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Lead-Time Bias

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101. Time‐Dependent Bias of Tumor Growth Rate and Time to Tumor Regrowth (PubMed)

Time‐Dependent Bias of Tumor Growth Rate and Time to Tumor Regrowth 27730754 2018 11 13 2163-8306 5 11 2016 11 CPT: pharmacometrics & systems pharmacology CPT Pharmacometrics Syst Pharmacol Time-Dependent Bias of Tumor Growth Rate and Time to Tumor Regrowth. 587 10.1002/psp4.12145 Mistry H B HB Manchester School of Pharmacy, Manchester, UK. eng Letter 2016 11 10 United States CPT Pharmacometrics Syst Pharmacol 101580011 2163-8306 2016 09 15 2016 10 05 2016 10 13 6 0 2016 10 13 6 0 2016 10 13

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2016 CPT: pharmacometrics & systems pharmacology

102. Magnetic susceptibility induced echo time shifts: Is there a bias in age-related fMRI studies? (PubMed)

Magnetic susceptibility induced echo time shifts: Is there a bias in age-related fMRI studies? To evaluate the potential for bias in functional magnetic resonance imaging (fMRI) aging studies resulting from age-related differences in magnetic field distributions that can impact echo time and functional contrast.Magnetic field maps were taken on 31 younger adults (age: 22 ± 2.9 years) and 46 older adults (age: 66 ± 4.5 years) on a 3T scanner. Using the spatial gradients of the magnetic field map (...) for each participant, an echo planar imaging (EPI) trajectory was simulated. The effective echo time, time at which the k-space trajectory is the closest to the center of k-space, was calculated. This was used to examine both within-subject and across-age-group differences in the effective echo time maps. The blood oxygenation level-dependent (BOLD) percent signal change resulting from those echo time shifts was also calculated to determine their impact on fMRI aging studies.For a single subject

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2016 Journal of magnetic resonance imaging : JMRI

103. Bias and precision of methods for estimating the difference in restricted mean survival time from an individual patient data meta-analysis. (PubMed)

Bias and precision of methods for estimating the difference in restricted mean survival time from an individual patient data meta-analysis. The difference in restricted mean survival time ([Formula: see text]), the area between two survival curves up to time horizon [Formula: see text], is often used in cost-effectiveness analyses to estimate the treatment effect in randomized controlled trials. A challenge in individual patient data (IPD) meta-analyses is to account for the trial effect. We (...) study, we varied the between-trial heterogeneity for the baseline hazard and for the treatment effect (possibly correlated), the overall treatment effect, the time horizon [Formula: see text], the number of trials and of patients, the use of fixed or DerSimonian-Laird random effects model, and the proportionality of hazards. We compared the methods in terms of bias, empirical and average standard errors. We used IPD from the Meta-Analysis of Chemotherapy in Nasopharynx Carcinoma (MAC-NPC) and its

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2016 BMC medical research methodology

104. Limited benefits of cognitive bias modification for adolescents: is it time to move on?

Limited benefits of cognitive bias modification for adolescents: is it time to move on? Limited benefits of cognitive bias modification for adolescents Search National Elf Service Search National Elf Service » » » » Limited benefits of cognitive bias modification for adolescents: is it time to move on? Mar 9 2015 Posted by Cognitive bias modification (CBM) interventions have grown extremely popular over the last decade, both with researchers, as well as with end-users. The term is an umbrella (...) for CBM interventions . Is it time to move on from cognitive bias modification? Limitations The “dose” of training might have been insufficient, though on the other hand there is no evidence that for children and adolescents a dose effect of number of sessions would exist. Participant feedback for the task was mixed, with many reporting it as too long or too stereotyped. Participants were unselected so maybe they did not really have negative interpretation biases that could be reduced through training

2015 The Mental Elf

105. Reporting Bias Leading to Discordant Venous Thromboembolism Rates in the United States Versus Non-US Countries Following Radical Cystectomy: A Systematic Review and Meta-analysis. (PubMed)

Reporting Bias Leading to Discordant Venous Thromboembolism Rates in the United States Versus Non-US Countries Following Radical Cystectomy: A Systematic Review and Meta-analysis. Postcystectomy bladder cancer (BCa) patients are at high risk for developing venous thromboembolism (VTE). The literature varies widely in the reporting of VTE in this population.To determine the VTE rate in subjects undergoing radical cystectomy (RC) and highlight specific factors affecting this rate.This meta

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2017 European urology focus

106. Reporting Bias Leading to Discordant Venous Thromboembolism Rates in the United States Versus Non-US Countries Following Radical Cystectomy: A Systematic Review and Meta-analysis.

