Identifying and Avoiding Risk of Bias in Caries Diagnostic Studies.
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ABSTRACT:
SUBMITTER: Kuhnisch J
PROVIDER: S-EPMC8347423 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Many studies, including self-controlled case series (SCCS) studies, are being undertaken to quantify the risks of complications following infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19). One such SCCS study, based on all COVID-19 cases arising in Sweden over an 8-month period, has shown that SARS-CoV-2 infection increases the risks of AMI and ischemic stroke. Some features of SARS-CoV-2 infection and COVID-19, present in this study and likely in others, complicate the analysis and may introduce bias. In the present paper we describe these features, and explore the biases they may generate. Motivated by data-based simulations, we propose methods to reduce or remove these biases.
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Project description:BACKGROUND:Moderately elevated blood levels of homocysteine are weakly correlated with coronary heart disease (CHD) risk, but causality remains uncertain. When folate levels are low, the TT genotype of the common C677T polymorphism (rs1801133) of the methylene tetrahydrofolate reductase gene (MTHFR) appreciably increases homocysteine levels, so "Mendelian randomization" studies using this variant as an instrumental variable could help test causality. METHODS AND FINDINGS:Nineteen unpublished datasets were obtained (total 48,175 CHD cases and 67,961 controls) in which multiple genetic variants had been measured, including MTHFR C677T. These datasets did not include measurements of blood homocysteine, but homocysteine levels would be expected to be about 20% higher with TT than with CC genotype in the populations studied. In meta-analyses of these unpublished datasets, the case-control CHD odds ratio (OR) and 95% CI comparing TT versus CC homozygotes was 1.02 (0.98-1.07; p?=?0.28) overall, and 1.01 (0.95-1.07) in unsupplemented low-folate populations. By contrast, in a slightly updated meta-analysis of the 86 published studies (28,617 CHD cases and 41,857 controls), the OR was 1.15 (1.09-1.21), significantly discrepant (p?=?0.001) with the OR in the unpublished datasets. Within the meta-analysis of published studies, the OR was 1.12 (1.04-1.21) in the 14 larger studies (those with variance of log OR<0.05; total 13,119 cases) and 1.18 (1.09-1.28) in the 72 smaller ones (total 15,498 cases). CONCLUSIONS:The CI for the overall result from large unpublished datasets shows lifelong moderate homocysteine elevation has little or no effect on CHD. The discrepant overall result from previously published studies reflects publication bias or methodological problems.
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Project description:In conducting a systematic review, assessing the risk of bias of the included studies is a vital step; thus, choosing the most pertinent risk of bias (ROB) tools is crucial. This paper determined the most appropriate ROB tools for assessing observational studies in a systematic review assessing the association between anthropometric measurements and dental caries among children. First, we determined the ROB tools used in previous reviews on a similar topic. Subsequently, we reviewed articles on ROB tools to identify the most recommended ROB tools for observational studies. Of the twelve ROB tools identified from the previous steps, three ROB tools that best fit the eight criteria of a good ROB tool were the Newcastle-Ottawa Scale (NOS) for cohort and case-control studies, and Agency for Healthcare Research and Quality (AHRQ) and the Effective Public Health Practice Project (EPHPP) for a cross-sectional study. We further assessed the inter-rater reliability for all three tools by analysing the percentage agreement, inter-class correlation coefficient (ICC) and kappa score. The overall percentage agreements and reliability scores of these tools ranged from good to excellent. Two ROB tools for the cross-sectional study were further evaluated qualitatively against nine of a tool's advantages and disadvantages. Finally, the AHRQ and NOS were selected as the most appropriate ROB tool to assess cross-sectional and cohort studies in the present review.
