Publications by authors named "Rolf H H Groenwold"

187 Publications

Is a chest radiograph indicated after chest tube removal in trauma patients? A systematic review.

J Trauma Acute Care Surg 2021 Feb 16. Epub 2021 Feb 16.

Department of Surgery, University Medical Center Utrecht, Utrecht, the Netherlands Department of Surgery, Noordwest Ziekenhuisgroep, Alkmaar, the Netherlands Department of Surgery, University Medical Center Groningen, Groningen, the Netherlands Department of Orthopedics and Trauma Surgery, Luzerner Kantonsspital, Luzern, Switzerland Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

Purpose: The aim of this systematic review was to assess the necessity of routine chest radiographs after chest tube removal in ventilated and non-ventilated trauma patients.

Methods: A systematic literature search was conducted in MEDLINE, EMBASE, CENTRAL and CINAHL on May 15th, 2020. Quality assessment was performed using the MINORS criteria. Primary outcome measures were abnormalities on post-removal chest radiograph (e.g. recurrence of a pneumothorax, hemothorax, pleural effusion) and reintervention after chest tube removal. Secondary outcome measures were emergence of new clinical symptoms or vital signs after chest tube removal.

Results: Fourteen studies were included, consisting of seven studies on non-ventilated patients and seven studies on combined cohorts of ventilated and non-ventilated patients, all together containing 1855 patients. Non-ventilated patients had abnormalities on post-removal chest radiograph in 10% (range across studies 0 - 38%) of all chest tubes and 24% (range 0 - 78%) of those underwent reintervention. In the studies that reported on clinical symptoms after chest tube removal, all patients that underwent reintervention also had symptoms of recurrent pathology. Combined cohorts of ventilated and non-ventilated patients had abnormalities on post-removal chest radiograph in 20% (range 6 - 49%) of all chest tubes and 45% (range 8 - 63%) of those underwent reintervention.

Conclusion: In non-ventilated patients, one in ten developed recurrent pathology after chest tube removal, with almost a quarter of them underwent reintervention. In two studies that reported on clinical symptoms, all reinterventions were performed in patients with symptoms of recurrent pathology. In these two studies, omission of routine post-removal chest radiograph seemed safe. However, current literature remains insufficient to draw definitive conclusions on this matter and future studies are needed.

Level Of Evidence: IV.
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http://dx.doi.org/10.1097/TA.0000000000003118DOI Listing
February 2021

To Adjust or Not to Adjust? When a "Confounder" Is Only Measured After Exposure.

Epidemiology 2021 Mar;32(2):194-201

MRC Integrative Epidemiology Unit, Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

Advice regarding the analysis of observational studies of exposure effects usually is against adjustment for factors that occur after the exposure, as they may be caused by the exposure (or mediate the effect of exposure on outcome), so potentially leading to collider stratification bias. However, such factors could also be caused by unmeasured confounding factors, in which case adjusting for them will also remove some of the bias due to confounding. We derive expressions for collider stratification bias when conditioning and confounding bias when not conditioning on the mediator, in the presence of unmeasured confounding (assuming that all associations are linear and there are no interactions). Using simulations, we show that generally neither the conditioned nor the unconditioned estimate is unbiased, and the trade-off between them depends on the magnitude of the effect of the exposure that is mediated relative to the effect of the unmeasured confounders and their relations with the mediator. We illustrate the use of the bias expressions via three examples: neuroticism and mortality (adjusting for the mediator appears the least biased option), glycated hemoglobin levels and systolic blood pressure (adjusting gives smaller bias), and literacy in primary school pupils (not adjusting gives smaller bias). Our formulae and simulations can inform quantitative bias analysis as well as analysis strategies for observational studies in which there is a potential for unmeasured confounding.
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http://dx.doi.org/10.1097/EDE.0000000000001312DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7850592PMC
March 2021

MIPO versus nailing for humeral shaft fractures: a meta-analysis and systematic review of randomised clinical trials and observational studies.

Eur J Trauma Emerg Surg 2021 Jan 15. Epub 2021 Jan 15.

Department of Orthopaedic and Trauma Surgery, Lucerne Cantonal Hospital, Spitalstrasse 16, 6000, Luzern, Switzerland.

Purpose: There is no consensus on the optimal operative technique for humeral shaft fractures. This meta-analysis aims to compare minimal-invasive plate osteosynthesis (MIPO) with nail fixation for humeral shaft fractures regarding healing, complications and functional results.

Methods: PubMed/Medline/Embase/CENTRAL/CINAHL were searched for randomized clinical trials (RCT) and observational studies comparing MIPO with nailing for humeral shaft fractures. Effect estimates were pooled across studies using random effects models and presented as weighted odds ratio (OR), risk difference (RD), mean difference (MD) and standardized mean difference (SMD) with corresponding 95% confidence interval (95%CI). Analyses were repeated stratified by study design (RCTs and observational studies).

