Predictors of the likelihood that patients with rheumatoid arthritis will communicate information about rheumatoid arthritis risk to relatives:a quantitative assessment

First-degree relatives (FDRs) of people with rheumatoid arthritis (RA) are increasingly recruited to prediction and prevention studies. Access to FDRs is usually via their proband with RA. Quantitative data on predictors of family risk communication are lacking. RA patients completed a questionnaire assessing likelihood of communicating RA risk information to their FDRs, demographic variables, disease impact, illness perceptions, autonomy preferences, interest in FDRs taking a predictive test for RA, dispositional openness, family functioning, and attitudes towards predictive testing. Ordinal regression examined associations between patients’ characteristics and their median likelihood of communicating RA risk to FDRs. Questionnaires were completed by 482 patients. The majority (75.1%) were likely/extremely likely to communicate RA risk information to FDRs, especially their children. Decision-making preferences, interest in FDRs taking a predictive test, and beliefs that risk knowledge would increase people’s empowerment over their health increased patients’ odds of being likely to communicate RA risk information to FDRs. Beliefs that risk information would cause stress to their relatives decreased odds that patients would be likely to communicate RA risk. These findings will inform the development of resources to support family communication about RA risk.<br/

Comorbidity phenotypes and risk of mortality in patients with osteoarthritis in the UK:a latent class analysis

BACKGROUND: Osteoarthritis (OA) is a common chronic condition but its association with other chronic conditions and mortality is largely unknown. This study aimed to use latent class analysis (LCA) of 30 comorbidities in patients with OA and matched controls without OA to identify clusters of comorbidities and examine the associations between the clusters, opioid use, and mortality. METHODS: A matched cohort analysis of patients derived from the IQVIA Medical Research Data (IMRD-UK) database between 2000 and 2019. 418,329 patients with newly diagnosed OA were matched to 243,170 patients without OA to identify comorbidity phenotypes. Further analysis investigated the effect of opioid use on mortality in individuals with OA and their matched controls. RESULTS: The median (interquartile range (IQR)) number of comorbidities was 2 (1–4) and 1 (0–3) in the OA and control groups respectively. LCA identified six comorbidity phenotypes in individuals with and without OA. Clusters with a high prevalence of comorbidities were characterised by hypertension, circulatory, and metabolic diseases. We identified a comorbidity cluster with the aforementioned comorbidities plus a high prevalence of chronic kidney disease, which was associated with twice the hazard of mortality in hand OA with a hazard ratio (HR) (95% CI) of 2.53 (2.05–3.13) compared to the hazard observed in hip/knee OA subtype 1.33 (1.24–1.42). The impact of opioid use in the first 12 months on hazards of mortality was significantly greater for weak opioids and strong opioids across all groups HR (95% CI) ranging from 1.11 (1.07–11.6) to 1.80 (1.69–1.92)). There was however no evidence of association between NSAID use and altered risk of mortality. CONCLUSION: This study identified six comorbidity clusters in individuals with OA and matched controls within this cohort. Opioid use and comorbidity clusters were differentially associated with the risk of mortality. The analyses may help shape the development of future interventions or health services that take into account the impact of these comorbidity clusters. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13075-022-02909-4

Predictors of interest in predictive testing for rheumatoid arthritis among first degree relatives of rheumatoid arthritis patients

