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Article ; Online: Commentary: Mendelian randomization for causal inference.

Moodie, Erica E M / Le Cessie, Saskia

2024

Language	English
Publishing date	2024-04-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	3019-3
ISSN	1537-6613 ; 0022-1899
ISSN (online)	1537-6613
ISSN	0022-1899
DOI	10.1093/infdis/jiae178
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Article ; Online: A Bayesian (meta-)regression model for treatment effects on the risk difference scale.

Thomassen, Doranne / Steyerberg, Ewout / le Cessie, Saskia

Statistics in medicine

2023 Volume 42, Issue 11, Page(s) 1741–1759

Abstract: In clinical settings, the absolute risk reduction due to treatment that can be expected in a particular patient is of key interest. However, logistic regression, the default regression model for trials with a binary outcome, produces estimates of the ... ...

Abstract	In clinical settings, the absolute risk reduction due to treatment that can be expected in a particular patient is of key interest. However, logistic regression, the default regression model for trials with a binary outcome, produces estimates of the effect of treatment measured as a difference in log odds. We explored options to estimate treatment effects directly as a difference in risk, specifically in the network meta-analysis setting. We propose a novel Bayesian (meta-)regression model for binary outcomes on the additive risk scale. The model allows treatment effects, covariate effects, interactions and variance parameters to be estimated directly on the linear scale of clinical interest. We compared effect estimates from this model to (1) a previously proposed additive risk model by Warn, Thompson and Spiegelhalter ("WTS model") and (2) backtransforming the predictions from a logistic model to the natural scale after regression. The models were compared in a network meta-analysis of 20 hepatitis C trials, as well as in the analysis of simulated single trial settings. The resulting estimates diverged, in particular for small sample sizes or true risks close to 0% or 100%. Researchers should be aware that modelling untransformed risk can yield very different results from default logistic models. The treatment effect in participants with such extreme predicted risks weighed more heavily on the overall treatment effect estimate from our proposed model compared to the WTS model. In our network meta-analysis, this sensitivity of our proposed model was needed to detect all information in the data.
MeSH term(s)	Humans ; Bayes Theorem ; Sample Size ; Logistic Models ; Network Meta-Analysis
Language	English
Publishing date	2023-03-06
Publishing country	England
Document type	Meta-Analysis ; Journal Article
ZDB-ID	843037-8
ISSN	1097-0258 ; 0277-6715
ISSN (online)	1097-0258
ISSN	0277-6715
DOI	10.1002/sim.9697
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Article ; Online: Tying research question and analytical strategy when variables are affected by medication use.

Choi, Jungyeon / Dekkers, Olaf M / le Cessie, Saskia

Pharmacoepidemiology and drug safety

2023 Volume 32, Issue 6, Page(s) 661–670

Abstract: Ill-defined research questions could be particularly problematic in an epidemiological setting where measurements fluctuate over time due to intercurrent events, such as medication use. When a research question fails to specify how medication use should ... ...

Abstract	Ill-defined research questions could be particularly problematic in an epidemiological setting where measurements fluctuate over time due to intercurrent events, such as medication use. When a research question fails to specify how medication use should be handled methodologically, arbitrary decisions may be made during the analysis phase, which likely leads to a mismatch between the intended question and the performed analysis. The mismatch can result in vastly different or meaningless interpretations of estimated effects. Thus, a research question such as "what is the effect of X on Y?" requires further elaboration, and it should consider whether and how medication use has affected the measurements of interest. In our study, we will discuss how well-defined questions can be formulated when medication use is involved in observational studies. We will distinguish between a situation where an exposure is affected by medication use and where the outcome of interest is affected by medication use. For each setting, we will give examples of different research questions that could be asked depending on how medication use is considered in the estimand and discuss methodological considerations under each question.
Language	English
Publishing date	2023-02-13
Publishing country	England
Document type	Journal Article
ZDB-ID	1099748-9
ISSN	1099-1557 ; 1053-8569
ISSN (online)	1099-1557
ISSN	1053-8569
DOI	10.1002/pds.5599
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Article ; Online: Effective sample size: A measure of individual uncertainty in predictions.

Thomassen, Doranne / le Cessie, Saskia / van Houwelingen, Hans C / Steyerberg, Ewout W

Statistics in medicine

2024 Volume 43, Issue 7, Page(s) 1384–1396

Abstract: Clinical prediction models are estimated using a sample of limited size from the target population, leading to uncertainty in predictions, even when the model is correctly specified. Generally, not all patient profiles are observed uniformly in model ... ...

