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Thielecke J, Kuper P, Lehr D, Schuurmans L, Harrer M, Ebert DD, Cuijpers P, Behrendt D, Brückner H, Horvath H, Riper H, Buntrock C. Who benefits from indirect prevention and treatment of depression using an online intervention for insomnia? Results from an individual-participant data meta-analysis. Psychol Med 2024:1-14. [PMID: 38469832 DOI: 10.1017/s0033291724000527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) is highly prevalent and burdensome for individuals and society. While there are psychological interventions able to prevent and treat MDD, uptake remains low. To overcome structural and attitudinal barriers, an indirect approach of using online insomnia interventions seems promising because insomnia is less stigmatized, predicts MDD onset, is often comorbid and can outlast MDD treatment. This individual-participant-data meta-analysis evaluated the potential of the online insomnia intervention GET.ON Recovery as an indirect treatment to reduce depressive symptom severity (DSS) and potential MDD onset across a range of participant characteristics. METHODS Efficacy on depressive symptom outcomes was evaluated using multilevel regression models controlling for baseline severity. To identify potential effect moderators, clinical, sociodemographic, and work-related variables were investigated using univariable moderation and random-forest methodology before developing a multivariable decision tree. RESULTS IPD were obtained from four of seven eligible studies (N = 561); concentrating on workers with high work-stress. DSS was significantly lower in the intervention group both at post-assessment (d = -0.71 [95% CI-0.92 to -0.51]) and at follow-up (d = -0.84 [95% CI -1.11 to -0.57]). In the subsample (n = 121) without potential MDD at baseline, there were no significant group differences in onset of potential MDD. Moderation analyses revealed that effects on DSS differed significantly across baseline severity groups with effect sizes between d = -0.48 and -0.87 (post) and d = - 0.66 to -0.99 (follow-up), while no other sociodemographic, clinical, or work-related characteristics were significant moderators. CONCLUSIONS An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.
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Affiliation(s)
- Janika Thielecke
- Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany
- Department of Clinical Psychology and Psychotherapy, Institute of Psychology, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
- Unit Healthy Living & Work, TNO (The Netherlands Organization for Applied Scientific Research), Leiden, Netherlands
| | - Paula Kuper
- Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany
- Institute of Social Medicine and Health Systems Research, Faculty of Medicine, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Dirk Lehr
- Department of Health Psychology and Applied Biological Psychology, Institute for Sustainability, Education & Psychology, Leuphana University Luneburg, Luneburg, Germany
| | - Lea Schuurmans
- Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany
| | - Mathias Harrer
- Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany
- GET.ON Institute for Online Health Trainings GmbH, Berlin, Germany
| | - David D Ebert
- Department of Sports and Health Sciences, Technical University of Munich, Munich, Germany
| | - Pim Cuijpers
- Department of Clinical, Neuro and Developmental Psychology, VU University, Amsterdam, Netherlands
- Amsterdam Public Health, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Dörte Behrendt
- Department of Health Psychology and Applied Biological Psychology, Institute for Sustainability, Education & Psychology, Leuphana University Luneburg, Luneburg, Germany
| | - Hanna Brückner
- Department of Health Psychology and Applied Biological Psychology, Institute for Sustainability, Education & Psychology, Leuphana University Luneburg, Luneburg, Germany
| | - Hanne Horvath
- GET.ON Institute for Online Health Trainings GmbH, Berlin, Germany
| | - Heleen Riper
- Department of Clinical, Neuro and Developmental Psychology, VU University, Amsterdam, Netherlands
- Amsterdam Public Health, Amsterdam University Medical Centers, Amsterdam, Netherlands
- Department of Psychiatry, VU University Medical Center, Amsterdam, Netherlands
| | - Claudia Buntrock
- Institute of Social Medicine and Health Systems Research, Faculty of Medicine, Otto von Guericke University Magdeburg, Magdeburg, Germany
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Perneger T, Combescure C, Poncet A. Adjustment for baseline characteristics in randomized trials using logistic regression: sample-based model versus true model. Trials 2023; 24:107. [PMID: 36782238 PMCID: PMC9924183 DOI: 10.1186/s13063-022-07053-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 12/26/2022] [Indexed: 02/15/2023] Open
Abstract
BACKGROUND Adjustment for baseline prognostic factors in randomized clinical trials is usually performed by means of sample-based regression models. Sample-based models may be incorrect due to overfitting. To assess whether overfitting is a problem in practice, we used simulated data to examine the performance of the sample-based model in comparison to a "true" adjustment model, in terms of estimation of the treatment effect. METHODS We conducted a simulation study using samples drawn from a "population" in which both the treatment effect and the effect of the potential confounder were specified. The outcome variable was binary. Using logistic regression, we compared three estimates of the treatment effect in each situation: unadjusted, adjusted for the confounder using the sample, adjusted for the confounder using the true effect. Experimental factors were sample size (from 2 × 50 to 2 × 1000), treatment effect (logit of 0, 0.5, or 1.0), confounder type (continuous or binary), and confounder effect (logit of 0, - 0.5, or - 1.0). The assessment criteria for the estimated treatment effect were bias, variance, precision (proportion of estimates within 0.1 logit units), type 1 error, and power. RESULTS Sample-based adjustment models yielded more biased estimates of the treatment effect than adjustment models that used the true confounder effect but had similar variance, accuracy, power, and type 1 error rates. The simulation also confirmed the conservative bias of unadjusted analyses due to the non-collapsibility of the odds ratio, the smaller variance of unadjusted estimates, and the bias of the odds ratio away from the null hypothesis in small datasets. CONCLUSIONS Sample-based adjustment yields similar results to exact adjustment in estimating the treatment effect. Sample-based adjustment is preferable to no adjustment.
