Abstract
OBJECTIVE: Knee replacement (KR) rates are increasing exponentially in the US and straining insurance budgets. This study was undertaken to investigate how many KRs would be prevented at different levels of pain improvement, a major target of osteoarthritis (OA) trials. METHODS: We used data from the Osteoarthritis Initiative (OAI) to emulate a trial of knee pain interventions on KR risk changes. We modeled hypothetical 1-, 2- or 3-unit reductions of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale whenever a person reported a pain score of ≥5 (of 20) in an affected knee at any clinic visit. We used causal inference-based targeted learning to estimate treatment effects for hypothesized pain intervention strategies adjusted for time-dependent confounding. Sensitivity analyses assessed interventions at WOMAC pain scores of ≥4 and ≥7. RESULTS: Of the 9,592 knees studied (n = 4,796 participants; 58.5% female; baseline age 61.2 years), 40.7% experienced WOMAC pain scores of ≥5. The estimated knee-level (reference) risk of a KR, adjusted for loss to follow-up and death, was 6.3% (95% confidence interval 5.0, 7.7%) in the OAI. Reductions of WOMAC pain scores by 1, 2, or 3 units decreased the KR risk from 6.3% to 5.8%, 5.3%, and 4.9%, respectively. Larger reductions in KR risk were achieved when interventions were applied at a WOMAC pain score of ≥4. CONCLUSION: Modest pain reductions from OA interventions would substantially reduce the number of KRs, with greater reductions achieved when pain decreased more and when interventions were introduced at lower pain levels.