hip megaprosthesis.

METHODS

We retrospectively reviewed all patients affected by extracapsular metastases of proximal femur. Anthropometric and anamnestic data, routine blood exams and complications were collected. VAS score and MSTS score was administered before the surgery, ad 1-6-12 months after surgery. An un-paired T test and Chi-square were used. Multiple linear regression and logistic regression was performed. Significance was set for p < 0.05.

RESULT

Twenty patients were assigned in intramedullary Group, twenty-five in megaprostheses Group. The mean operative time is shorter in intramedullary group. Differential shows a higher anemization in megaprostheses group (2 ± 2 vs 3.6 ± 1.3; p = 0.02). The patients of intramedullary group showed malnutrition (Albumin: 30.5 ± 6.5 vs 37.6 ± 6 g/L; p = 0.03) and pro-inflammatory state (NLR: 7.1 ± 6.7 vs 3.8 ± 2.4; p = 0.05) (PLR: 312 ± 203 vs 194 ± 99; p = 0.04) greater than megaprostheses group. The patients in intramedullary groups shows a higher functional performance score than megaprostheses group at 1 month follow-up (MSTS: 16.4 ± 6.3 vs 12.2 ± 3.7; p = 0.004). A multivariate analysis confirms the role of type of surgery (p = 0.001), surgery duration (p = 0.005) and NLR (p = 0.02) in affecting the MSTS. Globally eight complications were recorded, no statistical difference was noticed between the two groups (p = 0.7), no predictor was found at logistic analysis.

CONCLUSION

Intramedullary nailing guarantees a rapid functional recovery, compared to patients undergoing hip megaprosthesis who instead improve gradually over time. The selection of patients with poor prognosis allows the correct surgical indication of nailing, while in the case of a more favorable prognosis, the intervention of hip megaprosthesis is to be preferred.

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.

Cemented vs uncemented megaprostheses in proximal femur metastases: a multicentric comparative study

BACKGROUND

Hip megaprostheses are a long known reconstructive method in the treatment of proximal femur metastases. The use of cemented or uncemented stems is still matter of debate. The aim of this study to compare cemented and uncemented megaprostheses on functional outcomes and complications, in order to establish the role of cementation.

METHODS

We retrospectively analysed 51 metastatic patients with proximal femur metastases treated with endoprosthetic reconstruction by megaprostheses, 25 with cementless stems and 26 with cemented ones with different megaprosthetic implants. The primary endpoint was MSTS score, and the secondary endpoint was to state the incidence of surgical and clinical complications in the two groups. An un-paired T test was used to compare anthropometric, anamnestic data, and MSTS. Chi-square test was performed for evaluation of complication in the two group. Multiple linear regression was used to match the functional outcomes and complications' incidence in the population study. Logistic regression was performed to analyse the odds ratio of different parameters and their role in the incidence of complications.

RESULTS

The mean follow-up was 50.1 months (+ 12.5). In thirty case right side was involved. No statistical differences were noticed between Group A and B regard the age, gender, active fracture/impending fracture. Comparing the MSTS results within the two groups at last follow-up, the score cemented group was higher than cementless one (17.9 + 7.8 vs 24.2 + 5.3; statistical significance p = 0.001). Regarding surgical complications a logistic regression was performed to analyse the odds ratio of age, cementation and length of resection; cementation confirm and odds ratio of 11 times in the incidence of surgical complications.

CONCLUSIONS

Cementation seems to be more liable to complications onset, while improves functional score in metastatic patients compared to uncemented megaprostheses. More studies have to be conducted in order to create a protocol and establish criteria to use cemented or uncemented stems in a frail population like metastatic patients.

Survival Prediction in Patients Treated Surgically for Metastases of the Appendicular Skeleton—An External Validation of 2013-SPRING Model

Simple Summary

Bone tumour metastases are highly prevalent among cancer patients. In case these have to be treated surgically due to impending or pathological fracture, estimation of patients’ life expectancy is of importance in order to choose the best treatment option possible. In the current study, the 2013-SPRING model, developed to predict prognosis of surgically treated bone metastasis patients, was validated in an external patient cohort of 303 bone metastasis patients. AUC ROCs at all three endpoints assessed (i.e., survival at 3, 6 and 12 months following surgery for bone metastases) were all above 0.780. Furthermore, stratification into type of surgery (endoprosthesis (n = 162) vs. osteosynthesis (n = 141) and metastasis location (upper limb (n = 65) vs. lower limb (n = 238)) revealed a comparable predictive accuracy of the 2013-SPRING model, albeit slightly better performance in the osteosynthesis as compared with endoprosthesis subgroup, as well as upper limb in comparison to lower limb subgroup was observed.

