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Identifying Cases of Type 2 Diabetes in Heterogeneous Data Sources: Strategy from the EMIF Project.

Due to the heterogeneity of existing European sources of observational healthcare data, data source-tailored choices are needed to execute multi-data source, multi-national epidemiological studies. This makes transparent documentation paramount. In this proof-of-concept study, a novel standard data derivation procedure was tested in a set of heterogeneous data sources. Identification of subjects with type 2 diabetes (T2DM) was the test case. We included three primary care data sources (PCDs), three record linkage of administrative and/or registry data sources (RLDs), one hospital and one biobank. Overall, data from 12 million subjects from six European countries were extracted. Based on a shared event definition, sixteeen standard algorithms (components) useful to identify T2DM cases were generated through a top-down/bottom-up iterative approach. Each component was based on one single data domain among diagnoses, drugs, diagnostic test utilization and laboratory results. Diagnoses-based components were subclassified considering the healthcare setting (primary, secondary, inpatient care). The Unified Medical Language System was used for semantic harmonization within data domains. Individual components were extracted and proportion of population identified was compared across data sources. Drug-based components performed similarly in RLDs and PCDs, unlike diagnoses-based components. Using components as building blocks, logical combinations with AND, OR, AND NOT were tested and local experts recommended their preferred data source-tailored combination. The population identified per data sources by resulting algorithms varied from 3.5% to 15.7%, however, age-specific results were fairly comparable. The impact of individual components was assessed: diagnoses-based components identified the majority of cases in PCDs (93–100%), while drug-based components were the main contributors in RLDs (81–100%). The proposed data derivation procedure allowed the generation of data source-tailored case-finding algorithms in a standardized fashion, facilitated transparent documentation of the process and benchmarking of data sources, and provided bases for interpretation of possible inter-data source inconsistency of findings in future studies.

Patterns of use of incretin-based therapies in Europe and USA:

Background: Sudden discontinuation of some antihypertensive agents such as beta-blockers and centrally acting antihypertensive agents are associated with increased risk of acute coronary events. Objectives: The aim of this study was to assess the association between discontinuation of different antihypertensive agents and the risk of acute myocardial infarction (AMI). Methods: A nested case control study was performed in a cohort of antihypertensive drug users from the Utrecht Cardiovascular Pharmacogenetics (UCP) database. Within this cohort, patients who were hospitalized for first AMI were considered cases. Cases were matched (1 up to 4) to controls at the same AMI date (index date). Antihypertensive users were defined as current users if the index date fell within prescribed duration or as stoppers if this date fell outside the prescribed duration. According to recency of stopping, stoppers were divided into recent stoppers (≤90 days), intermediate-term stoppers (91-180 days), and longterm stoppers (>180 days). The study included only antihypertensive users who were specifically current users or stoppers of one antihypertensive agent. Logistic regression analysis was used to assess the association between the discontinuation of antihypertensive agents and the risk of AMI and to control for confounding. Results: We included 1245 cases and 4994 controls in our analysis. The risk of AMI was significantly increased with all stoppers of beta-blockers (adjusted OR: 1.54, 95%CI (1.25-1.90)), calcium channel blockers (CCBs) (adjusted OR: 2.25, 95%CI (1.53- 3.30)), and diuretics (adjusted OR: 1.76, 95%CI (1.24-2.48)) compared with current users. Moreover, the risk of AMI was significantly increased for longterm stoppers (beta-blockers, CCBs, angiotensinconverting enzyme inhibitors, and diuretics) and intermediate- term stoppers (beta-blockers and CCBs) versus current users. There was no difference in AMI risk between recent stoppers of antihypertensive agents versus current users. Conclusions: Discontinuation of antihypertensive agents increases the risk of AMI after more than 90 days of stopping. Adherence to antihypertensive agents plays an important role in reducing the risk of AMI in patients with hypertension.Background: It has been reported that patients with type 1 diabetes (T1DM) have a decreased lung function. Studies on the association of T1DM and asthma in children show controversial results. Objectives: The aim of this study was to