Approximately 10% of patients in orthopaedic sports medicine randomized controlled trials are lost to follow-up (LTF), jeopardizing the internal and external validity of even the most meticulously planned trials. Identifying patients likely to be LTF may help investigators target retention strategies to prevent attrition.
The purpose of this study was to identify pre-operative patient characteristics associated with LTF or the failure to fully complete outcomes in the Stability 1 Study.
A cohort of young, active patients undergoing anterior cruciate ligament reconstruction in the STABILITY 1 study were included in this analysis. Patients completed clinical testing and 9 questionnaires at 3-, 6-, 12-, and 24- months post-operative. Multivariable logistic regression was performed using five different definitions for LTF as the dependent variable: 1) LTF – missing all endpoint data at two-years; 2) Early LTF - LTF within one-year post-operative; 3) Late LTF – complete data through one-year after which they were LTF; 4) Clinical LTF – patients unwilling to visit the surgical office for clinical assessment and thus missing primary outcome data, and; 5) Missing Any Data – patients who miss any study visit throughout the trial. Eight predictors, including sex, age, smoking status, employment status, body mass index, pre-injury level of sport participation, delayed mobilization post-operatively, and distance from the patients’ primary residence and the clinical site were included in the analysis, along with clinical site.
Six-hundred and eighteen patients from the Stability 1 Study were included in this analysis (mean age = 18.9 years, 51.5% female). The LTF rate was 8.9%. Smokers (odds ratio [OR] = 2.61, 95% confidence interval [CI]: 1.15 to 5.96) and those employed part-time (OR = 2.33, 95%CI: 1.06 to 5.12) had significantly greater odds of LTF than other patients. No clinically meaningful predictors were identified for missing the in-person clinical exam at any visit or LTF after the first post-operative year. Clinical site was the single biggest predictor of missing outcomes at any visit.
Smoking and part-time employment status were significant predictors of LTF, and part-time employment was significantly associated with early LTF. While we cannot accurately predict who will be LTF, investigators should be aware of these factors so they can identify high-risk patients and focus retention strategies accordingly, particularly on sites with inadequate resources.