Introduction: Various statistical approaches can be used to deal with unmeasured confounding when estimating treatment effects in observational studies, each with its own pros and cons. This study... Show moreIntroduction: Various statistical approaches can be used to deal with unmeasured confounding when estimating treatment effects in observational studies, each with its own pros and cons. This study aimed to compare treatment effects as estimated by different statistical approaches for two interventions in observational stroke care data. Patients and methods: We used prospectively collected data from the MR CLEAN registry including all patients (n = 3279) with ischemic stroke who underwent endovascular treatment (EVT) from 2014 to 2017 in 17 Dutch hospitals. Treatment effects of two interventions - i.e., receiving an intravenous thrombolytic (IVT) and undergoing general anesthesia (GA) before EVT- on good functional outcome (modified Rankin Scale <= 2) were estimated. We used three statistical regression-based approaches that vary in assumptions regarding the source of unmeasured confounding: individual-level (two subtypes), ecological, and instrumental variable analyses. In the latter, the preference for using the interventions in each hospital was used as an instrument. Results: Use of IVT (range 66-87%) and GA (range 0-93%) varied substantially between hospitals. For IVT, the individual-level (OR similar to 1.33) resulted in significant positive effect estimates whereas in instrumental variable analysis no significant treatment effect was found (OR 1.11; 95% CI 0.58-1.56). The ecological analysis indicated no statistically significant different likelihood (beta = - 0.002%; P=0.99) of good functional outcome at hospitals using IVT 1% more frequently. For GA, we found non-significant opposite directions of points estimates the treatment effect in the individual-level (ORs similar to 0.60) versus the instrumental variable approach (OR =1.04).The ecological analysis also resulted in a non-significant negative association (0.03% lower probability). Discussion and conclusion: Both magnitude and direction of the estimated treatment effects for both interventions depend strongly on the statistical approach and thus on the source of (unmeasured) confounding.These issues should be understood concerning the specific characteristics of data, before applying an approach and interpreting the results. Instrumental variable analysis might be considered when unobserved confounding and practice variation is expected in observational multicenter studies. Show less
Amini, M.; Hartog, S.J. den; Leeuwen, N. van; Eijkenaar, F.; Kuhrij, L.S.; Stolze, L.J.; ... ; PERFEQTOS Investigators 2021
Background: Although the provision of performance feedback to healthcare professionals based on data from quality registries is common practice in many fields of medicine, observational studies of... Show moreBackground: Although the provision of performance feedback to healthcare professionals based on data from quality registries is common practice in many fields of medicine, observational studies of its effect on the quality of care have shown mixed results. The objective of this study is to evaluate the effect of performance feedback on the quality of care for acute ischemic stroke.Methods: PERFEQTOS is a stepped wedge cluster randomized trial in 13 hospitals in the Netherlands providing endovascular thrombectomy for ischemic stroke. The primary outcome is the hospital's door-to-groin time. The study starts with a 6-month period in which none of the hospitals receives the performance feedback intervention. Subsequently, every 6 months, three or four hospitals are randomized to cross over from the control to the intervention conditions, until all hospitals receive the feedback intervention. The feedback intervention consists of a dashboard with quarterly reports on patient characteristics, structure, process, and outcome indicators related to patients with ischemic stroke treated with endovascular thrombectomy. Hospitals can compare their present performance with their own performance in the past and with other hospitals. The performance feedback is provided to local quality improvement teams in each hospital, who define their own targets on specific indicators and develop performance improvement plans. The impact of the performance feedback and improvement plans will be evaluated by comparing the primary outcome before and after the intervention.Discussion: This study will provide evidence on the effectiveness of performance feedback to healthcare providers. The results will be actively disseminated through peer-reviewed journals, conference presentations, and various stakeholder engagement activities. Show less
Amini, M.; Leeuwen, N. van; Eijkenaar, F.; Mulder, M.J.H.L.; Schonewille, W.; Nijeholt, G.L.A.; ... ; MR CLEAN Registry Investigators 2020
BackgroundBetween-center variation in outcome may offer opportunities to identify variation in quality of care. By intervening on these quality differences, patient outcomes may be improved.... Show moreBackgroundBetween-center variation in outcome may offer opportunities to identify variation in quality of care. By intervening on these quality differences, patient outcomes may be improved. However, whether observed differences in outcome reflect the true quality improvement potential is not known for many diseases. Therefore, we aimed to analyze the effect of differences in performance on structure and processes of care, and case-mix on between-center differences in outcome after endovascular treatment (EVT) for ischemic stroke.MethodsIn this observational cohort study, ischemic stroke patients who received EVT between 2014 and 2017 in all 17 Dutch EVT-centers were included. Primary outcome was the modified Rankin Scale, ranging from 0 (no symptoms) to 6 (death), at 90days. We used random effect proportional odds regression modelling, to analyze the effect of differences in structure indicators (center volume and year of admission), process indicators (time to treatment and use of general anesthesia) and case-mix, by tracking changes in tau(2), which represents the amount of between-center variation in outcome.ResultsThree thousand two hundred seventy-nine patients were included. Performance on structure and process indicators varied significantly between EVT-centers (P<0.001). Predicted probability of good functional outcome (modified Rankin Scale 0-2 at 90days), which can be interpreted as an overall measure of a center's case-mix, varied significantly between 17 and 50% across centers. The amount of between-center variation (tau(2)) was estimated at 0.040 in a model only accounting for random variation. This estimate more than doubled after adding case-mix variables (tau(2): 0.086) to the model, while a small amount of between-center variation was explained by variation in performance on structure and process indicators (tau(2): 0.081 and 0.089, respectively). This indicates that variation in case-mix affects the differences in outcome to a much larger extent.ConclusionsBetween-center variation in outcome of ischemic stroke patients mostly reflects differences in case-mix, rather than differences in structure or process of care. Since the latter two capture the real quality improvement potential, these should be used as indicators for comparing center performance. Especially when a strong association exists between those indicators and outcome, as is the case for time to treatment in ischemic stroke. Show less
Sung, Y.J.; Fuentes, L. de las; Winkler, T.W.; Chasman, D.I.; Bentley, A.R.; Kraja, A.T.; ... ; Lifelines Cohort Study 2019
Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five... Show moreElevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene-smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene-smoking interaction analysis and 38 were newly identified (P < 5 x 10(-8), false discovery rate < 0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings. Show less
A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene... Show moreA person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 x 10(-6)) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 x 10(-8) using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models. Show less