quantify asthma medication use in children and adolescents with and without (reference cohort) T1DM 5 years before and after the onset of diabetes. Methods: A population-based cohort study was conducted in the Dutch PHARMO Record Linkage System. All children (1. Modelling of Endpoint Postponement for All-Cause Mortality in Statin Trials Morten Rix Hansen, Anton Pottegård, Asbjørn Hróbjartsson, Per Damkier, René D Christensen, Kasper Søltoft Larsen, Malene EL Kristensen, Palle M Christensen, Jesper Hallas. Clinical Pharmacology, University of Southern Denmark, Odense, Denmark; Department of Clinical Chemistry and Pharmacology, Odense University Hospital, Odense, Denmark; The Nordic Cochrane Centre, Rigshospitalet, Copenhagen, Denmark; Research Unit for General Practice, University of Southern Denmark, Odense, Denmark. Background: The average postponement of the outcome event has been proposed as a novel method to present the magnitude of effect for preventive medications. This measure has been shown to have better agreement with patient preferences than conventional outcomemeasures, including the “number needed to treat” (NNT), possibly because it is more intuitively understood. For some interventions, it may also provide a better theoretical frame for how benefit is distributed among participants than the NNT measure. The aim of this study was to present a novel method for modelling endpoint postponement (EP) from trial data and compare it with the usual approach of measuring the area between survival curves. We also present a formalized meta-analysis of modelled EP for all-cause mortality in statin trials. Methods: We identified 17 placebo-controlled statin trials that fulfilled our inclusion criteria. Eleven of these presented Kaplan–Meier curves for all-cause mortality. Average EP was calculated as the area between Kaplan–Meier curves by counting pixels on magnified prints for these 11 trials. The modelled EP was computed for all trials on the basis of (1) hazard ratio, relative risk or odds ratio; (2) the cumulative event rate in the untreated group; and (3) the trial’s running time. The underlying assumption was that the mortality was reasonably stable within the trials’ running time. The modelled EP was subjected to a meta-analysis, using inverse variance weighting in a random effect model. Results: EPswere generally small for estimates based on pixel-counting, 10 and 27days for trials both primary and secondary intervention that typically ran over 1.9– 6.1years. The modelled EPs varied between 2 and 34days. The difference between modeled EP and EP based on pixel-counting was between 8 and 12days. The results of the meta-analyses will be presented at the meeting. Conclusions: Based on these trial data, statin treatment results in a surprisingly small gain in average survival. Our modelled EP estimates agreed reasonably with EPs based on pixel-counting. The modeled EP is amenable to meta-analyses and may be a useful approach to presenting the benefit of preventive treatment. 2. Permanent User Bias in Case–Crossover Studies in Pharmacoepidemiology Jesper Hallas, Shirley V. Wang, Joshua J. Gagne, Sebastian Schneeweiss, Anton Pottegård. Clinical Pharmacology, University of Southern Denmark, Odense C, Denmark; Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA. Background: In pharmacoepidemiology, the case– crossover design is based on cases that have contrasting drug exposure at the time of an event and at a reference time in the past. If the drug in question should be taken permanently, only certain exposure patterns will occur. These patients cannot be unexposed at the event time and exposed at the reference time, while the opposite pattern can occur if the drug was initiated recently. The resulting odds ratio (OR) would thus be biased upward. As many drugs have a subpopulation of permanent users, this bias might pervade many case–crossover analyses of drug effects. Objectives: The aims of this study were to demonstrate this “permanent user bias” and to evaluate whether it can be remedied by including a control group (case–time–control design). Methods: Using nationwide Danish data resources, we conducted case–crossover and case–time–control analyses for combinations of three exposures that are

Trends of use of non‐insulin blood glucose lowering drugs in Europe and USA