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Affiliation(s)
- Thomas Perneger
- Division of Clinical Epidemiology, University of Geneva and Geneva University Hospitals, 6 Rue Gabrielle-Perret-Gentil, 1211, Geneva, Switzerland.
| | - Christophe Combescure
- grid.8591.50000 0001 2322 4988Division of Clinical Epidemiology, University of Geneva and Geneva University Hospitals, 6 Rue Gabrielle-Perret-Gentil, 1211 Geneva, Switzerland
| | - Antoine Poncet
- grid.8591.50000 0001 2322 4988Division of Clinical Epidemiology, University of Geneva and Geneva University Hospitals, 6 Rue Gabrielle-Perret-Gentil, 1211 Geneva, Switzerland
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3
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Sharshar T, Porcher R, Asfar P, Grimaldi L, Jabot J, Argaud L, Lebert C, Bollaert PE, Harlay ML, Chillet P, Maury E, Santoli F, Blanc P, Sonneville R, Vu DC, Rohaut B, Mazeraud A, Alvarez JC, Navarro V, Clair B, Outin H, Azabou E, Beloncle F, Ben-Hadj O, Blanc P, Bollaert PE, Bolgert F, Bouadma L, Chillet P, Clair B, Corne P, Clere-Jehl R, Cour M, Crespel A, Déiler V, Dellamonica J, Demeret S, Harley ML, Henry-Lagarrigue M, Jabot J, Heming N, Hernu R, Kouatchet A, Lebert C, Lerolle N, Maury E, Letrou S, Mazeraud A, Mercat A, Mortaza S, Mourvillier B, Outin H, Paugham-Burtz C, Pierrot M, Provent M, Rohaut B, De La Salle S, Santoli F, Schenk M, Siami S, Souday V, Sharshar T, Sonneville R, Timsit JF, Thuong M, Weiss N. Valproic acid as adjuvant treatment for convulsive status epilepticus: a randomised clinical trial. Crit Care 2023; 27:8. [PMID: 36624526 PMCID: PMC9830759 DOI: 10.1186/s13054-022-04292-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 12/21/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Generalised convulsive status epilepticus (GCSE) is a medical emergency. Guidelines recommend a stepwise strategy of benzodiazepines followed by a second-line anti-seizure medicine (ASM). However, GCSE is uncontrolled in 20-40% patients and is associated with protracted hospitalisation, disability, and mortality. The objective was to determine whether valproic acid (VPA) as complementary treatment to the stepwise strategy improves the outcomes of patients with de novo established GCSE. METHODS This was a multicentre, double-blind, randomised controlled trial in 244 adults admitted to intensive care units for GCSE in 16 French hospitals between 2013 and 2018. Patients received standard care of benzodiazepine and a second-line ASM (except VPA). Intervention patients received a 30 mg/kg VPA loading dose, then a 1 mg/kg/h 12 h infusion, whilst the placebo group received an identical intravenous administration of 0.9% saline as a bolus and continuous infusion. Primary outcome was proportion of patients discharged from hospital by day 15. The secondary outcomes were seizure control, adverse events, and cognition at day 90. RESULTS A total of 126 (52%) and 118 (48%) patients were included in the VPA and placebo groups. 224 (93%) and 227 (93%) received a first-line and a second-line ASM before VPA or placebo infusion. There was no between-group difference for patients hospital-discharged at day 15 [VPA, 77 (61%) versus placebo, 72 (61%), adjusted relative risk 1.04; 95% confidence interval (0.89-1.19); p = 0.58]. There were no between-group differences for secondary outcomes. CONCLUSIONS VPA added to the recommended strategy for adult GCSE is well tolerated but did not increase the proportion of patients hospital-discharged by day 15. TRIAL REGISTRATION NO NCT01791868 (ClinicalTrials.gov registry), registered: 15 February 2012.