Reporting Bias Leading to Discordant Venous Thromboembolism Rates in the United States Versus Non-US Countries Following Radical Cystectomy: A Systematic Review and Meta-analysis. Postcystectomy bladder cancer (BCa) patients are at high risk for developing venous thromboembolism (VTE). The literature varies widely in the reporting of VTE in this population.To determine the VTE rate in subjects undergoing radical cystectomy (RC) and highlight specific factors affecting this rate.This meta

2017 European urology focus

107. PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies. (PubMed)

PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies. Clinical prediction models combine multiple predictors to estimate risk for the presence of a particular condition (diagnostic models) or the occurrence of a certain event in the future (prognostic models). PROBAST (Prediction model Risk Of Bias ASsessment Tool), a tool for assessing the risk of bias (ROB) and applicability of diagnostic and prognostic prediction model studies, was developed by a steering (...) group that considered existing ROB tools and reporting guidelines. The tool was informed by a Delphi procedure involving 38 experts and was refined through piloting. PROBAST is organized into the following 4 domains: participants, predictors, outcome, and analysis. These domains contain a total of 20 signaling questions to facilitate structured judgment of ROB, which was defined to occur when shortcomings in study design, conduct, or analysis lead to systematically distorted estimates of model

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2019 Annals of Internal Medicine

108. Design characteristics, risk of bias, and reporting of randomised controlled trials supporting approvals of cancer drugs by European Medicines Agency, 2014-16: cross sectional analysis. (PubMed)

or coprimary endpoint, with the remaining trials evaluating surrogate measures such as progression free survival and response rates. Overall, 19 randomised controlled trials (49%) were judged to be at high risk of bias for their primary outcome. Concerns about missing outcome data (n=10) and measurement of the outcome (n=7) were the most common domains leading to high risk of bias judgments. Fewer randomised controlled trials that evaluated overall survival as the primary endpoint were at high risk of bias (...) Design characteristics, risk of bias, and reporting of randomised controlled trials supporting approvals of cancer drugs by European Medicines Agency, 2014-16: cross sectional analysis. To examine the design characteristics, risk of bias, and reporting adequacy of pivotal randomised controlled trials of cancer drugs approved by the European Medicines Agency (EMA).Cross sectional analysis.European regulatory documents, clinical trial registry records, protocols, journal publications

2019 BMJ

109. Failure to Fail Part 2: Types of Evaluation Bias

Failure to Fail Part 2: Types of Evaluation Bias Failure to Fail Part 2: Types of Evaluation Bias - CanadiEM Failure to Fail Part 2: Types of Evaluation Bias In by Nadim Lalani July 14, 2016 We know that the best way to evaluate learners is by directly observing what they do in the workplace. Unfortunately [for a variety of reasons] we do not do enough of this. In my I described some reasons why we sometimes fail at making appropriate judgments about failing learners. When it comes to providing (...) feedback, there is much room for improvement.We know that feedback can be influenced by the source, the recipient and the message. What most people don’t know is that, when you’re evaluating a learner, you yourself could be unwittingly introducing bias – just like when we make diagnoses. Types of Evaluation Bias: If a learner really excels in one area, this may positively influence their evaluation in other areas. For example, a resident successfully/quickly intubates a patient with respiratory arrest

2016 CandiEM

110. Gender-Bias Bias Part 2: Unpicking Cherry-Picking

is a highly-cited review on gender bias that I’d been asked for an opinion on ( ). It’s in the Proceedings of the National Academy of Sciences of the USA (PNAS). And it doesn’t need take long to realize it’s a very shaky house of cards. But it took a long time to work through thoroughly. I had several false starts, going down roads that would need far too much time to finish. I hadn’t found a recent rigorous systematic review. So I tried to weigh up how much cherry-picking there was from within the study (...) Gender-Bias Bias Part 2: Unpicking Cherry-Picking Gender-Bias Bias Part 2: Unpicking Cherry-Picking | PLOS Blogs Network PLOS Blogs Staff Blogs Blogs by Topic Biology & Life Sciences Earth & Environmental Sciences Multi-disciplinary Sciences Medicine & Health Research Analysis & Scientific Policy Diverse perspectives on science and medicine Staff Blogs Blogs by Topic Biology & Life Sciences Earth & Environmental Sciences Multi-disciplinary Sciences Medicine & Health Research Analysis

