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Previous research linking opioid prescribing to adverse drug events failed to properly account for the time-varying nature of opioid exposure. This study aimed to explore how the risk of opioid-related emergency department visits, re-admissions or deaths (composite outcome) varies with opioid dose and duration, comparing different novel modeling techniques. A prospective cohort of 1,511 hospitalized patients discharged from two McGill-affiliated hospitals in Montreal, 2014-2016, was followed from the first post-discharge opioid dispensation until one year post-discharge. Marginal structural Cox proportional hazards models (MSM Cox) and their flexible extensions were used to explore the association between time-varying opioid use and the composite outcome. Weighted cumulative exposure (WCE) models assessed cumulative effects of past use and explored how its impact depends on the recency of exposure. The patient mean age was 69.6 years (SD = 10.3), 57.7% were male. In MSM analyses current opioid use was associated with a 71% increase in the hazard of opioid-related adverse events (adjusted hazard ratio (aHR): 1.71, 95% CI (1.21 – 2.43). The WCE results suggested that the risk cumulates over the past 50 days of opioid consumption. Flexible modeling techniques helped assess how the risk of opioid-related adverse events may be associated with time-varying opioid exposures while accounting for non-linear relationships and the recency of past use.

Both inadequate and excessive maternal weight gain are correlated with preterm delivery in singleton pregnancies, yet this relationship has not been adequately studied in twins. We investigated the relationship between time-varying maternal weight gain and gestational age at delivery in twin pregnancies and compared to that in singletons delivered in the same study population. We used serial weight measurements abstracted from charts for twin and singleton pregnancies delivered from 1998-2013 in Pittsburgh, Pennsylvania. Our exposure was time-varying weight gain z-score calculated using gestational age-standardized and pre-pregnancy body mass index-stratified twin- and singleton-specific charts, and our outcome was gestational age at delivery. Our analyses used a flexible extension of the Cox proportional hazards model that allowed for non-linear and time-dependent effects. We found a U-shaped relationship between weight gain z-score and gestational age at delivery among twin pregnancies (lowest hazard of delivery observed at z-score=1.2), which we attributed to increased hazard of early preterm spontaneous delivery among pregnancies with low weight gain and increased hazard of late preterm delivery without labour among pregnancies with high weight gain. Our findings may be useful for updating provisional guidelines for maternal weight gain in twin pregnancies.

Supplemental Digital Content is available in the text., Background: Cross-sectional studies of hospital-level administrative data have suggested that 4 nurse staffing practices—using adequate staffing levels, higher proportions of registered nurses (RNs) (skill mix), and more educated and experienced RNs—are each associated with reduced hospital mortality. To increase the validity of this evidence, patient-level longitudinal studies assessing the simultaneous associations of these staffing practices with mortality are required. Methods: A dynamic cohort of 146,349 adult medical, surgical, and intensive care patients admitted to a Canadian University Health Center was followed for 7 years (2010–2017). We used a multivariable Cox proportional hazards model to estimate the associations between patients’ time-varying cumulative exposure to measures of RN understaffing, skill mix, education, and experience, each relative to nursing unit and shift means, and the hazard of in-hospital mortality, while adjusting for patient and nursing unit characteristics, and modeling the current nursing unit of hospitalization as a random effect. Results: Overall, 4854 in-hospital deaths occurred during 3,478,603 patient-shifts of follow-up (13.95 deaths/10,000 patient-shifts). In multivariable analyses, every 5% increase in the cumulative proportion of understaffed shifts was associated with a 1.0% increase in mortality (hazard ratio: 1.010; 95% confidence interval: 1.002–1.017; P=0.009). Moreover, every 5% increase in the cumulative proportion of worked hours by baccalaureate-prepared RNs was associated with a 2.0% reduction of mortality (hazard ratio: 0.980; 95% confidence interval: 0.965–0.995, P=0.008). RN experience and skill mix were not significantly associated with mortality. Conclusion: Reducing the frequency of understaffed shifts and increasing the proportion of baccalaureate-prepared RNs are associated with reduced hospital mortality.

Many flexible extensions of the Cox proportional hazards model incorporate time-dependent (TD) and/or nonlinear (NL) effects of time-invariant covariates. In contrast, little attention has been given to the assessment of such effects for continuous time-varying covariates (TVCs). We propose a flexible regression B-spline-based model for TD and NL effects of a TVC. To account for sparse TVC measurements, we added to this model the effect of time elapsed since last observation (TEL), which acts as an effect modifier. TD, NL, and TEL effects are estimated with the iterative alternative conditional estimation algorithm. Furthermore, a simulation extrapolation (SIMEX)-like procedure was adapted to correct the estimated effects for random measurement errors in the observed TVC values. In simulations, TD and NL estimates were unbiased if the TVC was measured with a high frequency. With sparse measurements, the strength of the effects was underestimated but the TEL estimate helped reduce the bias, whereas SIMEX helped further to correct for bias toward the null due to "white noise" measurement errors. We reassessed the effects of systolic blood pressure (SBP) and total cholesterol, measured at two-year intervals, on cardiovascular risks in women participating in the Framingham Heart Study. Accounting for TD effects of SBP, cholesterol and age, the NL effect of cholesterol, and the TEL effect of SBP improved substantially the model's fit to data. Flexible estimates yielded clinically important insights regarding the role of these risk factors. These results illustrate the advantages of flexible modeling of TVC effects.

