Abstract
Background: Predicting survival for patients with metastatic bone disease in the extremities (MBDex) is important for ensuring the implant will outlive the patient. Hitherto, prediction models for these patients have been constructed using subjective assessments, mostly lacking biochemical variables. Objectives: To develop a prediction model for survival after surgery due to MBDex using biochemical variables and externally validate the model. Methods: We created Bayesian Belief Network models to estimate likelihood of survival 1, 3, 6, and 12 months after surgery using 140 patients. We validated the models using the data of 130 other patients and calculated the area under the Receiver Operator Characteristic curve (ROC). Variables included: hemoglobin, neutrophil-count, C-reactive protein, alkaline phosphatase, primary cancer, Karnofsky-score, ASA-score, visceral metastases, bone metastases, days from diagnose of primary cancer to index surgery for MBDex, ischemic heart disease, diabetes, fracture/impending-fracture and age. Results: Survival probabilities were influenced by all biochemical variables. Validation showed ROC for the 1, 3, 6, and 12-months model: 68% (C.I.: 55%-80%), 69% (C.I.: 60%-78%), 81% (C.I.: 74%-87%) and 84% (C.I.: 77%-90%). Conclusion: Biochemical markers can be incorporated into a prediction model for survival in patients having surgery for MBDex allowing surgeons to offer more objective and individualized treatment options.
Highlights
Successful treatment of metastatic bone disease in the extremities (MBDex) requires a multidisciplinary approach
Biochemical markers can be incorporated into a prediction model for survival in patients having surgery for MBDex allowing surgeons to offer more objective and individualized treatment options
We aim to investigate if a multivariate prediction model for survival after surgery due to MBDex can be built using biochemical variables and ; investigate how such model perform in an external validation
Summary
Successful treatment of metastatic bone disease in the extremities (MBDex) requires a multidisciplinary approach. In case of a pathological fracture or intractable pain, surgery is often necessary [3]. Various surgical implants such as internal fixation devices or joint replacement prostheses can be used, but each has different indications, complication profiles and rehabilitation requirements. To determine which patients may benefit from surgery, and, to determine whether a more durable implant may be necessary, surgeons need a tool that can help predict each patient’s residual life expectancy. The definitive surgical strategy is often considered within a multidisciplinary environment Factors such as anatomical location of the metastatic lesion, information regarding the primary cancer causing the lesion, and the general health status of the patient influence surgical decision-making. Prediction models for these patients have been constructed using subjective assessments, mostly lacking biochemical variables
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