Related Experiment Video
Updated: May 17, 2025
Assessment of Bone Fracture Healing Using Micro-Computed Tomography
Published on: December 9, 2022
An External Validation of the Pathologic Fracture Mortality Index for Predicting 30-day Postoperative Morbidity Using
Joseph O Werenski1, Marie W Su, Ryan K Krueger
1From the Orthopaedic Oncology Service, Department of Orthopaedic Surgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA (Werenski, Su, Krueger, Groot, Clunk, Sodhi, Patil, Bell, and Lozano-Calderon), and the Division of Oncology, Department of Orthopaedic Surgery, Johns Hopkins Medicine, Baltimore, MD (Levin).
The Pathologic Fracture Mortality Index (PFMI) showed limited accuracy in predicting 30-day morbidity for patients with bone metastases. While it outperformed other indices for utilization morbidity, further refinement is needed for better risk stratification in metastatic bone disease.
Area of Science:
- Orthopedic Surgery
- Oncology
- Medical Statistics
Background:
- Skeletal metastases frequently cause pathologic fractures, leading to pain and functional decline.
- Predicting postoperative morbidity in these complex cases is challenging.
- The Pathologic Fracture Mortality Index (PFMI) was developed to assess 30-day morbidity after surgical fixation of long bone fractures due to metastases.
Purpose of the Study:
- To externally validate the PFMI's predictive accuracy for 30-day medical, surgical, utilization, and all-cause morbidity in patients with long bone metastases.
- To compare the PFMI's performance against established indices: American Society of Anesthesiologists (ASA) classification, modified 5-Item Frailty Index (mF-I5), and modified Charlson Comorbidity Index (mCCI).
Main Methods:
- Analysis of 978 patients undergoing internal fixation for pathologic fractures at two tertiary centers.
- Calculation of the area under the receiver operating characteristic curve (AUC) for each index to evaluate predictive accuracy.
- Comparison of PFMI against ASA, mF-I5, and mCCI for various morbidity outcomes.
Main Results:
- All tested indices, including PFMI, demonstrated suboptimal predictive performance (AUCs 0.45-0.62).
- PFMI showed superior prediction for utilization morbidity compared to ASA, mF-I5, and mCCI.
- PFMI also outperformed ASA for medical and all-cause morbidity, but not mF-I5 or mCCI.
Conclusions:
- Current predictive indices, including PFMI, require significant refinement for accurate morbidity risk stratification in metastatic bone disease.
- Updating these tools with current data and identifying novel prognostic factors are crucial for improving patient care.
