Survival Analysis in Orthopaedics: Techniques to Evaluate Long-term Treatment Efficacy and Patient Outcomes

Survival analysis is critical in orthopaedics for determining how long procedures such as joint replacements and spinal operations are successful. Traditional approaches do not account for the timing of events such as implant failure or problems, whereas survival analysis does, allowing surgeons to make informed judgments. Key approaches for assessing risk variables and implant lifetime include Kaplan-Meier curves, log-rank tests, and Cox regression. This approach improves the evaluation of treatments across joint arthroplasty, fracture care, and spine surgery. Despite limitations such as data shortages and model assumptions, combining survival analysis with emerging technologies such as electronic health records and artificial intelligence improves personalised patient care and long-term outcome prediction, eventually leading to better surgical treatment.