Abstract
Osteoarthritis of the hip is common and the mainstay of surgical treatment for end-stage disease is total hip replacement. There are few RCTs comparing long-term outcomes between prostheses; therefore, surgeons and patients are reliant on single-centre case-series and recently, analysis of joint registries, when making evidence-based implant choices.
We conducted a systematic review, conforming to PRISMA, of Medline and Embase in September 2017. Single-centre case-series and papers analysing registries were included. Series looking at disease-specific cohorts (other than OA), under 15 years follow-up or lacking survival analyses were excluded. Resurfacings, revisions and complex-primaries were also excluded. 2750 abstracts were screened, resulting in 299 full-text articles. Following full review 124 articles were excluded and 21 series added from references, resulting in 150 analyses of individual prostheses/constructs and 12 papers from registries. We also analysed annual reports of registries.
Registry data indicated cemented prostheses tended to better outcomes at late follow-ups, whereas case-series showed cementless prostheses tended to have better survival past 15 years with revision for any reason (of stem, cup or either component) as the end-point.
The discrepancy between results from registry data and single-centre case series is stark, and whilst the reasons for these differences may be multifactorial, single-centre case-series included in this review often lacked sufficient power to provide precise estimates of survival. This is contrasted to data from registries, which tended to have far greater numbers from multiple centres, allowing results to be generalised to the population.
The difference between these two modes of analysis suggests bias exists in selection and outcomes from single-centre series. The varied quality of reporting in case-series make it difficult for a reader to adequately assess bias, and accurately inform contemporary decision making.
Surgeons and patients should be cautious when interpreting single-centre case series and systems relying on data generated from them.