Objectives: There is increasing interest in prediction and prevention of RA. It is important to understand the views of those at risk to inform the development of effective approaches. First-degree relatives (FDRs) of RA patients are at increased risk of RA. This study assessed predictors of their interest in predictive testing for RA. Methods: Questionnaires were completed by RA patients (provided with their questionnaire by a healthcare professional) and their FDRs (provided with their questionnaire by their RA proband). FDR surveys assessed interest in taking a predictive test, demographic variables, perceived RA risk, attitudes about predictive testing, autonomy preferences, illness perceptions, avoidance coping and health anxiety. Patient surveys included demographic variables, disease impact, RA duration and treatment. Ordinal logistic regression examined the association between FDRs’ characteristics and their interest in predictive testing. Generalized estimating equations assessed associations between patient characteristics and FDRs’ interest in predictive testing. Results: Three hundred and ninety-six FDRs responded. Paired data from the RA proband were available for 292. The proportion of FDRs interested in predictive testing was 91.3%. Information-seeking preferences, beliefs that predictive testing can increase empowerment over health and positive attitudes about risk knowledge were associated with increased interest. Beliefs that predictive testing could cause psychological harm predicted lower interest. Patient characteristics of the proband were not associated with FDRs’ interest. Conclusions: FDRs’ interest in predictive testing for RA was high, and factors associated with interest were identified. These findings will inform the development of predictive strategies and informational resources for those at risk

Healthcare resource utilisation and economic burden attributable to back pain in primary care: A matched case-control study in the United Kingdom

Objective Incremental healthcare costs attributed to back pain, and characterisation by patient and clinical factors have rarely been documented. This study aimed to assess annual healthcare resource utilisation and costs associated with back pain in primary care. Methods Using the IQVIA Medical Research Data (IMRD), patients with back pain were identified (study period: 01 January 2006 to 31 December 2015) using diagnostic records and analgesics prescriptions ( n = 133,341), and propensity score matched 1:1 to patients without back pain. The annual incremental costs of back pain associated with consultations and prescriptions were estimated and extrapolated to a national level. Sensitivity analysis was conducted by restricting the study population to the most recent diagnosis of back pain. Variations in cost were assessed stratified by gender, age-groups, deprivation, and comorbidity categories. Results The mean age was 57 years, and 62% were females in both the case and control groups. The total incremental healthcare costs associated with back pain was £32.5 million in 2015 (£35.9 million in 2020), with per-patient cost of £244 (£265 in 2020) per year. On a national level, this translated to an estimated £3.2 billion (£3.5 billion in 2020). Eighty percent of the costs were attributed to consultations; and female gender, older age, higher deprivation, and higher comorbidity were all associated with increased mean healthcare costs of patients with back pain. Conclusion Our findings confirm the substantial healthcare costs attributed to back pain, even with primacy care costs only. The data also revealed significant cost variations across socio-demographic and clinical factors

The cost of primary care consultations associated with long COVID in non-hospitalised adults:a retrospective cohort study using UK primary care data

Abstract Background The economic impact of managing long COVID in primary care is unknown. We estimated the costs of primary care consultations associated with long COVID and explored the relationship between risk factors and costs. Methods Data were obtained on non-hospitalised adults from the Clinical Practice Research Datalink Aurum primary care database. We used propensity score matching with an incremental cost method to estimate additional primary care consultation costs associated with long COVID (12 weeks after COVID-19) at an individual and UK national level. We applied multivariable regression models to estimate the association between risk factors and consultations costs beyond 12 weeks from acute COVID-19. Results Based on an analysis of 472,173 patients with COVID-19 and 472,173 unexposed individuals, the annual incremental cost of primary care consultations associated with long COVID was £2.44 per patient and £23,382,452 at the national level. Among patients with COVID-19, a long COVID diagnosis and reporting of longer-term symptoms were associated with a 43% and 44% increase in primary care consultation costs respectively, compared to patients without long COVID symptoms. Older age, female sex, obesity, being from a white ethnic group, comorbidities and prior consultation frequency were all associated with increased primary care consultation costs. Conclusions The costs of primary care consultations associated with long COVID in non-hospitalised adults are substantial. Costs are significantly higher among those diagnosed with long COVID, those with long COVID symptoms, older adults, females, and those with obesity and comorbidities

The economic burden and determinants of healthcare costs of back pain in the UK: an empirical investigation using electronic health records

