Study population and participant flow
Of the 457,577 patients (UKR, n = 32,293; TKR, n = 425,284) available in the source-linked data, 383,522 patients (UKR, n = 29,403; TKR, n = 353,119) had an ASA grade of 1 or 2 and were, therefore, eligible for TOPKAT and UTMoSt stage 1, but excluded from stage 2 (). The stage 2 exclusion criteria (see Chapter 6, Target population) excluded a further 15,117 patients. The resulting cohort for analysing safety outcomes (safety cohort) comprised 57,682 TKR patients and 2256 UKR patients. Of these patients, OKS postoperative data were available for 145 UKR and 23,344 TKR patients (OKS cohort).
Stage 2-specific eligibility criteria and resulting patient selection.
shows the unadjusted baseline characteristics for the safety and OKS cohorts. TKR patients in the OKS cohort had similar baseline characteristics to those in the safety cohort. UKR patients in the OKS cohort were healthier (34% vs. 38% had a Charlson Comorbidity Index score of 0) and more likely to live in the countryside (22% vs. 16% with a Rural Index of 3 or 4) than UKR patients in the safety cohort.
Baseline patient-level characteristics for patients who received TKR or UKR
In the safety cohort, UKR patients were younger than TKR patients [mean age (SD): 69 (10) years vs. 73.5 (8.9) years, respectively] and were more likely to be men (57% vs. 44%, respectively) and live in the countryside (16% vs. 11%, respectively, with a Rural Index of 3 or 4) or the least deprived areas (26% vs. 18%, respectively). UKR patients were less likely than TKR patients to have a history of osteoarthritis and other joint problems (19% vs. 26%, respectively).
In the OKS cohort, there are similar noticeable differences in sex, Rural Index and socioeconomic status between UKR and TKR patients. UKR patients were also more likely than TKR patients to be healthy (Charlson Comorbidity Index score of 0) (34% vs. 39%, respectively). There was a vast difference in the number and proportion of UKR and TKR patients who responded to the postoperative OKS: 145 out of 2256 (6.4%) UKR patients versus 23,344 out of 57,682 (40.5%) TKR patients.
Covariate balance assessment
Oxford Knee Score cohort
We applied the three validated methods (IPW, PSSwhole and PSSexp) to the OKS cohort to compare the treatment effect, as measured by the OKS, for UKR and TKR recipients.
Propensity score stratification based on the distribution of PSs in the whole cohort (PSSwhole) resulted in few UKR patients in some groups, leading to imbalanced PS distributions in some strata (see ). Within-stratum covariate balance was not always achieved in all strata in each of the 10 imputed data sets. For example, across the 10 imputed data sets, all covariates had an ASMD of > 0.1 in stratum 1. This is not surprising because there were only two (0.09%) UKR patients in this stratum, which was defined by a low PS and, therefore, a low probability of UKR treatment. Strata 2–5 had between six and 17 UKR patients each, and the distribution of some covariates remained imbalanced when UKR and TKR patients were compared in some of the 10 imputed data sets. Within-stratum covariate balance improved in strata 6–10 because they were defined by a higher PS and probability of treatment; therefore, strata 6–10 included a larger number and higher proportion of UKR patients. However, the average ASMD across strata for each of the covariates was ≤ 0.1 (), indicating that good balance was achieved for all individual covariates across strata using this widely accepted, pre-defined threshold.
The ASMD of each covariate included in the PS for the postoperative OKS cohort before and after balancing covariates by (a) PSSwhole, (b) PSSexp and (c) IPW. 1, overall PS; 2, males; 3a, Rural Index – urban (≥ 10,000); 3, age; (more...)
The PSSexp stratified based on the distribution of PSs in the exposure (UKR) cohort and most accurately replicated the TOPKAT findings in UTMoSt stage 1. It resulted in equal numbers of UKR patients in each stratum, and obtained better balance than PSSwhole in the PS distribution between UKR and TKR patients (see ). It also led to better within-stratum covariate balance for each of the identified confounders, although most covariates had an ASMD of > 0.1 in at least one stratum. Overall, average covariate balance across the 10 strata was achieved ().
The IPW pseudo-population included 145 UKR patients with a stabilised weight ranging from 0.08 to 4.45 (IQR 0.38–1.28) and 23,344 TKR patients with a stabilised weight close to 1 (minimum, 25th percentile, 75th percentile, maximum: 0.99, 1.00, 1.00, 1.10). Four covariates remained imbalanced (ASMD of > 0.1) after IPW: respiratory disease, sex, socioeconomic deprivation and history of spondylosis (). UKR patients had a higher prevalence than TKR patients of respiratory disease (31% vs. 26%, respectively), male sex (53% vs. 46%, respectively) and residence in more deprived areas (40% vs. 29%, respectively). They were also less likely than TKR patients to have spondylosis (2% vs. 4%, respectively). These covariates were further (double) adjusted in the outcome analyses in Primary outcome analyses: postoperative Oxford Knee Score and Comparative safety analyses.
