UTMoSt stage 2 aimed to evaluate the risks, benefits, costs and cost-effectiveness of UKR (compared with TKR) for patients who would not have been eligible for the TOPKAT surgical RCT.
This chapter details the methods used in stage 2, focusing on where the methods differed from stage 1. We used the analysis methods that had been shown to replicate TOPKAT’s findings in UTMoSt stage 1. These validated methods, PS stratification and IPW, were discussed in detail in Chapter 2, Propensity score stratification; Chapter 2, Inverse probability weighting; and Chapter 3. Stage 2 used the same observational data sources as stage 1, which were presented in detail in Chapter 2; however, the source population, study population, outcomes and statistical analyses differed from stage 1.
Target population
The target population for UTMoSt stage 2 was NJR participants undergoing primary UKR or TKR surgery who had severe comorbidities, defined as an ASA grade of 3 or 4 at the time of surgery.
Besides the general inclusion and exclusion criteria listed in Table 1, we also excluded patients who met any of the following exclusion criteria:
NJR participants with no possible linkage to an episode in HES, as this was needed to study complications and costs
NJR participants with no linked data available on pre or postoperative PROMs, as these were required for comparative effectiveness analyses
NJR participants with previous cruciate ligament injury or inflammatory arthritis, as they would not have been eligible for UKR
participants for whom revision costs could not be estimated because the linked HES episode did not provide valid/adequate information on a Healthcare Resource Group (HRG), as this was needed for the health economic analysis.
In stage 1, patients with a record of foot, hip or spinal pain in the 1 year before surgery were excluded. These patients were not excluded in stage 2, as this information was instead included as a PS covariate. We did not include the stage 1 exclusion criteria of prior knee surgery, patella dislocation or septic arthritis as PS covariates because too few patients had positive records.
Outcomes
UTMoSt stage 2 used the same primary outcome (postoperative OKS) as TOPKAT and UTMoSt stage 1. The secondary outcomes of interest were:
Participants were followed up from the index surgery date to the earliest of:
end of enrolment in the database or 31 December 2016
date of revision surgery (for secondary outcome analyses)
date of a surgery for the other knee (for secondary outcome analyses)
death
end of 5 years of observation after the index surgery date.
We censored people at the surgery date in case of contralateral knee replacement, which would have made it difficult to attribute any surgical complications and costs to a specific knee.
Statistical analyses
Patient-level characteristics of the included TKR and UKR patients were compared using ASMDs with a cut-off value of 0.1. Any remaining imbalance (ASMD of > 0.1) in patient-level characteristics was accounted for by including the non-balanced covariate in the subsequent outcome analyses.
The following analyses were conducted for each of the proposed outcomes:
Primary outcome – differences in postoperative OKS between UKR and TKR patients were estimated using multilevel linear regression (cluster 1: lead surgeons; cluster 2: patients).
Secondary outcomes – postoperative complications. For each 90-day risk of an adverse event, we compared the cumulative incidence of all adverse events of interest between UKR and TKR patients. Relative risk and 95% CIs were estimated using Poisson models with robust standard errors. Mortality was not considered a competing risk in the 90-day risk because of low mortality rates over this period.
Secondary outcomes – mortality and revision risk. Incidence rates and 95% CIs of revision and mortality for UKR and TKR patients were estimated using Poisson models, with the jack-knife method for CI calculations, and reported per 1000 person-years. Cause-specific hazard models were fitted to estimate risk of revision or mortality, censoring patients when they had a competing event (revision or mortality).
All outcome analyses were conducted in each of the imputed data sets and combined using Rubin’s rules.
The methods used to analyse hospital costs, health-related quality of life (HRQoL) and derived cost-effectiveness analyses are shown in Chapter 8.
Sensitivity analyses
No sensitivity analyses were conducted for postoperative OKS or any of the 90-day postoperative complications. As few patients had these outcomes, there was a lack of statistical power to detect a significant difference.
Sensitivity analyses were conducted for 5-year revision risk. Three predefined interactions were tested for using multiplicative terms in the above models. Stratified analyses by sex, age (younger or older than the median age in the study data sets) and ASA grade were reported if the p-value was < 0.1. To explore the impact of learning curves, revision analyses were restricted to surgeries undertaken by lead surgeons who had performed at least 10, 30 or 50 surgeries of the same type in the previous year.