Objectives To obtain comprehensive insight into the association of ciprofloxacin use at different times in the past with the current risk of detecting resistance. Methods This retrospective nested case–control study of ciprofloxacin users used Dutch data from the PHARMO Database Network and one laboratory for the period 2003–14. Cases and controls were selected as patients with an antibiotic susceptibility test (AST) indicating ciprofloxacin resistance or susceptibility, respectively. We performed univariable and multivariable conditional logistic regression analyses, defining time-dependent exposure using standard definitions (current ciprofloxacin use, used 0–30, 31–90, 91–180 and 181–360 days ago) and a flexible weighted cumulative effect (WCE) model with four alternative time windows of past doses (0–30, 0–90, 0–180 and 0–360 days). Results The study population consisted of 230 cases and 909 controls. Under the standard exposure definitions, the association of ciprofloxacin use with resistance decreased with time [current use: adjusted OR 6.8 (95% CI 3.6–12.4); used 181–360 days ago: 1.3 (0.8–1.9)]. Under the 90 day WCE model (best-fitting model), more recent doses were more strongly associated with resistance than past doses, as was longer or repeated treatment. The 180 day WCE model, which fitted the data equally well, suggested that doses taken 91–180 days ago were also significantly associated with resistance. Conclusions The estimates for the association between ciprofloxacin use at different times and resistance show that ciprofloxacin prescribers should consider ciprofloxacin use 0–180 days ago to ensure that patients receive suitable treatment. The OR of ciprofloxacin resistance could be reduced by eliminating repeated ciprofloxacin prescription within 180 days and by treating for no longer than necessary.

Aims Randomized trials suggest reductions in all-cause mortality and heart failure (HF) rehospitalizations with catheter ablation (CA) in patients with atrial fibrillation (AF) and HF. Whether these results can be replicated in a real-world population with long-term follow-up or varies over time is unknown. We sought to evaluate the long-term effectiveness of CA in reducing the incidence of all-cause mortality, HF hospitalizations, stroke, and major bleeding in AF–HF patients. Methods and results In a cohort of patients newly diagnosed with AF–HF in Quebec, Canada (2000–2017), CA patients were matched 1:2 to controls on time and frequency of hospitalizations. Confounders were controlled for using inverse probability of treatment weighting. Multivariable Cox models adjusted for the presence of cardiac electronic implantable devices and medication use during follow-up, and the effect of time since CA was modelled with B-splines. For non-fatal outcomes, the Lunn–McNeil approach was used to account for the competing risk of death. Among 101 933 AF–HF patients, 451 underwent CA and were matched to 899 controls. Over a median follow-up of 3.8 years, CA was associated with a statistically significant reduction in all-cause mortality [hazard ratio 0.4 (95% confidence interval 0.2–0.7)], but no difference in stroke or major bleeding. The hazard of HF rehospitalization for CA patients, relative to non-CA patients, varied with time since CA (P = 0.01), with a reduction in HF rehospitalizations until approximately 3 years post-CA. Conclusion Compared with matched non-CA patients, CA was associated with a long-term reduction in all-cause mortality and a reduction in HF rehospitalizations until 3 years post-CA.

Aims To evaluate the association between metformin use and heart failure (HF) exacerbation in people with type 2 diabetes (T2D) and pre-existing HF using alternative exposure models. Materials and methods We analysed data for patients with T2D and incident HF from a national US insurance claims database. We compared the results of several multivariable Cox models where time-varying use of metformin was modelled as: (1) current use; (2) total duration of past use; and (3) use within the past 30 days or 10 days. The outcome was defined as time to HF-related hospitalization. We then re-analysed the data using flexible weighted cumulative exposure (WCE) models. Results A total of 7620 patients with diabetes and incident HF were analysed. The mean (SD) patient age was 54 (8) years, and 58% (n = 4440) were men. In all, 3799 individuals (50%) were exposed to metformin, and 837 HF hospitalizations (11%) occurred (mean follow-up 1.7 years). Results of conventional models suggested potential acute benefits in reducing HF exacerbation with metformin use in the past 10 days (adjusted hazard ratio [aHR] 0.76, 95% confidence interval [CI] 0.60-0.97), while WCE models, which provided a better fit for the data, suggested lack of a systematic effect (aHR 0.91, 95% CI 0.69-1.20). Conclusions Our results suggest that cumulative metformin exposure does not decrease the risk of HF-related exacerbation. Use of other anti-hyperglycaemic agents with proven efficacy in patients with HF should also be considered as treatment options in this population.

M Ellen Kuenzig,1–3 Mohsen Sadatsafavi,4 J Antonio Aviña-Zubieta,5 Rebecca M Burne,6 Michal Abrahamowicz,6,7 Marie-Eve Beauchamp,7 Gilaad G Kaplan,8–11,* Eric I Benchimol1–3,12,13,* 1Children’s Hospital of Eastern Ontario (CHEO) Inflammatory Bowel Disease Centre, Division of Gastroenterology, Hepatology and Nutrition, Children’s Hospital of Eastern Ontario, Ottawa, ON, Canada; 2Health Information Technology Program, CHEO Research Institute, Ottawa, ON, Canada; 3Institute for Clinical Evaluative Sciences, Ottawa, ON, Canada; 4Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada; 5Arthritis Research Canada, Division of Rheumatology, University of British Columbia, Vancouver, BC, Canada; 6Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada; 7Centre for Health Outcomes Research (CORE), Research Institute of the McGill University Health Centre, Montreal, QC, Canada; 8Department of Medicine, University of Calgary, Calgary, AB, Canada; 9Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada; 10O’Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada; 11Snyder Institute for Chronic Diseases, University of Calgary, Calgary, AB, Canada; 12Department of Pediatrics, University of Ottawa; Ottawa, ON, Canada; 13School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada *These authors contributed equally to this work Purpose: Growing evidence suggests asthma and Crohn’s disease commonly cooccur. However, the impact of asthma on the prognosis of Crohn’s disease is unknown. The aim of our study was to assess the effect of asthma on the need for intestinal resection in patients with Crohn’s disease while adjusting for smoking status, imputed from a smaller, secondary data set. Patients and methods: Using health administrative data from a universally funded healthcare plan in Alberta, Canada, we conducted a cohort study to assess the effect of asthma on the need for surgery in patients with Crohn’s disease diagnosed between 2002 and 2008 (N=2,113). Validated algorithms were used to identify incident cases of Crohn’s disease, cooccurring asthma, and intestinal resection. The association between asthma and intestinal resection was estimated using multivariable Cox proportional hazards regression. Smoking status was imputed using a novel method using martingale residuals, derived from a data set of 485 patients enrolled in the Alberta Inflammatory Bowel Disease Consortium (2007 to 2014) who completed environmental questionnaires. All analyses were adjusted for age, sex, rural/urban status, and mean neighborhood income quintile. Results: Asthma did not increase the risk of surgery in the health administrative data when not adjusting for smoking status (HR 1.03, 95% CI 0.81 to 1.29). The association remained nonsignificant after imputing smoking status in the health administrative data (HR 1.03, 95% CI 0.81 to 1.29). Conclusion: Although asthma is associated with an increased risk of Crohn’s disease, co-occurring asthma is not associated with the risk of surgery in these patients. This null association persisted after adjusting for smoking status. This study described a novel method to adjust for confounding (smoking status) in time-to-event analyses, even when the confounding variable is unmeasured in health administrative data. Keywords: Crohn’s disease, asthma, surgery, unmeasured confounding, health administrative data