Safety cohort
We also applied the three validated methods to the safety cohort. PSSwhole resulted in similar overall PS distributions for UKR and TKR patients in each stratum (see ). UKR patients had a higher predicted probability than TKR patients of receiving UKR based on their baseline characteristics, which was indicated through a higher PS. As a result, the lower PS quintiles (strata 1–3) each included < 1% of the UKR patients. Within-stratum covariate balance between UKR and TKR was much better than that in the OKS cohort, probably because the safety cohort had higher power. Overall, PSSwhole stratification controlled confounding to an acceptable degree based on ASMD ().
The ASMD of each covariate included in the PS for the postoperative safety cohort before and after covariate balancing by (a) PSSwhole, (b) PSSexp and (c) IPW. 1, overall PS; 2, males; 3a, Rural Index – urban (≥ 10,000); 3, age; (more...)
The PSSexp stratification yielded a more equally distributed PS than PSSwhole (see ) between UKR and TKR patients. The within-stratum covariate balance was also better with PSSexp than with PSSwhole, with fewer variables with an ASMD of > 0.1. Overall, good covariate balance was achieved for all of the observed confounders, with average ASMDs of < 0.1 across all strata (see ).
In the IPW pseudo-population, 2256 UKR patients were given a stabilised weight ranging from 0.09 to 9.45 and TKR patients were given weights of around 1. There were balanced distributions in all of the covariates (ASMD of ≤ 0.1) (see ).
Primary outcome analyses: postoperative Oxford Knee Score
shows the pre and postoperative OKS estimates from the stage 1 (ASA grade of 1 or 2) and stage 2 (ASA grade of 3 or 4) OKS cohort for the validated analyses using IPW, PSSwhole and PSSexp:
Pre and postoperative OKS in the stage 1 and 2 cohorts, calculated by PSSwhole, PSSexp and IPW
Stage 2 patients had a baseline (preoperative) OKS, on average, about 3 points lower than stage 1 patients for both UKR and TKR recipients and for any of the three methods. This difference was probably a result of stage 2 participants having higher comorbidity than stage 1 participants, or having surgery delayed because of high ASA grade.
Stage 2 TKR and UKR patients in the IPW pseudo-population had similar mean (SD) preoperative OKSs [16.99 (7.56) versus 17.28 (8.37), respectively].
PSSwhole and PSSexp both included the whole cohort and, therefore, found a better mean (SD) preoperative OKS for stage 2 UKR patients [19.44 (8.55)] than TKR patients [16.97 (7.55)]. However, the variance in the mean preoperative OKS for UKR patients was larger than that for TKR patients, resulting in an agreeable degree of balance, as demonstrated in and .
Approximately 6–8 months after the operation, the mean OKS was more than twice the preoperative OKS in all participant groups, indicating a dramatic improvement because of surgery in both stage 1 and stage 2 patients. PSSexp, the preferred method from stage 1, resulted in a statistically significant positive effect for UKR, with an estimated mean postoperative OKS difference of 1.83 (95% CI 0.10 to 3.56) points in favour of UKR. The other validated PS stratification method (PSSwhole) found very similar results, with an estimated mean difference in postoperative OKS of 1.82 (95% CI 0.10 to 3.56) points, again favouring UKR. IPW analyses found a non-significant difference in postoperative OKS between TKR and UKR, with a mean difference between groups of 1.00 (95% CI –1.28 to 3.27) points.
Comparative safety analyses
Short-term (90-day postoperative) complications
The 90-day cumulative incidence of postoperative venous thromboembolism observed was lower for UKR participants (relative risk 2.66, 95% CI 1.20 to 5.91, per 1000 people) than for TKR participants (relative risk 7.96, 95% CI 7.26 to 8.71, per 1000 people), resulting in a crude relative risk of 0.33 (95% CI 0.15 to 0.75) in favour of UKR patients. The differences were not attenuated and persisted after adjusting for confounding using the validated methods. Adjustment with PSSwhole or PSSexp resulted in a relative risk of 0.33 (95% CI 0.15 to 0.74), and with IPW resulted in a relative risk of 0.39 (95% CI 0.16 to 0.96).
By contrast, UKR and TKR patients had similar 90-day cumulative incidences of myocardial infarction and prosthetic joint infection. No significant differences in the risk of myocardial infarction or prosthetic joint infection were noted after adjustment with any of the three methods ().