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Project description:AimThis systematic review and meta-analysis aimed to assess the diagnostic accuracy and reliability of commonly used caries detection methods for proximal caries diagnostics. Visual examination (VE), bitewing radiography (BWR), laser fluorescence (LF), and fibre-optic transillumination (FOTI) were considered in detail.Material and methodsPRISMA guidelines for the reporting of systematic reviews and meta-analyses were applied. The mnemonic PIRDS (problem, index test, reference test, diagnostic and study type) concept was used to guide the literature search. Next, studies that met the inclusion criteria were stepwise selected and evaluated for their quality with a risk of bias (RoB) assessment tool. Studies with low/moderate bias and sufficient reporting were considered for meta-analysis. The pooled sensitivity (SE), specificity (SP), diagnostic odds ratio (DOR), and area under the ROC curve (AUC) were calculated.ResultsFrom 129 studies meeting the selection criteria, 31 in vitro studies and five clinical studies were finally included in the meta-analysis. The AUC values for in vitro VE amounted to 0.84 (caries detection) and 0.85 (dentin caries detection). BWR ranged in vitro from 0.55 to 0.82 (caries detection) and 0.81-0.92 (dentin caries detection). LF showed higher AUC values for overall caries detection (0.91) and dentin caries detection (0.83) than did other methods. Clinical data are limited.ConclusionThe number of diagnostic studies with low/moderate RoB was found to be low and indicates a need for high-quality, well-designed caries diagnostic studies.Clinical relevanceBWR and LF showed good diagnostic performance on proximal surfaces. However, because of the low number of includable clinical studies, these data should be interpreted with caution.
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Project description:In classical growth analysis, relative growth rate (RGR) is calculated as RGR = (ln W2 - ln W1)/(t2 - t1), where W1 and W2 are plant dry weights at times t1 and t2. Since RGR is usually calculated using destructive harvests of several individuals, an obvious approach is to substitute W1 and W2 with sample means W1 and W2. Here we demonstrate that this approach yields a biased estimate of RGR whenever the variance of the natural logarithm-transformed plant weight changes through time. This bias increases with an increase in the variance in RGR, in the length of the interval between harvests, or in sample size. The bias can be avoided by using the formula RGR = (ln W2 - ln W1)/(t2 - t1),where ln W1 and ln W2 are the means of the natural logarithm-transformed plant weights.
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Project description:ObjectiveMachine learning (ML) diagnostic tools have significant potential to improve health care. However, methodological pitfalls may affect diagnostic test accuracy studies used to appraise such tools. We aimed to evaluate the prevalence and reporting of design characteristics within the literature. Further, we sought to empirically assess whether design features may be associated with different estimates of diagnostic accuracy.Materials and methodsWe systematically retrieved 2 × 2 tables (n = 281) describing the performance of ML diagnostic tools, derived from 114 publications in 38 meta-analyses, from PubMed. Data extracted included test performance, sample sizes, and design features. A mixed-effects metaregression was run to quantify the association between design features and diagnostic accuracy.ResultsParticipant ethnicity and blinding in test interpretation was unreported in 90% and 60% of studies, respectively. Reporting was occasionally lacking for rudimentary characteristics such as study design (28% unreported). Internal validation without appropriate safeguards was used in 44% of studies. Several design features were associated with larger estimates of accuracy, including having unreported (relative diagnostic odds ratio [RDOR], 2.11; 95% confidence interval [CI], 1.43-3.1) or case-control study designs (RDOR, 1.27; 95% CI, 0.97-1.66), and recruiting participants for the index test (RDOR, 1.67; 95% CI, 1.08-2.59).DiscussionSignificant underreporting of experimental details was present. Study design features may affect estimates of diagnostic performance in the ML diagnostic test accuracy literature.ConclusionsThe present study identifies pitfalls that threaten the validity, generalizability, and clinical value of ML diagnostic tools and provides recommendations for improvement.