Results: A total of 2 RCTs (87 patients) and 5 observational studies (595 patients) were included. The effects estimated in observational studies and RCTs were similar in direction and magnitude for all outcomes except operation duration. MIPO has a lower risk for non-union (RD 7%; OR 0.2, 95% CI 0.1-0.5) and re-intervention (RD 13%; OR 0.3, 95% CI 0.1-0.8). Functional shoulder (SMD 1.0, 95% CI 0.2-1.8) and elbow scores (SMD 0.4, 95% CI 0-0.8) were better among patients treated with MIPO. The risk for radial nerve palsy following surgery was equal (RD 2%; OR 0.6, 95% CI 0.3-1.2) and nerve function recovered spontaneously in all patients in both groups. No difference was detected with regard to infection, time to union and operation duration.

Conclusion: MIPO has a considerable lower risk for non-union and re-intervention, leads to better shoulder function and, to a lesser extent, better elbow function compared to nailing. Although nailing appears to be a viable option, the evidence suggests that MIPO should be the preferred treatment of choice. The learning curve of minimal-invasive plating should, however, be taken into account when interpreting these results.
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http://dx.doi.org/10.1007/s00068-020-01585-wDOI Listing
January 2021

Multiple testing: when is many too much?

Eur J Endocrinol 2021 Mar;184(3):E11-E14

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

In almost all medical research, more than a single hypothesis is being tested or more than a single relation is being estimated. Testing multiple hypotheses increases the risk of drawing a false-positive conclusion. We briefly discuss this phenomenon, which is often called multiple testing. Also, methods to mitigate the risk of false-positive conclusions are discussed.
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http://dx.doi.org/10.1530/EJE-20-1375DOI Listing
March 2021

Text-mining in electronic healthcare records can be used as efficient tool for screening and data collection in cardiovascular trials: a multicenter validation study.

J Clin Epidemiol 2020 Nov 25;132:97-105. Epub 2020 Nov 25.

Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; Department of Cardiology, Meander Medical Center, Amersfoort, the Netherlands; Dutch Network for Cardiovascular Research (WCN), Utrecht, the Netherlands.

Objective: This study aimed to validate trial patient eligibility screening and baseline data collection using text-mining in electronic healthcare records (EHRs), comparing the results to those of an international trial.

Study Design And Setting: In three medical centers with different EHR vendors, EHR-based text-mining was used to automatically screen patients for trial eligibility and extract baseline data on nineteen characteristics. First, the yield of screening with automated EHR text-mining search was compared with manual screening by research personnel. Second, the accuracy of extracted baseline data by EHR text mining was compared to manual data entry by research personnel.

Results: Of the 92,466 patients visiting the out-patient cardiology departments, 568 (0.6%) were enrolled in the trial during its recruitment period using manual screening methods. Automated EHR data screening of all patients showed that the number of patients needed to screen could be reduced by 73,863 (79.9%). The remaining 18,603 (20.1%) contained 458 of the actual participants (82.4% of participants). In trial participants, automated EHR text-mining missed a median of 2.8% (Interquartile range [IQR] across all variables 0.4-8.5%) of all data points compared to manually collected data. The overall accuracy of automatically extracted data was 88.0% (IQR 84.7-92.8%).

Conclusion: Automatically extracting data from EHRs using text-mining can be used to identify trial participants and to collect baseline information.
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http://dx.doi.org/10.1016/j.jclinepi.2020.11.014DOI Listing
November 2020

Approaches to addressing missing values, measurement error, and confounding in epidemiologic studies.

J Clin Epidemiol 2020 Nov 8;131:89-100. Epub 2020 Nov 8.

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.

Objectives: Epidemiologic studies often suffer from incomplete data, measurement error (or misclassification), and confounding. Each of these can cause bias and imprecision in estimates of exposure-outcome relations. We describe and compare statistical approaches that aim to control all three sources of bias simultaneously.

Study Design And Setting: We illustrate four statistical approaches that address all three sources of bias, namely, multiple imputation for missing data and measurement error, multiple imputation combined with regression calibration, full information maximum likelihood within a structural equation modeling framework, and a Bayesian model. In a simulation study, we assess the performance of the four approaches compared with more commonly used approaches that do not account for measurement error, missing values, or confounding.

Results: The results demonstrate that the four approaches consistently outperform the alternative approaches on all performance metrics (bias, mean squared error, and confidence interval coverage). Even in simulated data of 100 subjects, these approaches perform well.

Conclusion: There can be a large benefit of addressing measurement error, missing values, and confounding to improve the estimation of exposure-outcome relations, even when the available sample size is relatively small.
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http://dx.doi.org/10.1016/j.jclinepi.2020.11.006DOI Listing
November 2020

Response to Letter on immunoassay measurement errors.

Eur J Endocrinol 2021 02;184(2):L3-L4

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

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http://dx.doi.org/10.1530/EJE-20-1183DOI Listing
February 2021

When observational studies can give wrong answers: the potential of immortal time bias.

