ArticleClinical orthopaedics and related research2020
External Validation of PATHFx Version 3.0 in Patients Treated Surgically and Nonsurgically for Symptomatic Skeletal Metastases.
Article in Clinical orthopaedics and related research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.
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Who cites it
41 citing papers in PubMed, 2 syntheses or guidelines pooled it, 97 citations in OpenAlex.
- Artificial intelligence applied to musculoskeletal oncology: a systematic review.Skeletal radiology · 2022Pooled it
- Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review.Acta orthopaedica · 2021Pooled it
- Article
- Predicting survival of patients with spinal involvement in multiple myeloma using PATHFx 3.0 - a validation study of 100 patients in Germany.World journal of surgical oncology · 2026Article
- Differential survival outcomes in upper versus lower extremity metastatic bone disease: a retrospective comparative cohort analysis.Journal of orthopaedic surgery and research · 2025Article
- Artificial Intelligence in bone Metastases: A systematic review in guideline adherence of 92 studies.Journal of bone oncology · 2025Review
- What Factors Are Associated With Implant Revision in the Treatment of Pathologic Subtrochanteric Femur Fractures?Clinical orthopaedics and related research · 2025Article
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- 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.Clinical orthopaedics and related research · 2024Article
- Reply to the Letter to the Editor: Are Current Survival Prediction Tools Useful When Treating Subsequent Skeletal-related Events From Bone Metastases?Clinical orthopaedics and related research · 2024Article
- Management of metastatic bone disease of the pelvis: current concepts.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2024Review
- Prognostic factors and real-life applicability of prognostic models for patients with bone metastases of carcinoma.Acta orthopaedica et traumatologica turcica · 2024Article
- The Importance of Awaiting Biopsy Results in Solitary Pathological Proximal Femoral Fractures : Do We Need to Biopsy Solitary Pathological Fractures?Annals of surgical oncology · 2023Article
- Functional outcomes after open reconstruction or nonoperative management of 81 pathologic acetabular fractures from metastatic bone disease.Journal of orthopaedics · 2023Article
- Bone Mass Changes Following Percutaneous Radiofrequency Ablation, Osteoplasty, Reinforcement, and Internal Fixation of Periacetabular Osteolytic Metastases.Journal of clinical medicine · 2023Article
- Comparison of eight modern preoperative scoring systems for survival prediction in patients with extremity metastasis.Cancer medicine · 2023Article
- Artificial Intelligence and Predictive Modeling in Spinal Oncology: A Narrative Review.International journal of spine surgery · 2023Article
- What are the indications and survivorship of tumor endoprosthetic reconstructions for patients with extremity metastatic bone disease?Journal of surgical oncology · 2023Review
- 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.Journal of orthopaedic surgery and research · 2023Observational
- Fifty years of bone tumors.Journal of surgical oncology · 2022Article
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6 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundPATHFx 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.
methodsAfter 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]).
resultsThe 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.
conclusionsWe 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.
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