Elsevier

The Journal of Arthroplasty

Volume 31, Issue 8, August 2016, Pages 1654-1660
The Journal of Arthroplasty

Health Policy & Economics
Development of a Prognostic Nomogram for Predicting the Probability of Nonresponse to Total Knee Arthroplasty 1 Year After Surgery

https://doi.org/10.1016/j.arth.2016.02.003Get rights and content

Abstract

Background

Indications for total knee arthroplasty (TKA) currently depend on clinical judgment. Up to one fifth of those who undergo primary TKA do not report a clinically meaningful improvement in pain and function after surgery. Our aim was to develop and internally validate a prognostic tool for predicting the probability of nonresponse to surgery at 12 months.

Methods

Patients from 1 center who underwent primary TKA (N = 615) between 2012 and 2013. The Western Ontario and McMaster Universities Arthritis Index was collected pre- and 12 months after TKA from which nonresponse to surgery was determined using the Outcome Measures in Rheumatology-Osteoarthritis Research Society International responder criteria. Using independent prognostic correlates of postoperative nonresponse observed in adjusted modeling, we derived a prognostic nomogram to estimate the probability of nonresponse to TKA based on this suite of explanatory variables.

Results

A total of 90/615 (15%) cases were nonresponders to TKA. The degree of contribution (odds ratio, 95% confidence interval) of each explanatory factor to nonresponse nomogram points was body mass index ≥40 kg/m2 (3.48; 1.97-6.12), Kellgren and Lawrence <4 (2.59; 1.58-4.24), mental disability on Short Form Health Survey (SF-12) mental component score (3.30; 1.44-7.58), and every 10-point increase in preoperative Western Ontario and McMaster Universities Arthritis Index score (0.81; 0.68-0.97). The concordance index for this model was 0.74.

Conclusion

We have created a prognostic nomogram that displays the predictive probabilities of nonresponse to TKA as a source of decision support for clinicians and patients, about their likely functional outcome from TKA. Although our own internal validation suggested good nomogram performance, external validation in a comparable surgical population is required to confirm generalizability of the nomogram.

Section snippets

Study Setting and Participants

This study was conducted at a university-affiliated tertiary hospital in Melbourne, Australia. All patients admitted to the hospital who underwent a primary elective TKA between January 2012 and December 2013 were considered eligible for study inclusion.

Data Collection

The hospital houses the SMART Registry, which is a clinical registry of all elective lower limb joint arthroplasties performed at the institution since 1998. As previously described, data collection and storage include an extensive range of

Study Population

There were 626 primary elective TKAs performed in 562 patients all of whom had complete baseline data. Eleven cases did not complete a WOMAC at 12 months due to death (n = 5), declined to complete survey (n = 3), and relocated overseas (n = 3). These cases were excluded, leaving 615/626 (98%) with complete baseline and follow-up data for analysis. In total, 90/615 (15%) cases did not achieve the cut point for response to surgery according to the OMERACT-OARSI criteria and were deemed

Discussion

We have created a prognostic nomogram that displays the predictive probabilities of nonresponse to surgery as a source of decision support for health care professionals and patients, about their likely functional outcome from TKA. We constructed our prediction tool in the form of a nomogram given its wide use in many areas of medicine and its superior accuracy in clinical prediction when compared with clinician predictions 23, 24. To our knowledge, however, this is the first tool to accurately

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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 http://dx.doi.org/10.1016/j.arth.2016.02.003.

    Michelle M. Dowsey is the recipient of an NHMRC Early Career Australian Clinical Fellowship (APP1035810). Tim Spelman is the recipient of an NHMRC Postgraduate Public Health Scholarship (APP1055761).

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