Eur J Endocrinol 2021 Jan;184(1):E1-E4

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

Immortal time bias should always be considered in an observational study if exposure status is determined based on a measurement or event that occurs after baseline. This bias can lead to an overestimation of an effect, but also to an underestimation, which is explained. Several approaches are illustrated that can be used to avoid immortal time bias in the analysis phase of the study; a time-dependent analysis to avoid immortal time bias optimizes the use of available information.
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http://dx.doi.org/10.1530/EJE-20-1124DOI Listing
January 2021

Study design: what's in a name?

Eur J Endocrinol 2020 Dec;183(6):E11-E13

Departments of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

The name of the study should properly reflect the actual conduct and analysis of the study. This short paper provides guidance on how to properly name the study design. The first distinction is between a trial (intervention given to patients to study its effect) and an observational study. For observational studies, it should further be decided whether it is cross-sectional or whether follow-up time is taken into account (cohort or case-control study). The distinction prospective-retrospective has two disadvantages: prospective is often seen as marker of higher quality, which is not necessarily true; there is no unifying definition that makes a proper distinction between retrospective and prospective possible.
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http://dx.doi.org/10.1530/EJE-20-0873DOI Listing
December 2020

Global changes in mortality rates in polytrauma patients admitted to the ICU-a systematic review.

World J Emerg Surg 2020 Sep 30;15(1):55. Epub 2020 Sep 30.

Department of Trauma Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3585 GA, Utrecht, The Netherlands.

Background: Many factors of trauma care have changed in the last decades. This review investigated the effect of these changes on global all-cause and cause-specific mortality in polytrauma patients admitted to the intensive care unit (ICU). Moreover, changes in trauma mechanism over time and differences between continents were analyzed.

Main Body: A systematic review of literature on all-cause mortality in polytrauma patients admitted to ICU was conducted. All-cause and cause-specific mortality rates were extracted as well as trauma mechanism of each patient. Poisson regression analysis was used to model time trends in all-cause and cause-specific mortality. Thirty studies, which reported mortality rates for 82,272 patients, were included and showed a decrease of 1.8% (95% CI 1.6-2.0%) in all-cause mortality per year since 1966. The relative contribution of brain injury-related death has increased over the years, whereas the relative contribution of death due to multiple organ dysfunction syndrome (MODS), acute respiratory distress syndrome, and sepsis decreased. MODS was the most common cause of death in North America, and brain-related death was the most common in Asia, South America, and Europe. Penetrating trauma was most often reported in North America and Asia.

Conclusions: All-cause mortality in polytrauma patients admitted to the ICU has decreased over the last decades. A shift from MODS to brain-related death was observed. Geographical differences in cause-specific mortality were present, which may provide region-specific learning possibilities resulting in improvement of global trauma care.
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http://dx.doi.org/10.1186/s13017-020-00330-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7526208PMC
September 2020

Quantitative Bias Analysis for a Misclassified Confounder: A Comparison Between Marginal Structural Models and Conditional Models for Point Treatments.

Epidemiology 2020 11;31(6):796-805

Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Observational data are increasingly used with the aim of estimating causal effects of treatments, through careful control for confounding. Marginal structural models estimated using inverse probability weighting (MSMs-IPW), like other methods to control for confounding, assume that confounding variables are measured without error. The average treatment effect in an MSM-IPW may however be biased when a confounding variable is error prone. Using the potential outcome framework, we derive expressions for the bias due to confounder misclassification in analyses that aim to estimate the average treatment effect using an marginal structural model estimated using inverse probability weighting (MSM-IPW). We compare this bias with the bias due to confounder misclassification in analyses based on a conditional regression model. Focus is on a point-treatment study with a continuous outcome. Compared with bias in the average treatment effect in a conditional model, the bias in an MSM-IPW can be different in magnitude but is equal in sign. Also, we use a simulation study to investigate the finite sample performance of MSM-IPW and conditional models when a confounding variable is misclassified. Simulation results indicate that confidence intervals of the treatment effect obtained from MSM-IPW are generally wider, and coverage of the true treatment effect is higher compared with a conditional model, ranging from overcoverage if there is no confounder misclassification to undercoverage when there is confounder misclassification. Further, we illustrate in a study of blood pressure-lowering therapy, how the bias expressions can be used to inform a quantitative bias analysis to study the impact of confounder misclassification, supported by an online tool.
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http://dx.doi.org/10.1097/EDE.0000000000001239DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523582PMC
November 2020

Assessment of the Regulatory Dialogue Between Pharmaceutical Companies and the European Medicines Agency on the Choice of Noninferiority Margins.

Clin Ther 2020 08 8;42(8):1588-1594. Epub 2020 Aug 8.

Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands. Electronic address:

Choosing a noninferiority margin is one of the main challenges when designing a noninferiority trial. The European Medicines Agency (EMA) published a guidance report on the choice of margins in 2005. Nonetheless, in 2008 and 2009 they did not accept 41% (35 of 86) of the noninferiority margins that were proposed by pharmaceutical companies in the context of scientific-advice letters. In this study, we focus on whether the EMA's recommendations were followed by pharmaceutical companies, and on a possible relationship with eventual drug approval. Five of the 35 unaccepted margins were equivalence margins; we considered only the 30 unaccepted noninferiority margins in our analysis. Twelve of these margins were defined based on clinical and statistical considerations (the approach recommended by the EMA) and were rejected due to unacceptable clinical considerations. The other 18 margins were rejected because they were considered too wide. The EMA's recommendations were followed in the cases of 10 of the 15 margins (67%) for which information on follow-through of recommendations was available. The main reason for ignoring the EMA's recommendation in the other 5 cases was that the margins had been accepted by the US Food and Drug Administration. The proportions of approved drugs for which recommendations were and were not followed were similar, yet numbers were too low for formal statistical testing. This study shows that the main concern of regulators with regard to noninferiority trials was the strictness of margins from a clinical perspective. Future studies using more recent data, including data on the US Food and Drug Administration, may help in assessing the impact of guideline recommendations on noninferiority margins used for drug approval and may assist in reaching consensus among regulators about the choice of margins.
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http://dx.doi.org/10.1016/j.clinthera.2020.06.004DOI Listing
August 2020

Informative missingness in electronic health record systems: the curse of knowing.

Diagn Progn Res 2020 2;4. Epub 2020 Jul 2.

Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, the Netherlands.

Electronic health records provide a potentially valuable data source of information for developing clinical prediction models. However, missing data are common in routinely collected health data and often missingness is informative. Informative missingness can be incorporated in a clinical prediction model, for example by including a separate category of a predictor variable that has missing values. The predictive performance of such a model depends on the transportability of the missing data mechanism, which may be compromised once the model is deployed in practice and the predictive value of certain variables becomes known. Using synthetic data, this phenomenon is explained and illustrated.
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http://dx.doi.org/10.1186/s41512-020-00077-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371469PMC
July 2020

Missing data: the impact of what is not there.

Eur J Endocrinol 2020 Oct;183(4):E7-E9

Departments of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

The validity of clinical research is potentially threatened by missing data. Any variable measured in a study can have missing values, including the exposure, the outcome, and confounders. When missing values are ignored in the analysis, only those subjects with complete records will be included in the analysis. This may lead to biased results and loss of power. We explain why missing data may lead to bias and discuss a commonly used classification of missing data.
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http://dx.doi.org/10.1530/EJE-20-0732DOI Listing
October 2020

Commentary: Quantifying the unknown unknowns.

Int J Epidemiol 2020 Oct;49(5):1503-1505

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.

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http://dx.doi.org/10.1093/ije/dyaa092DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746407PMC
October 2020

A cautionary note on the use of the missing indicator method for handling missing data in prediction research.

J Clin Epidemiol 2020 09 19;125:188-190. Epub 2020 Jun 19.

Julius Center for Health Science and Primary Care, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands.

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http://dx.doi.org/10.1016/j.jclinepi.2020.06.007DOI Listing
September 2020

Traumatic rib fractures: a marker of severe injury. A nationwide study using the National Trauma Data Bank.

Trauma Surg Acute Care Open 2020 10;5(1):e000441. Epub 2020 Jun 10.

Department of Orthopaedic Surgery, Harvard Medical School Orthopedic Trauma Initiative, Massachusetts General Hospital, Boston, Massachusetts, USA.

Background: In recent years, there has been increasing interest in the treatment of patients with rib fractures. However, the current literature on the epidemiology and outcomes of rib fractures is outdated and inconsistent. Furthermore, although it has been suggested that there is a large heterogeneity among patients with traumatic rib fractures, there is insufficient literature reporting on the outcomes of different subgroups.

Methods: A retrospective cohort study using the National Trauma Data Bank was performed. All adult patients with one or more traumatic rib fractures or flail chest who were admitted to a hospital between January 2010 and December 2016 were identified by the International Classification of Diseases Ninth Revision diagnostic codes.

Results: Of the 564 798 included patients with one or more rib fractures, 44.9% (n=2 53 564) were patients with polytrauma. Two per cent had open rib fractures (n=11 433, 2.0%) and flail chest was found in 4% (n=23 388, 4.1%) of all cases. Motor vehicle accidents (n=237 995, 51.6%) were the most common cause of rib fractures in patients with polytrauma and flail chest. Blunt chest injury accounted for 95.5% (n=5 39 422) of rib fractures. Rib fractures in elderly patients were predominantly caused by high and low energy falls (n=67 675, 51.9%). Ultimately, 49.5% (n=2 79 615) of all patients were admitted to an intensive care unit, of whom a quarter (n=146 191, 25.9%) required invasive mechanical ventilatory support. The overall mortality rate was 5.6% (n=31 524).

Discussion: Traumatic rib fractures are a marker of severe injury as approximately half of patients were patients with polytrauma. Furthermore, patients with rib fractures are a very heterogeneous group with a considerable difference in epidemiology, injury characteristics and in-hospital outcomes. Worse outcomes were predominantly observed among patients with polytrauma and flail chest. Future studies should recognize these differences and treatment should be evaluated accordingly.

Level Of Evidence: II/III.
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http://dx.doi.org/10.1136/tsaco-2020-000441DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7292040PMC
June 2020

Measurement error in clinical research, yes it matters.