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Affiliation(s)
- Tarek Sharshar
- grid.508487.60000 0004 7885 7602Neuro-Intensive Care Medicine, Anaesthesiology and ICU Department, GHU-Psychiatry and Neurosciences, Pole Neuro, Sainte-Anne Hospital, Institute of Psychiatry and Neurosciences of Paris, INSERM U1266, Université Paris Cité, Paris, France
| | - Raphaël Porcher
- Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), F-75004 Paris, France ,grid.411394.a0000 0001 2191 1995Centre d’Epidémiologie Clinique, AP-HP, Hôpital Hôtel Dieu, F-75004 Paris, France
| | - Pierre Asfar
- grid.411147.60000 0004 0472 0283Department of Medical Intensive Care, University Hospital, Angers, France
| | - Lamiae Grimaldi
- grid.50550.350000 0001 2175 4109Clinical Research Unit, Assistance Publique - Hôpitaux de Paris University Paris-Saclay. Faculty of medicine, University of Versailles Saint-Quentin en Yvelines. Inserm U1018 Team Anti-infective evasion and pharmacoepidemiology, Boulogne-Billancourt, France
| | - Julien Jabot
- Medical-Surgical Intensive Care Unit, CHU Felix-Guyon, Saint-Denis, La Réunion, France
| | - Laurent Argaud
- grid.412180.e0000 0001 2198 4166Service de Médecine Intensive-Réanimation, Hospices Civils de Lyon, Hôpital Edouard Herriot, Lyon, France
| | - Christine Lebert
- grid.477015.00000 0004 1772 6836Médecine Intensive Réanimation, Centre Hospitalier Départemental de Vendée, La Roche-sur-Yon, France
| | - Pierre-Edouard Bollaert
- grid.29172.3f0000 0001 2194 6418CHRU-Nancy, Service de Médecine Intensive Réanimation, Université de Lorraine, 54000 Nancy, France
| | - Marie Line Harlay
- grid.412201.40000 0004 0593 6932Médecine Intensive Réanimation, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Patrick Chillet
- Service de Médecine Intensive - Réanimation, Centre hospitalier Léon Bourgeois, Châlons en Champagne, France
| | - Eric Maury
- grid.462844.80000 0001 2308 1657Service de Médecine Intensive et Réanimation Hôpital Saint-Antoine, Paris-Sorbonne Université, Paris, France
| | - Francois Santoli
- grid.414308.a0000 0004 0594 0368Médecine Intensive—Réanimation, Centre Hospitalier Robert Ballanger, Aulnay sous Bois, France
| | - Pascal Blanc
- grid.440383.80000 0004 1765 1969Réanimation Médico Chirurgicale, Centre Hospitalier René Dubos, Pontoise, France
| | - Romain Sonneville
- Université de Paris Cité, INSERM UMR1137, Paris, France ,grid.411119.d0000 0000 8588 831XAPHP Nord, Médecine Intensive – Réanimation, Hôpital Bichat—Claude Bernard, Paris, France
| | - Dinh Chuyen Vu
- General Intensive Care Unit, Sud-Essonne Hospital, Etampes, France
| | - Benjamin Rohaut
- grid.462844.80000 0001 2308 1657Department of Neurology, Neuro-ICU & Brain institute - ICM, Pitié-Salpêtrière Hospital APHP, Sorbonne Université, Paris, France
| | - Aurelien Mazeraud
- grid.508487.60000 0004 7885 7602Anaesthesiology and ICU Department, GHU-Psychiatry and Neurosciences, Pole Neuro, Sainte-Anne Hospital, Perception and Memory Unit, Neurosciences Department, Institut Pasteur, Université Paris Cité, Paris, France
| | - Jean-Claude Alvarez
- grid.12832.3a0000 0001 2323 0229Department of Pharmacology and Toxicology, Inserm U-1173, Raymond Poincare Hospital, AP-HP, Versailles Saint-Quentin-en-Yvelines University, Paris-Saclay University, 104 Boulevard Raymond Poincare, 92380 Garches, France
| | - Vincent Navarro
- grid.425274.20000 0004 0620 5939AP-HP, Epilepsy Unit, Pitié-Salpêtrière Hospital, Sorbonne Université, and Paris Brain Institute, Paris, France
| | - Bernard Clair
- grid.12832.3a0000 0001 2323 0229General Intensive Care Unit, APHP, Raymond Poincaré Hospital, University of Versailles Saint-Quentin en Yvelines, Garches, France
| | - Hervé Outin
- grid.418056.e0000 0004 1765 2558Intensive Care Unit Centre Hospitalier Intercommunal, Poissy/Saint-Germain-en-Laye, France
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Zou G, Zou L, Choi YH. Distribution-Free Approach to the Design and Analysis of Randomized Stroke Trials With the Modified Rankin Scale. Stroke 2022; 53:3025-3031. [PMID: 35975666 DOI: 10.1161/strokeaha.121.037744] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Many methods have been suggested for analyzing the modified Rankin Scale (mRS). However, there lacks a unified approach to analysis and sample size determination that properly uses the ordinal nature of the data. We propose a simple method for CI estimation and corresponding sample size determination. METHODS We quantify treatment effect by the win probability (WinP) that a randomly selected patient in the treatment group has an equal or a better mRS score than a patient in the control group. Thus, a win probability of 0.5 means no effect, likened to a draw in competitive sports. We estimate the win probability and its SE based on the ranks of mRS scores, where tied scores are handled by average ranks. Corresponding methods for hypothesis testing, CI estimation, and sample size determination are derived. The methods are evaluated with a simulation study based on real data from 10 randomized stroke trials that used mRS as the outcome measure. RESULTS Simulation results demonstrated that the methods performed very well in terms of CI coverage, tail errors, and assurance to achieving the prespecified precision. Because the methods are very simple, we implemented them in an Excel spreadsheet, requiring only user inputs on frequencies of mRS scores in 2 comparison groups. CONCLUSIONS Sound statistical methods are important for the success of randomized stroke trials. The proposed methods and associated spreadsheet should prove useful for stroke researchers in the planning and analysis of randomized trials. Meta-analysis has also been made easy for trials with ordinal scores.
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Affiliation(s)
- Guangyong Zou
- Department of Epidemiology and Biostatistics, Western University, London, Canada. (G.Z., Y.-H.C.).,Robarts Research Institute, Western University, London, Canada. (G.Z.).,Alimentiv Inc (formerly Robarts Clinical Trials' Inc)' London' Canada (G.Z.)
| | - Lily Zou
- Department of Statistics and Actuarial Sciences, University of Waterloo, Canada (L.Z.)
| | - Yun-Hee Choi
- Department of Epidemiology and Biostatistics, Western University, London, Canada. (G.Z., Y.-H.C.)