Abstract

Introduction: The aim of this study was to externally validate the 2013-SPRING model, a survival prediction tool for patients treated surgically for bone metastases in a retrospective patient cohort from a single institution. Moreover, subgroup analyses on patients treated with (A) endoprostheses or (B) osteosynthesis, as well as (C) upper limb and (D) lower limb metastases, were performed. Methods: Altogether, 303 cancer patients (mean age: 67.6 ± 11.1 years; 140 males (46.2%)) with bone metastases to the extremities, treated surgically between March 2000 and June 2018 at a single tertiary sarcoma centre, were retrospectively included. Median follow-up amounted to 6.3 (interquartile range (IQR): 2.3–21.8) months, with all patients followed-up for at least one year or until death. The 2013-SPRING model was applied to assess the prognostication accuracy at 3, 6 and 12 months. Models were validated with area under the curve receiver operator characteristic (AUC ROC; the higher the better), as well as Brier score. Results: Of the 303 patients, 141 had been treated with osteosynthesis (46.5%), and the remaining 162 patients with endoprosthesis (53.5%). Sixty-five (21.5%) metastases were located in the upper limbs, and two hundred and thirty-eight (78.5%) in the lower limbs. Using the 2013-SPRING model for the entire cohort, the accuracy of risk of death prediction at 3, 6 and 12 months, determined by the AUC ROC, was 0.782 (95% CI: 0.729–0.843), 0.810 (95% CI: 0.763–0.858) and 0.802 (95% CI: 0.751–0.854), respectively. Corresponding Brier scores were 0.170, 0.178 and 0.169 at 3, 6 and 12 months. In the subgroup analyses, predictive accuracy of the 2013-SPRING model was likewise encouraging, albeit being slightly higher in the osteosynthesis subgroup as compared with the endoprosthesis subgroup, and also higher in the upper limb in comparison to the lower limb metastasis subgroup. Conclusions: The current validation study of the 2013-SPRING model shows that this model is clinically relevant to use in an external cohort, also after stratification for surgical procedure and metastasis location.

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.

Outcomes of Intercalary Endoprostheses as a Treatment for Metastases in the Femoral and Humeral Diaphysis

BACKGROUND

The purpose of this study was to evaluate the implant survival, functional score and complications of intercalary endoprostheses implanted for metastatic involvement of the femoral and humeral diaphysis.

METHODS

The selected group covered patients with bone metastasis who were surgically treated with an intercalary endoprosthesis between 2012 and 2021. The functional outcome was evaluated with the Musculoskeletal Tumor Society (MSTS) scoring system, and complications were evaluated by using the failure classification for prosthetics designed by Henderson.

RESULTS

The mean follow-up was 29.8 months. In our group of 25 patients with 27 intercalary endoprostheses (18 femurs, 9 humeri), there were 7 implant-related complications (25.9%), which were more common on the humerus (4 cases, 44.4%) than on the femur (3 cases, 16.7%). Only type II failure-aseptic loosening (5 cases, 18.5%)-and type III failure-structural failure (2 cases, 7.4%)-occurred. There was a significantly higher risk of aseptic loosening of the endoprosthesis in the humerus compared with that in the femur (odds ratio 13.79, 95% confidence interval 1.22-151.05, p = 0.0297). The overall cumulative implant survival was 92% 1 year after surgery and 72% 5 years after surgery. The average MSTS score was 82%. The MSTS score was significantly lower (p = 0.008) in the humerus (75.9%) than in the femur (84.8%).

CONCLUSIONS

The resection of bone metastases and replacement with intercalary endoprosthesis has excellent immediate functional results with an acceptable level of complications in prognostically favourable patients.

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.

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.

The Surgical Management of Proximal Femoral Metastases: A Narrative Review

The proximal femur is a common location for the development of bony metastatic disease. Metastatic bone disease in this location can cause debilitating pain, pathologic fractures, reduced quality of life, anemia or hypercalcemia. A thorough history, physical examination and preoperative investigations are required to ensure accurate diagnosis and prognosis. The goals of surgical management is to provide pain relief and return to function with a construct that provides stability to allow for immediate weightbearing. Current surgical treatment options include intramedullary nailing, hemiarthroplasty or total hip arthroplasty and endoprosthetic reconstructions. Oligometastatic renal cell carcinoma must be given special consideration as tumor resection and reconstruction has survival benefit. Both tumor and patient characteristics must be taken into account before deciding on the appropriate surgical intervention.

Albumin and Survival in Extremity Metastatic Bone Disease: An Analysis of Two Independent Datasets

INTRODUCTION

Numerous prognostication models have been developed to estimate survival in patients with extremity metastatic bone disease, but few include albumin despite albumin's role in malnutrition and inflammation. The purpose of this study was to examine two independent datasets to determine the value for albumin in prognosticating survival in this population.

MATERIALS AND METHODS

Extremity metastatic bone disease patients undergoing surgical management were identified from two independent populations. Population 1: Retrospective chart review at two tertiary care centers. Population 2: A large, national, North American multicenter surgical registry with 30-day follow-up. Bivariate and multivariate analyses were used to examine albumin's value for prognostication at 1-, 3-, and 12-month after surgery.