Purpose Real-life use of nonsteroidal anti-inflammatory drugs (NSAIDs) is dynamic. This study aimed to characterize the temporal association between time-varying NSAID exposure and acute myocardial infarction (MI). Methods Nested case-control analyses were conducted on a Quebec administrative health cohort. NSAID dose, confounders, and outcome status were determined for each day of follow-up. To better account for dose and timing of past exposures, flexible weighted cumulative exposure models were also fitted. Results The cohort consisted of 233 816 older adults including 21 256 acute MI cases. Dose-related increased risks of MI were found with current use of all NSAIDs. In models not accounting for duration of use, ORs (95%CI) for the most common current daily dose vs. no current exposure were: celecoxib 200 mg: 1.16 (1.10, 1.22), diclofenac 150 mg: 1.59 (1.38, 1.84), ibuprofen 1200 mg: 1.42 (1.17, 1.74), naproxen 750 mg: 1.38 (1.21, 1.58), and rofecoxib 25 mg: 1.54 (1.43, 1.66). Weighted cumulative exposure models confirmed that all NSAIDs—including naproxen—are associated with an increased risk of MI and suggested that doses taken up to 3 weeks ago for rofecoxib, ibuprofen, and naproxen and up to 75 days ago for diclofenac and celecoxib may contribute to the current MI risk. However, the celecoxib risk seems to require continuous use for more than 30 days, whereas for other NSAIDs, a heightened MI risk occurs within 7 days. Conclusions Weighted cumulative exposure analysis uncovered NSAID-specific differences in the immediate MI risk and how this risk seems to accumulate. KEY POINTS Accurate assessment of drug safety requires an etiologically correct model encompassing all relevant aspects of exposure. Weighted cumulative exposure models suggest that the relative importance of past doses on the risk of MI differs among NSAIDs. All common NSAIDs are associated with an increased MI risk. Celecoxib MI risk seems to depend on continuously using the drug for more than 30 days, whereas for ibuprofen, rofecoxib, diclofenac, and naproxen, a heightened MI risk occurs within 7 days of use.

Adults with congenital heart disease are increasingly being exposed to low-dose ionizing radiation (LDIR) from cardiac procedures. In a recent study, Cohen et al. (Circulation. 2018;137(13):1334–1345) reported an association between increased LDIR exposure and cancer incidence but did not explore temporal relationships. Yet, the impact of past exposures probably accumulates over years, and its strength may depend on the amount of time elapsed since exposure. Furthermore, LDIR procedures performed shortly before a cancer diagnosis may have been ordered because of early symptoms of cancer, raising concerns about reversal causality bias. To address these challenges, we combined flexible modeling of cumulative exposures with competing-risks methodology to estimate separate associations of time-varying LDIR exposure with cancer incidence and all-cause mortality. Among 24,833 patients from the Quebec Congenital Heart Disease Database, 602 had incident cancer and 500 died during a follow-up period of up to 15 years (1995–2010). Initial results suggested a strong association of cancer incidence with very recent LDIR exposures, likely reflecting reverse causality bias. When exposure was lagged by 2 years, an increased cumulative LDIR dose from the previous 2–6 years was associated with increased cancer incidence, with a stronger association for women. These results illustrate the importance of accurate modeling of temporal relationships between time-varying exposures and health outcomes.