Background: Sudden discontinuation of some antihypertensive agents such as beta-blockers and centrally acting antihypertensive agents are associated with increased risk of acute coronary events. Objectives: The aim of this study was to assess the association between discontinuation of different antihypertensive agents and the risk of acute myocardial infarction (AMI). Methods: A nested case control study was performed in a cohort of antihypertensive drug users from the Utrecht Cardiovascular Pharmacogenetics (UCP) database. Within this cohort, patients who were hospitalized for first AMI were considered cases. Cases were matched (1 up to 4) to controls at the same AMI date (index date). Antihypertensive users were defined as current users if the index date fell within prescribed duration or as stoppers if this date fell outside the prescribed duration. According to recency of stopping, stoppers were divided into recent stoppers (≤90 days), intermediate-term stoppers (91-180 days), and longterm stoppers (>180 days). The study included only antihypertensive users who were specifically current users or stoppers of one antihypertensive agent. Logistic regression analysis was used to assess the association between the discontinuation of antihypertensive agents and the risk of AMI and to control for confounding. Results: We included 1245 cases and 4994 controls in our analysis. The risk of AMI was significantly increased with all stoppers of beta-blockers (adjusted OR: 1.54, 95%CI (1.25-1.90)), calcium channel blockers (CCBs) (adjusted OR: 2.25, 95%CI (1.53- 3.30)), and diuretics (adjusted OR: 1.76, 95%CI (1.24-2.48)) compared with current users. Moreover, the risk of AMI was significantly increased for longterm stoppers (beta-blockers, CCBs, angiotensinconverting enzyme inhibitors, and diuretics) and intermediate- term stoppers (beta-blockers and CCBs) versus current users. There was no difference in AMI risk between recent stoppers of antihypertensive agents versus current users. Conclusions: Discontinuation of antihypertensive agents increases the risk of AMI after more than 90 days of stopping. Adherence to antihypertensive agents plays an important role in reducing the risk of AMI in patients with hypertension.Background: It has been reported that patients with type 1 diabetes (T1DM) have a decreased lung function. Studies on the association of T1DM and asthma in children show controversial results. Objectives: The aim of this study was to quantify asthma medication use in children and adolescents with and without (reference cohort) T1DM 5 years before and after the onset of diabetes. Methods: A population-based cohort study was conducted in the Dutch PHARMO Record Linkage System. All children (1. Modelling of Endpoint Postponement for All-Cause Mortality in Statin Trials Morten Rix Hansen, Anton Pottegård, Asbjørn Hróbjartsson, Per Damkier, René D Christensen, Kasper Søltoft Larsen, Malene EL Kristensen, Palle M Christensen, Jesper Hallas. Clinical Pharmacology, University of Southern Denmark, Odense, Denmark; Department of Clinical Chemistry and Pharmacology, Odense University Hospital, Odense, Denmark; The Nordic Cochrane Centre, Rigshospitalet, Copenhagen, Denmark; Research Unit for General Practice, University of Southern Denmark, Odense, Denmark. Background: The average postponement of the outcome event has been proposed as a novel method to present the magnitude of effect for preventive medications. This measure has been shown to have better agreement with patient preferences than conventional outcomemeasures, including the “number needed to treat” (NNT), possibly because it is more intuitively understood. For some interventions, it may also provide a better theoretical frame for how benefit is distributed among participants than the NNT measure. The aim of this study was to present a novel method for modelling endpoint postponement (EP) from trial data and compare it with the usual approach of measuring the area between survival curves. We also present a formalized meta-analysis of modelled EP for all-cause mortality in statin trials. Methods: We identified 17 placebo-controlled statin trials that fulfilled our inclusion criteria. Eleven of these presented Kaplan–Meier curves for all-cause mortality. Average EP was calculated as the area between Kaplan–Meier curves by counting pixels on magnified prints for these 11 trials. The modelled EP was computed for all trials on the basis of (1) hazard ratio, relative risk or odds ratio; (2) the cumulative event rate in the untreated group; and (3) the trial’s running time. The underlying assumption was that the mortality was reasonably stable within the trials’ running time. The modelled EP was subjected to a meta-analysis, using inverse variance weighting in a random effect model. Results: EPswere generally small for estimates based on pixel-counting, 10 and 27days for trials both primary and secondary intervention that typically ran over 1.9– 6.1years. The modelled EPs varied between 2 and 34days. The difference between modeled EP and EP based on pixel-counting was between 8 and 12days. The results of the meta-analyses will be presented at the meeting. Conclusions: Based on these trial data, statin treatment results in a surprisingly small gain in average survival. Our modelled EP estimates agreed reasonably with EPs based on pixel-counting. The modeled EP is amenable to meta-analyses and may be a useful approach to presenting the benefit of preventive treatment. 