Instruct: Given a scientific claim, retrieve passages that support or refute the claim.
Query: Traditional reviews are biased in their interpretations.
Systematic literature reviews are widely used as an aid to evidence based decision making. For example, reviews of randomised controlled trials are regularly used to answer questions about the effectiveness of healthcare interventions. The high profile of systematic reviews as a cornerstone of evidence based medicine, however, has led to several misconceptions about their purpose and methods. Among these is the belief that systematic reviews are applicable only to randomised controlled trials and that they are incapable of dealing with other forms of evidence, such as from non-randomised studies or qualitative research. The systematic literature review is a method of locating, appraising, and synthesising evidence. The value of regularly updated systematic reviews in the assessment of effectiveness of healthcare interventions was dramatically illustrated by Antman and colleagues, who showed that review articles failed to mention advances in treatment identified by an updated systematic review.1  It is nearly a quarter of a century since Gene Glass coined the term “meta-analysis” to refer to the quantitative synthesis of the results of primary studies.2 The importance of making explicit efforts to limit bias in the review of literature, however, has been emphasised by social scientists at least since the 1960s.3 In recent years systematic reviews have found an important role in health services research, and the growing interest in evidence based approaches to decision making makes it likely that their use will increase. Not everybody accepts that systematic reviews are necessary or desirable, and as one moves further away from the clinical applications of systematic reviews cynicism about their utility grows. Several arguments are commonly used to reject a wider role for systematic reviews, and these arguments are often based on major misconceptions about the history, purpose, methods, and uses of systematic reviews. I have examined eight common myths about …
Although interest in clinical guidelines has never been greater, uncertainty persists about whether they are effective. The debate has been hampered by the lack of a rigorous overview. We have identified 59 published evaluations of clinical guidelines that met defined criteria for scientific rigour; 24 investigated guidelines for specific clinical conditions, 27 studied preventive care, and 8 looked at guidelines for prescribing or for support services. All but 4 of these studies detected significant improvements in the process of care after the introduction of guidelines and all but 2 of the 11 studies that assessed the outcome of care reported significant improvements. We conclude that explicit guidelines do improve clinical practice, when introduced in the context of rigorous evaluations. However, the size of the improvements in performance varied considerably.
In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al. (2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under more general settings where the first and third quartiles are also available for the trials. Through simulation studies, we demonstrate that the proposed methods greatly improve the existing methods and enrich the literature. We conclude our work with a summary table that serves as a comprehensive guidance for performing meta-analysis in different situations.
The ecologic study design is routinely used by epidemiologists in spite of its limitations. It is presently unknown how well the challenges of the design are dealt with in epidemiologic research. The purpose of this bibliometric review was to critically evaluate the characteristics, statistical methods, and reporting of results of modern cross-sectional ecologic papers. A search through 6 major epidemiology journals identified all cross-sectional ecologic studies published since January 1, 2000. A total of 125 articles met the inclusion requirements and were assessed via common evaluative criteria. It was found that a considerable number of cross-sectional ecologic studies use unreliable methods or contain statistical oversights; most investigators who adjusted their outcomes for age or sex did so improperly (64%), statistical validity was a potential issue for 20% of regression models, and simple linear regression was the most common analytic approach (31%). Many authors omitted important information when discussing the ecologic nature of their study (31%), the choice of study design (58%), and the susceptibility of their research to the ecological fallacy (49%). These results suggest that there is a need for an international set of guidelines that standardizes reporting on ecologic studies. Additionally, greater attention should be given to the relevant biostatistical literature.
This glossary was developed to provide technical references to support work in the field of the alternatives to animal testing. It was compiled from various existing reference documents coming from different sources and is meant to be a point of reference on alternatives to animal testing. Giving the ever-increasing number of alternative test methods and approaches being developed over the last decades, a combination, revision, and harmonization of earlier published collections of terms used in the validation of such methods is required. The need to update previous glossary efforts came from the acknowledgement that new words have emerged with the development of new approaches, while others have become obsolete, and the meaning of some terms has partially changed over time. With this glossary we intend to provide guidance on issues related to the validation of new or updated testing methods consistent with current approaches. Moreover, because of new developments and technologies, a glossary needs to be a living, constantly updated document. An Internet-based version based on this compilation may be found at http://altweb.jhsph.edu/, allowing the addition of new material.
Like other branches of surgery, Urology has encountered major challenges in aligning the research processes by which new interventions are assessed with the principles of Evidence-Based Medicine. This article explains the IDEAL framework and recommendations and illustrates how they might affect the evaluation of current controversial urological procedures. From an inside perspective, we provide an overview of the efforts of the IDEAL Working Group to date with special emphasis on the field of Urology. There are clear differences between drugs and interventions in the natural history of innovations. Since the conventional framework for conducting trials of new treatments is largely based on the former, the evaluation of surgical innovations using the same template can encounter significant problems. Difficulties in performing randomized controlled trials of surgical techniques and the persistence of the case series as an important feature of the scientific literature have been the two most controversial aspects of this mismatch between the subject of research and the methodology used. The IDEAL framework provides a description of the process of innovation and development for surgical trials, and the associated recommendations provide a suggested alternative approach to developing study designs, which are appropriate for the specific problems of new techniques. IDEAL provides a new framework for surgical innovation that was developed with broad stakeholder input from the surgical community and is expected to have a transformative impact on the way that urologists perform clinical research.