Eur J Endocrinol 2020 Sep;183(3):E3-E5

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

The validity of any biomedical study is potentially affected by measurement error or misclassification. It can affect different variables included in a statistical analysis, such as the exposure, the outcome, and confounders, and can result in an overestimation as well as in an underestimation of the relation under investigation. We discuss various aspects of measurement error and argue that often an in-depth discussion is needed to appropriately assess the quality and validity of a study.
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http://dx.doi.org/10.1530/EJE-20-0550DOI Listing
September 2020

Rivaroxaban was found to be noninferior to warfarin in routine clinical care: A retrospective noninferiority cohort replication study.

Pharmacoepidemiol Drug Saf 2020 10 14;29(10):1263-1272. Epub 2020 Jun 14.

Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands.

Purpose: To compare the effectiveness and safety of a drug in daily practice with the outcomes of a target non-inferiority trial by rigorously mimickingin an observational study the trial's design features.

Methods: This cohort study was conducted using the British Clinical Practice Research Datalink (CPRD) to emulate the ROCKET AF (Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation) trial. Patients with atrial fibrillation who were newly prescribed (>=12 months of no use) either rivaroxaban or warfarinfrom October 2008 to December 2017 were included. Non-inferiority of rivaroxaban to warfarin in the prevention of stroke or systemic embolism was assessed in different analysis populations (intention-to-treat [ITT], per-protocol [PP], and as-treated populations) using a hazardratio (HR) of 1.46 as the non-inferiority margin. Major bleeding (safety outcome) was also assessed and compared to that of the target trial. All outcomes were analyzed using Cox-proportional hazard analyses.

Results: We included 25,473 incident users of rivaroxaban (n=4,008) or warfarin(n=21,465). Similar to the trial, non-inferiority in the primary out come was demonstrated in all three analysis populations: HR=1.04 (95%CI 0.84 to 1.30) (ITT), HR=0.98 (95%CI 0.70 to 1.38) (PP), and HR=1.11 (95%CI 0.86 to 1.42) (as-treated). Risk of major bleeding was also similar to the target trial.

Conclusion: The results of this study provide supportive evidence to the effectiveness of rivaroxaban and adds knowledge on the usefulness of emulating a non-inferiority trial to assess drug effectiveness.
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http://dx.doi.org/10.1002/pds.5065DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7687233PMC
October 2020

Epidemiology and outcome of rib fractures: a nationwide study in the Netherlands.

Eur J Trauma Emerg Surg 2020 Jun 6. Epub 2020 Jun 6.

Department of Surgery, University Medical Center Utrecht, PO Box 85500, 3508 GA, Utrecht, The Netherlands.

Purpose: Rib fractures following thoracic trauma are frequently encountered injuries and associated with a significant morbidity and mortality. The aim of this study was to provide current data on the epidemiology, in-hospital outcomes and 30-day mortality of rib fractures, and to evaluate these results for different subgroups.

Methods: A nationwide retrospective cohort study was performed with the use of the Dutch Trauma Registry which covers 99% of the acutely admitted Dutch trauma population. All patients aged 18 years and older admitted to the hospital between January 2015 and December 2017 with one or more rib fractures were included. Incidence rates were calculated using demographic data from the Dutch Population Register. Subgroup analyses were performed for flail chest, polytrauma, primary thoracic trauma, and elderly patients.

Results: A total of 14,850 patients were admitted between 2015 and 2017 with one or more rib fractures, which was 6.0% of all trauma patients. Of these, 573 (3.9%) patients had a flail chest, 4438 (29.9%) were polytrauma patients, 9273 (63.4%) were patients with primary thoracic trauma, and 6663 (44.9%) were elderly patients. The incidence rate of patients with rib fractures for the entire cohort was 29 per 100.000 person-years. The overall 30-day mortality was 6.9% (n = 1208) with higher rates observed in flail chest (11.9%), polytrauma (14.8%), and elderly patients (11.7%). The median hospital length of stay was 6 days (IQR, 3-11) and 37.3% were admitted to the intensive care unit (ICU).

Conclusions: Rib fractures are a relevant and frequently occurring problem among the trauma population. Subgroup analyses showed that there is a substantial heterogeneity among patients with rib fractures with considerable differences regarding the epidemiology, in-hospital outcomes, and 30-day mortality.
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http://dx.doi.org/10.1007/s00068-020-01412-2DOI Listing
June 2020

Prediction meets causal inference: the role of treatment in clinical prediction models.

Eur J Epidemiol 2020 Jul 22;35(7):619-630. Epub 2020 May 22.

Department of Biomedical Data Sciences, Leiden University Medical Center, Zone S5-P, PO Box 9600, 2300 RC, Leiden, The Netherlands.