RESULTS

In Population 1, 1,090 patients were identified with 1-, 3-, and 12-month mortality rates of 95 (8.8%), 305 (28.9%), and 639 (62.0%), respectively. In Population 2, 1,675 patients were identified with one-month postoperative mortality rates of 148 (8.8%). In both populations, hypoalbuminemia was an independent prognostic factor for mortality at 30 days. In the institutional set, hypoalbuminemia was additionally associated with 3- and 12-month mortality.

CONCLUSIONS

Hypoalbuminemia is a marker for mortality in extremity metastatic bone disease. Further consideration of this marker could improve existing prognostication models in this population.

LEVEL OF EVIDENCE

III.

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.

Harrington rods for periacetabular pathological lesion: is it an option?

Advancement in cancer treatment has prolonged the survival of cancer patients; as a result, there are an increased number of patients with bone metastases and pathological fractures referred to orthopaedic surgeons for surgical intervention for a better quality of life. Metastasis around the hip joint can be painful and intervene with patients' daily activity, and reconstruction of the hip joint with periacetabular metastasis is complex and challenging especially longer cancer survivals might out-live their fixation. Several acetabular reconstruction techniques and implants have been described to overcome this problem; acetabular reconstruction and total hip arthroplasty still remains the standard surgical treatment, to relief pain and to improve function and quality of life. Harrington reconstruction of periacetabular metastatic disease combined with hip arthroplasty is one of the options that can address this clinical scenario safely; it is reproducible and cost-effective. In this review, we present case series of patients treated in our institution using Harrington rod technique for acetabular pathological lesions with good outcome.

Compilation and Analysis of Web-Based Orthopedic Personalized Predictive Tools: A Scoping Review

Web-based personalized predictive tools in orthopedic surgery are becoming more widely available. Despite rising numbers of these tools, many orthopedic surgeons may not know what tools are available, how these tools were developed, and how they can be utilized. The aim of this scoping review is to compile and synthesize the profile of existing web-based orthopedic tools. We conducted two separate PubMed searches-one a broad search and the second a more targeted one involving high impact journals-with the aim of comprehensively identifying all existing tools. These articles were then screened for functional tool URLs, methods regarding the tool's creation, and general inputs and outputs required for the tool to function. We identified 57 articles, which yielded 31 unique web-based tools. These tools involved various orthopedic conditions (e.g., fractures, osteoarthritis, musculoskeletal neoplasias); interventions (e.g., fracture fixation, total joint arthroplasty); outcomes (e.g., mortality, clinical outcomes). This scoping review highlights the availability and utility of a vast array of web-based personalized predictive tools for orthopedic surgeons. Increased awareness and access to these tools may allow for better decision support, surgical planning, post-operative expectation management, and improved shared decision-making.

New concepts in the surgical treatment of actual and impending pathological fractures in metastatic disease

INTRODUCTION

Long bone metastases are a disease of high social importance. The goals of surgical treatment are to relieve pain, maintain or restore joint function, and prevent or treat pathological fractures. "Oligometastases" is a disease with a limited number (3-5) of metastatic lesions in the same body district, where an aggressive treatment can be carried out with "curative" intent. This study aimed to evaluate patients with bone metastases surgically treated to determine how surgical treatment can influence prognosis and quality of life, comparing solitary metastasis, oligometastases, and multiple metastases.

PATIENTS AND METHODS

This is a retrospective analysis of 130 patients with long bone metastases surgically treated between October 2015 and August 2019: 40 patients had solitary metastasis; 38 had less than three metastases (oligometastases), and 52 had multiple metastases. Surgery was resection and reconstruction with a cemented prosthesis (95) or nailing (35).

RESULTS

Overall survival was significantly better in patients with solitary metastasis or oligometastases than in those with multiple metastases (p <0.0001). Patients treated with resection and prosthesis had significantly better survival than those treated with nailing (p <0.0001). Implant complications requiring surgical revision occurred in 20 patients treated with prostheses, while no complications occurred in patients treated with nailing.

DISCUSSION

Survival of cancer patients has improved in the last two decades, leading to an increase of diagnosed metastases. Patients with oligometastases have a survival similar to those with a single metastasis. Optimal implants survival curves should stay above the curves of patients survival.

CONCLUSIONS

Since there are no differences in survival, patients with oligometastases should be treated as patients with a solitary lesion, with more aggressive surgery (wide resection and reconstruction with prosthesis). Intramedullary nailing is still indicated in metaphyseal or diaphyseal metastases in patients with advanced disease or poor prognosis when the life expectancy does not overcome the expected survival of the nail, avoiding the need for further surgery.

