Nephron Clin Pr. Article Google Scholar. Berger VW. Quantifying the magnitude of baseline covariate imbalances resulting from selection bias in randomized clinical trials. Biom J Biom Z. Methods of blinding in reports of randomized controlled trials assessing pharmacologic treatments: a systematic review. PLoS Med. Post-randomisation exclusions: the intention to treat principle and excluding patients from analysis.
The impact of outcome reporting bias in randomised controlled trials on a cohort of systematic reviews. Article PubMed Google Scholar. Empirical evidence of bias in treatment effect estimates in controlled trials with different interventions and outcomes: meta-epidemiological study. Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials.
Download references. Mark R. Biostatistics Unit, St. You can also search for this author in PubMed Google Scholar. MP was responsible for conception of idea, writing of paper and review of paper.
VC was responsible for conception of idea, writing of paper and review of paper. MB was responsible for conception of idea, writing of paper and review of paper. PK was responsible for critical review and feedback on paper. LT was responsible for critical review and feedback on paper.
Correspondence to Varun Chaudhary. MP: Nothing to disclose. LT: Nothing to disclose. Study Group are listed below Author contributions. Reprints and Permissions. Phillips, M. Risk of bias: why measure it, and how?. Withdrawals from the study lead to incomplete outcome data. There are two reasons for withdrawals or incomplete outcome data in clinical trials.
Exclusions refer to situations in which some participants are omitted from reports of analyses, despite outcome data being available to the trialists. Attrition refers to situations in which outcome data are not available. Reporting bias refers to systematic differences between reported and unreported findings. Within a published report those analyses with statistically significant differences between intervention groups are more likely to be reported than non-significant differences.
In addition there are other sources of bias that are relevant only in certain circumstances. These relate mainly to particular trial designs e. Does quality of reports of randomised trials affect estimates of intervention efficacy reported in meta-analyses? Proceedings of the 7th Cochrane colloquium. Universita S. Milan: Centro Cochrane Italiano; Quality of randomised clinical trials affects estimates of intervention efficacy; p.
Oxford: Centre for Statistics in Medicine; Assessment of the quality of controlled trials in meta-analyses published in leading journals; p. The impact of blinding on the results of a randomized, placebo-controlled multiple sclerosis clinical trial. Blinding was judged more difficult to achieve and maintain in nonpharmacologic than pharmacologic trials. J Clin Epidemiol.
Article PubMed Google Scholar. Reporting methods of blinding in randomized trials assessing nonpharmacological treatments.
PLoS Med. Syst Rev. Empirical evidence for selective reporting of outcomes in randomized trials: comparison of protocols to published articles. Industry bias in randomized controlled trials in general and abdominal surgery: an empirical study.
Ann Surg. Single data extraction generated more errors than double data extraction in systematic reviews. R Core Team. R: a language and environment for statistical computing.
R Foundation for Statistical Computing. Vienna, Austria, Cochrane collaboration. Association of industry sponsorship and positive outcome in randomised controlled trials in general and abdominal surgery: protocol for a systematic review and empirical study. Download references. No additional funding source is available. However, the resources and facilities of the University of Heidelberg were used in conducting this review.
You can also search for this author in PubMed Google Scholar. Correspondence to Markus K. PP developed the study concept, wrote the first draft of the protocol and wrote the first draft of the protocol publication. KG developed the search strategy, gave methodological advice and helped writing the protocol. PH made acquisition of literature and revised the protocol. SZ helped to develop the study concept and drafted the protocol. PK and MKD helped to develop the study concept and gave methodological advice.
All authors read and approved the final manuscript. KG is a methodological specialist and core member of the surgical systematic review group at the Study Center of the German Surgical Society. PH is a surgical resident. PK is a surgeon and head of the surgical clinical trial unit. AU is the chief attending in the surgical department and head of surgical oncology.
Reprints and Permissions. Probst, P. Blinding in randomized controlled trials in general and abdominal surgery: protocol for a systematic review and empirical study. Syst Rev 5, 48 Download citation.
Received : 13 January Accepted : 18 March Published : 24 March Other studies have suggested that rates of second breast cancers may be higher among women taking statins and lower among women taking antibiotics than a comparison group of women not taking these treatments. In a cohort study of breast cancer survivors , there were systematic differences in how much screening the women received, depending on which medicines they were taking.
This meant that any associations observed might be affected by detection bias. A cohort study investigating the relationship between smoking and risks of basal cell or squamous cell cancer found that current smokers had significantly lower risks of basal cell carcinoma, but higher risks of squamous cell carcinoma. Former smokers had similar risks for each cancer as did never smokers. However, when they looked more closely, the researchers discovered that current smokers had had fewer skin examinations and procedures than never smokers.
Intervention studies should be designed to ensure that all groups have an equivalent chance of being affected by known factors that influence detection. The use of randomisation in intervention studies also aims to generate groups equivalent in unknown factors. In observational studies, potential sources of detection bias should be sought out, and if identified, adjusted for or stratified by to clarify the observed associations of interest. Detection bias can also be due to the knowledge of the allocated interventions by outcome assessors; therefore outcome assessors should be blinded to the intervention.
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