2016 PLOS Blogs Network

111. Applying quantitative bias analysis to estimate the plausible effects of selection bias in a cluster randomised controlled trial: secondary analysis of the Primary care Osteoarthritis Screening Trial (POST) (PubMed)

of bias present in studies. Due to lack of information on the selection probability, probabilistic bias analysis with a range of triangular distributions was also used, applied at all three follow-up time points; 3, 6, and 12 months post consultation. A simple bias analysis was also applied to the study.Worse pain outcomes were observed among intervention participants than control participants (crude odds ratio at 3, 6, and 12 months: 1.30 (95% CI 1.01, 1.67), 1.39 (1.07, 1.80), and 1.17 (95% CI 0.90 (...) Applying quantitative bias analysis to estimate the plausible effects of selection bias in a cluster randomised controlled trial: secondary analysis of the Primary care Osteoarthritis Screening Trial (POST) Selection bias is a concern when designing cluster randomised controlled trials (c-RCT). Despite addressing potential issues at the design stage, bias cannot always be eradicated from a trial design. The application of bias analysis presents an important step forward in evaluating whether

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2017 Trials

112. This is How Research Gender-Bias Bias Works

and publication selection bias: hands up who’s not here? The Ceci and Williams paper included 35 studies to come to their conclusions that “it’s a level playing field” and it’s women’s choices that lead to their underrepresentation. Some of those were reviews, and some were a few – but not all! – of the studies in those reviews. It was an odd set and we don’t know how or why they were selected for the review. Take the level playing field they say exists at journals. There were at least 16,000 active science (...) This is How Research Gender-Bias Bias Works This is How Research Gender-Bias Bias Works | Absolutely Maybe PLOS Blogs Staff Blogs Blogs by Topic Biology & Life Sciences Earth & Environmental Sciences Multi-disciplinary Sciences Medicine & Health Research Analysis & Scientific Policy Diverse perspectives on science and medicine Staff Blogs Blogs by Topic Biology & Life Sciences Earth & Environmental Sciences Multi-disciplinary Sciences Medicine & Health Research Analysis & Scientific Policy Post

2016 Absolutely Maybe

113. Gender-Bias Bias Part 2: Unpicking Cherry-Picking

on gender bias that I’d been asked for an opinion on ( ). It’s in the Proceedings of the National Academy of Sciences of the USA (PNAS). And it doesn’t take long to realize it’s a very shaky house of cards. But it took a long time to work through thoroughly. I had several false starts, going down roads that would need far too much time to finish. I hadn’t found a recent rigorous systematic review. So I tried to weigh up how much cherry-picking there was from within the study itself: by looking at all (...) Gender-Bias Bias Part 2: Unpicking Cherry-Picking Gender-Bias Bias Part 2: Unpicking Cherry-Picking | Absolutely Maybe PLOS Blogs Staff Blogs Blogs by Topic Biology & Life Sciences Earth & Environmental Sciences Multi-disciplinary Sciences Medicine & Health Research Analysis & Scientific Policy Diverse perspectives on science and medicine Staff Blogs Blogs by Topic Biology & Life Sciences Earth & Environmental Sciences Multi-disciplinary Sciences Medicine & Health Research Analysis & Scientific

2016 Absolutely Maybe

114. 2018 EHRA Expert Consensus Statement on Lead Extraction: Recommendations on Definitions, Endpoints, Research Trial Design, and Data Collection Requirements for Clinical Scientific Studies and Registries: Endorsed by APHRS/HRS/LAHRS

of functional integrity Abandoned lead Lead left in place in the heart and not con- nected to a CIED. It may be functional or non-functional. ‘Redundant’ lead is some- times used to describe an abandoned lead Recall Firm’s removal or correction of a marketed product that the US Food and Drug Administration (FDA) or the European Medicines Agency (EMA) consider to be in violation of the laws it administers and against, which the agency would initiate legal action. Recall does not include a market withdrawal (...) without the use of specialized tools (other than a standard stylet) was used in 27% of patients in the ELECTRa registry, 4 and may be effective for leads with a short dwell time (i.e. time since implant 4 cm remainsinsitu). (12) Reimplantation (if applicable): access site, type of device (as this may affect total procedure and fluoroscopy durations). (13) Intra-operative complications (tachyarrhythmias, atrioventricular block, pericardial bleeding etc.) and their management. If known, the location