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Lee KM, Robertson DS, Jaki T, Emsley R. The benefits of covariate adjustment for adaptive multi-arm designs. Stat Methods Med Res 2022; 31:2104-2121. [PMID: 35876412 PMCID: PMC7613816 DOI: 10.1177/09622802221114544] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Covariate adjustment via a regression approach is known to increase the precision
of statistical inference when fixed trial designs are employed in randomized
controlled studies. When an adaptive multi-arm design is employed with the
ability to select treatments, it is unclear how covariate adjustment affects
various aspects of the study. Consider the design framework that relies on
pre-specified treatment selection rule(s) and a combination test approach for
hypothesis testing. It is our primary goal to evaluate the impact of covariate
adjustment on adaptive multi-arm designs with treatment selection. Our secondary
goal is to show how the Uniformly Minimum Variance Conditionally Unbiased
Estimator can be extended to account for covariate adjustment analytically. We
find that adjustment with different sets of covariates can lead to different
treatment selection outcomes and hence probabilities of rejecting hypotheses.
Nevertheless, we do not see any negative impact on the control of the familywise
error rate when covariates are included in the analysis model. When adjusting
for covariates that are moderately or highly correlated with the outcome, we see
various benefits to the analysis of the design. Conversely, there is negligible
impact when including covariates that are uncorrelated with the outcome.
Overall, pre-specification of covariate adjustment is recommended for the
analysis of adaptive multi-arm design with treatment selection. Having the
statistical analysis plan in place prior to the interim and final analyses is
crucial, especially when a non-collapsible measure of treatment effect is
considered in the trial.
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Affiliation(s)
- Kim May Lee
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | | | - Thomas Jaki
- 47959MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
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van Mourik Y, Rutten FH, Bertens LC, Cramer MJ, Lammers JWJ, Gohar A, Reitsma JB, Moons KG, Hoes AW. Clinical research study implementation of case-finding strategies for heart failure and chronic obstructive pulmonary disease in the elderly with reduced exercise tolerance or dyspnea: A cluster randomized trial. Am Heart J 2020; 220:73-81. [PMID: 31790904 DOI: 10.1016/j.ahj.2019.08.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2019] [Accepted: 08/27/2019] [Indexed: 11/25/2022]
Abstract
BACKGROUND Heart failure (HF) and chronic obstructive pulmonary disease (COPD) often remain undiagnosed in older individuals, although both disorders inhibit functionality and impair health. The aim of the study was to assess the effectiveness of a case-finding strategy of these disorders. METHODS This is a clustered randomized trial; 18 general practices from the vicinity of Utrecht, the Netherlands, were randomly allocated to a case-finding strategy or usual care. Multimorbid community subjects (≥65 years) with dyspnea or reduced exercise tolerance were eligible for inclusion. The case-finding strategy consisted of history taking, physical examination, blood tests, electrocardiography, spirometry, and echocardiography. Subsequent treatment decisions were at the discretion of the general practitioner. Questionnaires regarding health status and functionality were filled out at baseline and after 6 months of follow-up. Information regarding changes in medication and health care use during the 6 months follow-up was extracted. RESULTS A total of 829 participants were randomized: 389 in the case-finding strategy group and 440 in the usual care group. More patients in the case-finding group received a new diagnosis of HF or COPD than the usual care group (cumulative incidence 34% vs 2% and 17% vs. 2%, respectively). Scores for health status, functionality, and health care use were similar between the 2 strategies after 6 months of follow-up. CONCLUSIONS A case-finding strategy applied in primary care to multimorbid older people with dyspnea or reduced exercise tolerance resulted in a number of new diagnoses of HF and COPD but did not result in short-term improvement of health status compared to usual care.
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Impact of Modified Transesophageal Echocardiography on Mortality and Stroke after Cardiac Surgery: A Large Cohort Study. Int J Vasc Med 2017; 2017:1857069. [PMID: 29085679 PMCID: PMC5611872 DOI: 10.1155/2017/1857069] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Revised: 06/27/2017] [Accepted: 07/18/2017] [Indexed: 11/18/2022] Open
Abstract
The aim of this study was to investigate the impact of perioperative screening with modified transesophageal echocardiography (A-View method). We compared, in consecutive patients who underwent cardiac surgery between 2006 and 2014, 30-day mortality and in-hospital stroke incidence, operated either with perioperative modified TEE screening (intervention group) or only with conventional TEE screening (control group). Of the 8,605 study patients, modified TEE was applied in 1,391 patients (16.2%). Patients in the intervention group were on average older (71 versus 68 years, p < 0.001) and more often females (31.0% versus 28.0%, p < 0.001) and had a higher predicted mortality (EuroSCORE I: 5.9% versus 4.0%, p < 0.001). The observed 30-day mortality was 2.2% and 2.5% in both groups, respectively, with multivariable and propensity-score adjusted relative risks (RRs) of 0.70 (95% CI: 0.50–1.00, p = 0.05) and 0.67 (95% CI: 0.45–0.98, p = 0.04). In-hospital stroke was 2.9% and 2.1% in both groups, respectively, with adjusted RRs of 1.03 (95% CI: 0.73–1.45) and 1.01 (95% CI: 0.71–1.43). In patients undergoing cardiac surgery, use of perioperative screening for aortic atherosclerosis with modified TEE was associated with lower postoperative mortality, but not stroke, as compared to patients operated on without such screening.
