Random effects modelling versus logistic regression for the inclusion of cluster-level covariates in propensity score estimation: A Monte Carlo simulation and registry cohort analysis.

Purpose: Surgeon and hospital-related features, such as volume, can be associated with treatment choices and outcomes. Accounting for these covariates with propensity score (PS) analysis can be challenging due to the clustered nature of the data. We studied six different PS estimation strategies for clustered data using random effects modelling (REM) compared with logistic regression. Methods: Monte Carlo simulations were used to generate variable cluster-level confounding intensity [odds ratio (OR) = 1.01-2.5] and cluster size (20-1,000 patients per cluster). The following PS estimation strategies were compared: i) logistic regression omitting cluster-level confounders; ii) logistic regression including cluster-level confounders; iii) the same as ii) but including cross-level interactions; iv), v), and vi), similar to i), ii), and iii), respectively, but using REM instead of logistic regression. The same strategies were tested in a trial emulation of partial versus total knee replacement (TKR) surgery, where observational versus trial-based estimates were compared as a proxy for bias. Performance metrics included bias and mean square error (MSE). Results: In most simulated scenarios, logistic regression, including cluster-level confounders, led to the lowest bias and MSE, for example, with 50 clusters × 200 individuals and confounding intensity OR = 1.5, a relative bias of 10%, and MSE of 0.003 for (i) compared to 32% and 0.010 for (iv). The results from the trial emulation also gave similar trends. Conclusion: Logistic regression, including patient and surgeon-/hospital-level confounders, appears to be the preferred strategy for PS estimation.

Characterising complex health needs and the use of preventive therapies in the older population: a population-based cohort analysis of UK primary care and hospital linked data.

BACKGROUND: While several definitions exist for multimorbidity, frailty or polypharmacy, it is yet unclear to what extent single healthcare markers capture the complexity of health-related needs in older people in the community. We aimed to identify and characterise older people with complex health needs based on healthcare resource use (unplanned hospitalisations or polypharmacy) or frailty using large population-based linked records. METHODS: In this cohort study, data was extracted from UK primary care records (CPRD GOLD), with linked Hospital Episode Statistics inpatient data. People aged > 65 on 1st January 2010, registered in CPRD for ≥ 1 year were included. We identified complex health needs as the top quintile of unplanned hospitalisations, number of prescribed medicines, and electronic frailty index. We characterised all three cohorts, and quantified point-prevalence and incidence rates of preventive medicines use. RESULTS: Overall, 90,597, 110,225 and 116,076 individuals were included in the hospitalisation, frailty, and polypharmacy cohorts respectively; 28,259 (5.9%) were in all three cohorts, while 277,332 (58.3%) were not in any (background population). Frailty and polypharmacy cohorts had the highest bi-directional overlap. Most comorbidities such as diabetes and chronic kidney disease were more common in the frailty and polypharmacy cohorts compared to the hospitalisation cohort. Generally, prevalence of preventive medicines use was highest in the polypharmacy cohort compared to the other two cohorts: For instance, one-year point-prevalence of statins was 64.2% in the polypharmacy cohort vs. 60.5% in the frailty cohort. CONCLUSIONS: Three distinct groups of older people with complex health needs were identified. Compared to the hospitalisation cohort, frailty and polypharmacy cohorts had more comorbidities and higher preventive therapies use. Research is needed into the benefit-risk of different definitions of complex health needs and use of preventive therapies in the older population.

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. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 66. See the NIHR Journals Library website for further project information.