| S-EPMC7647361 | biostudies-literature
Project description:AimDiagnosing heart failure with preserved ejection fraction (HFpEF) in the non-acute setting remains challenging. Natriuretic peptides have limited value for this purpose, and a multitude of studies investigating novel diagnostic circulating biomarkers have not resulted in their implementation. This review aims to provide an overview of studies investigating novel circulating biomarkers for the diagnosis of HFpEF and determine their risk of bias (ROB).Methods and resultsA systematic literature search for studies investigating novel diagnostic HFpEF circulating biomarkers in humans was performed up until 21 April 2020. Those without diagnostic performance measures reported, or performed in an acute heart failure population were excluded, leading to a total of 28 studies. For each study, four reviewers determined the ROB within the QUADAS-2 domains: patient selection, index test, reference standard, and flow and timing. At least one domain with a high ROB was present in all studies. Use of case-control/two-gated designs, exclusion of difficult-to-diagnose patients, absence of a pre-specified cut-off value for the index test without the performance of external validation, the use of inappropriate reference standards and unclear timing of the index test and/or reference standard were the main bias determinants. Due to the high ROB and different patient populations, no meta-analysis was performed.ConclusionThe majority of current diagnostic HFpEF biomarker studies have a high ROB, reducing the reproducibility and the potential for clinical care. Methodological well-designed studies with a uniform reference diagnosis are urgently needed to determine the incremental value of circulating biomarkers for the diagnosis of HFpEF.
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Project description:BACKGROUND: Systematic Reviews (SRs) of experimental animal studies are not yet common practice, but awareness of the merits of conducting such SRs is steadily increasing. As animal intervention studies differ from randomized clinical trials (RCT) in many aspects, the methodology for SRs of clinical trials needs to be adapted and optimized for animal intervention studies. The Cochrane Collaboration developed a Risk of Bias (RoB) tool to establish consistency and avoid discrepancies in assessing the methodological quality of RCTs. A similar initiative is warranted in the field of animal experimentation. METHODS: We provide an RoB tool for animal intervention studies (SYRCLE's RoB tool). This tool is based on the Cochrane RoB tool and has been adjusted for aspects of bias that play a specific role in animal intervention studies. To enhance transparency and applicability, we formulated signalling questions to facilitate judgment. RESULTS: The resulting RoB tool for animal studies contains 10 entries. These entries are related to selection bias, performance bias, detection bias, attrition bias, reporting bias and other biases. Half these items are in agreement with the items in the Cochrane RoB tool. Most of the variations between the two tools are due to differences in design between RCTs and animal studies. Shortcomings in, or unfamiliarity with, specific aspects of experimental design of animal studies compared to clinical studies also play a role. CONCLUSIONS: SYRCLE's RoB tool is an adapted version of the Cochrane RoB tool. Widespread adoption and implementation of this tool will facilitate and improve critical appraisal of evidence from animal studies. This may subsequently enhance the efficiency of translating animal research into clinical practice and increase awareness of the necessity of improving the methodological quality of animal studies.
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Project description:There is concern that accelerating sea-level rise will exceed the vertical growth capacity of coastal-wetland substrates in many regions by the end of this century. Vertical vulnerability estimates rely on measurements of accretion and/or surface-elevation-change derived from soil cores and/or surface elevation tables (SETs). To date there has not been a broad examination of whether the multiple timescales represented by the processes of accretion and elevation change are equally well-suited for quantifying the trajectories of wetland vertical change in coming decades and centuries. To examine the potential for timescale bias in assessments of vertical change, we compared rates of accretion and surface elevation change using data derived from a review of the literature. In the first approach, average rates of elevation change were compared with timescale-averaged accretion rates from six regions around the world where sub-decadal, decadal, centennial, and millennial timescales were represented. Second, to isolate spatial variability, temporal comparisons were made for regionally unique environmental categories within each region. Last, comparisons were made of records from sites where SET-MH stations and radiometric measurements were co-located in close proximity. We find that rates vary significantly as a function of measurement timescale and that the pattern and magnitude of variation between timescales are location-specific. Failure to identify and account for temporal variability in rates will produce biased assessments of the vertical change capacity of coastal wetlands. Robust vulnerability assessments should combine accretion rates from multiple timescales with the longest available SET record to provide long-term context for ongoing monitoring observations and projections.
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