Application of propensity scores and marginal structural models evaluating the effect of allopurinol in gout using primary care medical records

Background Primary care electronic health records (EHR) capture real life patterns of healthcare utilisation over time. This provides the opportunity to estimate the effect of allopurinol on long term outcomes in people with gout. However, use of such data gives rise to confounding by indication which may change over time, a major impediment in treatment effect estimation. Methods A cohort of patients consulting for gout between 1997 2002 and not previously prescribed urate-lowering drugs were identified from the Clinical Practice Research Datalink GOLD and were followed up until the end of 2014. Effect of allopurinol vs. non-use was evaluated on reaching target serum urate (SU) level ≤360μmol/L, mortality, healthcare utilisation, vascular and renal diseases. Three statistical approaches with differing complexities and assumptions imposed were considered: (1) baseline measurement of allopurinol and covariates with confounding controlled for using propensity score (PS) subclassification; (2) extending the methods in (1) to repeated measures where allopurinol and covariates were measured yearly; (3) using marginal structural models (MSM) within the repeated measures set-up. Survival models estimated hazard ratios with 95% confidence intervals. Robustness of estimated treatment effects to unmeasured confounding was evaluated. Results 16,876 patients were eligible for analysis (mean age (standard deviation) 62 (14.1) years, 77% male). Baseline analysis found allopurinol was associated with higher chance of reaching target SU level (2.32 (1.97, 2.74)) and fewer gout consultations (0.70 (0.65, 0.75)), and with increased risk of mortality (1.10 (1.03, 1.17)), gout hospitalisation (1.82 (1.64, 2.02)), coronary heart disease (1.11 (1.02, 1.21)), and renal disease (1.19 (1.10, 1.28)). In the repeated measures setting, issues with poor performance of PS estimation were identified in both time-varying PS subclassification and MSM. These were resolved by allowing associations between covariates and initiation and continuation of allopurinol to differ in MSM; larger treatment effect estimates were obtained for most outcomes compared with baseline analysis and statistical significance was lost for mortality. The treatment effect estimates for target SU level and gout hospitalisation were likely to be robust to unmeasured confounding however, unmeasured confounding may explain away the treatment effects for coronary heart disease and renal disease. Conclusion Fitting complex models to EHR is challenging and consideration needs to be given to both clinical and statistical assumptions made during data preparation and analysis. Associations of allopurinol with adverse outcomes persisted, regardless of statistical approach used. This may be due to remaining residual confounding and/or because allopurinol dosage and adherence is suboptimal in primary care. Nevertheless, the treatment effect estimates obtain are relevant to UK primary care and provide evidence that managing gout in the long term needs to be improved

The association between gout and radiographic hand, knee and foot osteoarthritis: a cross-sectional study

BackgroundGout is the most common type of inflammatory arthritis and is largely managed in primary care. It classically affects the first metatarsophalangeal joint and distal peripheral joints, whereas the axial joints are typically spared. The reason for this particular distribution is not well understood, however, it has been suggested that osteoarthritis (OA) may be the key factor.One hypothesis is that there is an association between the disease states of gout and OA as the conditions share common risk factors. The objective of this study was to determine whether there is an association between gout and radiographic osteoarthritis (OA).MethodsA cross-sectional study was nested within three observational cohorts of people aged =50 years with hand, knee and foot pain. Participants with gout were identified through primary care medical records and each matched by age and gender to four individuals without gout. The presence and severity of radiographic OA were scored using validated atlases. Conditional logistic regression models were used to examine associations between gout and the presence, frequency and severity of radiographic OA at the hand, knee and foot and adjusted for BMI, diuretic use and site of joint pain.ResultsFifty-three people with gout were compared to 211 matched subjects without gout. No statistically significant associations were observed between gout and radiographic hand, knee or foot OA. However, individuals with gout had increased odds of having nodal hand OA (aOR 1.46; 95 % CI 0.61, 3.50), =8 hand joints with moderate to severe OA (aOR 3.57; 95 %CI 0.62, 20.45), foot OA (aOR 2.16; 95 % CI 0.66, 7.06), =3 foot joints affected (aOR 4.00; 95 % CI 0.99, 16.10) and =1 foot joints with severe OA (aOR 1.46; 95 % CI 0.54, 3.94) but decreased odds of tibiofemoral (aOR 0.44; 95 % CI 0.15, 1.29) or patellofemoral (aOR 0.70; 95 % CI 0.22, 2.22) OA in either knee.ConclusionThere was no association between gout and radiographic OA, however, people with gout appeared to be more likely to have small joint OA and less likely to have large joint OA

