MCID normalization: A methodological framework for harmonizing heterogeneous PROMs in hip arthroscopy research.

Hip arthroscopy (HAS) research employs a wide range of patient-reported outcome measures (PROMs). This heterogeneity complicates cross-study comparisons and meta-analyses, as no gold-standard PROM exists. The minimal clinically important difference (MCID) offers a clinically meaningful threshold of change, but methodological guidance on integrating heterogeneous PROMs through MCID has been lacking. Can heterogeneous PROMs in HAS be harmonized through MCID normalization? PROMs reported in 100 HAS studies were identified and ranked according to frequency of use. The most frequently reported MCID values from published validation studies were applied. Each PROM was then evaluated and normalized by dividing observed mean values and standard deviations by the respective MCID, thereby yielding a standardized metric expressed in 'MCID units'. A proof-of-concept data set with seven simulated two-arm studies was created to demonstrate the stepwise process of PROM prioritization, MCID-based normalization and subsequent synthesis through random-effects meta-analysis using the restricted maximum likelihood (REML) estimator. Across the 100 included studies, 214 PROM mentions were identified, with modified Harris Hip Score (mHHS) (33.2%), International Hip Outcome Tool-12 items (iHOT-12) (16.4%) and Hip Outcome Score-Sports Subscale (HOS-SSS) (15.4%) being the most frequent. Normalization successfully transformed heterogeneous PROMs into a unified outcome scale, enabling synthesis of results as 'number of clinically meaningful improvements'. The framework preserved clinical interpretability and allowed transparent, reproducible pooling of outcomes. A proof-of-concept data set of seven simulated studies illustrated stepwise MCID-based normalization and synthesis through random-effects meta-analysis (REML). MCID normalization may offer a robust and clinically relevant methodology to harmonize diverse PROMs in HAS research. Its application may enhance comparability, reduce bias in evidence synthesis and support meaningful interpretation of meta-analytic findings. Importantly, it translates heterogeneous PROMs into a unified, clinically interpretable metric, thereby helping clinicians and researchers to better assess treatment effectiveness across studies. This approach could also be adapted to other surgical fields with fragmented outcome reporting. Level of Evidence: Level V, expert opinion.