Back pain is a common health problem globally and it imposes great costs associated with its treatment. In the UK, the healthcare costs associated with back pain were last estimated 20 years ago in a cost-of-illness (COI) study. Given the aging population worldwide, these costs are likely to rise putting further pressure on healthcare services. The use of robust, and more advanced econometric methods to exploit national electronic health records (EHRs) may present up-to-date and more precise estimates for the healthcare costs of back pain. This thesis utilises such data source and methods to estimate the consultations, and prescriptions costs of back pain and to investigate factors associated with these costs. The systematic review of the literature assessed the methodologies used in COI studies of back pain. The vast majority of studies used a direct method of summing up back pain related costs which underestimated the true cost of back pain compared to an incremental cost approach. The latter approach which is conducted using a matched control or regression-based methods is more accurate, and comprehensive. This thesis further explored potential data sources that could be utilised for estimating healthcare resource use and costs of back pain in the UK. The Health Improvement Network (THIN), one of the two most widely used primary care databases in clinical research, was identified providing complete records of consultations and prescriptions data. Matched control studies, using propensity score matching, were conducted to estimate annual healthcare costs (2011-2015), and to assess how estimates vary by socio-economic factors, and over time. The incremental costs obtained in comparison with a similar reference population enabled the risk of confounding effects due to differences in baseline characteristics to be minimised. The thesis further evaluated several alternative econometric methods used in modelling healthcare cost data. A cross-sectional study was then conducted to assess factors associated with healthcare costs of back pain. Regression analysis methods applied included OLS, log transformed OLS, generalised linear models (GLMs), extended estimating equations (EEE) model, and a quantile regression approach. How well the alternative estimators performed in terms of bias, accuracy and goodness-of-fit was compared by examining regression diagnostics, and predictive performance of the models. The findings demonstrate the need for researchers to examine their assumptions about the most appropriate model for analysing healthcare cost data

Cluster analysis of patients with granulomatosis with polyangiitis (GPA) based on clinical presentation symptoms:a UK population-based cohort study

BACKGROUND: Granulomatosis with polyangiitis (GPA) is small vessel vasculitis with heterogeneous clinical presentation. In the present population-based cohort study, we classified patients with GPA based on clinical features at presentation using an unsupervised clustering approach and compared their mortality, infections and frequency of comorbidities. METHODS: In this open cohort study, de-identified primary care data of patients with GPA included in the IQVIA Medical Research Data database between 1 January 1995 and 25 September 2019 was analysed retrospectively. Latent class analysis was performed to create symptom clusters of patients based on 16 categories of symptoms representing various organ involvement. All-cause mortality of resultant clusters was compared after adjusting for age, sex, Townsend deprivation quintile and smoking status at index date using extended Cox proportional hazards models. Prescription of antibiotics, considered as an indirect indicator of recurrent bacterial infection, was compared using a recurrent event model, after adjusting for quarterly use of steroid as a time-dependent covariate. Cumulative frequencies of common comorbidities were compared among the clusters at index visit, 1-year and 3-year follow-up. RESULTS: Altogether, 649 patients with GPA [median age 60.0 (IQR: 49.6–70.1)] were included. Three clusters were identified: patients with limited disease mainly with involvement of ENT and cough were classified into cluster 1 (n = 426); cluster 2 had generalised non-renal disease (n = 176); while patients in cluster 3 had renal-predominant disease (n = 47). Many patients in cluster 1 developed generalised disease at the end of 1 year. Mortality in clusters 2 and 3 was higher compared with cluster 1. Mortality in cluster 1 itself was 68% higher than the general population without GPA. The duration of antibiotics prescription and frequency of coexisting medical illnesses was also higher in clusters 2 and 3. CONCLUSIONS: In a primary care setting, patients with GPA can be classified into three distinct clusters with different prognosis, susceptibility to recurrent infections and presence of comorbidities. The tendency of cluster 1 to evolve into a more generalised disease raises questions about current immunosuppressive treatment approaches in these patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13075-022-02885-9