Comorbidity burden in the first three years after diagnosis in patients with rheumatoid arthritis, psoriatic arthritis or spondyloarthritis: a general practice registry-based study

Objectives Rheumatoid arthritis (RA), psoriatic arthritis (PsA) and spondyloarthritis (SpA) are chronic inflammatory rheumatic conditions with high levels of comorbidity requiring additional therapeutic attention. We aimed to compare the 3-year comorbidity incidence and pain medication prescription in patients diagnosed with RA, PsA or SpA versus controls.Methods Data between 1999 and 2012 were obtained from Intego, a general practitioner (GP) morbidity registry in Flanders, Belgium. Cases were identified by International Classification of Primary Care (ICPC-2) codes representing ‘rheumatoid/seropositive arthritis (L88)’ or ‘musculoskeletal disease other (L99)’. The registered keywords mapped to these ICPC-2 codes were further verified and mapped to a RA/SpA/PsA diagnosis. Controls were matched on age, gender, GP practice and diagnosis date. We analysed the 3-year comorbidity burden in cases and controls, measured by the Rheumatic Diseases Comorbidity Index (RDCI). All electronically GP-prescribed drugs were registered.Results In total, 738, 229 and 167 patients were included with a diagnosis of RA, SpA or PsA, respectively. Patients with RA or PsA had comparable median RDCI scores at baseline, but higher scores at year 3 compared with controls (RA: p=0.010; PsA: p=0.008). At baseline, depression was more prevalent in PsA patients vs controls (p<0.003). RA patients had a higher 3-year incidence of cardiovascular disease including myocardial infarction than controls (p<0.035). All disease population were given more prescriptions than controls for any pain medication type, even opioids excluding tramadol.Conclusions This study highlights the increasing comorbidity burden of patients with chronic inflammatory rheumatic conditions, especially for individuals with RA or PsA. The high opioid use in all populations was remarkable

Epidemiology of knee osteoarthritis in general practice: a registry-based study

OBJECTIVES: The present study investigated (1) trends in the prevalence and incidence of knee osteoarthritis over a 20-year period (1996-2015); (2) trends in multimorbidity and (3) trends in drug prescriptions. DESIGN: Registry-based study. SETTING: Primary healthcare, Flanders, Belgium. PARTICIPANTS: Data were collected from Intego, a general practice-based morbidity registration network. In the study period between 1996 and 2015, data from 440 140 unique patients were available. OUTCOME MEASURES: Trends in prevalence and incidence rate of knee osteoarthritis were computed using joinpoint regression analysis. The mean disease count was calculated to assess trends in multimorbidity. In addition, the number of drug prescriptions was identified by the Anatomical Therapeutic Chemical Classification code and trends were equally recorded with joinpoint regression. RESULTS: The total age-standardised prevalence of knee osteoarthritis increased from 2.0% in 1996 to 3.6% in 2015. An upward trend was observed with an average annual percentage change (AAPC) of 2.5 (95% CI 2.2 to 2.9). In 2015, the prevalence rates in the 10 year age groups from the 45-54 years age group onwards were 3.1%, 5.6%, 9.0% and 13.9%, to reach 15.0% in people aged 85 years and older. The incidence remained stable with 3.75 per thousand in 2015 (AAPC=-0.5, 95% CI -1.4 to 0.5). The mean disease count significantly increased from 1.63 to 2.34 (p<0.001) for incident cases with knee osteoarthritis. Finally, we observed a significantly positive trend in the overall prescription of acetaminophen (AAPC=6.7, 95% CI 5.6 to 7.7), weak opioids (AAPC=4.0, 95% CI 0.9 to 7.3) and glucosamine (AAPC=8.6, 95% CI 2.4 to 15.1). Oral non-steroidal anti-inflammatory drugs were most prescribed, with a prevalence rate of 29.8% in 2015, but remained stable during the study period (AAPC=0.0, 95% CI -1.1 to 1.1). CONCLUSIONS: Increased prevalence, multimorbidity, and number of drug prescriptions confirm an increased burden of knee osteoarthritis. In future, these trends can be used to prioritise initiatives for improvement in care

