Clinical Orthopaedics and Related Research: January 2017 - Volume 475 - Issue 1 - p 160–167 doi: 10.1007/s11999-016-4886-0 Symposium: 2016 Knee Society Proceedings

Can Original Knee Society Scores Be Used to Estimate New 2011 Knee Society Scores?

Odum, Susan, M., PhD1,a; Fehring, Thomas, K., MD2On Behalf of Knee Society Crosswalk Writing Group

Background The Knee Society Score (KSS) instrument is one of the most commonly reported primary outcome measures for total knee arthroplasty (TKA). Originally developed in 1989, the KSS was expanded and updated in 2011; however, the original KSS does not directly translate into the 2011 KSS. To date, no conversion algorithm has been developed, hindering the ability of researchers to adopt the 2011 KSS while maintaining their historical/longitudinal original KSS data.


Questions/purposes The purpose of this study is to develop regression equations to map the original KSS to the 2011 KSS, allowing original and 2011 KSS data sets to be combined.


Methods In this multicenter, nonrandomized study, a convenience sample of 815 patients undergoing primary TKA completed the original KSS questionnaire and the 2011 KSS questionnaire. Additionally, patient gender, patient age, and patient ethnicity were recorded. These data were then used to generate regression models to estimate the 2011 objective and function KSS from the original KSS. Of the 815 study patients, 476 (58%) were female and 339 (42%) were male at an average age of 67 years (SD 9.4). Roughly half of patients were assessed preoperatively (430 of 815 [53%]) with the remaining patients assessed postoperatively (386 of 815 [47%]). The average followup for postoperative patients was 4.4 years (SD 3.5 years).


Results We have created a spreadsheet that can be used by individuals with no statistical training to crosswalk the objective and function subscores from the original KSS to the 2011 KSS [Supplemental materials are available with the online version of CORR®.]. The predictive model very accurately estimated the 2011 objective score, on average, within 0.22 points on the 100-point 2011 objective KSS at the cohort or aggregate level. The objective model accurately estimated the 2011 objective KSS within 8.83 points, on average, of the actual 2011 objective KSS at the individual patient level. However, as a result of large outliers, 37% of the estimated 2011 objective KSS were greater than 10 points from the actual 2011 objective KSS. To illustrate, if you use the model to estimate the 2011 objective KSS on a cohort of 100 patients, a patient with an original objective KSS of 88 will have an estimated objective KSS between 79 and 97 points. On the other hand, if you calculate an average original objective KSS of 88 for all 100 patients, the estimated average 2011 objective KSS will be 88 for the group. The predictive model accurately estimated the 2011 function KSS within 0.14 points on the 1000-point 2011 function KSS at the cohort level. At the patient level, the 2011 function KSS was also estimated within 8.8 points of the actual 2011 function KSS. However, 43% of the estimated function scores were greater than 10 points of the actual 2011 function KSS.


Conclusions Clinicians and researchers can input their original KSS with demographic data into these equations to estimate the 2011 KSS objective and function scores. The small prediction error of 0.22 points that we calculated indicates that these models can be used to estimate the 2011 objective and function KSS at the aggregated cohort level. Although the average error score was within 10 points at the individual patient level, there was a high percentage of large errors resulting from outliers in the data set. These outliers seemed to be related to patients with excellent range of motion who had substantial pain and limited function or patients who have poor range of motion with excellent function and little pain. This may be inherent with the KSS or with the study sample. Nevertheless, one must use caution when estimating at the patient level. Additionally, the accuracy of the prediction scores decreases if any of the demographic variables included in this study are not available.

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