New open access research published on PLOS ONE has become the first academic paper to use data from RCVS Knowledge’s Canine Cruciate Registry (CCR) to determine its findings.
The research provides estimates on the minimal clinically-important differences (MCIDs) for the two validated outcomes measures that are used by the CCR.
Based on a year of accumulated data, the research demonstrates the CCR’s utility and how it fills a crucial knowledge gap.
The new paper, titled “Minimal clinically-important differences for the ‘Liverpool Osteoarthritis in Dogs’ (LOAD) and the ‘Canine Orthopaedic Index’ (COI) client-reported outcomes measures”, looks at important statistical parameters of the outcome measures that are used in the CCR.
The research includes a combination of anchor-based and distribution-based methods to provide MCID estimates, defined as “the smallest change in the score of an outcome measure that a client would identify as important”.
The research team were able to provide estimates of MCID for LOAD and COI, which is useful for the purposes of study design and sample-size estimates in research and clinical trials.
In addition, regulators may use the MCID to define the threshold between “responder” and “non-responder” in regulatory clinical trials.
The MCID is also useful in the context of monitoring patients’ responses to interventions, and in clinical-decision-making.
Professor John Innes, a director of Movement Referrals, an independent veterinary referrals provider in UK, and honorary professor at University of Liverpool, led the research study.
He said: “As an academic, I developed LOAD with the vision that it would help to standardise outcomes and facilitate projects such as the RCVS Knowledge Canine Cruciate Registry.
“Both LOAD and COI are used internationally now and having estimates of the MCID for these clinical tools will be useful step forward for researchers, regulators, clinicians and clients.”
The CCR, launched in July 2021, addresses a knowledge gap in cruciate ligament surgery by gathering data on techniques and their impact on large populations of dogs.
Using free, anonymised data collection and an audit tool to build case data to guide decision-making, it provides information including rates of success and potential complications with different techniques. It relies on the involvement of both surgeons and dog owners.
The research is co-authored by John Innes, Mark Morton and Duncan Lascelles.