Randomized clinical trials in dentistry: Risks of bias, risks of random errors, reporting quality, and methodologic quality over the years 1955–2013

Saltaji, Humam; Armijo‐Olivo, Susan; Cummings, Greta G.; Amin, Maryam; Flores-Mir, Carlos

doi:10.1371/journal.pone.0190089

Cited by 36 publications

(27 citation statements)

References 69 publications

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“…At the current rate of improvement, it would take 50 years for 95% of RCTs to be adequately reported. These results are consistent with previous research finding improvements in reporting in several clinical areas such as physiotherapy10 and dentistry 26. The trends for each dimension assessed separately are also very similar to those found in another large sample of RCTs 25…”

Section: Discussionsupporting

confidence: 91%

“…Previous scientific work aiming to evaluate the reliability of biomedical research has been limited by data and methodological issues. Data challenges included the time and resources necessary to assess methods and reporting, resulting in the use of small selected samples and/or limited information available for each scientific article evaluated in larger samples 9–28. As a result, it remains unknown what is the overall magnitude of waste due to inadequate methods and reporting in biomedical research and what factors are associated with the use of adequate vs inadequate research methods.…”

Section: Introductionmentioning

confidence: 99%

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Trends and predictors of biomedical research quality, 1990–2015: a meta-research study

Catillon

2019

BMJ Open

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ObjectiveTo measure the frequency of adequate methods, inadequate methods and poor reporting in published randomised controlled trials (RCTs) and test potential factors associated with adequacy of methods and reporting.DesignRetrospective analysis of RCTs included in Cochrane reviews. Time series describes the proportion of RCTs using adequate methods, inadequate methods and poor reporting. A multinomial logit model tests potential factors associated with methods and reporting, including funding source, first author affiliation, clinical trial registration status, study novelty, team characteristics, technology and geography.DataRisk of bias assessments for random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data and selective reporting, for each RCT, were mapped to bibliometric and funding data.OutcomesRisk of bias on six methodological dimensions and RCT-level overall assessment of adequate methods, inadequate methods or poor reporting.ResultsThis study analysed 20 571 RCTs. 5.7% of RCTs used adequate methods (N=1173). 59.3% used inadequate methods (N=12 190) and 35.0% were poorly reported (N=7208). The proportion of poorly reported RCTs decreased from 42.5% in 1990 to 30.2% in 2015. The proportion of RCTs using adequate methods increased from 2.6% in 1990 to 10.3% in 2015. The proportion of RCTs using inadequate methods increased from 54.9% in 1990 to 59.5% in 2015. Industry funding, top pharmaceutical company affiliation, trial registration, larger authorship teams, international teams and drug trials were associated with a greater likelihood of using adequate methods. National Institutes of Health funding and university prestige were not.ConclusionEven though reporting has improved since 1990, the proportion of RCTs using inadequate methods is high (59.3%) and increasing, potentially slowing progress and contributing to the reproducibility crisis. Stronger incentives for the use of adequate methods are needed.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Trends and predictors of biomedical research quality, 1990–2015: a meta-research study

Catillon

2019

BMJ Open

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“…Also, the screening process and summary of judgments to reach the risk of bias assessment are described transparently in the supplementary material. Nevertheless, some limitations also should be mentioned, such as the methodological issues found in the included studies, and which are characteristic of clinical trials in dentistry (21,22). The statistical heterogeneity observed was a consequence of both clinical and methodological heterogeneity among the included studies.…”

Section: Discussionmentioning

confidence: 98%

Patient morbidity after impacted third molar extraction with different flap designs. A systematic review and meta-analysis

Glera-Suárez¹,

Soto-Peñaloza²,

Peñarrocha‐Oltra³

et al. 2020

Med Oral

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Background: To review the literature on the effect of different surgical flaps upon patient morbidity (pain perception, trismus, swelling and osteitis) after impacted third molar extraction. Material and methods: An electronic and complementary search of main databases and grey literature was performed up to January 2019 to retrieve randomized clinical trials. The Cochrane risk of bias assessment tool was used for methodological appraisal. A random-effects meta-analysis was conducted of pain perception and trismus. Results: From the initially 1314 screened studies, only 11 were included in the qualitative synthesis, and 5 in the meta-analysis. There were no statistically significant differences in pain between the envelope and triangular flap designs over time, except on the sixth postoperative day, when the envelope flap proved more painful. Regarding trismus, statistically significant differences were observed on the seventh postoperative day, with greater mouth opening in the envelope flap group than in the triangular flap group. There were no clear differences in swelling and osteitis among the flap designs. Conclusions: Despite its limitations, the present meta-analysis found no clear differences in patient morbidity between the different flap designs.

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“…This focus is likely a function of three factors. First, in the literature on human studies the reporting of these design elements has been evaluated for years and continues to be the focus of many studies; second, there is empirical evidence of an association between reporting of these elements and the effect size of intervention studies [ 26 – 31 ]. Finally, the assessment of these factors does not require advanced understanding of study design because authors use typical expressions or keywords more commonly to describe the options for these design elements, i.e., randomization and blinding, and therefore the task of assessment of reporting is relatively simple.…”

Section: Discussionmentioning

confidence: 99%

The study design elements employed by researchers in preclinical animal experiments from two research domains and implications for automation of systematic reviews

O’Connor

Totton²,

Cullen

et al. 2018

PLoS ONE

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Systematic reviews are increasingly using data from preclinical animal experiments in evidence networks. Further, there are ever-increasing efforts to automate aspects of the systematic review process. When assessing systematic bias and unit-of-analysis errors in preclinical experiments, it is critical to understand the study design elements employed by investigators. Such information can also inform prioritization of automation efforts that allow the identification of the most common issues. The aim of this study was to identify the design elements used by investigators in preclinical research in order to inform unique aspects of assessment of bias and error in preclinical research. Using 100 preclinical experiments each related to brain trauma and toxicology, we assessed design elements described by the investigators. We evaluated Methods and Materials sections of reports for descriptions of the following design elements: 1) use of comparison group, 2) unit of allocation of the interventions to study units, 3) arrangement of factors, 4) method of factor allocation to study units, 5) concealment of the factors during allocation and outcome assessment, 6) independence of study units, and 7) nature of factors. Many investigators reported using design elements that suggested the potential for unit-of-analysis errors, i.e., descriptions of repeated measurements of the outcome (94/200) and descriptions of potential for pseudo-replication (99/200). Use of complex factor arrangements was common, with 112 experiments using some form of factorial design (complete, incomplete or split-plot-like). In the toxicology dataset, 20 of the 100 experiments appeared to use a split-plot-like design, although no investigators used this term. The common use of repeated measures and factorial designs means understanding bias and error in preclinical experimental design might require greater expertise than simple parallel designs. Similarly, use of complex factor arrangements creates novel challenges for accurate automation of data extraction and bias and error assessment in preclinical experiments.

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Randomized clinical trials in dentistry: Risks of bias, risks of random errors, reporting quality, and methodologic quality over the years 1955–2013

Cited by 36 publications

References 69 publications

Trends and predictors of biomedical research quality, 1990–2015: a meta-research study

Trends and predictors of biomedical research quality, 1990–2015: a meta-research study

Patient morbidity after impacted third molar extraction with different flap designs. A systematic review and meta-analysis

The study design elements employed by researchers in preclinical animal experiments from two research domains and implications for automation of systematic reviews

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