Validation of PATHFx 2.0: An open-source tool for estimating survival in patients undergoing pathologic fracture fixation

Treatment decisions in patients with metastatic bone disease rely on accurate survival estimation. We developed the original PATHFx models using expensive, proprietary software and now seek to provide a more cost-effective solution. Using open-source machine learning software to create PATHFx version 2.0, we asked whether PATHFx 2.0 could be created using open-source methods and externally validated in two unique patient populations. The training set of a well-characterized, database records of 189 patients and the bnlearn package within R Version 3.5.1 (R Foundation for Statistical Computing), was used to establish a series of Bayesian belief network models designed to predict survival at 1, 3, 6, 12, 18, and 24 months. Each was externally validated in both a Scandinavian (n = 815 patients) and a Japanese (n = 261 patients) data set. Brier scores and receiver operating characteristic curves to assessed discriminatory ability. Decision curve analysis (DCA) evaluated whether models should be used clinically. DCA showed that the model should be used clinically at all time points in the Scandinavian data set. For the 1-month time point, DCA of the Japanese data set suggested to expect better outcomes assuming all patients will survive greater than 1 month. Brier scores for each curve demonstrate that the models are accurate at each time point. Statement of Clinical Significance: we successfully transitioned to PATHFx 2.0 using open-source software and externally validated it in two unique patient populations, which can be used as a cost-effective option to guide surgical decisions in patients with metastatic bone disease.

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

BACKGROUND

PATHFx is a clinical decision-support tool based on machine learning capable of estimating the likelihood of survival after surgery for patients with skeletal metastases. The applicability of any machine-learning tool depends not only on successful external validation in unique patient populations but also on remaining relevant as more effective systemic treatments are introduced. With advancements in the treatment of metastatic disease, it is our responsibility to patients to ensure clinical support tools remain contemporary and accurate.

QUESTION/PURPOSES

Therefore, we sought to (1) generate updated PATHFx models using recent data from patients treated at one large, urban tertiary referral center and (2) externally validate the models using two contemporary patient populations treated either surgically or nonsurgically with external-beam radiotherapy alone for symptomatic skeletal metastases for symptomatic lesions.

METHODS

After obtaining institutional review board approval, we collected data on 208 patients undergoing surgical treatment for pathologic fractures at Memorial Sloan Kettering Cancer Center between 2015 and 2018. These data were combined with the original PATHFx training set (n = 189) to create the final training set (n = 397). We then created six Bayesian belief networks designed to estimate the likelihood of 1-month, 3-month, 6-month, 12-month, 18-month, and 24-month survival after treatment. Bayesian belief analysis is a statistical method that allows data-driven learning to arise from conditional probabilities by exploring relationships between variables to estimate the likelihood of an outcome using observed data. For external validation, we extracted the records of patients treated between 2016 and 2018 from the International Bone Metastasis Registry and records of patients treated nonoperatively with external-beam radiation therapy for symptomatic skeletal metastases from 2012 to 2016 using the Military Health System Data Repository (radiotherapy-only group). From each record, we collected the date of treatment, laboratory values at the time of treatment initiation, demographic data, details of diagnosis, and the date of death. All records reported sufficient follow-up to establish survival (yes/no) at 24-months after treatment. For external validation, we applied the data from each record to the new PATHFx models. We assessed calibration (calibration plots), accuracy (Brier score), discriminatory ability (area under the receiver operating characteristic curve [AUC]).

RESULTS

The updated PATHFx version 3.0 models successfully classified survival at each time interval in both external validation sets and demonstrated appropriate discriminatory ability and model calibration. The Bayesian models were reasonably calibrated to the Memorial Sloan Kettering Cancer Center training set. External validation with 197 records from the International Bone Metastasis Registry and 192 records from the Military Health System Data Repository for analysis found Brier scores that were all less than 0.20, with upper bounds of the 95% confidence intervals all less than 0.25, both for the radiotherapy-only and International Bone Metastasis Registry groups. Additionally, AUC estimates were all greater than 0.70, with lower bounds of the 95% CI all greater than 0.68, except for the 1-month radiotherapy-only group. To complete external validation, decision curve analysis demonstrated clinical utility. This means it was better to use the PATHFx models when compared to the default assumption that all or no patients would survive at all time periods except for the 1-month models. We believe the favorable Brier scores (< 0.20) as well as DCA indicate these models are suitable for clinical use.

CONCLUSIONS

We successfully updated PATHFx using contemporary data from patients undergoing either surgical or nonsurgical treatment for symptomatic skeletal metastases. These models have been incorporated for clinical use on PATHFx version 3.0 (https://www.pathfx.org). Clinically, external validation suggests it is better to use PATHFx version 3.0 for all time periods except when deciding whether to give radiotherapy to patients with the life expectancy of less than 1 month. This is partly because most patients survived 1-month after treatment. With the advancement of medical technology in treatment and diagnosis for patients with metastatic bone disease, part of our fiduciary responsibility is to the main current clinical support tools.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Development of Machine Learning Algorithms for Prediction of 30-Day Mortality After Surgery for Spinal Metastasis

BACKGROUND

Preoperative prognostication of short-term postoperative mortality in patients with spinal metastatic disease can improve shared decision making around end-of-life care.