2018 Heart Rhythm Society

115. Household interventions for preventing domestic lead exposure in children. (PubMed)

, or combinations of interventions to prevent lead exposure in children (from birth to 18 years of age), where investigators reported at least one standardised outcome measure.Two authors independently reviewed all eligible studies for inclusion, assessed risk of bias and extracted data. We contacted trialists to obtain missing information. We assessed the quality of the evidence using the GRADE approach.We included 14 studies involving 2643 children: 13 RCTs (involving 2565 children) and one quasi-RCT (...) of bias in all assessed domains. We rated two RCTs and one quasi-RCT as being at high risk of selection bias and six RCTs as being at high risk of attrition bias. For educational interventions, we rated the quality of evidence to be high for continuous blood lead levels and moderate for all other outcomes. For environmental interventions, we assessed the quality of evidence as moderate to low. National or international research grants or governments funded 12 studies, while the other 2 did not report

2016 Cochrane

116. The risk of bias in observational studies of exposures (ROBINS-E) tool: concerns arising from application to observational studies of exposures. (PubMed)

related to some critical sources of bias, such as exposure and funding source, are not assessed. ROBINS-E fails to discriminate between studies with a single risk of bias or multiple risks of bias. ROBINS-E is severely limited at determining whether confounders will bias study outcomes. The construct of co-exposures was difficult to distinguish from confounders. Applying ROBINS-E was time-consuming and confusing.Our experience suggests that the ROBINS-E tool does not meet the need for an international (...) The risk of bias in observational studies of exposures (ROBINS-E) tool: concerns arising from application to observational studies of exposures. Systematic reviews, which assess the risk of bias in included studies, are increasingly used to develop environmental hazard assessments and public health guidelines. These research areas typically rely on evidence from human observational studies of exposures, yet there are currently no universally accepted standards for assessing risk of bias

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2018 Systematic Reviews

117. Attenuating the nonresponse bias in hunting bag surveys: The multiphase sampling strategy. (PubMed)

Attenuating the nonresponse bias in hunting bag surveys: The multiphase sampling strategy. Reliable hunting bag statistics are a prerequisite for sustainable harvest management based on quantitative modeling. Estimating the total hunting bag for a given game species is faced with a multiplicity of error sources. Of particular concern is the nonresponse error. We consider that the major cause of nonresponse bias is when the reluctance to respond is related to a null harvest, which leads (...) to a potentially important overestimation. For tackling the nonresponse bias issue, we advocate the repeated subsampling of nonrespondents, with a final phase of personal interview by phone, intended to be without nonresponse. When a 100% response rate is actually reached at the last phase, both total and sampling variance can be estimated without bias, whatever the response rates at the previous phases. The actual case of imperfect response at the last phase is studied using Monte Carlo simulations

2019 PLoS ONE

118. Thinking about negative life events as a mediator between depression and fading affect bias. (PubMed)

Thinking about negative life events as a mediator between depression and fading affect bias. The current research examined the links between depressive symptomology and anxiety on the fading of affect associated with positive and negative autobiographical memories. Participants (N = 296) recalled and rated positive and negative events in terms of how pleasant or unpleasant they were at the time they occurred and at the time of event recollection. Multilevel mediation analyses identified

2019 PLoS ONE

119. Hospital productivity bias when not adjusting for cost heterogeneity: The case of Spain. (PubMed)

that increases up to 0.974 if heterogeneity is considered. Hence, the omission of heterogeneity leads to a bias of 24.4 percentage points in the mean cost efficiency. Therefore, not adjusting for heterogeneity in costs gives rise to distorted measurements of hospital productivity, as well as distortions in the contribution of each of its components, which may lead to the adoption of inadequate policies and decisions on resource allocation. (...) Hospital productivity bias when not adjusting for cost heterogeneity: The case of Spain. This research quantifies the bias caused in hospital productivity measurements when cost heterogeneity is not considered. A multi-output stochastic cost frontier under a normalised translog specification is used to approximate the structure of technology of a sample of public general hospitals in Spain during the period 2002-2009. To control for observable heterogeneity in costs, a set of variables related

2019 PLoS ONE

120. Hostile attribution bias and angry rumination: A longitudinal study of undergraduate students. (PubMed)

the longitudinal mutual relationship between hostile attribution bias and angry rumination; 941 undergraduate students (38.5% male) completed questionnaires assessing the variables at two time points. The results indicate that hostile attribution bias showed a small but statistically significant effect on angry rumination 6 months later, and angry rumination showed a quite small but marginally significant effect on hostile attribution bias across time. The present study supports the idea that hostile (...) Hostile attribution bias and angry rumination: A longitudinal study of undergraduate students. Angry rumination and hostile attribution bias are important cognitive factors of aggression. Although prior theoretical models of aggression suggest that aggressive cognitive factors may influence each other, there are no studies examining the longitudinal relationship between angry rumination and hostile attribution bias. The present study used cross-lagged structural equation modeling to explore

2019 PLoS ONE

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