The treatment for hepatitis C virus (HCV) infection has evolved over time, and direct-acting antivirals (DAA) have revolutionized HCV therapy.To (a) assess early treatment discontinuation and (b) identify predictors of early discontinuation in a cohort of patients receiving second-generation DAAs.We identified HCV patients newly prescribed simeprevir/sofosbuvir (SIM/SOF), ledipasvir/sofosbuvir (LDV/SOF), ombitasvir/paritaprevir/ritonavir + dasabuvir (OPrD), sofosbuvir/velpatasvir (SOF/VEL), elbasvir/grazoprevir (EBR/GZR), and glecaprevir/pibrentasvir (GLE/PIB) between 2014 and 2017. Early discontinuation was defined as duration of therapy less than 8 weeks. Multivariable logistic regression was performed to evaluate the association of drug regimens and potential predictive factors to early discontinuation.We identified 26,098 DAA-treated patients: 67.8% with LDV/SOF, 9.9% with OPrD, 8.5% with SIM/SOF, 7.8% with SOF/VEL, 5.2% with EBR/GZR, and 0.8% with GLE/PIB. With approval of new therapies in 2016 and 2017, use of OPrD, LDV/SOF, and SIM/SOF declined substantially. At baseline, there was some heterogeneity of past HCV drug use and comorbidity across groups; patients on SIM/SOF had the highest frequency of previous interferon, cirrhosis, and decompensated cirrhosis. Most HCV patients received therapy for 8-12 weeks; fewer patients went through 16-week and 24-week therapy courses. Early discontinuation rates (95% CI) were 7.1% (6.0-8.2) for SIM/SOF, 3.2% (2.9-3.5) for LDV/SOF, 9.6% (8.5-10.7) for OPrD, 3.1% (2.3-3.8) for SOF/VEL, 4.2% (3.1-5.3) for EBR/GZR, and 2.5% (0.3-4.7) for GLE/PIB. In multivariable analyses, versus OPrD, patients starting other drug regimens were less likely to discontinue therapy early. Early discontinuation was more common in women, patients with baseline anemia, and Medicare and Medicaid patients.These real-world data confirm low rates of early discontinuation in users of second-generation DAAs. Future research focusing on socio-economic and sex/gender issues may help further optimize care for patients with HCV.This study was funded by the Canadian Institutes of Health Research. Klein has received grants for investigator-initiated trials from ViiV Healthcare, Janssen, Gilead, and Merck, as well as consulting fees from ViiV Healthcare, Merck, and AbbVie. Feld has received research support and/or scientific consulting fees from AbbVie, Contravir, Enanta, Gilead, Janssen, Merck, and Wako. All other authors have no conflicts of interest to declare. Results from this study were presented as a poster at the 34th International Conference of Phamacoepidemiology and Therapeutic Risk Management; August 22-26, 2018; Prague, Czech Republic.

Unmeasured confounding is a major threat to the validity of pharmacoepidemiological studies of medication safety and effectiveness. We propose a new method for detecting and reducing the impact of unobserved confounding in large observational database studies. The method uses assumptions similar to the prescribing preference-based instrumental variable (IV) approach. Our method relies on the new ‘missing cause’ principle, according to which the impact of unmeasured confounding by (contra-)indication may be detected by assessing discrepancies between the following: (i) treatment actually received by individual patients and (ii) treatment that they would be expected to receive based on the observed data. Specifically, we use the treatment-by-discrepancy interaction to test for the presence of unmeasured confounding and correct the treatment effect estimate for the resulting bias. Under standard IV assumptions, we first proved that unmeasured confounding induces a spurious treatment-by-discrepancy interaction in risk difference models for binary outcomes and then simulated large pharmacoepidemiological studies with unmeasured confounding. In simulations, our estimates had four to six times smaller bias than conventional treatment effect estimates, adjusted only for measured confounders, and much smaller variance inflation than unbiased but very unstable IV estimates, resulting in uniformly lowest root mean square errors. The much lower variance of our estimates, relative to IV estimates, was also observed in an application comparing gastrointestinal safety of two classes of anti-inflammatory drugs. In conclusion, our missing cause-based method may complement other methods and enhance accuracy of analyses of large pharmacoepidemiological studies. Copyright © 2016 John Wiley & Sons, Ltd.

Objective.We evaluated the associations between time-varying methotrexate (MTX) use and risk of cardiovascular events (CVE) in patients with rheumatoid arthritis (RA).Methods.We studied an inception cohort of 23,994 patients with RA diagnosed after their 65th birthday. Multivariable Cox regression models were fit to evaluate the associations between time-varying MTX use, controlling for other risk factors, and time to CVE. Alternative models assessed the cumulative duration of MTX use over the (1) first year, (2) previous year (recent use), and (3) entire duration of followup. We also assessed whether the strength of the association varied over time.Results.Over 115,453 patient-years (PY), 3294 (13.7%) patients experienced a CVE (28.5 events per 1000 PY; 95% CI 27.6–29.5). In the multivariable analyses, the model assessing time-varying continuous use in the most recent year yielded the best fit. Increasing recent MTX use was associated with lower CVE risks (HR 0.79 for continuous use vs no use in past 12 months, 95% CI 0.70–0.88; p < 0.0001). Greater MTX use in the first year after cohort entry was also protective (HR 0.84, 95% CI 0.72–0.96; p = 0.0048), but this effect decreased with increasing followup. In contrast, longer MTX use during the entire followup was not clearly associated with CVE risk (HR 0.98, 95% CI 0.95–1.01; p = 0.1441).Conclusion.We observed about a 20% decrease in CVE associated with recent continuous MTX use. Greater MTX use in the first year of cohort entry also appeared to be important in the association between MTX and CVE risk.

BACKGROUND: Growing evidence suggests that asthma and Crohn’s disease (CD) commonly co-occur. The impact of asthma on the prognosis of CD is not known. Studies evaluating the risk of surgery in CD patients using health administrative data are limited by their inability to adjust for confounding variables not included in these data, such as smoking. AIMS: The aim of our study was to assess the impact of asthma on the need for intestinal resection in CD adjusting for smoking status, despite smoking status being unmeasured in health administrative data, using a secondary dataset and novel methodology. METHODS: Using population-based health administrative data from Alberta, we conducted a cohort study to assess the impact of asthma on the need for surgery in patients with CD diagnosed between April 1, 2002 and March 31, 2008 (n=2,113). Validated algorithms were used to identify incident CD cases, patients with co-occurring asthma, and intestinal resection surgeries. The association between asthma and intestinal resection was estimated using Cox proportional hazards regression. Smoking status was imputed using a method based on martingale residuals, leveraging information from a secondary dataset in which smoking status was measured. This second dataset included patients enrolled in the Alberta IBD Consortium between 2007 and 2014 who completed environmental questionnaires (n=485). All analyses were adjusted for age, sex, rural/urban status, and mean neighbourhood income quintile. RESULTS: Asthma did not increase the risk of surgery in either the health administrative data unadjusted for smoking status (HR 1.03, 95% CI 0.81 to 1.29) or in the secondary data adjusted for smoking status (HR 0.74, 95% CI 0.50 to 1.37). The association remained non-significant after using the secondary data to impute smoking status in the health administrative data (HR 0.92, 95% CI 0.75 to 1.15). CONCLUSIONS: Although asthma is associated with an increased risk of CD, co-occurring asthma was not associated with the risk of surgery in patients with CD. This null association persisted after adjusting for smoking status. This study also demonstrates a novel method to adjust for smoking status in research using health administrative data when it is measured in a smaller secondary dataset. FUNDING AGENCIES: CAG, CCC, CIHR