In this paper we study approaches for dealing with treatment when developing a clinical prediction model. Analogous to the estimand framework recently proposed by the European Medicines Agency for clinical trials, we propose a 'predictimand' framework of different questions that may be of interest when predicting risk in relation to treatment started after baseline. We provide a formal definition of the estimands matching these questions, give examples of settings in which each is useful and discuss appropriate estimators including their assumptions. We illustrate the impact of the predictimand choice in a dataset of patients with end-stage kidney disease. We argue that clearly defining the estimand is equally important in prediction research as in causal inference.
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http://dx.doi.org/10.1007/s10654-020-00636-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7387325PMC
July 2020

Operative vs Nonoperative Treatment of Distal Radius Fractures in Adults: A Systematic Review and Meta-analysis.

JAMA Netw Open 2020 04 1;3(4):e203497. Epub 2020 Apr 1.

Department of Orthopedic Surgery, Harvard Medical School Orthopedic Trauma Initiative, Massachusetts General Hospital, Boston.

Importance: No consensus has been reached to date regarding the optimal treatment for distal radius fractures. The international rate of operative treatment has been increasing, despite higher costs and limited functional outcome evidence to support this shift.

Objectives: To compare functional, clinical, and radiologic outcomes after operative vs nonoperative treatment of distal radius fractures in adults.

Data Sources: The PubMed/MEDLINE, Embase, CENTRAL (Cochrane Central Register of Controlled Trials), and CINAHL (Cumulative Index to Nursing and Allied Health Literature) databases were searched from inception to June 15, 2019, for studies comparing operative vs nonoperative treatment of distal radius fractures.

Study Selection: Randomized clinical trials (RCTs) and observational studies reporting on the following: acute distal radius fracture with operative treatment (internal or external fixation) vs nonoperative treatment (cast immobilization, splinting, or bracing); patients 18 years or older; and functional outcome. Studies in a language other than English or reporting treatment for refracture were excluded.

Data Extraction And Synthesis: Data extraction was performed independently by 2 reviewers. Effect estimates were pooled using random-effects models and presented as risk ratios (RRs) or mean differences (MDs) with 95% CIs. Data were analyzed in September 2019.

Main Outcomes And Measures: The primary outcome measures included medium-term functional outcome measured with the Disabilities of the Arm, Shoulder and Hand questionnaire (DASH) and the overall complication rate after operative and nonoperative treatment.

Results: A total of 23 unique studies were included, consisting of 8 RCTs and 15 observational studies, that described 2254 unique patients. Among the studies that presented sex data, 1769 patients were women [80.6%]. Overall weighted mean age was 67 [range, 22-90] years). The RCTs included 656 patients (29.1%); observational studies, 1598 patients (70.9%). The overall pooled effect estimates the showed a significant improvement in medium-term (≤1 year) DASH score after operative treatment compared with nonoperative treatment (MD, -5.22 [95% CI, -8.87 to -1.57]; P = .005; I2 = 84%). No difference in complication rate was observed (RR, 1.03 [95% CI, 0.69-1.55]; P = .87; I2 = 62%). A significant improvement in grip strength was noted after operative treatment, measured in kilograms (MD, 2.73 [95% CI, 0.15-5.32]; P = .04; I2 = 79%) and as a percentage of the unaffected side (MD, 8.21 [95% CI, 2.26-14.15]; P = .007; I2 = 76%). No improvement in medium-term DASH score was found in the subgroup of studies that only included patients 60 years or older (MD, -0.98 [95% CI, -3.52 to 1.57]; P = .45; I2 = 34%]), compared with a larger improvement in medium-term DASH score after operative treatment in the other studies that included patients 18 years or older (MD, -7.50 [95% CI, -12.40 to -2.60]; P = .003; I2 = 77%); the difference between these subgroups was statically significant (test for subgroup differences, P = .02).

Conclusions And Relevance: This meta-analysis suggests that operative treatment of distal radius fractures improves the medium-term DASH score and grip strength compared with nonoperative treatment in adults, with no difference in overall complication rate. The findings suggest that operative treatment might be more effective and have a greater effect on the health and well-being of younger, nonelderly patients.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.3497DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180423PMC
April 2020

Confounding adjustment performance of ordinal analysis methods in stroke studies.

PLoS One 2020 16;15(4):e0231670. Epub 2020 Apr 16.

Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands.

Background: In stroke studies, ordinal logistic regression (OLR) is often used to analyze outcome on the modified Rankin Scale (mRS), whereas the non-parametric Mann-Whitney measure of superiority (MWS) has also been suggested. It is unclear how these perform comparatively when confounding adjustment is warranted.

Aims: Our aim is to quantify the performance of OLR and MWS in different confounding variable settings.

Methods: We set up a simulation study with three different scenarios; (1) dichotomous confounding variables, (2) continuous confounding variables, and (3) confounding variable settings mimicking a study on functional outcome after stroke. We compared adjusted ordinal logistic regression (aOLR) and stratified Mann-Whitney measure of superiority (sMWS), and also used propensity scores to stratify the MWS (psMWS). For comparability, OLR estimates were transformed to a MWS. We report bias, the percentage of runs that produced a point estimate deviating by more than 0.05 points (point estimate variation), and the coverage probability.

