Elsevier

The Journal of Arthroplasty

Volume 34, Issue 11, November 2019, Pages 2624-2631
The Journal of Arthroplasty

Primary Arthroplasty
Clinical and Statistical Validation of a Probabilistic Prediction Tool of Total Knee Arthroplasty Outcome

https://doi.org/10.1016/j.arth.2019.06.007Get rights and content

Abstract

Background

Predicting patients at risk of a poor outcome would be useful in patient selection for total knee arthroplasty (TKA). Existing models to predict outcome have seen limited functional implementation. This study aims to validate a model and shared decision-making tool for both clinical utility and predictive accuracy.

Methods

A Bayesian belief network statistical model was developed using data from the Osteoarthritis Initiative. A consecutive series of consultations for osteoarthritis before and after introduction of the tool was used to evaluate the clinical impact of the tool. A data audit of postoperative outcomes of TKA patients exposed to the tool was used to evaluate the accuracy of predictions.

Results

The tool changed consultation outcomes and identified patients at risk of limited improvement. After introduction of the tool, patients booked for surgery reported worse Knee Osteoarthritis and Injury Outcome Score pain scores (difference, 15.2; P < .001) than those not booked, with no significant difference prior. There was a 27% chance of not improving if predicted at risk, and a 1.4% chance if predicted to improve. This gives a risk ratio of 19× (P < .001) for patients not improving if predicted at risk.

Conclusion

For a prediction tool to be clinically useful, it needs to provide a better understanding of the likely clinical outcome of an intervention than existed without its use when the clinical decisions are made. The tool presented here has the potential to direct patients to surgical or nonsurgical pathways on a patient-specific basis, ensuring patients who will benefit most from TKA surgery are selected.

Section snippets

Model Generation

A BBN was developed using a publicly accessible database created and maintained by the National Institutes of Health Osteoarthritis Initiative (OAI) (available at https://data-archive.nimh.nih.gov/oai/). The OAI is a multicenter, longitudinal, prospective observational study of knee OA based in the United States, recruiting from Brown University, Ohio State University, the University of Maryland/Johns Hopkins University joint center, and the University of Pittsburgh in Pennsylvania. Data

Consecutive Case Series Validation

For the consecutive case series cohort, the demographics and difference in pain scores preoperatively between the 2 groups are shown in Table 1, showing no difference between the 2 groups.

The use of the tool’s predictions during consultation did not significantly change the proportion of patients booked for TKA surgery. Without the use of the tool’s predictions, 20 patients (26.7%) were booked for surgery, and with use of the tool, 24 patients (32%) were booked for surgery (P = .44). However, a

Discussion

This study demonstrates validation of a shared decision-making tool in the prediction of outcome by demonstrating a moderately strong correlation between predicted and actual improvements in KOOS. Patients predicted at risk of not improving were found to be 19.3 times more likely to not meet the MCID. This study also validated clinical utility of tool by demonstrating a change in the characteristic preoperative KOOS pain scores of patients booked for surgery before and after introduction of the

Conclusion

In order to be useful clinically, a prediction tool has to provide outputs that are accurate and can be integrated easily with consultation workflows. Indications for TKA are complex, and selecting patients for surgery based on prediction of outcome alone may not be reasonable given the limitations of prediction tools. Instead, prediction tools should aim to communicate information to both patients and surgeons, highlight potentially modifiable risk factors, and enable a shared decision-making

Acknowledgments

The OAI is a public-private partnership comprised of 5 contracts (N01-AR-2-2258; N01-AR-2-2259; N01-AR-2-2260; N01-AR-2-2261; N01-AR-2-2262) funded by the National Institutes of Health, a branch of the Department of Health and Human Services, and conducted by the OAI Study Investigators. Private funding partners include Merck Research Laboratories; Novartis Pharmaceuticals Corporation, GlaxoSmithKline, and Pfizer, Inc Private sector funding for the OAI is managed by the Foundation for the

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    One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to https://doi.org/10.1016/j.arth.2019.06.007.

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