Randomized controlled trials (RCTs) are a gold standard for estimating benefits of clinical interventions, but their decision-making utility can be limited by relatively short follow-up time. Longer-term follow-up of RCT participants is essential to support treatment decisions. However, as time from randomization accrues, loss to follow-up and competing events can introduce biases and requires covariate adjustment even for intention-to-treat effects. We describe a process for synthesizing expert knowledge and apply this to long-term follow-up of an RCT of treatments for meniscal tear in patients with knee osteoarthritis.