Abstract	Clinical prediction models are estimated using a sample of limited size from the target population, leading to uncertainty in predictions, even when the model is correctly specified. Generally, not all patient profiles are observed uniformly in model development. As a result, sampling uncertainty varies between individual patients' predictions. We aimed to develop an intuitive measure of individual prediction uncertainty. The variance of a patient's prediction can be equated to the variance of the sample mean outcome in
MeSH term(s)	Humans ; Uncertainty ; Linear Models ; Sample Size
Language	English
Publishing date	2024-01-31
Publishing country	England
Document type	Journal Article
ZDB-ID	843037-8
ISSN	1097-0258 ; 0277-6715
ISSN (online)	1097-0258
ISSN	0277-6715
DOI	10.1002/sim.10018
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Article ; Online: Influence of initial misdiagnosis on mortality in patients with bacteraemia: propensity score matching and propensity score weighting analyses.

Eikenboom, Anna M / Lambregts, Merel M C / de Boer, Mark G J / le Cessie, Saskia

BMC infectious diseases

2024 Volume 24, Issue 1, Page(s) 389

Abstract: Background: The diagnostic process is a key element of medicine but it is complex and prone to errors. Infectious diseases are one of the three categories of diseases in which diagnostic errors can be most harmful to patients. In this study we aimed to ... ...

Abstract	Background: The diagnostic process is a key element of medicine but it is complex and prone to errors. Infectious diseases are one of the three categories of diseases in which diagnostic errors can be most harmful to patients. In this study we aimed to estimate the effect of initial misdiagnosis of the source of infection in patients with bacteraemia on 14 day mortality using propensity score methods to adjust for confounding. Methods: Data from a previously described longitudinal cohort of patients diagnosed with monobacterial bloodstream infection (BSI) at the Leiden University Medical Centre (LUMC) between 2013 and 2015 were used. Propensity score matching and inversed probability of treatment weighting (IPTW) were applied to correct for confounding. The average treatment effect on the treated (ATT), which in this study was the average effect of initial misdiagnosis on the misdiagnosed (AEMM), was estimated. Methodological issues that were encountered when applying propensity score methods were addressed by performing additional sensitivity analyses. Sensitivity analyses consisted of varying caliper in propensity score matching and using different truncated weights in inversed probability of treatment weighting. Results: Data of 887 patients were included in the study. Propensity scores ranged between 0.015 and 0.999 and 80 patients (9.9%) had a propensity score > 0.95. In the matched analyses, 35 of the 171 misdiagnosed patients died within 14 days (20.5%), versus 10 of the 171 correctly diagnosed patients (5.8%), yielding a difference of 14.6% (7.6%; 21.6%). In the total group of patients, the observed percentage of patients with an incorrect initial diagnosis that died within 14 days was 19.8% while propensity score reweighting estimated that their probability of dying would have been 6.5%, if they had been correctly diagnosed (difference 13.3% (95% CI 6.9%;19.6%)). After adjustment for all variables that showed disbalance in the propensity score a difference of 13.7% (7.4%; 19.9%) was estimated. Sensitivity analyses yielded similar results. However, performing weighted analyses without truncation yielded unstable results. Conclusion: Thus, we observed a substantial increase of 14 day mortality in initially misdiagnosed patients. Furthermore, several patients received propensity scores extremely close to one and were almost sure to be initially misdiagnosed.
MeSH term(s)	Humans ; Propensity Score ; Bacteremia/diagnosis ; Diagnostic Errors
Language	English
Publishing date	2024-04-11
Publishing country	England
Document type	Journal Article
ZDB-ID	2041550-3
ISSN	1471-2334 ; 1471-2334
ISSN (online)	1471-2334
ISSN	1471-2334
DOI	10.1186/s12879-024-09299-9
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Article ; Online: How measurements affected by medication use are reported and handled in observational research: A literature review.

Choi, Jungyeon / Dekkers, Olaf M / le Cessie, Saskia

Pharmacoepidemiology and drug safety

2022 Volume 31, Issue 7, Page(s) 739–748

Abstract: Purpose: In epidemiological research, measurements affected by medication, for example, blood pressure lowered by antihypertensives, are common. Different ways of handling medication are required depending on the research questions and whether the ... ...