OBJECTIVE

To (1) develop machine learning algorithms for prediction of short-term mortality and (2) deploy these models in an open access web application.

METHODS

The American College of Surgeons, National Surgical Quality Improvement Program was used to identify patients that underwent operative intervention for metastatic disease. Four machine learning algorithms were developed, and the algorithm with the best performance across discrimination, calibration, and overall performance was integrated into an open access web application.

RESULTS

The 30-d mortality for the 1790 patients undergoing surgery for spinal metastatic disease was 8.49%. Preoperative factors used for prognostication were albumin, functional status, white blood cell count, hematocrit, alkaline phosphatase, spinal location (cervical, thoracic, lumbosacral), and severity of comorbid systemic disease (American Society of Anesthesiologist Class). In this population, machine learning algorithms developed to predict 30-d mortality performed well on discrimination (c-statistic), calibration (assessed by calibration slope and intercept), Brier score, and decision analysis. An open access web application was developed for the best performing model and this web application can be found here: https://sorg-apps.shinyapps.io/spinemets/.

CONCLUSION

Machine learning algorithms are promising for prediction of postoperative outcomes in spinal oncology and these algorithms can be integrated into clinically useful decision tools. As the volume of data in oncology continues to grow, creation of learning systems and deployment of these systems as accessible tools may significantly enhance prognostication and management.

Artificial Intelligence and Machine Learning: A New Disruptive Force in Orthopaedics

Orthopaedics as a surgical discipline requires a combination of good clinical acumen, good surgical skill, a reasonable physical strength and most of all, good understanding of technology. The last few decades have seen rapid adoption of new technologies into orthopaedic practice, power tools, new implants, CAD-CAM design, 3-D printing, additive manufacturing just to name a few. The new disruption in orthopaedics in the current time and era is undoubtedly the advent of artificial intelligence and robotics. As these technologies take root and innovative applications continue to be incorporated into the main-stream orthopedics, as we know it today, it is imperative to look at and understand the basics of artificial intelligence and what work is being done in the field today. This article takes the form of a loosely structured narrative review and will introduce the reader to key concepts in the field of artificial intelligence as well as some of the directions in application of the same in orthopaedics. Some of the recent work has been summarised and we present our viewpoint at the conclusion as to why we must consider artificial intelligence as a disrupting positive influence on orthopaedic surgery.

Atypical diaphyseal femoral fractures: Considerations on surgical technique

In the last two decades bisphosphonates (BP) has become the mainstream therapy for osteoporosis and the benefit in reducing the incidence of fractures has been well demonstrated in several studies, together with the drug long term (5-10 years) efficacy and safety. A complication of the long-term use of bisphosphonates is a low-energy stress fractures located in the sub-trochanteric region and the femoral shaft called atypical femur fracture (AFF). These stress fractures can be seen on plain radiographs as simple transverse patterns, with unicortical beaking and hypertrophy of the diaphyseal lateral cortex. Usually a localized thigh pain in the prodromal phase may precede the fracture by months. The current surgical treatment of choice for AFFs is intramedullary nailing (IMN). However, the treatment of AFFs is associated with a higher rate of intra-operative and post-surgical complications. This is related to anatomical e biomechanical reasons. Iatrogenic fractures, deformities, medial gap opening, eccentric position of the distal nail tip with anterior cortex perforation, delayed or non-union are frequent complications of this procedure and healing rate of AFFs. The average healing time of almost 8 months for AFFs appeared to be longer than that for typical femoral fractures, which heal at an average of 3-6 months. The purpose of this study is to analyze the different surgical devices and techniques and to advance some considerations that can be useful to diminish the rate of failure and/or complications in the treatment of AFFs in both oncologic and osteoporotic patients.

Prediction of survival after surgical management of femoral metastatic bone disease - A comparison of prognostic models

Background

Operative fixation for femoral metastatic bone disease is based on the principles of reducing pain and restoring function. Recent literature has proposed a number of prognostic models for appendicular metastatic bone disease. The aim of this study was to compare the accuracy of proposed soring systems in the setting of femoral metastatic bone disease in order to provide surgeons with information to determine the most appropriate scoring system in this setting.

Methods

A retrospective cohort analysis of patients who underwent surgical management of femoral metastatic bone disease at a single institution were included. A pre-operative predicted survival for all 114 patients was retrospectively calculated utilising the revised Katagiri model, PathFx model, SSG score, Janssen nomogram, OPTModel and SPRING 13 nomogram. Univariate and multivariate Cox regression proportional hazard models were constructed to assess the role of prognostic variables in the patient group. Area under the receiver characteristics and Brier scores were calculated for each prognostic model from comparison of predicted survival and actual survival of patients to quantify the accuracy of each model.

