J. Antonio Aviña-Zubieta

Risk of cardiovascular mortality in patients with rheumatoid arthritis: A meta-analysis of observational studies

OBJECTIVE To determine the magnitude of risk of cardiovascular mortality in patients with rheumatoid arthritis (RA) compared with the general population through a meta-analysis of observational studies. METHODS We searched Medline, EMBase, and Lilacs databases from their inception to July 2005. Observational studies that met the following criteria were assessed by 2 researchers: 1) prespecified RA definition, 2) clearly defined cardiovascular disease (CVD) outcome, including ischemic heart disease (IHD) and cerebrovascular accidents (CVAs), and 3) reported standardized mortality ratios (SMRs) and 95% confidence intervals (95% CIs). We calculated weighted-pooled summary estimates of SMRs (meta-SMRs) for CVD, IHD, and CVAs using the random-effects model, and tested for heterogeneity using the I(2) statistic. RESULTS Twenty-four studies met the inclusion criteria, comprising 111,758 patients with 22,927 cardiovascular events. Overall, there was a 50% increased risk of CVD death in patients with RA (meta-SMR 1.50, 95% CI 1.39-1.61). Mortality risks for IHD and CVA were increased by 59% and 52%, respectively (meta-SMR 1.59, 95% CI 1.46-1.73 and meta-SMR 1.52, 95% CI 1.40-1.67, respectively). We identified asymmetry in the funnel plot (Eggers test P = 0.002), as well as significant heterogeneity in all main analyses (P < 0.0001). Subgroup analyses showed that inception cohort studies (n = 4, comprising 2,175 RA cases) were the only group that did not show a significantly increased risk for CVD (meta-SMR 1.19, 95% CI 0.86-1.68). CONCLUSION Published data indicate that CVD mortality is increased by approximately 50% in RA patients compared with the general population. However, we found that study characteristics may influence the estimate.

Overall and Cause-Specific Mortality in Patients With Systemic Lupus Erythematosus: A Meta-Analysis of Observational Studies

To determine the magnitude of risk from all‐cause and cause‐specific mortality in patients with systemic lupus erythematosus (SLE) compared to the general population through a meta‐analysis of observational studies.

A systematic review identifies valid comorbidity indices derived from administrative health data

OBJECTIVES To conduct a systematic review of studies reporting on the development or validation of comorbidity indices using administrative health data and compare their ability to predict outcomes related to comorbidity (ie, construct validity). STUDY DESIGN AND SETTING We conducted a comprehensive literature search of MEDLINE and EMBASE, until September 2012. After title and abstract screen, relevant articles were selected for review by two independent investigators. Predictive validity and model fit were measured using c-statistic for dichotomous outcomes and R(2) for continuous outcomes. RESULTS Our review includes 76 articles. Two categories of comorbidity indices were identified: those identifying comorbidities based on diagnoses, using International Classification of Disease codes from hospitalization or outpatient data, and based on medications, using pharmacy data. The ability of indices studied to predict morbidity-related outcomes ranged from poor (C statistic ≤ 0.69) to excellent (C statistic >0.80) depending on the specific index, outcome measured, and study population. Diagnosis-based measures, particularly the Elixhauser Index and the Romano adaptation of the Charlson Index, resulted in higher ability to predict mortality outcomes. Medication-based indices, such as the Chronic Disease Score, demonstrated better performance for predicting health care utilization. CONCLUSION A number of valid comorbidity indices derived from administrative data are available. Selection of an appropriate index should take into account the type of data available, study population, and specific outcome of interest.

Immediate and past cumulative effects of oral glucocorticoids on the risk of acute myocardial infarction in rheumatoid arthritis: a population-based study

OBJECTIVES To determine the effect of glucocorticoids (GCs) on acute myocardial infarction (MI) risk in patients with RA. METHODS Using administrative health data, we conducted a population-based cohort study of 8384 incident RA cases (1997-2006). Primary exposure was incident GC use. MI events were ascertained using hospitalization and vital statistics data. We used Cox proportional-hazards models and modelled GC use as four alternative time-dependent variables (current use, current dose, cumulative dose and cumulative duration), adjusting for demographics, comorbidities, cardiovascular drug use, propensity score and RA characteristics. Sensitivity analyses explored potential effects of unmeasured confounding. RESULTS Within 50 238 person-years in 8384 RA cases, we identified 298 incident MI events. Multivariable models showed that current GC use was associated with 68% increased risk of MI [Hazard ratio (HR) = 1.68, 95% CI 1.14, 2.47]. Similarly, separate multivariable models showed that current daily dose (HR = 1.14, 95% CI 1.05, 1.24 per each 5 mg/day increase), cumulative duration of use (HR = 1.14, 95% CI 1.00, 1.29 per year of GC use) and total cumulative dose (HR = 1.06, 95% CI 1.02, 1.10 per gram accumulated in the past) were also associated with increased risk of MI. Furthermore, in the same multivariable model, current dose and cumulative use were independently associated with an increased risk of MI (10% per additional year on GCs and 13% per 5 mg/day increase). CONCLUSION GCs are associated with an increased risk of MI in RA. Our results suggest a dual effect of GCs on MI risk, an immediate effect mediated through current dosage and a long-term effect of cumulative exposure.

