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. 2021 Oct;36(10):3367-3371.
doi: 10.1016/j.arth.2021.06.002. Epub 2021 Jun 30.

Adjusted Survival Curves Improve Understanding of Multivariable Cox Model Results

Carly S Lundgreen  1 , Dirk R Larson  1 , Elizabeth J Atkinson  1 , Katrina L Devick  2 , David G Lewallen  3 , Daniel J Berry  3 , Hilal Maradit Kremers  4 , Cynthia S Crowson  5
Affiliations

Adjusted Survival Curves Improve Understanding of Multivariable Cox Model Results

Carly S Lundgreen et al. J Arthroplasty. 2021 Oct.

Abstract

Kaplan-Meier survival curves are the most common methods for unadjusted group comparison of outcomes in orthopedic research. However, they may be misleading due to an imbalance of confounders between patient groups. The Cox model is frequently used to adjust for confounders, but graphical display of adjusted survival curves is not commonly utilized. We describe the circumstances when adjusted survival curves are useful in orthopedic research, describe and use 2 different methods to obtain adjusted curves, and illustrate how they can improve understanding of the multivariable Cox model results. We further provide practical strategies for identifying the need for and performing adjusted survival curves. Please visit the followinghttps://youtu.be/ys0hy2CiMCAfor a video that explains the highlights of the paper in practical terms.

Keywords: Cox model; confounding; survival analysis; survival curves; total joint arthroplasty.

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Figures

Figure 1.
Figure 1.
Survival curves by surgical indication for total knee arthroplasty: unadjusted (Panel A), adjusted using inverse probability weighting (Panel B) and adjusted using Cox model with direct adjustment (Panel C).
See this image and copyright information in PMC

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