Lower limb reconstruction (LLR) has a profound impact on patients, affecting multiple areas of their lives. Many patient-reported outcome measures (PROMs) are employed to assess these impacts; however, there are concerns that they do not adequately capture all outcomes important to patients, and may lack content validity in this context. This review explored whether PROMs used with adults requiring, undergoing, or after undergoing LLR exhibited content validity and adequately captured outcomes considered relevant and important to patients. A total of 37 PROMs were identified. Systematic searches were performed to retrieve content validity studies in the adult LLR population, and hand-searches used to find PROM development studies. Content validity assessments for each measure were performed following Consensus-based Standards for the selection of health measurement Instruments (COSMIN) guidelines. A mapping exercise compared all PROMs to a conceptual framework previously developed by the study team ('the PROLLIT framework') to explore whether each PROM covered important and relevant concepts. The systematic searches found 13 studies, while hand searches found 50 PROM development studies, and copies of all 37 measures. Although several studies discussed content validity, none were found which formally assessed this measurement property in the adult LLR population. Development of many PROMs was rated as inadequate, no PROM had sufficient content validity in the study population, and none covered all areas of the PROLLIT framework. The LIMB-Q was the most promising and comprehensive measure assessed, although further validation in a wider sample of LLR patients was recommended. Current PROMs used in adults requiring, undergoing, or after undergoing LLR lack content validity and do not assess all important and relevant outcomes. There is an urgent need for improved outcome measurement in this population. This can be achieved through development of a new PROM, or through validation of existing measures in representative samples.
Read full abstract