2. Permanent User Bias in Case–Crossover Studies in Pharmacoepidemiology Jesper Hallas, Shirley V. Wang, Joshua J. Gagne, Sebastian Schneeweiss, Anton Pottegård. Clinical Pharmacology, University of Southern Denmark, Odense C, Denmark; Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA. Background: In pharmacoepidemiology, the case– crossover design is based on cases that have contrasting drug exposure at the time of an event and at a reference time in the past. If the drug in question should be taken permanently, only certain exposure patterns will occur. These patients cannot be unexposed at the event time and exposed at the reference time, while the opposite pattern can occur if the drug was initiated recently. The resulting odds ratio (OR) would thus be biased upward. As many drugs have a subpopulation of permanent users, this bias might pervade many case–crossover analyses of drug effects. Objectives: The aims of this study were to demonstrate this “permanent user bias” and to evaluate whether it can be remedied by including a control group (case–time–control design). Methods: Using nationwide Danish data resources, we conducted case–crossover and case–time–control analyses for combinations of three exposures that are

Trends of use of non-insulin blood glucose lowering drugs in Europe and USA (Meeting Abstract: 189)

Background: Sudden discontinuation of some antihypertensive agents such as beta-blockers and centrally acting antihypertensive agents are associated with increased risk of acute coronary events. Objectives: The aim of this study was to assess the association between discontinuation of different antihypertensive agents and the risk of acute myocardial infarction (AMI). Methods: A nested case control study was performed in a cohort of antihypertensive drug users from the Utrecht Cardiovascular Pharmacogenetics (UCP) database. Within this cohort, patients who were hospitalized for first AMI were considered cases. Cases were matched (1 up to 4) to controls at the same AMI date (index date). Antihypertensive users were defined as current users if the index date fell within prescribed duration or as stoppers if this date fell outside the prescribed duration. According to recency of stopping, stoppers were divided into recent stoppers (≤90 days), intermediate-term stoppers (91-180 days), and longterm stoppers (>180 days). The study included only antihypertensive users who were specifically current users or stoppers of one antihypertensive agent. Logistic regression analysis was used to assess the association between the discontinuation of antihypertensive agents and the risk of AMI and to control for confounding. Results: We included 1245 cases and 4994 controls in our analysis. The risk of AMI was significantly increased with all stoppers of beta-blockers (adjusted OR: 1.54, 95%CI (1.25-1.90)), calcium channel blockers (CCBs) (adjusted OR: 2.25, 95%CI (1.53- 3.30)), and diuretics (adjusted OR: 1.76, 95%CI (1.24-2.48)) compared with current users. Moreover, the risk of AMI was significantly increased for longterm stoppers (beta-blockers, CCBs, angiotensinconverting enzyme inhibitors, and diuretics) and intermediate- term stoppers (beta-blockers and CCBs) versus current users. There was no difference in AMI risk between recent stoppers of antihypertensive agents versus current users. Conclusions: Discontinuation of antihypertensive agents increases the risk of AMI after more than 90 days of stopping. Adherence to antihypertensive agents plays an important role in reducing the risk of AMI in patients with hypertension.Background: It has been reported that patients with type 1 diabetes (T1DM) have a decreased lung function. Studies on the association of T1DM and asthma in children show controversial results. Objectives: The aim of this study was to quantify asthma medication use in children and adolescents with and without (reference cohort) T1DM 5 years before and after the onset of diabetes. Methods: A population-based cohort study was conducted in the Dutch PHARMO Record Linkage System. All children (1. Modelling of Endpoint Postponement for All-Cause Mortality in Statin Trials Morten Rix Hansen, Anton Pottegård, Asbjørn Hróbjartsson, Per Damkier, René D Christensen, Kasper Søltoft Larsen, Malene EL Kristensen, Palle M Christensen, Jesper Hallas. Clinical Pharmacology, University of Southern Denmark, Odense, Denmark; Department of Clinical Chemistry and Pharmacology, Odense University Hospital, Odense, Denmark; The Nordic Cochrane Centre, Rigshospitalet, Copenhagen, Denmark; Research Unit for General Practice, University of Southern Denmark, Odense, Denmark. Background: The average postponement of the outcome event has been proposed as a novel method to present the magnitude of effect for preventive medications. This measure has been shown to have better agreement with patient preferences than conventional outcomemeasures, including the “number needed to treat” (NNT), possibly because it is more intuitively understood. For