We compared the risks and benefits of partial and total knee replacements in NHS patients with a complex medical history who would normally be excluded from randomised trials on this topic. We used information that was collected during hospital appointments for people who had a knee replacement between 2009 and 2016. It is difficult to directly compare the two groups because each individual patient has a different medical history. We tested advanced statistical methods to account for these differences. In stage 1, we showed that some of these advanced statistical methods could replicate the results of a recently published surgical trial using routine data from the NHS. We compared patients in the trial with similar patients who were operated on in the NHS. Three of the proposed methods showed results similar to those obtained from the Total or Partial Knee Arthroplasty Trial (TOPKAT). In stage 2, we used the successful methods from stage 1 to study the risks, benefits and costs of partial and total knee replacement surgery in patients with complex medical histories. Two of the statistical methods found that patients who had a partial knee replacement had less self-reported pain and better function after surgery than patients who had a total knee replacement. All three methods found that partial knee replacement was safer, was associated with a lower risk of blood clots (a known complication of knee surgery) and had lower mortality over 5 years. However, patients who had a partial knee replacement were twice as likely as those with a total knee replacement to need a second surgery within 5 years. We found that partial knee replacements were less costly to the NHS and were associated with better overall quality of life for patients than total knee replacement.

Bisphosphonates to reduce bone fractures in stage 3B+ chronic kidney disease: a propensity score-matched cohort study.

BACKGROUND: Bisphosphonates are contraindicated in patients with stage 4+ chronic kidney disease. However, they are widely used to prevent fragility fractures in stage 3 chronic kidney disease, despite a lack of good-quality data on their effects. OBJECTIVES: The aims of each work package were as follows. Work package 1: to study the relationship between bisphosphonate use and chronic kidney disease progression. Work package 2: to study the association between using bisphosphonates and fracture risk. Work package 3: to determine the risks of hypocalcaemia, hypophosphataemia, acute kidney injury and upper gastrointestinal events associated with using bisphosphonates. Work package 4: to investigate the association between using bisphosphonates and changes in bone mineral density over time. DESIGN: This was a new-user cohort study design with propensity score matching. SETTING AND DATA SOURCES: Data were obtained from UK NHS primary care (Clinical Practice Research Datalink GOLD database) and linked hospital inpatient records (Hospital Episode Statistics) for work packages 1-3 and from the Danish Odense University Hospital Databases for work package 4. PARTICIPANTS: Patients registered in the data sources who had at least one measurement of estimated glomerular filtration rate of < 45 ml/minute/1.73 m2 were eligible. A second estimated glomerular filtration rate value of < 45 ml/minute/1.73 m2 within 1 year after the first was requested for work packages 1 and 3. Patients with no Hospital Episode Statistics linkage were excluded from work packages 1-3. Patients with < 1 year of run-in data before index estimated glomerular filtration rate and previous users of anti-osteoporosis medications were excluded from work packages 1-4. INTERVENTIONS/EXPOSURE: Bisphosphonate use, identified from primary care prescriptions (for work packages 1-3) or pharmacy dispensations (for work package 4), was the main exposure. MAIN OUTCOME MEASURES: Work package 1: chronic kidney disease progression, defined as stage worsening or starting renal replacement. Work package 2: hip fracture. Work package 3: acute kidney injury, hypocalcaemia and hypophosphataemia identified from Hospital Episode Statistics, and gastrointestinal events identified from Clinical Practice Research Datalink or Hospital Episode Statistics. Work package 4: annualised femoral neck bone mineral density percentage change. RESULTS: Bisphosphonate use was associated with an excess risk of chronic kidney disease progression (subdistribution hazard ratio 1.12, 95% confidence interval 1.02 to 1.24) in work package 1, but did not increase the probability of other safety outcomes in work package 3. The results from work package 2 suggested that bisphosphonate use increased fracture risk (hazard ratio 1.25, 95% confidence interval 1.13 to 1.39) for hip fractures, but sensitivity analyses suggested that this was related to unresolved confounding. Conversely, work package 4 suggested that bisphosphonates improved bone mineral density, with an average 2.65% (95% confidence interval 1.32% to 3.99%) greater gain in femoral neck bone mineral density per year in bisphosphonate users than in matched non-users. LIMITATIONS: Confounding by indication was a concern for the clinical effectiveness (i.e. work package 2) data. Bias analyses suggested that these findings were due to inappropriate adjustment for pre-treatment risk. work packages 3 and 4 were based on small numbers of events and participants, respectively. CONCLUSIONS: Bisphosphonates were associated with a 12% excess risk of chronic kidney disease progression in participants with stage 3B+ chronic kidney disease. No other safety concerns were identified. Bisphosphonate therapy increased bone mineral density, but the research team failed to demonstrate antifracture effectiveness. FUTURE WORK: Randomised controlled trial data are needed to demonstrate antifracture efficacy in patients with stage 3B+ chronic kidney disease. More safety analyses are needed to characterise the renal toxicity of bisphosphonates in stage 3A chronic kidney disease, possibly using observational data. STUDY REGISTRATION: This study is registered as EUPAS10029. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 17. See the NIHR Journals Library website for further project information. The project was also supported by the National Institute for Health Research Biomedical Research Centre, Oxford.

