Unicompartmental compared with total knee replacement for patients with multimorbidities : a cohort study using propensity score stratification and inverse probability weighting

Background Although routine NHS data potentially include all patients, confounding limits their use for causal inference. Methods to minimise confounding in observational studies of implantable devices are required to enable the evaluation of patients with severe systemic morbidity who are excluded from many randomised controlled trials. Objectives Stage 1 – replicate the Total or Partial Knee Arthroplasty Trial (TOPKAT), a surgical randomised controlled trial comparing unicompartmental knee replacement with total knee replacement using propensity score and instrumental variable methods. Stage 2 – compare the risk benefits and cost-effectiveness of unicompartmental knee replacement with total knee replacement surgery in patients with severe systemic morbidity who would have been ineligible for TOPKAT using the validated methods from stage 1. Design This was a cohort study. Setting Data were obtained from the National Joint Registry database and linked to hospital inpatient (Hospital Episode Statistics) and patient-reported outcome data. Participants Stage 1 – people undergoing unicompartmental knee replacement surgery or total knee replacement surgery who met the TOPKAT eligibility criteria. Stage 2 – participants with an American Society of Anesthesiologists grade of ≥ 3. Intervention The patients were exposed to either unicompartmental knee replacement surgery or total knee replacement surgery. Main outcome measures The primary outcome measure was the postoperative Oxford Knee Score. The secondary outcome measures were 90-day postoperative complications (venous thromboembolism, myocardial infarction and prosthetic joint infection) and 5-year revision risk and mortality. The main outcome measures for the health economic analysis were health-related quality of life (EuroQol-5 Dimensions) and NHS hospital costs. Results In stage 1, propensity score stratification and inverse probability weighting replicated the results of TOPKAT. Propensity score adjustment, propensity score matching and instrumental variables did not. Stage 2 included 2256 unicompartmental knee replacement patients and 57,682 total knee replacement patients who had severe comorbidities, of whom 145 and 23,344 had linked Oxford Knee Scores, respectively. A statistically significant but clinically irrelevant difference favouring unicompartmental knee replacement was observed, with a mean postoperative Oxford Knee Score difference of < 2 points using propensity score stratification; no significant difference was observed using inverse probability weighting. Unicompartmental knee replacement more than halved the risk of venous thromboembolism [relative risk 0.33 (95% confidence interval 0.15 to 0.74) using propensity score stratification; relative risk 0.39 (95% confidence interval 0.16 to 0.96) using inverse probability weighting]. Unicompartmental knee replacement was not associated with myocardial infarction or prosthetic joint infection using either method. In the long term, unicompartmental knee replacement had double the revision risk of total knee replacement [hazard ratio 2.70 (95% confidence interval 2.15 to 3.38) using propensity score stratification; hazard ratio 2.60 (95% confidence interval 1.94 to 3.47) using inverse probability weighting], but half of the mortality [hazard ratio 0.52 (95% confidence interval 0.36 to 0.74) using propensity score stratification; insignificant effect using inverse probability weighting]. Unicompartmental knee replacement had lower costs and higher quality-adjusted life-year gains than total knee replacement for stage 2 participants. Limitations Although some propensity score methods successfully replicated TOPKAT, unresolved confounding may have affected stage 2. Missing Oxford Knee Scores may have led to information bias. Conclusions Propensity score stratification and inverse probability weighting successfully replicated TOPKAT, implying that some (but not all) propensity score methods can be used to evaluate surgical innovations and implantable medical devices using routine NHS data. Unicompartmental knee replacement was safer and more cost-effective than total knee replacement for patients with severe comorbidity and should be considered the first option for suitable patients. Future work Further research is required to understand the performance of propensity score methods for evaluating surgical innovations and implantable devices. Trial registration This trial is registered as EUPAS17435

Clustering of pain and its associations with health in people aged 50 years and older: cross-sectional results from the North Staffordshire Osteoarthritis Project

Objective: most pain in patients aged ≥50 years affects multiple sites and yet the predominant mode of presentation is single-site syndromes. The aim of this study was to investigate if pain sites form clusters in this population and if any such clusters are associated with health factors other than pain.Setting: six general practices in North Staffordshire, UK.Design: cross-sectional, postal questionnaire, study.Participants: community-dwelling adults aged ≥50 years registered at the general practices.Main outcomes measures: number of pain sites was measured by asking participants to shade sites of pain lasting ≥1 day in the past 4 weeks on a blank body manikin. Health factors measured included anxiety and depression (Hospital and Anxiety Depression Scale), cognitive complaint (Sickness Impact Profile) and sleep. Pain site clustering was investigated using latent class analysis. Association of clusters with health factors, adjusted for age, sex, body mass index and morbidities, was analysed using multinomial regression models.Results: 13 986 participants (adjusted response 70.6%) completed a questionnaire, of whom 12 408 provided complete pain data. Four clusters of participants were identified: (1) low number of pain sites (36.6%), (2) medium number of sites with no back pain (31.5%), (3) medium number of sites with back pain (17.9%) and (4) high number of sites (14.1%). Compared to Cluster 1, other clusters were associated with poor health. The strongest associations (relative risk ratios, 95% CI) were with Cluster 4: depression (per unit change in score) 1.11 (1.08 to 1.14); cognitive complaint 2.60 (2.09 to 3.24); non-restorative sleep 4.60 (3.50 to 6.05).Conclusions: these results indicate that in a general population aged ≥50 years, pain forms four clusters shaped by two dimensions—number of pain sites (low, medium, high) and, within the medium cluster, the absence or presence of back pain. The usefulness of primary care treatment approaches based on this simple classification should be investigated