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Hu YJ, Schmidt AF, Dudbridge F, Holmes MV, Brophy JM, Tragante V, Li Z, Liao P, Quyyumi AA, McCubrey RO, Horne BD, Hingorani AD, Asselbergs FW, Patel R, Long Q. Impact of Selection Bias on Estimation of Subsequent Event Risk. CIRCULATION. CARDIOVASCULAR GENETICS 2017; 10:e001616. [PMID: 28986451 PMCID: PMC5659743 DOI: 10.1161/circgenetics.116.001616] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Accepted: 07/07/2017] [Indexed: 02/06/2023]
Abstract
BACKGROUND Studies of recurrent or subsequent disease events may be susceptible to bias caused by selection of subjects who both experience and survive the primary indexing event. Currently, the magnitude of any selection bias, particularly for subsequent time-to-event analysis in genetic association studies, is unknown. METHODS AND RESULTS We used empirically inspired simulation studies to explore the impact of selection bias on the marginal hazard ratio for risk of subsequent events among those with established coronary heart disease. The extent of selection bias was determined by the magnitudes of genetic and nongenetic effects on the indexing (first) coronary heart disease event. Unless the genetic hazard ratio was unrealistically large (>1.6 per allele) and assuming the sum of all nongenetic hazard ratios was <10, bias was usually <10% (downward toward the null). Despite the low bias, the probability that a confidence interval included the true effect decreased (undercoverage) with increasing sample size because of increasing precision. Importantly, false-positive rates were not affected by selection bias. CONCLUSIONS In most empirical settings, selection bias is expected to have a limited impact on genetic effect estimates of subsequent event risk. Nevertheless, because of undercoverage increasing with sample size, most confidence intervals will be over precise (not wide enough). When there is no effect modification by history of coronary heart disease, the false-positive rates of association tests will be close to nominal.
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Affiliation(s)
- Yi-Juan Hu
- Dept of Biostatistics and Bioinformatics, Emory University, Atlanta, GA
| | - Amand F Schmidt
- Institute of Cardiovascular Science & The Farr Institute, University College London, UK
| | - Frank Dudbridge
- Dept of Non-communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine & Dept of Health Sciences, University of Leicester, UK
| | - Michael V Holmes
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Dept of Population Health, University of Oxford, UK
- Medical Research Council Population Health Research Unit at the University of Oxford, UK
| | - James M Brophy
- Dept of Medicine, McGill University, Montreal Quebec, Canada
| | - Vinicius Tragante
- Dept of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands
| | - Ziyi Li
- Dept of Biostatistics and Bioinformatics, Emory University, Atlanta, GA
| | - Peizhou Liao
- Dept of Biostatistics and Bioinformatics, Emory University, Atlanta, GA
| | - Arshed A Quyyumi
- Division of Cardiology, Dept of Medicine, Emory Clinical Cardiovascular Research Institute, Emory University School of Medicine, Atlanta, GA
| | - Raymond O. McCubrey
- Intermountain Heart Institute, Intermountain Medical Center, University of Utah, Salt Lake City, UT
| | - Benjamin D. Horne
- Intermountain Heart Institute, Intermountain Medical Center, University of Utah, Salt Lake City, UT
- Dept of Biomedical Informatics, University of Utah, Salt Lake City, UT
| | - Aroon D Hingorani
- Institute of Cardiovascular Science & The Farr Institute, University College London, UK
| | - Folkert W. Asselbergs
- Institute of Cardiovascular Science & The Farr Institute, University College London, UK
- Dept of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, Netherlands
| | - Riyaz Patel
- Institute of Cardiovascular Science & The Farr Institute, University College London, UK
| | - Qi Long
- Dept of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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Kortekaas MF, Bartelink MEL, Zuithoff NPA, van der Heijden GJMG, de Wit NJ, Hoes AW. Does integrated training in evidence-based medicine (EBM) in the general practice (GP) specialty training improve EBM behaviour in daily clinical practice? A cluster randomised controlled trial. BMJ Open 2016; 6:e010537. [PMID: 27625052 PMCID: PMC5030598 DOI: 10.1136/bmjopen-2015-010537] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVES Evidence-based medicine (EBM) is an important element in the general practice (GP) specialty training. Studies show that integrating EBM training into clinical practice brings larger benefits than stand-alone modules. However, these studies have neither been performed in GP nor assessed EBM behaviour of former trainees in daily clinical practice. SETTING GP specialty training in the Netherlands. PARTICIPANTS All 82 third year GP trainees who started their final third year in 2011 were approached for inclusion, of whom 79 (96%) participated: 39 in the intervention group and 40 in the control group. INTERVENTION Integrated EBM training, in which EBM is embedded closely within the clinical context by joint assignments for the trainee and supervisor in daily practice, and teaching sessions based on dilemmas from actual patient consultations. COMPARISON Stand-alone EBM training at the institute only. PRIMARY AND SECONDARY OUTCOMES Our primary outcome was EBM behaviour, assessed by measuring guideline adherence (incorporating rational, motivated deviation) and information-seeking behaviour. Our secondary outcomes were EBM attitude and EBM knowledge. Data were acquired using logbooks and questionnaires, respectively. Analyses were performed using mixed models. RESULTS Logbook data were available from 76 (96%) of the participating trainees at baseline (7614 consultations), 60 (76%) at the end of the third year (T1, 4973 consultations) and 53 (67%) 1 year after graduation (T2, 3307 consultations). We found no significant differences in outcomes between the 2 groups, with relative risks for guideline adherence varying between 0.96 and 0.99 (95% CI 0.86 to 1.11) at T1, and 0.99 and 1.10 (95% CI 0.92 to 1.25) at T2, and for information-seeking behaviour between 0.97 and 1.16 (95% CI 0.70 to 1.91) and 0.90 and 1.10 (95% CI 0.70 to 1.32), respectively. CONCLUSIONS Integrated EBM training compared with stand-alone EBM training does not improve EBM behaviour, attitude or knowledge of (future) GPs.