Purpose Interaction and subgroup analyses remain controversial topics in epidemiology. A recent theoretical paper suggested that a combination of no overall treatment-outcome association and treatment effect limited to a single subgroup would imply a clinically implausible interaction, with opposite treatment effects in the two subgroups. However, this argument was based entirely on point estimates and ignored sampling error and statistical inference. Methods We simulated hypothetical studies in which treatment truly affected the outcome in only one subgroup, with no effect in the other subgroup. We generated 1000 random samples for three study designs (small clinical study, case–control, and large cohort), and different values of total sample size (N), relative size of the affected subgroup, and treatment effect. We estimated the frequency of significant results for tests of overall and subgroup-specific treatment effects, and treatment-by-subgroup interaction. Results Combination of statistically non-significant overall treatment effect and significant treatment-by-subgroup interaction occurred frequently, especially if the affected subgroup was proportionally smaller, even in studies with high power to detect the overall effect (e.g. in 37.1% of samples with N = 20 000, with 600 outcomes, and an effect (odds ratio of 1.5) limited to 30% of subjects). Furthermore, in most samples with a significant interaction, subgroup analyses correctly indicated that the significant effect was limited to one subgroup. Conclusion In studies where the treatment truly affects the risks in only one subgroup, a non-significant overall effect will often coincide with a statistically significant treatment-by-subgroup interaction. Thus, a non-significant overall effect should not prevent testing plausible interactions. Copyright © 2013 John Wiley & Sons, Ltd.

Objective.Disease-modifying antirheumatic drugs (DMARD) have the greatest effect when initiated early. We evaluated the influence of early exposure to DMARD on time to joint replacement surgery among patients with incident rheumatoid arthritis (RA).Method.Using a common protocol, we undertook 2 independent population-based cohort studies of patients with incident RA aged 66 years or older in Ontario (ON) and Quebec (QC) covering the period 2000–2013. We used Cox proportional hazards regression with time-dependent variables measuring duration of drug use in the first year, separately for methotrexate (MTX) and other DMARD, adjusting for baseline demographics, clinical factors, and other potentially confounding drug exposures. Our outcome measure was any joint replacement derived from standardized procedure codes. Adjusted HR and 95% CI were estimated.Results.Among 20,918 ON and 6754 QC patients with RA followed for a median of 4.5 years, 2201 and 494 patients underwent joint replacement surgery for crude event rates of 2.0 and 1.4 per 100 person-years, respectively. Greater cumulative exposure to MTX (HR 0.97, 95% CI 0.95–0.98) and other DMARD (HR 0.98, 95% CI 0.97–0.99) in the first year after diagnosis was associated with longer times to joint replacement in ON, corresponding to a 2–3% decrease in the hazard of surgery with each additional month of early use. Similar results were observed in QC.Conclusion.Greater duration of exposure to DMARD soon after RA diagnosis was associated with delays to joint replacement surgery in both provinces. Early intensive treatment of RA may ultimately reduce demand for joint replacement surgery.

Objectives To explore the relationship of serious infection risk with current and prior oral glucocorticoid (GC) therapy in elderly patients with rheumatoid arthritis (RA). Methods A case-control analysis matched 1947 serious infection cases to five controls, selected from 16207 RA patients aged ≥65 between 1985–2003 in Quebec, Canada. Adjusted odds ratios for infection associated with different GC patterns were estimated using conventional models and a weighted cumulative dose (WCD) model. Results The WCD model predicted risks better than conventional models. Current and recent GC doses had highest impact on current risk. Doses taken up to 2.5 years ago were also associated with increased risk, albeit to a lesser extent. A current user of 5mg prednisolone had a 30%, 46% or 100% increased risk of serious infection when used continuously for the last 3 months, 6 months or 3 years, respectively, compared to a non-user. The risk associated with 5mg prednisolone taken for the last 3 years was similar to that associated with 30mg taken for the last month. Discontinuing a two-year course of 10mg prednisolone six months ago halved the risk compared to ongoing use. Conclusions GC therapy is associated with infection risk in older patients with RA. The WCD model provided more accurate risk estimates than conventional models. Current and recent doses have greatest impact on infection risk, but the cumulative impact of doses taken in the last 2–3 years still affects risk. Knowing how risk depends on pattern of GC use will contribute to an improved benefit/harm assessment.

Pharmacoepidemiology investigates associations between time-varying medication use/dose and risk of adverse events. Applied research typically relies on a priori chosen simple conventional models, such as current dose or any use in the past 3 months. However, different models imply different risk predictions, and only one model can be etiologically correct in any specific applications. We first formally defined several candidate models mapping the time vector of past drug doses (X (t), t = 1, … ,u) into the value of a time-varying exposure metric M(u) at current time u. In addition to conventional one-parameter models, we considered two-parameter models accounting for recent dose increase or withdrawal and a flexible spline-based weighted cumulative exposure (WCE) model that defines M(u) as the weighted sum of past doses. In simulations, we generated event times assuming one of the models was correct and then analyzed the data with all candidate models. We demonstrated that the minimum AIC criterion is able to identify the correct model as the best-fitting model or one of the equivalent (within 4 AIC points of the minimum) models in a vast majority of simulated samples, especially with 500 or more events. We also showed how relying on an incorrect a priori chosen model may largely reduce the power to test for an association. Finally, we demonstrated how the flexible WCE estimates may help with model diagnostics even if the correct model is not WCE. We illustrated the practical advantages of AIC-based a posteriori model selection and WCE modeling in a real-life pharmacoepidemiology example.