Invloed dalende eGFR op cardiovasculaire events

status: publishe

Fast and optimal algorithm for case-control matching using registry data: application on the antibiotics use of colorectal cancer patients

Background In case-control studies most algorithms allow the controls to be sampled several times, which is not always optimal. If many controls are available and adjustment for several covariates is necessary, matching without replacement might increase statistical efficiency. Comparing similar units when having observational data is of utter importance, since confounding and selection bias is present. The aim was twofold, firstly to create a method that accommodates the option that a control is not resampled, and second, to display several scenarios that identify changes of Odds Ratios (ORs) while increasing the balance of the matched sample. Methods The algorithm was derived in an iterative way starting from the pre-processing steps to derive the data until its application in a study to investigate the risk of antibiotics on colorectal cancer in the INTEGO registry (Flanders, Belgium). Different scenarios were developed to investigate the fluctuation of ORs using the combination of exact and varying variables with or without replacement of controls. To achieve balance in the population, we introduced the Comorbidity Index (CI) variable, which is the sum of chronic diseases as a means to have comparable units for drawing valid associations. Results This algorithm is fast and optimal. We simulated data and demonstrated that the run-time of matching even with millions of patients is minimal. Optimal, since the closest controls is always captured (using the appropriate ordering and by creating some auxiliary variables), and in the scenario that a case has only one control, we assure that this control will be matched to this case, thus maximizing the cases to be used in the analysis. In total, 72 different scenarios were displayed indicating the fluctuation of ORs, and revealing patterns, especially a drop when balancing the population. Conclusions We created an optimal and computationally efficient algorithm to derive a matched case-control sample with and without replacement of controls. The code and the functions are publicly available as an open source in an R package. Finally, we emphasize the importance of displaying several scenarios and assess the difference of ORs while using an index to balance population in observational data

Cost of healthcare utilization associated with incident cardiovascular and renal disease in individuals with type 2 diabetes: A multinational, observational study across 12 countries

Aim To examine how the development of cardiovascular and renal disease (CVRD) translates to hospital healthcare costs in individuals with type 2 diabetes (T2D) initially free from CVRD. Methods Data were obtained from the digital healthcare systems of 12 nations using a prespecified protocol. A fixed country-specific index date of 1 January was chosen to secure sufficient cohort disease history and maximal follow-up, varying between each nation from 2006 to 2017. At index, all individuals were free from any diagnoses of CVRD (including heart failure [HF], chronic kidney disease [CKD], coronary ischaemic disease, stroke, myocardial infarction [MI], or peripheral artery disease [PAD]). Outcomes during follow-up were hospital visits for CKD, HF, MI, stroke, and PAD. Hospital healthcare costs obtained from six countries, representing 68% of the total study population, were cumulatively summarized for CVRD events occurring during follow-up. Results In total, 1.2 million CVRD-free individuals with T2D were identified and followed for 4.5 years (mean), that is, 4.9 million patient-years. The proportion of individuals indexed before 2010 was 18% (n = 207 137); 2010-2015, 31% (361 175); and after 2015, 52% (609 095). Overall, 184 420 (15.7%) developed CVRD, of which cardiorenal disease was most frequently the first disease to develop (59.7%), consisting of 23.0% HF and 36.7% CKD, and more common than stroke (16.9%), MI (13.7%), and PAD (9.7%). The total cumulative cost for CVRD was US$1 billion, of which 59.0% was attributed to cardiorenal disease, 3-, 5-, and 6-fold times greater than the costs for stroke, MI, and PAD, respectively. Conclusion Across all nations, HF or CKD was the most frequent CVRD manifestation to develop in a low-risk population with T2D, accounting for the highest proportion of hospital healthcare costs. These novel findings highlight the importance of cardiorenal awareness when planning healthcare