Abstract	Purpose: In epidemiological research, measurements affected by medication, for example, blood pressure lowered by antihypertensives, are common. Different ways of handling medication are required depending on the research questions and whether the affected measurement is the exposure, the outcome, or a confounder. This study aimed to review handling of medication use in observational research. Methods: PubMed was searched for etiological studies published between 2015 and 2019 in 15 high-ranked journals from cardiology, diabetes, and epidemiology. We selected studies that analyzed blood pressure, glucose, or lipid measurements (whether exposure, outcome or confounder) by linear or logistic regression. Two reviewers independently recorded how medication use was handled and assessed whether the methods used were in accordance with the research aim. We reported the methods used per variable category (exposure, outcome, confounder). Results: A total of 127 articles were included. Most studies did not perform any method to account for medication use (exposure 58%, outcome 53%, and confounder 45%). Restriction (exposure 22%, outcome 23%, and confounders 10%), or adjusting for medication use using a binary indicator were also used frequently (exposure: 18%, outcome: 19%, confounder: 45%). No advanced methods were applied. In 60% of studies, the methods' validity could not be judged due to ambiguous reporting of the research aim. Invalid approaches were used in 28% of the studies, mostly when the affected variable was the outcome (36%). Conclusion: Many studies ambiguously stated the research aim and used invalid methods to handle medication use. Researchers should consider a valid methodological approach based on their research question.
MeSH term(s)	Causality ; Humans ; Observational Studies as Topic
Language	English
Publishing date	2022-05-04
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	1099748-9
ISSN	1099-1557 ; 1053-8569
ISSN (online)	1099-1557
ISSN	1053-8569
DOI	10.1002/pds.5437
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Article: Cardiac Troponin, Cognitive Function, and Dementia: A Systematic Review.

Zonneveld, Michelle H / Abbel, Denise / le Cessie, Saskia / Jukema, J Wouter / Noordam, Raymond / Trompet, Stella

Aging and disease

2023 Volume 14, Issue 2, Page(s) 386–397

Abstract: Elevated cardiac troponin, a biomarker of myocardial injury, has been found in individuals with brain damage and lower cognitive function. We conducted a systematic review to examine the association of troponin with cognitive function, incidence of ... ...

Abstract	Elevated cardiac troponin, a biomarker of myocardial injury, has been found in individuals with brain damage and lower cognitive function. We conducted a systematic review to examine the association of troponin with cognitive function, incidence of dementia and dementia-related outcomes. PubMed, Web of Science and EMBASE were searched from inception to August 2022. Inclusion criteria were: (i) population-based cohort studies; (ii) troponin measured as determinant; and (iii) cognitive function in any metric or diagnosis of any type of dementia or dementia-related measures as outcomes. Fourteen studies were identified and included, with a combined total of 38,286 participants. Of these studies, four examined dementia-related outcomes, eight studies examined cognitive function, and two studies examined both dementia-related outcomes and cognitive function. Studies report higher troponin to be associated with higher prevalence of cognitive impairment (n=1), incident dementia (n=1), increased risk of dementia hospitalization (specifically due to vascular dementia) (n=1), but not with incident Alzheimer's Disease (n=2). Majority of studies on cognitive function found elevated troponin also associated with worse global cognitive function (n=3), attention (n=2), reaction time (n=1) and visuomotor speed (n=1), both cross-sectionally and prospectively. Evidence regarding the association between higher troponin and memory, executive function, processing speed, language and visuospatial function was mixed. This was the first systematic review on the association between troponin, cognitive function, and dementia. Higher troponin is associated with subclinical cerebrovascular damage and might act as a risk-marker of cognitive vulnerability.
Language	English
Publishing date	2023-04-01
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2625789-0
ISSN	2152-5250
ISSN	2152-5250
DOI	10.14336/AD.2022.0818
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Article ; Online: Real-World Evidence to Inform Regulatory Decision Making: A Scoping Review.

Jansen, Marieke S / Dekkers, Olaf M / le Cessie, Saskia / Hooft, Lotty / Gardarsdottir, Helga / de Boer, Anthonius / Groenwold, Rolf H H

Clinical pharmacology and therapeutics

2024

Abstract: Real-world evidence (RWE) is increasingly considered in regulatory decision making. When, and to which extent, RWE is considered relevant by regulators likely depends on many factors. This review aimed to identify factors that make RWE necessary or ... ...