Results

For the femoral metastatic bone disease patients treated with surgical fixation, multivariate analysis demonstrated a number of pre-operative factors associated with survival in femoral metastatic bone disease, consistent with established literature. The OPTIModel demonstrated the highest accuracy at predicting 12-month (Area Under the Curve [AUC] = 0.79) and 24-month (AUC = 0.77) survival after surgical management. PathFx model was the most accurate at predicting 3-month survival (AUC = 0.70) and 6-month (AUC = 0.70) survival. The PathFx model was successfully externally validated in the femoral patient dataset for all time periods.

Conclusions

Among six prognostic models assessed in the setting of femoral metastatic bone disease, the present study observed the most accurate model for 3-month, 6-month, 12-month and 24-month survival. The results of this study may be utilised by the treating surgical team to determine the most accurate model for the required time period and therefore improve decision-making in the care of patients with femoral metastatic bone disease.

Endoprosthetic Reconstruction for a Displaced Atypical Femoral Fracture in a Cancer Patient with Poor Prognosis

Zoledronate or denosumab treatment is beneficial for cancer patients with bone metastasis. However, each agent may trigger atypical femoral fractures. Incomplete atypical femoral fractures can be successfully treated with prophylactic intramedullary nailing. On the other hand, intramedullary nailing for displaced atypical femoral fractures occasionally causes problems with regard to bone healing, resulting in long-term treatment. In cancer patients with poor prognosis who experience atypical femoral fractures, improvement in activities of daily living should be the priority. Thus, we performed endoprosthetic reconstruction for a displaced atypical femoral fracture in a breast cancer patient with poor prognosis to enable walking in the early stage after the operation. Two weeks after the operation, she could successfully walk. The postoperative Musculoskeletal Tumor Society score was 47%, and it had improved to almost the preoperative level before injury (50%). In conclusion, endoprosthetic reconstruction for displaced atypical femoral fractures may be a first-line treatment approach to acquire early postoperative walking ability for improving activities of daily living in cancer patients with poor prognosis.

Treatment Modalities for Pathologic Fractures of the Proximal Femur Pertrochanteric Region: A Systematic Review and Meta-Analysis of Reoperation Rates

BACKGROUND

The proximal femur represents the most common site of metastatic bone disease in the appendicular skeleton, and associated pathologic pertrochanteric femur fractures contribute to cancer-related morbidity and mortality. Controversy exists as to whether these injuries are best managed with intramedullary nailing (IMN) or with arthroplasty.

METHODS

A systematic review of the literature was performed using a PubMed search following PRISMA guidelines to identify studies performed within the last 20 years regarding treatment of proximal femur metastatic lesions with either nailing or arthroplasty with a reported reoperation rate. Sixteen studies were selected for inclusion containing 1414 patients. Pooled estimates and 95% confidence intervals (CIs) for reoperation rates associated with IMN and endoprosthetic reconstruction (EPR) were separately calculated.

RESULTS

The pooled estimate for reoperation for IMN was a median of 9% (95% CI, 5%-14%) and the pooled estimate for reoperation for EPR was a median of 7% (95% CI, 5%-11%). Significant heterogeneity was present in studies reporting on both treatment modalities: for IMN, I² = 55%, and for EPR, I² = 51%.

CONCLUSION

This systematic literature review identified 16 eligible, nonrandomized, retrospective studies that reported on the results of surgical treatment for proximal femur metastatic disease. The pooled estimate of reoperation was similar between patients treated with IMN and EPR. Inconsistencies among follow-up and the study designs used limited evidence-based conclusions. As the oncologic care of patients with metastatic disease continues to evolve and improve, patient-specific needs must be carefully considered when selecting an optimal treatment strategy.

LEVEL OF EVIDENCE

Level III.

An Easy-to-Use Prognostic Model for Survival Estimation for Patients with Symptomatic Long Bone Metastases

BACKGROUND

A survival estimation for patients with symptomatic long bone metastases (LBM) is crucial to prevent overtreatment and undertreatment. This study analyzed prognostic factors for overall survival and developed a simple, easy-to-use prognostic model.

METHODS

A multicenter retrospective study of 1,520 patients treated for symptomatic LBM between 2000 and 2013 at the radiation therapy and/or orthopaedic departments was performed. Primary tumors were categorized into 3 clinical profiles (favorable, moderate, or unfavorable) according to an existing classification system. Associations between prognostic variables and overall survival were investigated using the Kaplan-Meier method and multivariate Cox regression models. The discriminatory ability of the developed model was assessed with the Harrell C-statistic. The observed and expected survival for each survival category were compared on the basis of an external cohort.

RESULTS

Median overall survival was 7.4 months (95% confidence interval [CI], 6.7 to 8.1 months). On the basis of the independent prognostic factors, namely the clinical profile, Karnofsky Performance Score, and presence of visceral and/or brain metastases, 12 prognostic categories were created. The Harrell C-statistic was 0.70. A flowchart was developed to easily stratify patients. Using cutoff points for clinical decision-making, the 12 categories were narrowed down to 4 categories with clinical consequences. Median survival was 21.9 months (95% CI, 18.7 to 25.1 months), 10.5 months (95% CI, 7.9 to 13.1 months), 4.6 months (95% CI, 3.9 to 5.3 months), and 2.2 months (95% CI, 1.8 to 2.6 months) for the 4 categories.

