RESEARCH ARTICLE


Biochemical Variables are Predictive for Patient Survival after Surgery for Skeletal Metastasis. A Prediction Model Development and External Validation Study



Michala Skovlund Sørensen1, *, Elizabeth C. Silvius2, Saniya Khullar2, Klaus Hindsø3, Jonathan A. Forsberg4, 5, Michael Mørk Petersen1
1 Department of Orthopedic Surgery, Musculoskeletal Tumor Section Rigshospitalet, University of Copenhagen, København, Denmark
2 DecisionQ, Inc. Washington, D.C., US
3 Department of Orthopedic Surgery, Pediatric Orthopedics Section Rigshospitalet, University of Copenhagen, København, Denmark
4 Orthopaedics, USU-Walter Reed Department of Surgery, Bethesda, MD, USA
5 Division of Orthopaedic Oncology, Johns Hopkins University, Baltimore, MD, USA


Article Metrics

CrossRef Citations:
1
Total Statistics:

Full-Text HTML Views: 1424
Abstract HTML Views: 448
PDF Downloads: 206
ePub Downloads: 210
Total Views/Downloads: 2288
Unique Statistics:

Full-Text HTML Views: 680
Abstract HTML Views: 313
PDF Downloads: 162
ePub Downloads: 168
Total Views/Downloads: 1323



Creative Commons License
© 2018 Sørensen et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Orthopedic Surgery, Musculoskeletal Tumor Section Rigshospitalet, University of Copenhagen, Denmark; E-mail: Michala.skovlund@gmail.com


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.

Keywords: Metastatic bone disease, Biochemical, Survival prediction, Surgery, MBDex, Receiver Operator Characteristic curve (ROC).