Biomechanics and Movement Science Program, University of Delaware, Newark, Delaware.
Division of Physical Therapy, Department of Rehabilitation Medicine, University of Minnesota Medical School, Minneapolis, Minnesota.
J Bone Joint Surg Am. 2022 Apr 20;104(8):723-731. doi: 10.2106/JBJS.20.02233. Epub 2022 Feb 22.
Anterior cruciate ligament (ACL) registries do not all use the same patient-reported outcome measures, limiting comparisons and preventing pooling of data for meta-analysis. Our objective was to create a statistical crosswalk to convert cohort and registry mean Knee Injury and Osteoarthritis Outcome Scores (KOOS) to International Knee Documentation Committee-Subjective Knee Form (IKDC-SKF) scores and vice versa to allow these comparisons.
Data from 3 ACL registries were pooled (n = 14,412) and were separated into a training data set (70% of the sample) or a validation data set (30% of the sample). The KOOS and the IKDC-SKF scores were available prior to the operation and at 1, 2, and 5 or 6 years postoperatively. We used equipercentile equating methods to create crosswalks in the training data set and examined accuracy in the validation data set as well as bootstrapping analyses to assess the impact of sample size on accuracy.
Preliminary analyses suggested that crosswalks could be attempted: large correlations between scores on the 2 measures (r = 0.84 to 0.94), unidimensionality of scores, and subpopulation invariance were deemed sufficient. When comparing actual scores with crosswalked scores in the validation data set, negligible bias was observed at the group level; however, individual score deviations were variable. The crosswalks are successful for the group level only.
Our crosswalks successfully convert between the KOOS and the IKDC-SKF scores to allow for a group-level comparison of registry and other cohort data.
These crosswalks allow comparisons among different national ligament registries as well as other research cohorts and studies; they also allow data from different patient-reported outcome measures to be pooled for meta-analysis. These crosswalks have great potential to improve our understanding of recovery after ACL reconstruction and aid in our ongoing efforts to improve outcomes and patient satisfaction, as well as to allow the continued analysis of historical data.
前交叉韧带（ACL）登记处并非都使用相同的患者报告的结果测量指标，这限制了比较并防止为荟萃分析而汇集数据。我们的目标是创建一个统计交叉转换，将队列和登记处的平均膝关节损伤和骨关节炎结果评分（KOOS）转换为国际膝关节文献委员会主观膝关节评分（IKDC-SKF）评分，反之亦然，以进行这些比较。
汇总了 3 个 ACL 登记处的数据（n=14412），并将其分为训练数据集（样本的 70%）或验证数据集（样本的 30%）。KOOS 和 IKDC-SKF 评分在手术前以及术后 1、2 和 5 或 6 年时可用。我们使用等百分位等距法在训练数据集中创建交叉转换，并在验证数据集中检查准确性，以及进行自举分析以评估样本量对准确性的影响。
初步分析表明可以尝试进行交叉转换：两种测量方法的得分之间存在较大相关性（r=0.84 至 0.94），得分具有单维度性，子群体不变性被认为是足够的。在验证数据集中，将实际得分与交叉转换得分进行比较时，群组水平上观察到几乎没有偏差；但是，个体得分偏差是可变的。这些交叉转换仅在群组水平上是成功的。
我们的交叉转换成功地将 KOOS 和 IKDC-SKF 评分进行了转换，从而可以对登记处和其他队列数据进行群组水平比较。
这些交叉转换允许不同国家的韧带登记处以及其他研究队列和研究之间进行比较；它们还允许不同患者报告的结果测量指标的数据汇集进行荟萃分析。这些交叉转换具有很大的潜力，可以提高我们对 ACL 重建后恢复的理解，并有助于我们正在努力改善结果和患者满意度，以及允许对历史数据进行持续分析。