CONCLUSIONS

This study presents a model to easily stratify patients with symptomatic LBM according to their expected survival. The simplicity and clarity of the model facilitate and encourage its use in the routine care of patients with LBM, to provide the most appropriate treatment for each individual patient.

LEVEL OF EVIDENCE

Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Carbon-fiber reinforced intramedullary nailing in musculoskeletal tumor surgery: a national multicentric experience of the Italian Orthopaedic Society (SIOT) Bone Metastasis Study Group

INTRODUCTION

Carbon fiber reinforced (CFR) implants have been proposed for the treatment of fractures or impending fractures of the long bones in the oncology patient. Aim of this study is to present the largest cohort of oncology patients operated by CFR nailing by the Italian Orthopaedic Society (SIOT) Bone Metastasis Study Group.

METHODS

53 adult oncology patients were operated on with a CFR-PEEK nail. All the data from adjuvants therapies were collected. Bone callus formation, response to radiotherapy, relapse or progression of the osteolysis were recorded. Hardware survival and failure, breakage and need for implant revision were also analysed.

RESULTS

Anatomical implantation of nails include humerus (n = 35), femur (n =11) and tibia (n = 7). The most frequent tumors affecting the bone were myeloma (n = 13), breast (n = 11), lung (n = 8), and renal cell cancer (n = 7). Acrylic cement reinforcement was used in 2 patients. One patient was subjected to electrochemotherapy after nail insertion. Intraoperative and early postoperative complications occurred in 13.2% and 7.54% of patients respectively. Eight patients had local progression and one developed a stress fracture proximally to the distal static screw. Radiographic union occurred in 14 patients; one screw loosening was recorded.

DISCUSSION

There is currently a lack of solid evidence on the clinical use of CFR nails in oncologic patients. This is the first and largest study of CFR nailing, with the longest available follow up.

CONCLUSIONS

Implant related complications and surgery-related morbidity should be taken into account in the decision-making process for the surgical management of these patients. These data can improve the surgeon-patient communication and guide further studies on patients' survival and complications with respect to surgery.

Can A Multivariate Model for Survival Estimation in Skeletal Metastases (PATHFx) Be Externally Validated Using Japanese Patients?

BACKGROUND

Objective survival estimates are important when treating or studying outcomes in patients with skeletal metastases. One decision-support tool, PATHFx (www.pathfx.org) is designed to predict each patient's postsurgical survival trajectory at 1, 3, 6, and 12 months in patients undergoing stabilization for skeletal metastases. PATHFx has been externally validated in various western centers, but it is unknown whether it may be useful in Asian patient populations.

QUESTIONS/PURPOSES

We asked (1) whether the PATHFx models are as predictive in Japanese patients by estimating the area under the receiver operator characteristic curve (AUC); we considered an AUC greater than 0.7 as an adequate predictive value. We also (2) performed decision curve analysis at various times to determine whether and how PATHFx should be used clinically at those times.

PATIENTS AND METHODS

A Bayesian model is a statistical method to explore conditional, probabilistic relationships between variables to estimate the likelihood of an outcome using observed data. We applied the PATHFx Bayesian models to an independent dataset containing the records of patients who underwent skeletal stabilization for metastatic bone disease at one of five Japanese referral centers and had a followup longer than 12 months for survivors. Of 270 patients in the database, we excluded nine patients from analysis because their followup was less than 12 months, and finally we included 261 patients in the analysis. Data examined included age at the time of surgery, sex, indication for surgery (impending fracture or completed pathologic fracture), number of bone metastases (solitary or multiple), presence or absence of visceral or lymph node metastases, preoperative hemoglobin concentration, absolute lymphocyte count, and the primary oncologic diagnosis. We performed receiver operating characteristic curve analysis and estimated the AUC as a measure of discriminatory ability. Decision curve analysis was performed to determine if and how the models should be used in the clinical setting.

RESULTS

The AUCs for the 1-, 3-, 6-, and 12-month models were 0.77 (95% CI, 0.63-0.86), 0.80 (95% CI, 0.72-0.87), 0.83 (95% CI, 0.77-0.89), and 0.80 (95% CI, 0.75-0.86), respectively. Decision analysis indicated that the models conferred a positive net benefit (above the lines assuming none or all survive at each time) although the CIs of the AUC for 1 month were wide, suggesting that this dataset could not adequately predict 1-month survival.

CONCLUSIONS

Our findings show PATHFx is suitable for clinical use in Japan and may be used to guide surgical decision making or as a risk stratification method in support of clinical trials involving Japanese patients at 3, 6, and 12 months. More studies will be necessary to confirm the validity of the 1-month survival predictions of this mode. Other patient populations will need to be studied to confirm its usefulness in other non-Western and non-Japanese populations.