Instrumental variable (IV) methods based on the physician’s prescribing preference may remove bias due to unobserved confounding in pharmacoepidemiologic studies. However, IV estimates, originally defined as the treatment prescribed for a single previous patient of a given physician, show important variance inflation. The authors proposed and validated in simulations a new method to reduce the variance of IV estimates even when physicians’ preferences change over time. First, a potential ‘‘change-time,’’ after which the physician’s preference has changed, was estimated for each physician. Next, all patients of a given physician were divided into 2 homogeneous subsets: those treated before the change-time versus those treated after the change-time. The new IV was defined as the proportion of all previous patients in a corresponding homogeneous subset who were prescribed a specific drug. In simulations, all alternative IV estimators avoided strong bias of the conventional estimates. The change-time method reduced the standard deviation of the estimates by approximately 30% relative to the original previous patient-based IV. In an empirical example, the proposed IV correlated better with the actual treatment and yielded smaller standard errors than alternative IV estimators. Therefore, the new method improved the overall accuracy of IV estimates in studies with unobserved confounding and time-varying prescribing preferences. confounding factors (epidemiology); decision support techniques; pharmacoepidemiology

Background: C-reactive protein (CRP) is gaining credibility as a prognostic factor in different cancers. Cox's proportional hazard (PH) model is usually used to assess prognostic factors. However, this model imposes a priori assumptions, which are rarely tested, that (1) the hazard ratio associated with each prognostic factor remains constant across the follow-up (PH assumption) and (2) the relationship between a continuous predictor and the logarithm of the mortality hazard is linear (linearity assumption). Methods: We tested these two assumptions of the Cox's PH model for CRP, using a flexible statistical model, while adjusting for other known prognostic factors, in a cohort of 269 patients newly diagnosed with non-small cell lung cancer (NSCLC). Results: In the Cox's PH model, high CRP increased the risk of death (HR=1.11 per each doubling of CRP value, 95% CI: 1.03–1.20, P=0.008). However, both the PH assumption (P=0.033) and the linearity assumption (P=0.015) were rejected for CRP, measured at the initiation of chemotherapy, which kept its prognostic value for approximately 18 months. Conclusion: Our analysis shows that flexible modeling provides new insights regarding the value of CRP as a prognostic factor in NSCLC and that Cox's PH model underestimates early risks associated with high CRP.

We conducted a prospective observational study to (1) determine usage and construct validity of a method to gauge the cognitive impact of information derived from daily e-mail, and (2) describe self-reported impacts of research-based synopses ( InfoPOEMs ) delivered as e-mail. Ratings of InfoPOEMs using an Impact assessment scale provided (a) data on usage of the impact assessment method, (b) reports of impact by InfoPOEM and by doctor and (c) data for analysis of construct validity of the scale. Participants were family physicians or general practitioners who rated at least five InfoPOEMs delivered on e-mail. For each InfoPOEM rated, 0.1 continuing education credit was awarded by the College of Family Physicians of Canada. Use of the impact assessment scale linked to a daily InfoPOEM was sustained during the 150-day study period. 1,007 participants submitted 61,493 reports of ‘cognitive impact’ by rating on average 61 InfoPOEMs (range 5–111). ‘ I learned something new ’ was most frequently reported. ‘ I was frustrated as there was not enough information or nothing useful ’ was the most frequently reported negative type of impact. The proportion of reports of ‘No Impact’ varied substantially across individual InfoPOEMs . Impact patterns suggested an 8 or 9-factor solution. Our Impact assessment method facilitates knowledge transfer by promoting two-way exchange between providers of health information and family doctors. Providers of health information can use this method to better understand the impact of research-based synopses. Sustaining current practice and increasing knowledge about new developments in medicine are important outcomes arising from research-based synopses delivered as e-mail, in addition to practice change.

Objective To quantify the risk of incident diabetes mellitus (DM) associated with the dosage, duration, and timing of glucocorticoid (GC) use in patients with rheumatoid arthritis (RA). Methods We undertook a cohort study using 2 databases: a UK primary care database (the Clinical Practice Research Datalink [CPRD]) including 21,962 RA patients (1992–2009) and the US National Data Bank for Rheumatic Diseases (NDB) including 12,657 RA patients (1998–2013). Information on the dosage and timing of GC use was extracted. DM in the CPRD was defined using Read codes, at least 2 prescriptions for oral antidiabetic medication, or abnormal blood test results. DM in the NDB was defined through patient self-reports. Data were analyzed using time-dependent Cox models and a novel weighted cumulative dose (WCD) model that accounts for dosage, duration, and timing of treatment. Results The hazard ratio (HR) was 1.30 (95% confidence interval [95% CI] 1.17–1.45) and 1.61 (95% CI 1.37–1.89) in current GC users compared to nonusers in the CPRD and the NDB, respectively. A range of conventional statistical models consistently confirmed increases in risk with the GC dosage and duration. The WCD model showed that recent GC use contributed the most to the current risk of DM, while doses taken >6 months previously did not influence current risk. In the CPRD, 5 mg of prednisolone equivalent dose for the last 1, 3, and 6 months was significantly associated with HRs of 1.20, 1.43, and 1.48, respectively, compared to nonusers. Conclusion GC use is a clinically important and quantifiable risk factor for DM. Risk is influenced by the dosage and treatment duration, although only for GC use within the last 6 months.