Clinical diagnosis of symptomatic midfoot osteoarthritis:cross-sectional findings from the Clinical Assessment Study of the Foot

OBJECTIVE: To derive a multivariable diagnostic model for symptomatic midfoot osteoarthritis (OA). METHODS: Information on potential risk factors and clinical manifestations of symptomatic midfoot OA was collected using a health survey and standardised clinical examination of a population-based sample of 274 adults aged ≥50 years with midfoot pain. Following univariable analysis, random intercept multi-level logistic regression modelling that accounted for clustered data was used to identify the presence of midfoot OA independently scored on plain radiographs (dorso-plantar and lateral views), and defined as a score of ≥2 for osteophytes or joint space narrowing in at least one of four joints (first and second cuneometatarsal, navicular-first cuneiform and talonavicular joints). Model performance was summarised using the calibration slope and area under the curve (AUC). Internal validation and sensitivity analyses explored model over-fitting and certain assumptions. RESULTS: Compared to persons with midfoot pain only, symptomatic midfoot OA was associated with measures of static foot posture and range-of-motion at subtalar and ankle joints. Arch Index was the only retained clinical variable in a model containing age, gender and body mass index (BMI). The final model was poorly calibrated (calibration slope, 0.64, 95% CI: 0.39, 0.89) and discrimination was fair-to-poor (AUC, 0.64, 0.58, 0.70). Final model sensitivity and specificity were 29.9% (22.7, 38.0) and 87.5% (82.9, 91.3), respectively. Bootstrapping revealed the model to be over-optimistic and performance was not improved using continuous predictors. CONCLUSIONS: Brief clinical assessments provided only marginal information for identifying the presence of radiographic midfoot OA among community-dwelling persons with midfoot pain

Incidence and Progression of Hallux Valgus: A Prospective Cohort Study

OBJECTIVE: Hallux valgus is a common and disabling condition. The objective of this study was to identify factors associated with hallux valgus incidence and progression. METHODS: Participants were from a population-based prospective cohort study, the Clinical Assessment Study of the Foot. All adults aged =50 years registered with four general practices in North Staffordshire, UK were invited to take part in a postal survey at baseline and at 7-year follow-up which included health questionnaires and self-assessment of hallux valgus using line drawings. RESULTS: Complete baseline and follow-up data were available for 1,482 participants (739 women and 743 men, mean [standard deviation] age 62.9 [8.1] years), of whom 450 (30.4%) had hallux valgus in at least one foot at baseline. Incident hallux valgus was identified in 207 (20.1%) participants (349 [15.4%] feet) and was associated with baseline age, poorer physical health, foot pain and wearing shoes with a very narrow toe-box shape between the age of 20 and 29 years. Hallux valgus progression was identified in 497 (33.6%) participants (719 [24.3%] feet) but was not associated with any baseline factors. CONCLUSION: Incident hallux valgus develops in one in five adults aged =50 years over a 7-year period and is related to age, poorer physical health, foot pain and previous use of constrictive footwear. Progression occurs in one in three adults. These findings suggest that changes in first metatarsophalangeal joint alignment may still occur beyond the age of 50 years

Identification of Patterns of Foot and Ankle Pain in the Community: Cross-sectional Findings from the Clinical Assessment Study of the Foot