Validity of myocardial infarction diagnoses in administrative databases: a systematic review.

Background Though administrative databases are increasingly being used for research related to myocardial infarction (MI), the validity of MI diagnoses in these databases has never been synthesized on a large scale. Objective To conduct the first systematic review of studies reporting on the validity of diagnostic codes for identifying MI in administrative data. Methods MEDLINE and EMBASE were searched (inception to November 2010) for studies: (a) Using administrative data to identify MI; or (b) Evaluating the validity of MI codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value (PPV), negative predictive value, or Kappa scores) for MI, or data sufficient for their calculation. Additonal articles were located by handsearch (up to February 2011) of original papers. Data were extracted by two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Results Thirty studies published from 1984–2010 were included; most assessed codes from the International Classification of Diseases (ICD)-9th revision. Sensitivity and specificity of hospitalization data for identifying MI in most [≥50%] studies was ≥86%, and PPV in most studies was ≥93%. The PPV was higher in the more-recent studies, and lower when criteria that do not incorporate cardiac troponin levels (such as the MONICA) were employed as the gold standard. MI as a cause-of-death on death certificates also demonstrated lower accuracy, with maximum PPV of 60% (for definite MI). Conclusions Hospitalization data has higher validity and hence can be used to identify MI, but the accuracy of MI as a cause-of-death on death certificates is suboptimal, and more studies are needed on the validity of ICD-10 codes. When using administrative data for research purposes, authors should recognize these factors and avoid using vital statistics data if hospitalization data is not available to confirm deaths from MI.

Validity of Diagnostic Codes for Acute Stroke in Administrative Databases: A Systematic Review

Objective To conduct a systematic review of studies reporting on the validity of International Classification of Diseases (ICD) codes for identifying stroke in administrative data. Methods MEDLINE and EMBASE were searched (inception to February 2015) for studies: (a) Using administrative data to identify stroke; or (b) Evaluating the validity of stroke codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), or Kappa scores) for stroke, or data sufficient for their calculation. Additional articles were located by hand search (up to February 2015) of original papers. Studies solely evaluating codes for transient ischaemic attack were excluded. Data were extracted by two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Results Seventy-seven studies published from 1976–2015 were included. The sensitivity of ICD-9 430-438/ICD-10 I60-I69 for any cerebrovascular disease was ≥ 82% in most [≥ 50%] studies, and specificity and NPV were both ≥ 95%. The PPV of these codes for any cerebrovascular disease was ≥ 81% in most studies, while the PPV specifically for acute stroke was ≤ 68%. In at least 50% of studies, PPVs were ≥ 93% for subarachnoid haemorrhage (ICD-9 430/ICD-10 I60), 89% for intracerebral haemorrhage (ICD-9 431/ICD-10 I61), and 82% for ischaemic stroke (ICD-9 434/ICD-10 I63 or ICD-9 434&436). For in-hospital deaths, sensitivity was 55%. For cerebrovascular disease or acute stroke as a cause-of-death on death certificates, sensitivity was ≤ 71% in most studies while PPV was ≥ 87%. Conclusions While most cases of prevalent cerebrovascular disease can be detected using 430-438/I60-I69 collectively, acute stroke must be defined using more specific codes. Most in-hospital deaths and death certificates with stroke as a cause-of-death correspond to true stroke deaths. Linking vital statistics and hospitalization data may improve the ascertainment of fatal stroke.

Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.

Objective Heart failure (HF) is an important covariate and outcome in studies of elderly populations and cardiovascular disease cohorts, among others. Administrative data is increasingly being used for long-term clinical research in these populations. We aimed to conduct the first systematic review and meta-analysis of studies reporting on the validity of diagnostic codes for identifying HF in administrative data. Methods MEDLINE and EMBASE were searched (inception to November 2010) for studies: (a) Using administrative data to identify HF; or (b) Evaluating the validity of HF codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value [PPV], negative predictive value, or Kappa scores) for HF, or data sufficient for their calculation. Additional articles were located by hand search (up to February 2011) of original papers. Data were extracted by two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Using a random-effects model, pooled sensitivity and specificity values were produced, along with estimates of the positive (LR+) and negative (LR−) likelihood ratios, and diagnostic odds ratios (DOR = LR+/LR−) of HF codes. Results Nineteen studies published from1999–2009 were included in the qualitative review. Specificity was ≥95% in all studies and PPV was ≥87% in the majority, but sensitivity was lower (≥69% in ≥50% of studies). In a meta-analysis of the 11 studies reporting sensitivity and specificity values, the pooled sensitivity was 75.3% (95% CI: 74.7–75.9) and specificity was 96.8% (95% CI: 96.8–96.9). The pooled LR+ was 51.9 (20.5–131.6), the LR− was 0.27 (0.20–0.37), and the DOR was 186.5 (96.8–359.2). Conclusions While most HF diagnoses in administrative databases do correspond to true HF cases, about one-quarter of HF cases are not captured. The use of broader search parameters, along with laboratory and prescription medication data, may help identify more cases.