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Affiliation(s)
- M F Kortekaas
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - M E L Bartelink
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - N P A Zuithoff
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - G J M G van der Heijden
- Department of Social Dentistry, Academic Centre for Dentistry Amsterdam, University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands
| | - N J de Wit
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - A W Hoes
- Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, The Netherlands
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Pang M, Kaufman JS, Platt RW. Studying noncollapsibility of the odds ratio with marginal structural and logistic regression models. Stat Methods Med Res 2016; 25:1925-1937. [DOI: 10.1177/0962280213505804] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
One approach to quantifying the magnitude of confounding in observational studies is to compare estimates with and without adjustment for a covariate, but this strategy is known to be defective for noncollapsible measures such as the odds ratio. Comparing estimates from marginal structural and standard logistic regression models, the total difference between crude and conditional effects can be decomposed into the sum of a noncollapsibility effect and confounding bias. We provide an analytic approach to assess the noncollapsibility effect in a point-exposure study and provide a general formula for expressing the noncollapsibility effect. Next, we provide a graphical approach that illustrates the relationship between the noncollapsibility effect and the baseline risk, and reveals the behavior of the noncollapsibility effect for a range of different exposure and covariate effects. Various observations about noncollapsibility can be made from the different scenarios with or without confounding; for example, the magnitude of effect of the covariate plays a more important role in the noncollapsibility effect than does that of the effect of the exposure. In order to explore the noncollapsibility effect of the odds ratio in the presence of time-varying confounding, we simulated an observational cohort study. The magnitude of noncollapsibility was generally comparable to the effect in the point-exposure study in our simulation settings. Finally, in an applied example we demonstrate that collapsibility can have an important impact on estimation in practice.
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Affiliation(s)
- Menglan Pang
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
| | - Jay S Kaufman
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
| | - Robert W Platt
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
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11
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Su YS, Lee WC. False Appearance of Gene-Environment Interactions in Genetic Association Studies. Medicine (Baltimore) 2016; 95:e2743. [PMID: 26945360 PMCID: PMC4782844 DOI: 10.1097/md.0000000000002743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Under the assumption of gene-environment independence, unknown/unmeasured environmental factors, irrespective of what they may be, cannot confound the genetic effects. This may lead many people to believe that genetic heterogeneity across different levels of the studied environmental exposure should only mean gene-environment interaction--even though other environmental factors are not adjusted for. However, this is not true if the odds ratio is the effect measure used for quantifying genetic effects. This is because the odds ratio is a "noncollapsible" measure--a marginal odds ratio is not a weighted average of the conditional odds ratios, but instead has a tendency toward the null. In this study, the authors derive formulae for gene-environment interaction bias due to noncollapsibility. They use computer simulation and real data example to show that the bias can be substantial for common diseases. For genetic association study of nonrare diseases, researchers are advised to use collapsible measures, such as risk ratio or peril ratio.
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Affiliation(s)
- Yi-Shan Su
- From the Institute of Epidemiology and Preventive Medicine (Y-SS, W-CL), College of Public Health, National Taiwan University; and Research Center for Genes, Environment and Human Health (W-CL), College of Public Health, National Taiwan University, Taipei, Taiwan
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Ayubi E. Effects of nursery songs for infants and young children's anxiety: a reporting mistake of effect measure of association. Am J Emerg Med 2016; 34:663. [PMID: 26786516 DOI: 10.1016/j.ajem.2015.12.050] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Revised: 11/07/2015] [Accepted: 12/18/2015] [Indexed: 11/16/2022] Open
Affiliation(s)
- Erfan Ayubi
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
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Balasubramanian H, Ananthan A, Rao S, Patole S. Odds ratio vs risk ratio in randomized controlled trials. Postgrad Med 2015; 127:359-67. [PMID: 25746068 DOI: 10.1080/00325481.2015.1022494] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
OBJECTIVE Use of odds ratio (OR) in randomized controlled trials (RCTs) has been criticized because it overestimates the effect size, if incorrectly interpreted as risk ratio (RR). To what extent does this make a difference in the context of clinical research is unclear. We, therefore, aimed to address this issue considering its importance in evidence-based practice of medicine. METHODS We reviewed 580 RCTs published in the New England Journal of Medicine between January 2004 and June 2014 and identified 107 RCTs that reported unadjusted RR (n = 76) or OR (n = 31) for the primary outcome. For studies reporting ORs, we calculated RRs, and vice versa, using Stata software. The percentage of divergence between the reported and calculated effect size estimates was analyzed. RESULTS None of the RCTs showed a statistically significant result becoming insignificant or vice versa depending on the effect size estimate. OR exaggerated the RR in 62% of the RCTs. The percentage of overestimation was > 50% in 28 RCTs and > 100% in 13 RCTs. The degree of overestimation was positively correlated with the prevalence of outcomes (spearman's rho = 0.84 and 0.66, p < 0.001). CONCLUSION Use of OR instead of RR in RCTs does not change the qualitative inference of results. However, the use of OR can markedly exaggerate the effect size in RCTs if misinterpreted as RR and, hence, has the potential to mislead clinicians.
