Integrative Phenotyping of Knee Osteoarthritis: Linking WOMAC Cut-Offs, Kellgren–Lawrence Grades, and Cluster Analysis for Personalized Care

Abstract

Knee osteoarthritis (OA) is a complex condition with varying pain, functional limitations, and structural changes. Traditional classification using radiographic grades may not fully reflect individual patient experiences. This study aimed to establish WOMAC score cut-offs for KL grades and identify knee OA phenotypes through cluster analysis in a cohort of 99 adults, examining functional and radiological status, factors such as age, sex, body mass index (BMI), comorbidities, and psychological status. Receiver operating characteristic (ROC) analysis helped establish WOMAC cut-off scores related to KL grades, and cluster analysis identified phenotypic subgroups. The analysis showed that higher WOMAC scores correlated with advanced KL grades, leading to a five-tier classification of symptomatic severity: minimal or no symptoms (≤24), mild (25–41), moderate (42–69), severe (70–86), and extreme (≥87). Cluster analysis identified four distinct phenotypic groups: (1) younger patients exhibiting minimal symptoms and low KL grades; (2) individuals with moderate disease are characterized by functional deficits; (3) patients presenting with moderate-to-severe symptoms and significant joint narrowing; and (4) a subgroup experiencing severe pain, high levels of disability, advanced KL grades, elevated psychological distress, and an increased BMI. The study supports WOMAC cut-offs as key indicators of knee OA severity and shows that cluster analysis can reveal distinct phenotypes, underscoring the need for personalized management strategies in knee OA treatment.