Introduction Use of disease-modifying anti-rheumatic drugs (DMARDs) in rheumatoid arthritis (RA) may prevent joint damage and potentially reduce joint replacement surgeries. We assessed the association between RA drug use and joint replacement in Quebec, Canada. Methods A cohort of new-onset RA patients was identified from Quebec’s physician billing and hospitalization databases from 2002–2011. The outcome was defined using procedure codes submitted by orthopedic surgeons. Medication use was obtained from pharmacy databases. We used alternative Cox regression models with time-dependent variables measuring the cumulative effects of past use during different time windows (one model focussing on the first year after cohort entry) for methotrexate (MTX), and other DMARDs. Models were adjusted for baseline sociodemographics, co-morbidity and prior health service use, time-dependent cumulative use of other drugs (anti-tumor necrosis factor [anti-TNF] agents, other biologics, cyclooxygenase-2 inhibitors [COXIBs], nonselective nonsteroidal antiinflammatory drugs [NSAIDs], and systemic steroids), and markers of disease severity. Results During follow-up, 608 joint replacements occurred among 11,333 patients (median follow-up: 4.6 years). The best-fitting model relied on the cumulative early use (within the first year after cohort entry) of MTX and of other DMARDs, with an interaction between MTX and other DMARDs. In this model, greater exposure within the first year, to either MTX (adjusted hazard ratio, HR = 0.95 per 1 month, 95 % confidence interval, 95 % CI 0.93-0.97) or other DMARDs (HR = 0.97, 95 % CI 0.95-0.99) was associated with longer time to joint replacement. Conclusions Our results suggest that longer exposure to either methotrexate (MTX) or other DMARDs within the first year after RA diagnosis is associated with longer time to joint replacement surgery. Electronic supplementary material The online version of this article (doi:10.1186/s13075-015-0713-3) contains supplementary material, which is available to authorized users.

Unmeasured confounding is a major threat to the validity of pharmacoepidemiological studies of medication safety and effectiveness. We propose a new method for detecting and reducing the impact of unobserved confounding in large observational database studies. The method uses assumptions similar to the prescribing preference-based instrumental variable (IV) approach. Our method relies on the new 'missing cause' principle, according to which the impact of unmeasured confounding by (contra-)indication may be detected by assessing discrepancies between the following: (i) treatment actually received by individual patients and (ii) treatment that they would be expected to receive based on the observed data. Specifically, we use the treatment-by-discrepancy interaction to test for the presence of unmeasured confounding and correct the treatment effect estimate for the resulting bias. Under standard IV assumptions, we first proved that unmeasured confounding induces a spurious treatment-by-discrepancy interaction in risk difference models for binary outcomes and then simulated large pharmacoepidemiological studies with unmeasured confounding. In simulations, our estimates had four to six times smaller bias than conventional treatment effect estimates, adjusted only for measured confounders, and much smaller variance inflation than unbiased but very unstable IV estimates, resulting in uniformly lowest root mean square errors. The much lower variance of our estimates, relative to IV estimates, was also observed in an application comparing gastrointestinal safety of two classes of anti-inflammatory drugs. In conclusion, our missing cause-based method may complement other methods and enhance accuracy of analyses of large pharmacoepidemiological studies.

Interaction and subgroup analyses remain controversial topics in epidemiology. A recent theoretical paper suggested that a combination of no overall treatment-outcome association and treatment effect limited to a single subgroup would imply a clinically implausible interaction, with opposite treatment effects in the two subgroups. However, this argument was based entirely on point estimates and ignored sampling error and statistical inference.We simulated hypothetical studies in which treatment truly affected the outcome in only one subgroup, with no effect in the other subgroup. We generated 1000 random samples for three study designs (small clinical study, case-control, and large cohort), and different values of total sample size (N), relative size of the affected subgroup, and treatment effect. We estimated the frequency of significant results for tests of overall and subgroup-specific treatment effects, and treatment-by-subgroup interaction.Combination of statistically non-significant overall treatment effect and significant treatment-by-subgroup interaction occurred frequently, especially if the affected subgroup was proportionally smaller, even in studies with high power to detect the overall effect (e.g. in 37.1% of samples with N = 20 000, with 600 outcomes, and an effect (odds ratio of 1.5) limited to 30% of subjects). Furthermore, in most samples with a significant interaction, subgroup analyses correctly indicated that the significant effect was limited to one subgroup.In studies where the treatment truly affects the risks in only one subgroup, a non-significant overall effect will often coincide with a statistically significant treatment-by-subgroup interaction. Thus, a non-significant overall effect should not prevent testing plausible interactions.

Objective. Optimal care in RA includes early use of DMARDs to prevent joint damage and hopefully decrease the need for costly surgical interventions. Our objective was to determine whether a reduced rate of orthopaedic surgery was evident for persons with RA who saw a rheumatologist early in the disease course. Methods. We studied persons who had a diagnosis of RA based on billing code data in the province of Quebec in 1995, and for whom the initial date of RA diagnosis by a non-rheumatologist could be established before the confirmatory diagnosis by the rheumatologist. We followed these patients until 2007. Patients were classified as early consulters or late consulters depending on whether they were seen by a rheumatologist within or beyond 3 months of being diagnosed with RA by their referring physician. The outcome, orthopaedic surgery, was defined using International Classification of Diseases (ICD) procedure codes ICD9 and ICD10. Multivariate Cox regression with time-dependent covariates estimated the effect of early consultation on the time to orthopaedic surgery. Results. Our cohort consisted of 1051 persons; mean age at diagnosis was 55.7 years, 68.2% were female and 50.7% were early consulters. Among all patients, 20.5% (215) had an orthopaedic surgery during the observation interval. Early consulters were less likely to undergo orthopaedic surgery during the 12-year follow-up period (adjusted hazard ratio 0.60, 95% CI 0.44, 0.82). Conclusion. Persons with RA who consult a rheumatologist later in the disease course have a worse outcome in terms of eventual requirement for orthopaedic surgery.