Results: In scenario 1, there was no bias in both sMWS and aOLR, with similar point estimate variation and coverage probabilities. In scenario 2, sMWS resulted in more bias (0.04 versus 0.00), and higher point estimate variation (41.6% versus 3.3%), whereas coverage probabilities were similar. In scenario 3, there was no bias in both methods, point estimate variation was higher in the sMWS (6.7%) versus aOLR (1.1%), and coverage probabilities were 0.98 (sMWS) versus 0.95 (aOLR). With psMWS, bias remained 0.00, with less point estimate variation (1.5%) and a coverage probability of 0.95.

Conclusions: The bias of both adjustment methods was similar in our stroke simulation scenario, and the higher point estimate variation in the MWS improved with propensity score based stratification. The stratified MWS is a valid alternative for adjusted OLR only when the ratio of number of strata versus number of observations is relatively low, but propensity score based stratification extends the application range of the MWS.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0231670PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7162480PMC
July 2020

Complications and outcome after rib fracture fixation: A systematic review.

J Trauma Acute Care Surg 2020 08;89(2):411-418

From the Department of Surgery (J.P.), University Medical Center Utrecht, Utrecht, The Netherlands; Department of Orthopaedic Surgery (J.P.), Harvard Medical School Orthopedic Trauma Initiative, Massachusetts General Hospital, Boston, Massachusetts; Department of Surgery, University Medical Center Utrecht (R.B.B., F.H.), Utrecht, The Netherlands; Department of Orthopaedic Surgery (M.H.), Harvard Medical School Orthopedic Trauma Initiative, Massachusetts General Hospital, Boston, Massachusetts; Department of Surgery (M.B.D.J.), University Medical Center Utrecht, Utrecht, The Netherlands; Department of Orthopedic and Trauma Surgery (F.J.P.B.), Cantonal Hospital Lucerne, Lucerne, Switzerland; Department of Surgery (L.P.H.L.), University Medical Center Utrecht, Utrecht; Department of Clinical Epidemiology (R.H.H.G.), Leiden University Medical Center, Leiden; and Department of Surgery (R.M.H.), University Medical Center Utrecht, Utrecht, The Netherlands.

Background: In recent years, there has been a growing interest in operative treatment for multiple rib fractures and flail chest. However, to date, there is no comprehensive study that extensively focused on the incidence of complications associated with rib fracture fixation. Furthermore, there is insufficient knowledge about the short- and long-term outcomes after rib fracture fixation.

Methods: This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. The MEDLINE, EMBASE, and Cochrane databases were searched to identify studies reporting on complications and/or outcome of surgical treatment after rib fractures. Complications were subdivided into (1) surgery- and implant-related complications, (2) bone-healing complications, (3) pulmonary complications, and (4) mortality.

Results: Forty-eight studies were included, with information about 1,952 patients who received rib fracture fixation because of flail chest or multiple rib fractures. The overall risk of surgery- and implant-related complications was 10.3%, with wound infection in 2.2% and fracture-related infection in 1.3% of patients. Symptomatic nonunion was a relatively uncommon complication after rib fixation (1.3%). Pulmonary complications were found in 30.9% of patients, and the overall mortality was 2.9%, of which one third appeared to be the result of the thoracic injuries and none directly related to the surgical procedure. The most frequently used questionnaire to assess patient quality of life was the EuroQol-5D (EQ-5D) (n = 4). Four studies reporting on the EQ-5D had a weighted mean EQ-5D index of 0.80 indicating good quality of life after rib fracture fixation.

Conclusion: Surgical fixation can be considered as a safe procedure with a considerably low complication risk and satisfactory long-term outcomes, with surgery- and implant-related complications in approximately 10% of the patients. However, the clinically most relevant complications such as infections occur infrequently, and the number of complications requiring immediate (surgical) treatment is low.

Level Of Evidence: Systematic Review, level III.
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http://dx.doi.org/10.1097/TA.0000000000002716DOI Listing
August 2020

Re. Selecting Optimal Subgroups for Treatment Using Many Covariates.

Epidemiology 2020 07;31(4):e33-e34

Department of Statistics, University of Washington, Seattle, Washington, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington.

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http://dx.doi.org/10.1097/EDE.0000000000001189DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7269795PMC
July 2020

Conservative vs. operative treatment for humeral shaft fractures: a meta-analysis and systematic review of randomized clinical trials and observational studies.

J Shoulder Elbow Surg 2020 Jul 3;29(7):1493-1504. Epub 2020 Apr 3.

Department of Trauma Surgery, University Medical Center Utrecht, Utrecht, The Netherlands.

Background: This meta-analysis aimed to compare conservative vs. operative treatment for humeral shaft fractures in terms of the nonunion rate, reintervention rate, permanent radial nerve palsy rate, and functional outcomes. Secondarily, effect estimates from observational studies were compared with estimates of randomized clinical trials (RCTs).

Methods: The PubMed/Medline, Embase, CENTRAL (Cochrane Central Register of Controlled Trials), and CINAHL (Cumulative Index to Nursing and Allied Health Literature) databases were searched for both RCTs and observational studies comparing conservative with operative treatment for humeral shaft fractures.