LEVEL OF EVIDENCE

Level II, prognostic study.

Can We Estimate Short- and Intermediate-term Survival in Patients Undergoing Surgery for Metastatic Bone Disease?

BACKGROUND

Objective means of estimating survival can be used to guide surgical decision-making and to risk-stratify patients for clinical trials. Although a free, online tool ( www.pathfx.org ) can estimate 3- and 12-month survival, recent work, including a survey of the Musculoskeletal Tumor Society, indicated that estimates at 1 and 6 months after surgery also would be helpful. Longer estimates help justify the need for more durable and expensive reconstructive options, and very short estimates could help identify those who will not survive 1 month and should not undergo surgery. Thereby, an important use of this tool would be to help avoid unsuccessful and expensive surgery during the last month of life.

QUESTIONS/PURPOSES

We seek to provide a reliable, objective means of estimating survival in patients with metastatic bone disease. After generating models to derive 1- and 6-month survival estimates, we determined suitability for clinical use by applying receiver operator characteristic (ROC) (area under the curve [AUC] > 0.7) and decision curve analysis (DCA), which determines whether using PATHFx can improve outcomes, but also discerns in which kinds of patients PATHFx should not be used.

METHODS

We used two, existing, skeletal metastasis registries chosen for their quality and availability. Data from Memorial Sloan-Kettering Cancer Center (training set, n = 189) was used to develop two Bayesian Belief Networks trained to estimate the likelihood of survival at 1 and 6 months after surgery. Next, data from eight major referral centers across Scandinavia (n = 815) served as the external validation set-that is, as a means to test model performance in a different patient population. The diversity of the data between the training set from Memorial Sloan-Kettering Cancer Center and the Scandinavian external validation set is important to help ensure the models are applicable to patients in various settings with differing demographics and treatment philosophies. We considered disease-specific, laboratory, and demographic information, and the surgeon's estimate of survival. For each model, we calculated the area under the ROC curve (AUC) as a metric of discriminatory ability and the Net Benefit using DCA to determine whether the models were suitable for clinical use.

RESULTS

On external validation, the AUC for the 1- and 6-month models were 0.76 (95% CI, 0.72-0.80) and 0.76 (95% CI, 0.73-0.79), respectively. The models conferred a positive net benefit on DCA, indicating each could be used rather than assume all patients or no patients would survive greater than 1 or 6 months, respectively.

CONCLUSIONS

Decision analysis confirms that the 1- and 6-month Bayesian models are suitable for clinical use.

CLINICAL RELEVANCE

These data support upgrading www.pathfx.org with the algorithms described above, which is designed to guide surgical decision-making, and function as a risk stratification method in support of clinical trials. This updating has been done, so now surgeons may use any web browser to generate survival estimates at 1, 3, 6, and 12 months after surgery, at no cost. Just as short estimates of survival help justify palliative therapy or less-invasive approaches to stabilization, more favorable survival estimates at 6 or 12 months are used to justify more durable, complicated, and expensive reconstructive options.

Metastatic epidural spinal cord compression

INTRODUCTION

Metastatic epidural spinal cord compression (MESSC) is a frequent event in patients affected by solid tumor metastases. Current available approaches for MESCC include corticosteroids, radiotherapy and surgery. In the last few years, surgery has evolved from decompression by laminectomy alone, with the introduction of instrumentation systems by metalware (screws and hooks), and this has been associated to an improvement of clinical results compared to radiotherapy alone. Areas covered: In this narrative review, we outline the phases of management of cancer patients affected by MESSC, and discuss the timing of treatments, their impact on the Quality of life (QoL), and the relative benefits and harms of surgery and radiotherapy. Expert commentary: Despite the fact that clinical and surgical trials will be required to determine the most appropriate surgical technique and timing of surgery, we do expect a newer and more important role for radiotherapy in the management of MESCC patients in the next future. In particular, the implementation of radiotactic stereosurgery as adjuvant to decompressive surgery is expected to increase in the next few years, above all in those patients that can be candidate to the so called separation surgery.

Fractures in bone tumour prosthesis

PURPOSE

The aim of the present narrative review is to report the different aspects related to the fractures around tumour prosthetic implants in terms of technical and medical issues.

METHODS

A non systematic literature review on the topic was performed.

RESULTS

Given the increased rate of limb salvage procedures and megaprostheses implanted for bone tumours, the increased number of osteoporotic periprosthetic fractures, and the burden of revision arthroplasty, the number of surgeries using endoprosthetic implants is likely to increase in the near future. Surgeons will face more frequently the complications related to tumour endoprosthetic implant. Endoprosthetic reconstruction has a higher risk of intra-operative and post-operative complications compared to conventional prosthetic replacement.

CONCLUSIONS

Very rare reports and recommendations are available in literature regarding the treatment of periprosthetic fractures after megaprosthesis, and there is currently no consensus about which should be the standard management for periprosthetic fractures in this population of patients.