The risk of deep venous thrombosis and pulmonary embolism in giant cell arteritis: a general population-based study

Importance Patients with giant cell arteritis (GCA) may have an increased risk of pulmonary embolism (PE), similar to other systemic vasculitidies; however, no relevant population data are available to date. Objective To evaluate the future risk and time trends of new venous thromboembolism (VTE) in individuals with incident GCA at the general population level. Design Observational cohort study. Setting General population of British Columbia. Participants 909 patients with incident GCA and 9288 age-matched, sex-matched and entry-time-matched control patients without a history of VTE. Main outcome measures We calculated incidence rate ratios (IRR) overall, and stratified by GCA duration. We calculated HR of PE and deep vein thrombosis (DVT), adjusting for potential VTE risk factors. Results Among 909 individuals with GCA (mean age 76 years, 73% women), 18 developed PE and 20 developed DVT. Incidence rates (IR) of VTE, PE and DVT were 13.3, 7.7 and 8.5 per 1000 person-years (PY) in GCA cohort, versus 3.7, 1.9 and 2.2 per 1000 PY in the comparison cohort. The corresponding IRRs (95% CI) for VTE, PE and DVT were 3.58 (2.33 to 5.34), 3.98 (2.22 to 6.81) and 3.82 (2.21 to 6.34) with the highest IRR observed in the first year of GCA diagnosis (7.03, 7.23 and 7.85, respectively). Corresponding fully adjusted HRs (95% CI) were 2.49 (1.45 to 4.30), 2.71 (1.32 to 5.56) and 2.78 (1.39 to 5.54). Conclusions and significance These findings provide general population-based evidence that patients with GCA have an increased risk of VTE, calling for increased vigilance in preventing this serious, but preventable complication, especially within months after GCA diagnosis.

Why the findings of published multiple treatment comparison meta-analyses of biologic treatments for rheumatoid arthritis are different: an overview of recurrent methodological shortcomings

Objectives To evaluate the quality of published multiple treatment comparison (MTC) meta-analyses on biologic disease modifying antirheumatic drugs (bDMARDs) for rheumatoid arthritis (RA), and to identify methodological issues that can explain the discrepancies in the findings of these MTCs. Methods We searched MEDLINE for MTCs of bDMARDs for RA. Following the PRISMA guidelines, we extracted a large set of methodological items. These comprised of inclusion/exclusion criteria, information sources, reported results and outcomes measures, approaches to dealing with differing response profiles to available treatments, monotherapies versus combination therapies, and potential sources of heterogeneity. Results We identified 13 published MTCs, of which nine were published since 2009. Despite similar stated eligibility criteria and objectives across MTCs, we identified major discrepancies in the estimated treatment effects, the inclusion of trials and analytic approaches. The number of included trials was typically much smaller than the number of eligible trials at the time of publication. Three out of six MTCs including patients of differing response profiles inappropriately combined DMARD-naive and DMARD-inadequate responder patients in the analyses. Four out of eight MTCs that considered both monotherapy and combination therapy (ie, concomitant DMARD) did not adjust for the potential effect modification. Half of the identified MTCs did not explore potential sources of heterogeneity, and the explored sources varied considerably. Last, most MTCs only included one or two efficacy outcomes (eg, ACR50) and only two considered health related quality of life outcomes (eg, HAQ). Conclusions The identified methodological shortcomings and inconsistencies most likely explain the observed discrepancies in findings across MTCs.

Approaches for estimating minimal clinically important differences in systemic lupus erythematosus

A minimal clinically important difference (MCID) is an important concept used to determine whether a medical intervention improves perceived outcomes in patients. Prior to the introduction of the concept in 1989, studies focused primarily on statistical significance. As most recent clinical trials in systemic lupus erythematosus (SLE) have failed to show significant effects, determining a clinically relevant threshold for outcome scores (that is, the MCID) of existing instruments may be critical for conducting and interpreting meaningful clinical trials as well as for facilitating the establishment of treatment recommendations for patients. To that effect, methods to determine the MCID can be divided into two well-defined categories: distribution-based and anchor-based approaches. Distribution-based approaches are based on statistical characteristics of the obtained samples. There are various methods within the distribution-based approach, including the standard error of measurement, the standard deviation, the effect size, the minimal detectable change, the reliable change index, and the standardized response mean. Anchor-based approaches compare the change in a patient-reported outcome to a second, external measure of change (that is, one that is more clearly understood, such as a global assessment), which serves as the anchor. Finally, the Delphi technique can be applied as an adjunct to defining a clinically important difference. Despite an abundance of methods reported in the literature, little work in MCID estimation has been done in the context of SLE. As the MCID can help determine the effect of a given therapy on a patient and add meaning to statistical inferences made in clinical research, we believe there ought to be renewed focus on this area. Here, we provide an update on the use of MCIDs in clinical research, review some of the work done in this area in SLE, and propose an agenda for future research.