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

Meares, Charles; Badran, Alexander; Dewar, David

doi:10.1016/j.jbo.2019.100225

Cited by 32 publications

(42 citation statements)

References 39 publications

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“…The validation of the 1‐, 6‐, 18‐, and 24‐month models also demonstrated AUCs above the 0.70 threshold. This is consistent with the previous studies that used Scandinavian and Australian patient data 7,9 . While all of the AUCs were above 0.70 for all time points in this study, the confidence intervals of the 1‐ and 3‐month AUCs using the Japanese data set spanned 0.7.…”

Section: Discussionsupporting

confidence: 91%

“…Additionally, the Brier scores demonstrate that all models accurately predict the survival in both the Scandinavian and Japanese data sets. This is consistent with the findings of the recent study the original PATHFx model, which measured the Brier scores in the 3‐, 6‐, 12‐month models using an Australian patient data set 9 …”

Section: Discussionsupporting

confidence: 91%

“…Finally, 18‐ and 24‐month models were added to provide a comprehensive survival profile. These final two models were externally validated in Australian patients 9 …”

Section: Introductionmentioning

confidence: 99%

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

Overmann¹,

Clark²,

Tsagozis

et al. 2020

Journal Orthopaedic Research

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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.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 91%

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

Overmann¹,

Clark²,

Tsagozis

et al. 2020

Journal Orthopaedic Research

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“…Estimating survival and correlating choice of implant to survival estimates, prevents too extensive surgery and rehabilitation in patients with short survival and an unacceptably high implant failure rate in those who live longer. As externally validated survival models that are free to use exist, there are no reasons not to do so[ 28 - 31 , 32 ]. There are generally three treatment strategies: Osteosynthesis, prosthetic reconstruction or local excision with or without reconstruction ( i.e ., curettage with or without cementation, cementoplasty, excision arthroplasty, resection of a bone segment or amputation).…”

Section: Methods and Outcome Of Surgical Treatmentmentioning

confidence: 99%

Current concepts in the surgical treatment of skeletal metastases

Ehne

Tsagozis

2020

WJO

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Symptomatic metastatic bone disease affects a large proportion of patients with malignant tumours and significantly impairs patients’ quality of life. There are still controversies regarding both surgical indications and methods, mainly because of the relatively few high-quality studies in this field. Generally, prosthetic reconstruction has been shown to result in fewer implant failures and should be preferred in patients with a good prognosis. Survival estimation tools should be used as part of preoperative planning. Adjuvant treatment, which relies on radiotherapy and inhibition of osteoclast function may also offer symptomatic relief and prevent implant failure. In this review we discuss the epidemiology, indications for surgery, preoperative planning, surgical techniques and adjuvant treatment of metastatic bone disease.

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“… 17 Some studies have used the CPT and ICD codes to define cohorts of patients with metastatic disease of the femur, 17 whereas others do not explicitly state the criteria or methodology that were used to identify patient cohorts. 12 13 14 15 16 , 18 - 20 Efforts to produce studies with larger sample sizes will likely rely on structured data to identify patient cohorts. A lack of understanding of the characteristics and accuracy of cohorts defined by ICD and CPT codes could lead to biased conclusions.…”

mentioning

confidence: 99%

Utility of the Current Procedural Terminology Codes for Prophylactic Stabilization for Defining Metastatic Femur Disease

et al. 2020

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Introduction: Cohorts from the electronic health record are often defined by the Current Procedural Terminology (CPT) codes. The error prevalence of CPT codes for patients receiving surgical treatment of metastatic disease of the femur has not been investigated, and the predictive value of coding ontologies to identify patients with metastatic disease of the femur has not been adequately discussed. Methods: All surgical cases at a single academic tertiary institution from 2010 through 2015 involving prophylactic stabilization of the femur or fixation of a pathologic fracture of the femur were identified using the CPT and International Classification of Disease (ICD) codes. A detailed chart review was conducted to determine the procedure performed as documented in the surgical note and the patient diagnosis as documented in the pathology report, surgical note, and/or office visit notes. Results: We identified 7 CPT code errors of 171 prophylactic operations (4.1%) and one error of 71 pathologic fracture fixation s(1.4%). Of the 164 prophylactic operations that were coded correctly, 87 (53.0%) had metastatic disease. Of the 70 pathologic operations that were coded correctly, 41 (58%) had metastatic disease. Discussion: The error prevalence was low in both prophylactic stabilization and pathologic fixation groups (4.1% and 1%, respectively). The structured data (CPT and ICD-9 codes) had a positive predictive value for patients having metastatic disease of 53% for patients in the prophylactic stabilization group and 58% for patients in the pathologic fixation group. The CPT codes and ICD codes assessed in this analysis do provide a useful tool for defining a population in which a moderate proportion of individuals have metastatic disease in the femur at an academic medical center. However, verification is necessary.

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

Cited by 32 publications

References 39 publications

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

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

Current concepts in the surgical treatment of skeletal metastases

Utility of the Current Procedural Terminology Codes for Prophylactic Stabilization for Defining Metastatic Femur Disease

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