This work is published in Skeletal Radiology (https://doi.org/10.1007/s00256-024-04627-1).
The tool was developed based on the following dependencies:
- NumPy
- Scipy
- Pandas
- Lifelines
- Statistics
- Matplotlib
- Sksurv
- Sklearn
- Jupyter Notebooks
All data files for this project are stored within the folder 'OAI_SBL_Analysis_Data'. Within this folder all information for patients regarding demographics, TKR, BML size, and SBL can be found.
Notice: You must update the path to this folder within each script before conducting Cox Proportional Hazards or Kaplan-Meier Analysis.
loc_data = "~/OAI_SBL_Analysis_Data/" --> path to data
loc_module = "~/OAI_Github_scripts/" --> path to analysis scripts
These scripts can be found under the 'Kaplan_Meier_Analysis' folder. By running these you will be able to generate Figures 2A and 2B from the paper.
Notice: When saving figures from Kaplan-Meier analysis, be sure to change the path to your suited location.
plt.savefig('~/KMF_Curves/kmf_BML.pdf', format='pdf', bbox_inches = 'tight')
These scripts can be found under the 'CPH_Analysis' folder. By running these you will be able to generate the other figures from the paper.
Notice: When saving figures from CPH analysis, be sure to change the path to your suited location.
plt.savefig('~AUC_Curves/AUC_ALL_Knees_SBL_BML_figure_all_SBL.pdf', format='pdf', bbox_inches = 'tight')
Each CPH Analysis script will produce a time-dependent AUC, Concordance Index, and Brier Score. Kaplan-Meier Analysis scripts will generate Kaplan Meier curves and the Log-Rank test associated with each curve. Generated figures are located in ~/AUC_Curves/ and ~/KMF_Curves/.