Results: A total of 2 RCTs (150 patients) and 10 observational studies (1262 patients) were included. The pooled nonunion rate of all studies was higher in patients treated conservatively (15.3%) vs. operatively (6.4%) (risk difference, 8%; odds ratio [OR], 2.9; 95% confidence interval [CI], 1.8-4.5; I = 0%). The reintervention rate was also higher for conservative treatment (14.3%) than for operative treatment (8.9%) (risk difference, 6%; OR, 1.9; 95% CI, 1.1-3.5; I = 30%). The higher reintervention rate was predominantly attributable to the higher nonunion rate in patients treated conservatively. The permanent radial nerve palsy rate was equal in both groups (OR, 0.6; 95% CI, 0.2-1.9; I = 18%). There appeared to be no difference in mean time to union and mean Disabilities of the Arm, Shoulder and Hand scores between the treatment groups. No difference was found between effect estimates form observational studies and RCTs.

Conclusion: This systematic review shows that satisfactory results can be achieved with both conservative and operative management; however, operative treatment reduces the risk of nonunion compared with conservative treatment, with comparable reintervention rates (for indications other than nonunion). Furthermore, operative treatment results in a similar permanent radial nerve palsy rate, despite its inherent additional surgery-related risks. No difference in mean time-to-union and short-term functional results was detected.
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http://dx.doi.org/10.1016/j.jse.2020.01.072DOI Listing
July 2020

METHODOLOGY FOR THE ENDOCRINOLOGIST: Basic aspects of confounding adjustment.

Eur J Endocrinol 2020 May;182(5):E5-E7

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.

The results of observational studies of causal effects are potentially biased due to confounding. Various methods have been proposed to control for confounding in observational studies. Eight basic aspects of confounding adjustment are described, with a focus on correction for confounding through covariate adjustment using regression analysis. These aspects should be considered when planning an observational study of causal effects or when assessing the validity of the results of such a study.
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http://dx.doi.org/10.1530/EJE-20-0075DOI Listing
May 2020

Title, abstract, and keyword searching resulted in poor recovery of articles in systematic reviews of epidemiologic practice.

J Clin Epidemiol 2020 05 23;121:55-61. Epub 2020 Jan 23.

Department of Clinical Epidemiology, Leiden University Medical Center, PO Box 9600, 2300 RC, the Netherlands; Department of Biomedical Data Sciences, Leiden University Medical Center, PO Box 9600, 2300 RC, the Netherlands.

Objective: Article full texts are often inaccessible via the standard search engines of biomedical literature, such as PubMed and Embase, which are commonly used for systematic reviews. Excluding the full-text bodies from a literature search may result in a small or selective subset of articles being included in the review because of the limited information that is available in only title, abstract, and keywords. This article describes a comparison of search strategies based on a systematic literature review of all articles published in 5 top-ranked epidemiology journals between 2000 and 2017.

Study Design And Setting: Based on a text-mining approach, we studied how nine different methodological topics were mentioned across text fields (title, abstract, keywords, and text body). The following methodological topics were studied: propensity score methods, inverse probability weighting, marginal structural modeling, multiple imputation, Kaplan-Meier estimation, number needed to treat, measurement error, randomized controlled trial, and latent class analysis.

Results: In total, 31,641 Hypertext Markup Language (HTML) files were downloaded from the journals' websites. For all methodological topics and journals, at most 50% of articles with a mention of a topic in the text body also mentioned the topic in the title, abstract, or keywords. For several topics, a gradual decrease over calendar time was observed of reporting in the title, abstract, or keywords.

Conclusion: Literature searches based on title, abstract, and keywords alone may not be sufficiently sensitive for studies of epidemiological research practice. This study also illustrates the potential value of full-text literature searches, provided there is accessibility of full-text bodies for literature searches.
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http://dx.doi.org/10.1016/j.jclinepi.2020.01.009DOI Listing
May 2020

Reflection on modern methods: five myths about measurement error in epidemiological research.

Int J Epidemiol 2020 02;49(1):338-347

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.

Epidemiologists are often confronted with datasets to analyse which contain measurement error due to, for instance, mistaken data entries, inaccurate recordings and measurement instrument or procedural errors. If the effect of measurement error is misjudged, the data analyses are hampered and the validity of the study's inferences may be affected. In this paper, we describe five myths that contribute to misjudgments about measurement error, regarding expected structure, impact and solutions to mitigate the problems resulting from mismeasurements. The aim is to clarify these measurement error misconceptions. We show that the influence of measurement error in an epidemiological data analysis can play out in ways that go beyond simple heuristics, such as heuristics about whether or not to expect attenuation of the effect estimates. Whereas we encourage epidemiologists to deliberate about the structure and potential impact of measurement error in their analyses, we also recommend exercising restraint when making claims about the magnitude or even direction of effect of measurement error if not accompanied by statistical measurement error corrections or quantitative bias analysis. Suggestions for alleviating the problems or investigating the structure and magnitude of measurement error are given.
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http://dx.doi.org/10.1093/ije/dyz251DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7124512PMC
February 2020