Toward the Development of Data-Driven Diagnostic Subgroups for People With Patellofemoral Pain Using Modifiable Clinical, Biomechanical, and Imaging Features.

BACKGROUND: Unfavorable treatment outcomes for people with patellofemoral pain (PFP) have been attributed to the potential existence of subgroups that respond differently to treatment. OBJECTIVES: This study aimed to identify subgroups within PFP by combining modifiable clinical, biomechanical, and imaging features and exploring the prognosis of these subgroups. METHODS: This was a longitudinal cohort study, with baseline cluster analyses. Baseline data were analyzed using a 2-stage cluster analysis; 10 features were analyzed within 4 health domains before being combined at the second stage. Prognosis of the subgroups was assessed at 12 months, with subgroup differences reported as global rating of change and analyzed with an exploratory logistic regression adjusted for known confounders. RESULTS: Seventy participants were included (mean age, 31 years; 43 [61%] female). Cluster analysis revealed 4 subgroups: "strong," "pronation and malalignment," "weak," and "active and flexible." Descriptively, compared to the strong subgroup (55% favorable), the odds of a favorable outcome were lower in the weak subgroup (31% favorable; adjusted odds ratio [OR] = 0.30; 95% confidence interval [CI]: 0.07,1.36) and the pronation and malalignment subgroup (50%; OR = 0.64; 95% CI: 0.11, 3.66), and higher in the active and flexible subgroup (63%; OR = 1.24; 95% CI: 0.20, 7.51). After adjustment, compared to the strong subgroup, differences between some subgroups remained substantive, but none were statistically significant. CONCLUSION: In this relatively small cohort 4 PFP subgroups were identified that show potentially different outcomes at 12 months. Further research is required to determine whether a stratified treatment approach using these subgroups would improve outcomes for people with PFP.