Background Disease-modifying anti-rheumatic drugs (DMARDs) generally have the greatest impact if they are initiated early in the course of the disease. We hypothesized that greater cumulative exposure to DMARDs soon after RA diagnosis is associated with longer time to joint surgeries. Objectives To evaluate early exposure to DMARDs and time to joint surgery, comparing incident rheumatoid arthritis (RA) populations from Ontario (ON) and Quebec (QC). Methods Using a standard protocol, we performed population-based cohort analyses on new-onset RA patients in ON and QC from 2000-2013. Incident RA patients were followed from cohort entry until their first joint surgery, or were censored at death date, or the end of study period, whichever came first. We studied all recipients of public drug coverage, aged 66 years and older. Analyses were confined to “new users” for the drug of interest. We used Cox proportional hazards regression with time-dependent variables measuring duration of drug use (daily exposures in the first year of follow-up), separately for methotrexate and other DMARDs, adjusting for baseline age, sex, urban vs. rural residence, socioeconomic status, co-existing osteoarthritis (OA), comorbidities, prior joint surgeries, extra-articular RA manifestations, time-varying number of physician visits, and drug exposures (anti-TNF inhibitors, COXIBs, NSAIDs, systemic steroids). Adjusted hazard ratios (HRs) along with 95% confidence intervals (CIs), were estimated. Results Among 20,918 ON and 6,740 QC RA patients, 68% were female and the mean (SD) age was 75 (6) years in each setting. During follow-up, 2,201 (11%) in ON and 494 (7%) patients in QC underwent joint surgery, for a rate of 2 events per 100 person-years in both settings. In the multivariable analyses, greater exposure to methotrexate (HR 0.97 95%CI 0.95-0.98), and other DMARDs (HR 0.98 95%CI 0.97-0.99) within the first year was associated with longer time to surgery in both settings. The strongest independent associations with shorter time to surgery in ON and QC, respectively, included previous joint surgeries [HR=1.9 vs. 2.8], co-existing OA [HR=1.5 vs. 1.8], and greater exposure to NSAIDs [HR=1.2 vs. 1.3], and COXIBs [HR=1.1 vs. 1.3]. Conclusions Greater cumulative exposures to methotrexate and other DMARDs, within 1 year after RA diagnosis, were associated with longer time to joint surgeries in both ON and QC. Our coordinated approach across provincial data sources identified highly comparable and consistent findings. Disclosure of Interest None declared

Background Early DMARD use in RA may prevent damage and possibly, need for joint replacement. Objectives To assess joint replacements within incident RA patients in Quebec, Canada, and potential associations with early DMARD use. Methods A cohort of incident RA patients was identified from Quebec9s physician billing and hospitalization databases from 2002-2008; all patients covered by the provincial drug insurance for the duration of the study were included in analyses. We used Cox regression with time-dependent variables for: 1) methotrexate (MTX) use, 2) other non-biologic DMARDs and 3) anti-tumor necrosis factor (TNF) agents. Models were adjusted for baseline sociodemographic characteristics, co-morbidity including pre-existing osteoarthritis, and prior health service use, and for time-dependent variables reflecting cumulative use of other drugs (COXIBs, NSAIDs, and systemic steroids) and time-dependent indicators of disease severity (extra-articular RA features and number of rheumatology visits). The outcome (any joint replacement) was defined using procedure codes. Results During follow-up, 321 joint replacements occurred among 5,199 incident RA patients observed for a total of 19,693 years (1.6 events/100 person-years). The best-fitting models relied on cumulative duration of MTX and cumulative duration of non-MTX traditional DMARD use in the first year after RA diagnosis. Controlling for anti-TNF exposure, joint replacement rates throughout follow-up appeared to be significantly lower with greater cumulative MTX and with greater cumulative non-MTX traditional DMARD use in the first year of RA (Hazard ratio, HR=0.95 per month of MTX use, 95% Confidence Interval, CI 0.91-0.98; HR=0.93 per month of use of non-MTX traditional DMARDs, 95% CI 0.90-0.97). However, patients receiving both MTX and non-MTX traditional DMARDs, concurrently or sequentially, within the first year after RA onset, had a significantly higher risk of joint replacement than those who used only one of the two drug classes within the first year. We could not establish independent effects for anti-TNF agents. Conclusions Higher cumulative use of MTX and higher cumulative use of non-MTX traditional DMARDs within the first year after RA diagnosis appeared to be associated with fewer joint replacements. This may be consistent with joint-sparing effects of aggressive, early use of these drugs, though a causal link cannot be established with these observational data. The increased joint replacement risk in patients taking both MTX and other DMARDS, concurrently or sequentially, in the first year, suggests potential confounding by indication, as patients taking multiple drugs may have more severe disease, and greater risk for joint damage. References Gramling A, O9Dell JR (2012). Initial management of rheumatoid arthritis. Rheum. Dis. Clin. North Am. 38 (2): 311–25. Acknowledgements Canadian Institutes for Health Research/Drug Safety and Effectiveness Network (CIHR/DSEN) Disclosure of Interest : None declared DOI 10.1136/annrheumdis-2014-eular.3061

We previously developed a method to assess the clinical impact of electronic knowledge resources. This method has potential to advance e-health research by serving as a new outcome measure in the domain of clinical decision support or computer mediated communication. In this article, we outline how such a method can be validated. The validation includes a longitudinal field research study using a mixed methods approach. Doctors will use our method to complete a computerized impact assessment questionnaire for items of information they retrieve. This will reveal cognitive impacts and application of information in practice. Subsequently, doctors will be interviewed on their most recent information searches using log-stimulated recall. Archives and observations complement interviews. These analyses serve to validate the method for assessing the clinical impact of electronic knowledge resources.