RATIONALE AND AIMS: Bisphosphonates are used to prevent fractures in people with fragile bones. People with chronic kidney disease have a high risk of fracturing, but the safety and effectiveness of bisphosphonates in severe chronic kidney disease is unclear. The aim of this study was to assess the benefits (e.g. bone strength improvement and fracture prevention) and the risks of unwanted effects associated with bisphosphonates for people with moderate to severe chronic kidney disease. METHODS: Anonymised primary and secondary care electronic medical records data from the UK NHS were used, as well as a Danish equivalent that included bone density scans. Anyone in these databases with a measure of reduced kidney function that suggested moderate to severe chronic kidney disease was eligible, which was > 220,000 people from the UK. Over 20,000 of them used bisphosphonates. Bisphosphonate users were matched to non-users with similar age, sex and other characteristics. RESULTS: Bisphosphonate users had a 12% higher risk of their chronic kidney disease getting worse than non-users. Their risks of other side effects, such as acute kidney injuries and gastrointestinal problems, did not change. Bisphosphonate users had a 25% higher risk of fractures than non-users in the UK database, probably because the matching methods did not create similar-enough groups of users and non-users. However, it was found that bisphosphonate improved bone density in the Danish database. Bone density is a proxy for bone strength, so better bone density should mean fewer fractures. CONCLUSIONS: These results suggest that bisphosphonate therapy may make moderate to severe chronic kidney disease worse. More studies are needed on how bisphosphonates affect milder chronic kidney disease. Bisphosphonates were associated with better bone strength, but it could not be demonstrated that they reduced fracture risk. More data are required, probably from a placebo-controlled trial, to determine whether or not bisphosphonates prevent fractures in people with moderate to severe chronic kidney disease and whether or not this is worth the risk of their chronic kidney disease worsening.

Estimating the population health burden of musculoskeletal conditions using primary care electronic health records.

OBJECTIVES: Better indicators from affordable, sustainable data sources are needed to monitor population burden of musculoskeletal conditions. We propose five indicators of musculoskeletal health and assessed if routinely available primary care electronic health records (EHR) can estimate population levels in musculoskeletal consulters. METHODS: We collected validated patient-reported measures of pain experience, function and health status through a local survey of adults (≥35 years) presenting to English general practices over 12 months for low back pain, shoulder pain, osteoarthritis and other regional musculoskeletal disorders. Using EHR data we derived and validated models for estimating population levels of five self-reported indicators: prevalence of high impact chronic pain, overall musculoskeletal health (based on Musculoskeletal Health Questionnaire), quality of life (based on EuroQoL health utility measure), and prevalence of moderate-to-severe low back pain and moderate-to-severe shoulder pain. We applied models to a national EHR database (Clinical Practice Research Datalink) to obtain national estimates of each indicator for three successive years. RESULTS: The optimal models included recorded demographics, deprivation, consultation frequency, analgesic and antidepressant prescriptions, and multimorbidity. Applying models to national EHR, we estimated that 31.9% of adults (≥35 years) presenting with non-inflammatory musculoskeletal disorders in England in 2016/17 experienced high impact chronic pain. Estimated population health levels were worse in women, older aged and those in the most deprived neighbourhoods, and changed little over 3 years. CONCLUSION: National and subnational estimates for a range of subjective indicators of non-inflammatory musculoskeletal health conditions can be obtained using information from routine electronic health records.