Objectives: To investigate patterns of foot and ankle pain locations and symptoms, socio-demographic and comorbid characteristics to examine whether there are distinct foot and ankle pain phenotypes. Methods: Adults aged =50 years registered with four general practices in North Staffordshire were mailed a Health Survey questionnaire. Participants reporting foot pain in the last month indicated foot pain location on a foot manikin. Foot and ankle pain patterns were investigated by latent class analysis. Associations between the classes with foot pain symptoms, socio-demographic and comorbid characteristics were assessed. Results: 4455 participants with complete foot pain and manikin data were included in this analysis (mean age 65 years (SD 9.8), 49% male). Of those with foot and ankle pain (n=1356), 90% had pain in more than one region. Six distinct classes of foot and ankle pain were identified: no pain (71%); bilateral forefoot/midfoot pain (4%), bilateral hindfoot pain (5%), left forefoot/midfoot pain (8%), right forefoot/midfoot pain (5%) and bilateral widespread foot and ankle pain (6%). People with bilateral widespread foot and ankle pain were more likely to be female, obese, depressed, anxious, have/had a manual occupation, have comorbidities, lower SF-12 scores and greater foot-specific disability. Age did not differ between classes. Conclusions: Six distinct classes of foot and ankle pain locations were identified, and those with bilateral widespread foot and ankle pain had distinct characteristics. Further investigation of these individuals is required to determine if they have poorer outcomes over time and whether they would benefit from earlier identification and treatment

Determining cardiovascular risk in patients with unattributed chest pain in UK primary care: an electronic health record study

BACKGROUND: Most adults presenting in primary care with chest pain symptoms will not receive a diagnosis ("unattributed" chest pain) but are at increased risk of cardiovascular events. AIM: To assess within patients with unattributed chest pain, risk factors for cardiovascular events and whether those at greatest risk of cardiovascular disease can be ascertained by an existing general population risk prediction model or by development of a new model. METHODS: The study used UK primary care electronic health records from the Clinical Practice Research Datalink (CPRD) linked to admitted hospitalisations. Study population was patients aged 18 plus with recorded unattributed chest pain 2002-2018. Cardiovascular risk prediction models were developed with external validation and comparison of performance to QRISK3, a general population risk prediction model. RESULTS: There were 374,917 patients with unattributed chest pain in the development dataset. Strongest risk factors for cardiovascular disease included diabetes, atrial fibrillation, and hypertension. Risk was increased in males, patients of Asian ethnicity, those in more deprived areas, obese patients, and smokers. The final developed model had good predictive performance (external validation c-statistic 0.81, calibration slope 1.02). A model using a subset of key risk factors for cardiovascular disease gave nearly identical performance. QRISK3 underestimated cardiovascular risk. CONCLUSION: Patients presenting with unattributed chest pain are at increased risk of cardiovascular events. It is feasible to accurately estimate individual risk using routinely recorded information in the primary care record, focusing on a small number of risk factors. Patients at highest risk could be targeted for preventative measures

Identifying Long-Term Trajectories of Foot Pain Severity and Potential Prognostic Factors: A Population-Based Cohort Study.

ObjectivesTo identify distinct foot pain trajectories over 7 years and examine their associations with potential prognostic factors.MethodsAdults ages ≥50 years and registered with 4 general practices in North Staffordshire, UK were mailed a baseline health survey. Those reporting current or recent foot pain were invited to attend a research assessment clinic. Follow-up was by repeated postal surveys at 18, 36, 54, and 84 months. Distinct trajectories of foot pain were explored using latent class growth analysis (LCGA). Subsequently, identified trajectories were combined into most and least progressive groups, and covariate-adjusted associations with a range of prognostic factors were examined.ResultsOf 560 adults with foot pain attending baseline research clinics, 425 (76%) provided data at baseline and 2 or more follow-up time points. LCGA for foot pain severity (0-10 numerical rating scale) identified a 4-trajectory model: "mild, improving" (37%); "moderate, improving" (33%); "moderate-severe, persistent" (24%); and "severe, persistent" (6%). Compared with individuals in more favorable (improving) pain trajectories, those in less favorable (persistent) pain trajectories were more likely to be obese, have routine/manual and intermediate occupations, have poorer physical and mental health, have catastrophizing beliefs, have greater foot-specific functional limitation, and have self-assessed hallux valgus at baseline.ConclusionsFour distinct trajectories of foot pain were identified over a 7-year period, with one-third of individuals classified as having pain that is persistently moderate-severe and severe in intensity. The effect of intervening to target modifiable prognostic factors such as obesity and hallux valgus on long-term outcomes in people with foot pain requires investigation

Health services changes: is a run-in period necessary before evaluation in randomised clinical trials?