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Abstract
BACKGROUND Experimental studies suggest oxidative stress could lead to the development of hypertension. Serum bilirubin is a major contributor to the antioxidant capacity in blood plasma and has been identified as an independent cardiovascular risk factor in cohort studies. However, data on the relationship between bilirubin and blood pressure are scarce and inconclusive. METHODS We analysed data from the National Health and Nutrition Examination Surveys (NHANES) 1999-2012 (N=31069). Fifty multiple imputed data sets were generated and analysed to avoid selection/confounding bias due to excluding individuals/variables with missing values. A minimal sufficient adjustment set of variables (MSAS) needed to estimate the unconfounded effect of bilirubin on blood pressure and hypertension (systolic/diastolic blood pressure ≥ 140/90 mmHg or using antihypertensive medication) was identified using the back-door criterion and included in all regression models. RESULTS After adjustment for the MSAS variables, systolic blood pressure decreased progressively up to -2.5 mmHg (p<0.001) and the prevalence of hypertension was up to 25% lower (P<0.001) in those with bilirubin ≥ 1.0 mg/dl-the highest two deciles-compared with those with 0.1-0.4 mg/dl-the lowest decile. Sensitivity analyses showed these results were unlikely to be explained by residual confounding or selection bias. CONCLUSIONS High serum bilirubin may decrease the risk of hypertension by inactivating and inhibiting the synthesis of reactive oxygen species in vascular cells. Strategies to boost the bioavailability of circulating and tissue bilirubin or to mimic bilirubin's antioxidant properties could have a significant impact on prevention and control of hypertension as well as coronary heart disease.
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Affiliation(s)
- Lina Wang
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing, China and Department of Population Health Sciences, University of Wisconsin in Madison, Madison, WI, USA Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing, China and Department of Population Health Sciences, University of Wisconsin in Madison, Madison, WI, USA
| | - Leonelo E Bautista
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing, China and Department of Population Health Sciences, University of Wisconsin in Madison, Madison, WI, USA
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15
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Barger SD, Messerli-Bürgy N, Barth J. Social relationship correlates of major depressive disorder and depressive symptoms in Switzerland: nationally representative cross sectional study. BMC Public Health 2014; 14:273. [PMID: 24656048 PMCID: PMC3994328 DOI: 10.1186/1471-2458-14-273] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2013] [Accepted: 03/18/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The quality and quantity of social relationships are associated with depression but there is less evidence regarding which aspects of social relationships are most predictive. We evaluated the relative magnitude and independence of the association of four social relationship domains with major depressive disorder and depressive symptoms. METHODS We analyzed a cross-sectional telephone interview and postal survey of a probability sample of adults living in Switzerland (N=12,286). Twelve-month major depressive disorder was assessed via structured interview over the telephone using the Composite International Diagnostic Interview (CIDI). The postal survey assessed depressive symptoms as well as variables representing emotional support, tangible support, social integration, and loneliness. RESULTS Each individual social relationship domain was associated with both outcome measures, but in multivariate models being lonely and perceiving unmet emotional support had the largest and most consistent associations across depression outcomes (incidence rate ratios ranging from 1.55-9.97 for loneliness and from 1.23-1.40 for unmet support, p's<0.05). All social relationship domains except marital status were independently associated with depressive symptoms whereas only loneliness and unmet support were associated with depressive disorder. CONCLUSIONS Perceived quality and frequency of social relationships are associated with clinical depression and depressive symptoms across a wide adult age spectrum. This study extends prior work linking loneliness to depression by showing that a broad range of social relationship domains are associated with psychological well-being.
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Affiliation(s)
- Steven D Barger
- Department of Psychology, Northern Arizona University, PO Box 15106, Flagstaff, AZ 86011, USA.
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Schmidt AF, Rovers MM, Klungel OH, Hoes AW, Knol MJ, Nielen M, de Boer A, Groenwold RH. Differences in interaction and subgroup-specific effects were observed between randomized and nonrandomized studies in three empirical examples. J Clin Epidemiol 2013; 66:599-607. [DOI: 10.1016/j.jclinepi.2012.08.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2012] [Revised: 06/27/2012] [Accepted: 08/20/2012] [Indexed: 10/27/2022]
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Turner EL, Perel P, Clayton T, Edwards P, Hernández AV, Roberts I, Shakur H, Steyerberg EW. Covariate adjustment increased power in randomized controlled trials: an example in traumatic brain injury. J Clin Epidemiol 2012; 65:474-81. [PMID: 22169080 PMCID: PMC3589911 DOI: 10.1016/j.jclinepi.2011.08.012] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2011] [Revised: 07/05/2011] [Accepted: 08/10/2011] [Indexed: 11/29/2022]
Abstract
OBJECTIVE We aimed to determine to what extent covariate adjustment could affect power in a randomized controlled trial (RCT) of a heterogeneous population with traumatic brain injury (TBI). STUDY DESIGN AND SETTING We analyzed 14-day mortality in 9,497 participants in the Corticosteroid Randomization After Significant Head Injury (CRASH) RCT of corticosteroid vs. placebo. Adjustment was made using logistic regression for baseline covariates of two validated risk models derived from external data (International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury [IMPACT]) and from the CRASH data. The relative sample size (RESS) measure, defined as the ratio of the sample size required by an adjusted analysis to attain the same power as the unadjusted reference analysis, was used to assess the impact of adjustment. RESULTS Corticosteroid was associated with higher mortality compared with placebo (odds ratio=1.25, 95% confidence interval=1.13-1.39). RESS of 0.79 and 0.73 were obtained by adjustment using the IMPACT and CRASH models, respectively, which, for example, implies an increase from 80% to 88% and 91% power, respectively. CONCLUSION Moderate gains in power may be obtained using covariate adjustment from logistic regression in heterogeneous conditions such as TBI. Although analyses of RCTs might consider covariate adjustment to improve power, we caution against this approach in the planning of RCTs.
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Affiliation(s)
- Elizabeth L Turner
- Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.