Abstract	Real-world evidence (RWE) is increasingly considered in regulatory decision making. When, and to which extent, RWE is considered relevant by regulators likely depends on many factors. This review aimed to identify factors that make RWE necessary or desirable to inform regulatory decision making. A scoping review was conducted using literature databases (PubMed, Embase, Emcare, Web of Science, and Cochrane Library) and websites of regulatory agencies, health technology assessment agencies, research institutes, and professional organizations involved with RWE. Articles were included if: (1) they discussed factors or contexts that impact whether RWE could be necessary or desirable in regulatory decision making; (2) focused on pharmacological or biological interventions in humans; and (3) considered decision making in Europe or North America, or without a focus on a specific region. We included 118 articles in the scoping review. Two major themes and six subthemes were identified. The first theme concerns questions addressable with RWE, with subthemes epidemiology and benefit-risk assessment. The second theme concerns contextual factors, with subthemes feasibility, ethical considerations, limitations of available evidence, and disease and treatment-specific aspects. Collectively, these themes encompassed 43 factors influencing the need for RWE in regulatory decisions. Although single factors may not make RWE fully necessary, their cumulative influence could make RWE essential and pivotal in regulatory decision making. This overview contributes to ongoing discussions emphasizing the nuanced interplay of factors influencing the necessity or desirability of RWE to inform regulatory decision making.
Language	English
Publishing date	2024-02-23
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	123793-7
ISSN	1532-6535 ; 0009-9236
ISSN (online)	1532-6535
ISSN	0009-9236
DOI	10.1002/cpt.3218
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Article ; Online: Bias Formulas for Estimating Direct and Indirect Effects When Unmeasured Confounding Is Present.

le Cessie, Saskia

Epidemiology (Cambridge, Mass.)

2016 Volume 27, Issue 1, Page(s) 125–132

Abstract: Mediation analysis examines the influence of intermediate factors in the causal pathway between an exposure and an outcome. It yields estimates of the direct effect of the exposure on the outcome and of the indirect effect through the intermediate ... ...

Abstract	Mediation analysis examines the influence of intermediate factors in the causal pathway between an exposure and an outcome. It yields estimates of the direct effect of the exposure on the outcome and of the indirect effect through the intermediate variable. Both estimates can be biased if the relationship between the mediator and the outcome is confounded. In this article, we study the effect of unmeasured confounding on direct and indirect effect estimates for a continuous mediator and an outcome that may be either binary, count, or continuous. We formulate the effect of the confounder on the intermediate and on the outcome directly in regression models, which makes the formulas intuitive to use by applied users. The formulas are derived under the assumption that the confounder follows a normal distribution. In simulations, the formulas for a linear response model performed well, also as it did when the unmeasured confounder was binary. For a rare binary outcome, the formulas for logistic regression performed well if the unmeasured confounder followed a normal distribution, but for a binary confounder the bias in the direct effect was overcorrected. We applied the formulas to data from a case-control study (Leiden Thrombophilia Study) on risk factors for venous thrombosis. This showed that unmeasured confounding can severely bias the estimates of direct and indirect effects.
MeSH term(s)	Bias ; Computer Simulation ; Confounding Factors (Epidemiology) ; Data Interpretation, Statistical ; Epidemiologic Research Design ; Humans ; Linear Models ; Logistic Models
Language	English
Publishing date	2016-01
Publishing country	United States
Document type	Journal Article
ZDB-ID	1053263-8
ISSN	1531-5487 ; 1044-3983
ISSN (online)	1531-5487
ISSN	1044-3983
DOI	10.1097/EDE.0000000000000407
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Article ; Online: Who is afraid of non-normal data? Choosing between parametric and non-parametric tests.

le Cessie, Saskia / Goeman, Jelle J / Dekkers, Olaf M

European journal of endocrinology

2020 Volume 182, Issue 2, Page(s) E1–E3

Abstract: When statistically comparing outcomes between two groups, researchers have to decide whether to use parametric methods, such as the t-test, or non-parametric methods, like the Mann-Whitney test. In endocrinology, for example, many studies compare hormone ...

Abstract	When statistically comparing outcomes between two groups, researchers have to decide whether to use parametric methods, such as the t-test, or non-parametric methods, like the Mann-Whitney test. In endocrinology, for example, many studies compare hormone levels between groups, or at different points in time. Many papers apply non-parametric tests to compare groups. We will explain that non-parametric tests have clear drawbacks in medical research, and, that's the good news, they are often not necessary.
MeSH term(s)	Data Analysis ; Humans ; Statistics, Nonparametric
Language	English
Publishing date	2020-01-07
Publishing country	England
Document type	Editorial
ZDB-ID	1183856-5
ISSN	1479-683X ; 0804-4643
ISSN (online)	1479-683X
ISSN	0804-4643
DOI	10.1530/EJE-19-0922
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