Background Most randomised clinical trials (RCTs) testing a new health service do not allow a run-in period of consolidation before evaluating the new approach. Consequently, health professionals involved may feel insufficiently familiar or confident, or that new processes or systems that are integral to the service are insufficiently embedded in routine care prior to definitive evaluation in a RCT. This study aimed to determine the optimal run-in period for a new physiotherapy-led telephone assessment and treatment service known as PhysioDirect and whether a run-in was needed prior to evaluating outcomes in an RCT. Methods The PhysioDirect trial assessed whether PhysioDirect was as effective as usual care. Prior to the main trial, a run-in of up to 12 weeks was permitted to facilitate physiotherapists to become confident in delivering the new service. Outcomes collected from the run-in and main trial were length of telephone calls within the PhysioDirect service and patients’ physical function (SF-36v2 questionnaire) and Measure Yourself Medical Outcome Profile v2 collected at baseline and six months. Joinpoint regression determined how long it had taken call times to stabilise. Analysis of covariance determined whether patients’ physical function at six months changed from the run-in to the main trial. Results Mean PhysioDirect call times (minutes) were higher in the run-in (31 (SD: 12.6)) than in the main trial (25 (SD: 11.6)). Each physiotherapist needed to answer 42 (95% CI: 20,56) calls for their mean call time to stabilise at 25 minutes per call; this took a minimum of seven weeks. For patients’ physical function, PhysioDirect was equally clinically effective as usual care during both the run-in (0.17 (95% CI: -0.91,1.24)) and main trial (-0.01 (95% CI: -0.80,0.79)). Conclusions A run-in was not needed in a large trial testing PhysioDirect services in terms of patient outcomes. A learning curve was evident in the process measure of telephone call length. This decreased during the run-in and stabilised prior to commencement of the main trial. Future trials should build in a run-in if it is anticipated that learning would have an effect on patient outcome

An Evaluation of Different Strategies for Sampling Controls in an Online Case-Crossover Study of Acute Flares in Knee Osteoarthritis.

ObjectiveTo evaluate bias and precision of exposure-outcome effect estimates from three control sampling strategies in a case-crossover study.MethodsOnline case-crossover study investigating eight physical activity-related triggers for acute flares in knee osteoarthritis. Exposures were measured in hazard periods (≤24 hours before self-declared flare onset). Control period exposure was measured in three ways: (1) four scheduled questionnaires over 13-weeks, (2) "usual" physical activity levels ascertained at baseline, (3) over three days before flare onset. Derived odds ratios, 95% confidence intervals and standard errors were compared.ResultsOf 744 participants (mean age 62.1 [SD 10.2] years; 61% female), 493 reported 714 flares. Selecting controls from scheduled questionnaires, independent of hazard periods, yielded predominantly odds ratios in the expected direction (exposure "a lot" versus exposure "not at all", range: 0.57-3.22). When controls were sampled at baseline (range: 0.01-1.42) or immediately before a flare (range: 0.30-1.27) most odds ratio estimates were inverted. Standard errors of the log odds ratios were smallest when controls were sampled from scheduled questionnaires (range: 0.264-0.473) compared to controls sampled at baseline (range: 0.267-0.589) or immediately before a flare (range: 0.319-0.621).ConclusionOur findings are sensitive to control sample selection. Under certain conditions, different patterns could be attributed to over reporting and social desirability bias, where people may want to present themselves more positively about their "usual" physical activity levels, at baseline. Exposure measurement at the time of a flare may be less precise and more susceptible to recall bias due to systematically reporting exposures differently during a flare, compared to control measurement independent of flares