some interventions, it may also provide a better theoretical frame for how benefit is distributed among participants than the NNT measure. The aim of this study was to present a novel method for modelling endpoint postponement (EP) from trial data and compare it with the usual approach of measuring the area between survival curves. We also present a formalized meta-analysis of modelled EP for all-cause mortality in statin trials. Methods: We identified 17 placebo-controlled statin trials that fulfilled our inclusion criteria. Eleven of these presented Kaplan–Meier curves for all-cause mortality. Average EP was calculated as the area between Kaplan–Meier curves by counting pixels on magnified prints for these 11 trials. The modelled EP was computed for all trials on the basis of (1) hazard ratio, relative risk or odds ratio; (2) the cumulative event rate in the untreated group; and (3) the trial’s running time. The underlying assumption was that the mortality was reasonably stable within the trials’ running time. The modelled EP was subjected to a meta-analysis, using inverse variance weighting in a random effect model. Results: EPswere generally small for estimates based on pixel-counting, 10 and 27days for trials both primary and secondary intervention that typically ran over 1.9– 6.1years. The modelled EPs varied between 2 and 34days. The difference between modeled EP and EP based on pixel-counting was between 8 and 12days. The results of the meta-analyses will be presented at the meeting. Conclusions: Based on these trial data, statin treatment results in a surprisingly small gain in average survival. Our modelled EP estimates agreed reasonably with EPs based on pixel-counting. The modeled EP is amenable to meta-analyses and may be a useful approach to presenting the benefit of preventive treatment. 2. Permanent User Bias in Case–Crossover Studies in Pharmacoepidemiology Jesper Hallas, Shirley V. Wang, Joshua J. Gagne, Sebastian Schneeweiss, Anton Pottegård. Clinical Pharmacology, University of Southern Denmark, Odense C, Denmark; Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA. Background: In pharmacoepidemiology, the case– crossover design is based on cases that have contrasting drug exposure at the time of an event and at a reference time in the past. If the drug in question should be taken permanently, only certain exposure patterns will occur. These patients cannot be unexposed at the event time and exposed at the reference time, while the opposite pattern can occur if the drug was initiated recently. The resulting odds ratio (OR) would thus be biased upward. As many drugs have a subpopulation of permanent users, this bias might pervade many case–crossover analyses of drug effects. Objectives: The aims of this study were to demonstrate this “permanent user bias” and to evaluate whether it can be remedied by including a control group (case–time–control design). Methods: Using nationwide Danish data resources, we conducted case–crossover and case–time–control analyses for combinations of three exposures that are

Patterns of use of incretin-based therapies in Europe and USA (Meeting Abstract: 188)

Background: Sudden discontinuation of some antihypertensive agents such as beta-blockers and centrally acting antihypertensive agents are associated with increased risk of acute coronary events. Objectives: The aim of this study was to assess the association between discontinuation of different antihypertensive agents and the risk of acute myocardial infarction (AMI). Methods: A nested case control study was performed in a cohort of antihypertensive drug users from the Utrecht Cardiovascular Pharmacogenetics (UCP) database. Within this cohort, patients who were hospitalized for first AMI were considered cases. Cases were matched (1 up to 4) to controls at the same AMI date (index date). Antihypertensive users were defined as current users if the index date fell within prescribed duration or as stoppers if this date fell outside the prescribed duration. According to recency of stopping, stoppers were divided into recent stoppers (≤90 days), intermediate-term stoppers (91-180 days), and longterm stoppers (>180 days). The study included only antihypertensive users who were specifically current users or stoppers of one antihypertensive agent. Logistic regression analysis was used to assess the association between the discontinuation of antihypertensive agents and the risk of AMI and to control for confounding. Results: We included 1245 cases and 4994 controls in our analysis. The risk of AMI was significantly increased with all stoppers of beta-blockers (adjusted OR: 1.54, 95%CI (1.25-1.90)), calcium channel blockers (CCBs) (adjusted OR: 2.25, 95%CI (1.53- 3.30)), and diuretics (adjusted OR: 1.76, 95%CI (1.24-2.48)) compared with current users. Moreover, the risk of AMI was significantly increased for longterm stoppers (beta-blockers, CCBs, angiotensinconverting enzyme