Development and validation of prediction models to estimate risk of primary total hip and knee replacements using data from the UK: two prospective open cohorts using the UK Clinical Practice Research Datalink

Abstract

ObjectivesThe ability to efficiently and accurately predict future risk of primary total hip and knee replacement (THR/TKR) in earlier stages of osteoarthritis (OA) has potentially important applications. We aimed to develop and validate two models to estimate an individual’s risk of primary THR and TKR in patients newly presenting to primary care.MethodsWe identified two cohorts of patients aged ≥40 years newly consulting hip pain/OA and knee pain/OA in the Clinical Practice Research Datalink. Candidate predictors were identified by systematic review, novel hypothesis-free ‘Record-Wide Association Study’ with replication, and panel consensus. Cox proportional hazards models accounting for competing risk of death were applied to derive risk algorithms for THR and TKR. Internal–external cross-validation (IECV) was then applied over geographical regions to validate two models.Results45 predictors for THR and 53 for TKR were identified, reviewed and selected by the panel. 301 052 and 416 030 patients newly consulting between 1992 and 2015 were identified in the hip and knee cohorts, respectively (median follow-up 6 years). The resultant model C-statistics is 0.73 (0.72, 0.73) and 0.79 (0.78, 0.79) for THR (with 20 predictors) and TKR model (with 24 predictors), respectively. The IECV C-statistics ranged between 0.70–0.74 (THR model) and 0.76–0.82 (TKR model); the IECV calibration slope ranged between 0.93–1.07 (THR model) and 0.92–1.12 (TKR model).ConclusionsTwo prediction models with good discrimination and calibration that estimate individuals’ risk of THR and TKR have been developed and validated in large-scale, nationally representative data, and are readily automated in electronic patient records.

Thiazide diuretics and risk of knee replacement surgery among patients with knee osteoarthritis: a general population-based cohort study

“…Third, we postulated that an increased risk of KR among thiazide users may be through its impact on BMD and/or serum magnesium; however, we can't verify these mechanisms owing to lack of BMD or serum magnesium data in THIN. Fourth, although previous studies have used Read codes to define symptomatic knee OA in THIN 27,28 and KR has been generally accepted as a "hard" outcome in cohort studies of knee OA 10,14,29,30 , we were unable to confirm a diagnosis of radiographic knee OA and to assess the radiographic progression of knee OA since knee image data were not available in THIN. Nonetheless, 96% of primary KRs are performed for knee OA 31 , though we acknowledge that there is potential for individuals qualifying for KR but not undergoing the procedure due to other factors such as personal preference.…”

Cardiovascular risks and bleeding with non-vitamin K antagonist oral anticoagulant versus warfarin in patients with type 2 diabetes: a tapered matching cohort study

“…All 21 practices in CCG-1 and 19 practices in CCG-2 practices were linked at the patient level to hospital admission data (Secondary User Service (SUS) data). We used READ codes to extract the information from general practices [12,13] and ICD-10 (international classification of diseases, 10th revision) codes for outcomes extracted from SUS data (codes list is accessible by reasonable request via corresponding author) [14,15]. Anonymised data were used in this study.…”

Derivation and external validation of a risk prediction algorithm to estimate future risk of cardiovascular death among patients with type 2 diabetes and incident diabetic nephropathy: prospective cohort study

“…We assessed the performance of the models in terms of the C-statistic and calibration slope (where 1.00 is ideal). The C-statistic represents the probability that for any randomly selected pair of people with DN with and without outcomes, the patient with the outcome had a higher predicted risk 15. A value of o.50 indicated no discrimination and 1.00 represents perfect discrimination.…”