Short-term (90-day) complications after UKR or TKR
Long-term (5-year) complications
The cumulative risk of revision increased faster for UKR patients than for TKR patients over 5 years of follow-up (). The incidence rates of revision were 13.09 (95% CI 10.64 to 16.09) after UKR and 4.88 (95% CI 4.56 to 5.22) after TKR, an almost threefold increase in revision risk for UKR compared with TKR (crude hazard ratio 2.70, 95% CI 2.16 to 3.37). Adjustment for confounding using the validated methods did not attenuate this risk, with a resulting cause-specific hazard ratio of 2.70 (95% CI 2.15 to 3.38) for PSSwhole and PSSexp, and 2.60 (95% CI 1.94 to 3.47) for IPW ().
Cumulative incidence functions of (a) risk of revision and (b) mortality, for UKR (UKR = 1) and TKR (UKR = 0) over 5 years of follow-up. Number at risk: number of patients with a particular surgery who did not experience (more...)
Long-term (5-year) complications after UKR or TKR
Participants receiving UKR surgery had lower 5-year mortality than TKR patients (see ). UKR surgery, therefore, appeared to be associated with reduced all-cause mortality in the unadjusted analysis, with a crude hazard ratio of 0.64 (95% CI 0.55 to 0.75).
The observed decrease in mortality associated with UKR (vs. TKR) remained after adjustment for confounding using PSSwhole or PSSexp, both resulting in a cause-specific hazard ratio of 0.64 (95% CI 0.55 to 0.75) (see ). However, the observed effect on mortality was attenuated and became non-significant when using IPW, with a cause-specific hazard ratio of 0.83 (95% CI 0.67 to 1.03).
Sensitivity analyses
Prespecified interactions and stratified analyses
Significant interactions, predefined as having a p-value of < 0.1, were identified with ASA grade (p = 0.07 for PS stratification methods) and sex (p = 0.05 for IPW and p = 0.02 for PS stratification methods), but not with age (p = 0.48 for IPW and p = 0.68 for PS stratification methods).
When we stratified the analysis by sex, female UKR patients had a higher excess risk of revision (cause-specific hazard ratios around 3.5) than male UKR patients (hazard ratios around 2.0). When we stratified the analysis by ASA grade, the increase in revision risk associated with UKR was higher in patients with an ASA grade of 4 than patients with an ASA grade of 3. The hazard ratio estimates for patients with an ASA grade of 4 were around 8.0, but the CI could not be calculated owing to limited power for this analysis. gives the full results of the stratified analyses.
Sex-specific and ASA grade-specific cause-specific hazard ratios for UKR (vs. TKR) revision and mortality over 5-year follow-up
Analysis restricted to high-volume surgeons
We restricted the three validated analyses to surgeries performed by experienced surgeons to examine whether or not patients’ risk of long-term complications changed. As in Chapter 3, Revision cohort, we defined three subcohorts of the safety cohort based on the number of surgeries of the same type performed by the lead surgeon in the previous year: ≥ 10, ≥ 30 and ≥ 50 surgeries. Of the 57,682 TKR patients included in the total cohort, 51,118 (89%), 38,321 (66%) and 25,944 (45%) were included in these three lead surgeon subcohorts, respectively. Of the 2256 UKR patients included in the total cohort, a smaller proportion were included [1449 (64%), 610 (27%) and 242 (11%), respectively]. See Appendix 1, Table 30 for the baseline characteristics for these subcohorts.
Cause-specific risks of revision and mortality for UKR (vs. TKR) patients calculated with the three analytical methods are reported in . The observed excess risk of revision seen in UKR patients was somewhat reduced when the analyses were restricted to those operated on by high-volume surgeons. The cause-specific hazard ratio of 2.60 (95% CI 1.94 to 3.47) in the main cohort decreased to 2.05 (95% CI 1.03 to 4.09) when restricting to high-volume surgeons with ≥ 30 surgeries in the past year and using IPW, and to 1.65 (95% CI 1.01 to 2.69) when using PS stratification. However, the CIs of these estimates overlapped, indicating no significant difference (see ).
Cause-specific hazard ratios for risk of (a) 5-year revision and (b) mortality for patients undergoing UKR (vs. TKR) in sensitivity analyses restricted to lead surgeons with ≥ 10, ≥ 30 or ≥ 50 surgeries (more...)
Excess revision risks increased again when restricting to the highest-volume surgeons (≥ 50 surgeries of the same type in the previous year). However, this subanalysis was limited by low statistical power, resulting in wide CIs.
Restricting to high-volume surgeons did not have striking effects on the observed association with 5-year mortality following surgery (see ). The overlapping CIs of these estimates suggested no clear trend in differential mortality between UKR and TKR with increasing surgeon volume.