inhibitors, and diuretics) and intermediate- term stoppers (beta-blockers and CCBs) versus current users. There was no difference in AMI risk between recent stoppers of antihypertensive agents versus current users. Conclusions: Discontinuation of antihypertensive agents increases the risk of AMI after more than 90 days of stopping. Adherence to antihypertensive agents plays an important role in reducing the risk of AMI in patients with hypertension.Background: It has been reported that patients with type 1 diabetes (T1DM) have a decreased lung function. Studies on the association of T1DM and asthma in children show controversial results. Objectives: The aim of this study was to quantify asthma medication use in children and adolescents with and without (reference cohort) T1DM 5 years before and after the onset of diabetes. Methods: A population-based cohort study was conducted in the Dutch PHARMO Record Linkage System. All children (1. Modelling of Endpoint Postponement for All-Cause Mortality in Statin Trials Morten Rix Hansen, Anton Pottegård, Asbjørn Hróbjartsson, Per Damkier, René D Christensen, Kasper Søltoft Larsen, Malene EL Kristensen, Palle M Christensen, Jesper Hallas. Clinical Pharmacology, University of Southern Denmark, Odense, Denmark; Department of Clinical Chemistry and Pharmacology, Odense University Hospital, Odense, Denmark; The Nordic Cochrane Centre, Rigshospitalet, Copenhagen, Denmark; Research Unit for General Practice, University of Southern Denmark, Odense, Denmark. Background: The average postponement of the outcome event has been proposed as a novel method to present the magnitude of effect for preventive medications. This measure has been shown to have better agreement with patient preferences than conventional outcomemeasures, including the “number needed to treat” (NNT), possibly because it is more intuitively understood. For some interventions, it may also provide a better theoretical frame for how benefit is distributed among participants than the NNT measure. The aim of this study was to present a novel method for modelling endpoint postponement (EP) from trial data and compare it with the usual approach of measuring the area between survival curves. We also present a formalized meta-analysis of modelled EP for all-cause mortality in statin trials. Methods: We identified 17 placebo-controlled statin trials that fulfilled our inclusion criteria. Eleven of these presented Kaplan–Meier curves for all-cause mortality. Average EP was calculated as the area between Kaplan–Meier curves by counting pixels on magnified prints for these 11 trials. The modelled EP was computed for all trials on the basis of (1) hazard ratio, relative risk or odds ratio; (2) the cumulative event rate in the untreated group; and (3) the trial’s running time. The underlying assumption was that the mortality was reasonably stable within the trials’ running time. The modelled EP was subjected to a meta-analysis, using inverse variance weighting in a random effect model. Results: EPswere generally small for estimates based on pixel-counting, 10 and 27days for trials both primary and secondary intervention that typically ran over 1.9– 6.1years. The modelled EPs varied between 2 and 34days. The difference between modeled EP and EP based on pixel-counting was between 8 and 12days. The results of the meta-analyses will be presented at the meeting. Conclusions: Based on these trial data, statin treatment results in a surprisingly small gain in average survival. Our modelled EP estimates agreed reasonably with EPs based on pixel-counting. The modeled EP is amenable to meta-analyses and may be a useful approach to presenting the benefit of preventive treatment. 2. Permanent User Bias in Case–Crossover Studies in Pharmacoepidemiology Jesper Hallas, Shirley V. Wang, Joshua J. Gagne, Sebastian Schneeweiss, Anton Pottegård. Clinical Pharmacology, University of Southern Denmark, Odense C, Denmark; Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA. Background: In pharmacoepidemiology, the case– crossover design is based on cases that have contrasting drug exposure at the time of an event and at a reference time in the past. If the drug in question should be taken permanently, only certain exposure patterns will occur. These patients cannot be unexposed at the event time and exposed at the reference time, while the opposite pattern can occur if the drug was initiated recently. The resulting odds ratio (OR) would thus be biased upward. As many drugs have a subpopulation of permanent users, this bias might pervade many case–crossover analyses of drug effects. Objectives: The aims of this study were to demonstrate this “permanent user bias” and to evaluate whether it can be remedied by including a control group (case–time–control design). Methods: Using nationwide Danish data resources, we conducted case–crossover and case–time–control analyses for combinations of three exposures that are