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Groenwold RHH, Donders ART, Roes KCB, Harrell FE, Moons KGM. Dealing with missing outcome data in randomized trials and observational studies. Am J Epidemiol 2012; 175:210-7. [PMID: 22262640 DOI: 10.1093/aje/kwr302] [Citation(s) in RCA: 287] [Impact Index Per Article: 23.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Although missing outcome data are an important problem in randomized trials and observational studies, methods to address this issue can be difficult to apply. Using simulated data, the authors compared 3 methods to handle missing outcome data: 1) complete case analysis; 2) single imputation; and 3) multiple imputation (all 3 with and without covariate adjustment). Simulated scenarios focused on continuous or dichotomous missing outcome data from randomized trials or observational studies. When outcomes were missing at random, single and multiple imputations yielded unbiased estimates after covariate adjustment. Estimates obtained by complete case analysis with covariate adjustment were unbiased as well, with coverage close to 95%. When outcome data were missing not at random, all methods gave biased estimates, but handling missing outcome data by means of 1 of the 3 methods reduced bias compared with a complete case analysis without covariate adjustment. Complete case analysis with covariate adjustment and multiple imputation yield similar estimates in the event of missing outcome data, as long as the same predictors of missingness are included. Hence, complete case analysis with covariate adjustment can and should be used as the analysis of choice more often. Multiple imputation, in addition, can accommodate the missing-not-at-random scenario more flexibly, making it especially suited for sensitivity analyses.
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Affiliation(s)
- Rolf H H Groenwold
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, the Netherlands.
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Knol MJ, Le Cessie S, Algra A, Vandenbroucke JP, Groenwold RHH. Overestimation of risk ratios by odds ratios in trials and cohort studies: alternatives to logistic regression. CMAJ 2011; 184:895-9. [PMID: 22158397 DOI: 10.1503/cmaj.101715] [Citation(s) in RCA: 342] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Affiliation(s)
- Mirjam J Knol
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
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Groenwold RHH, de Vries F, de Boer A, Pestman WR, Rutten FH, Hoes AW, Klungel OH. Balance measures for propensity score methods: a clinical example on beta-agonist use and the risk of myocardial infarction. Pharmacoepidemiol Drug Saf 2011; 20:1130-7. [PMID: 21953948 DOI: 10.1002/pds.2251] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2011] [Revised: 08/05/2011] [Accepted: 08/18/2011] [Indexed: 11/11/2022]
Abstract
PURPOSE Propensity score (PS) methods aim to control for confounding by balancing confounders between exposed and unexposed subjects with the same PS. PS balance measures have been compared in simulated data but limited in empirical data. Our objective was to compare balance measures in clinical data and assessed the association between long-acting inhalation beta-agonist (LABA) use and myocardial infarction. METHODS We estimated the relationship between LABA use and myocardial infarction in a cohort of adults with a diagnosis of asthma or chronic obstructive pulmonary disorder from the Utrecht General Practitioner Research Network database. More than two thousand PS models, including information on the observed confounders age, sex, diabetes, cardiovascular disease and chronic obstructive pulmonary disorder status, were applied. The balance of these confounders was assessed using the standardised difference (SD), Kolmogorov-Smirnov (KS) distance and overlapping coefficient. Correlations between these balance measures were calculated. In addition, simulation studies were performed to assess the correlation between balance measures and bias. RESULTS LABA use was not related to myocardial infarction after conditioning on the PS (median heart rate = 1.14, 95%CI = 0.47-2.75). When using the different balance measures for selecting a PS model, similar associations were obtained. In our empirical data, SD and KS distance were highly correlated balance measures (r = 0.92). In simulations, SD, KS distance and overlapping coefficient were similarly correlated to bias (e.g. r = 0.55, r = 0.52 and r = -0.57, respectively, when conditioning on the PS). CONCLUSIONS We recommend using the SD or the KS distance to quantify the balance of confounder distributions when applying PS methods.
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Affiliation(s)
- Rolf H H Groenwold
- Department of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands.
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Groenwold RHH, Klungel OH, Grobbee DE, Hoes AW. Selection of confounding variables should not be based on observed associations with exposure. Eur J Epidemiol 2011; 26:589-93. [PMID: 21796419 PMCID: PMC3168755 DOI: 10.1007/s10654-011-9606-1] [Citation(s) in RCA: 72] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2011] [Accepted: 07/07/2011] [Indexed: 12/03/2022]
Abstract
In observational studies, selection of confounding variables for adjustment is often based on observed baseline incomparability. The aim of this study was to evaluate this selection strategy. We used clinical data on the effects of inhaled long-acting beta-agonist (LABA) use on the risk of mortality among patients with obstructive pulmonary disease to illustrate the impact of selection of confounding variables for adjustment based on baseline comparisons. Among 2,394 asthma and COPD patients included in the analyses, the LABA ever-users were considerably older than never-users, but cardiovascular co-morbidity was equally prevalent (19.9% vs. 19.9%). Adjustment for cardiovascular co-morbidity status did not affect the crude risk ratio (RR) for mortality: crude RR 1.19 (95% CI 0.93–1.51) versus RR 1.19 (95% CI 0.94–1.50) after adjustment for cardiovascular co-morbidity. However, after adjustment for age (RR 0.95, 95% CI 0.76–1.19), additional adjustment for cardiovascular co-morbidity status did affect the association between LABA use and mortality (RR 1.01, 95% CI 0.80–1.26). Confounding variables should not be discarded based on balanced distributions among exposure groups, because residual confounding due to the omission of confounding variables from the adjustment model can be relevant.
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Affiliation(s)
- Rolf H H Groenwold
- Department of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, The Netherlands,
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