In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
We study recently developed nonparametric methods for estimating the number of missing studies that might exist in a meta-analysis and the effect that these studies might have had on its outcome. These are simple rank-based data augmentation techniques, which formalize the use of funnel plots. We show that they provide effective and relatively powerful tests for evaluating the existence of such publication bias. After adjusting for missing studies, we find that the point estimate of the overall effect size is approximately correct and coverage of the effect size confidence intervals is substantially improved, in many cases recovering the nominal confidence levels entirely. We illustrate the trim and fill method on existing meta-analyses of studies in clinical trials and psychometrics.
Statements like "quality of care is more highly valued than waiting time" can neither be supported nor refuted by comparisons of utility parameters from a traditional discrete choice experiment (DCE). Best--worst scaling can overcome this problem because it asks respondents to perform a different choice task. However, whilst the nature of the best--worst task is generally understood, there are a number of issues relating to the design and analysis of a best--worst choice experiment that require further exposition. This paper illustrates how to aggregate and analyse such data and using a quality of life pilot study demonstrates how richer insights can be drawn by the use of best--worst tasks.
Short-term medical service trips (MSTs) aim to address unmet health care needs of low- and middle-income countries. The lack of critically reviewed empirical evidence of activities and outcomes is a concern. Developing evidence-based recommendations for health care delivery requires systematic research review. I focused on MST publications with empirical results. Searches in May 2013 identified 67 studies published since 1993, only 6% of the published articles on the topic in the past 20 years. Nearly 80% reported on surgical trips. Although the MST field is growing, its medical literature lags behind, with nearly all of the scholarly publications lacking significant data collection. By incorporating data collection into service trips, groups can validate practices and provide information about areas needing improvement.
A novel design for intervention studies is presented, the so called PROBE study (Prospective Randomized Open, Blinded End-point). This design is compared to the classical double-blind design. Among the advantages of the PROBE design are lower cost and greater similarity to standard clinical practice, which should make the results more easily applicable in routine medical care. Since end-points are evaluated by a blinded end-point committee it is obvious that there should be no difference between the two types of trials in this regard.
The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity.
The Bologna criteria for defining poor ovarian response (POR) during IVF provide a useful template for new research in this field of assisted conception. However, designing studies around the European Society for Human Reproduction and Embryology POR criteria can be methodologically challenging, as the new definition includes various POR subpopulations with diverse baseline characteristics and unknown clinical prognosis. When designing RCTs, potential result bias may be introduced if women from each subpopulation are not evenly allocated between intervention groups. In the case of small or moderate-size RCTs, a single-sequence randomization method may not ensure balanced allocation between groups. Stratified randomization methods provide an alternative methodological approach. Depending on the chosen methodology, patient characteristics and outcomes within each intervention group may be better reported according to relevant subpopulations.
BACKGROUND With increasing restrictions placed on physician-industry interactions, industry marketing may target other health professionals. Recent health policy developments confer even greater importance on the decision making of non-physician clinicians. The purpose of this systematic review is to examine the types and implications of non-physician clinician-industry interactions in clinical practice. METHODS AND FINDINGS We searched MEDLINE and Web of Science from January 1, 1946, through June 24, 2013, according to PRISMA guidelines. Non-physician clinicians eligible for inclusion were: Registered Nurses, nurse prescribers, Physician Assistants, pharmacists, dieticians, and physical or occupational therapists; trainee samples were excluded. Fifteen studies met inclusion criteria. Data were synthesized qualitatively into eight outcome domains: nature and frequency of industry interactions; attitudes toward industry; perceived ethical acceptability of interactions; perceived marketing influence; perceived reliability of industry information; preparation for industry interactions; reactions to industry relations policy; and management of industry interactions. Non-physician clinicians reported interacting with the pharmaceutical and infant formula industries. Clinicians across disciplines met with pharmaceutical representatives regularly and relied on them for practice information. Clinicians frequently received industry "information," attended sponsored "education," and acted as distributors for similar materials targeted at patients. Clinicians generally regarded this as an ethical use of industry resources, and felt they could detect "promotion" while benefiting from industry "information. " Free samples were among the most approved and common ways that clinicians interacted with industry. Included studies were observational and of varying methodological rigor; thus, these findings may not be generalizable. This review is, however, the first to our knowledge to provide a descriptive analysis of this literature. CONCLUSIONS Non-physician clinicians' generally positive attitudes toward industry interactions, despite their recognition of issues related to bias, suggest that industry interactions are normalized in clinical practice across non-physician disciplines. Industry relations policy should address all disciplines and be implemented consistently in order to mitigate conflicts of interest and address such interactions' potential to affect patient care. Please see later in the article for the Editors' Summary.
Next-generation-sequencing (NGS) has revolutionized the field of genome assembly because of its much higher data throughput and much lower cost compared with traditional Sanger sequencing. However, NGS poses new computational challenges to de novo genome assembly. Among the challenges, GC bias in NGS data is known to aggravate genome assembly. However, it is not clear to what extent GC bias affects genome assembly in general. In this work, we conduct a systematic analysis on the effects of GC bias on genome assembly. Our analyses reveal that GC bias only lowers assembly completeness when the degree of GC bias is above a threshold. At a strong GC bias, the assembly fragmentation due to GC bias can be explained by the low coverage of reads in the GC-poor or GC-rich regions of a genome. This effect is observed for all the assemblers under study. Increasing the total amount of NGS data thus rescues the assembly fragmentation because of GC bias. However, the amount of data needed for a full rescue depends on the distribution of GC contents. Both low and high coverage depths due to GC bias lower the accuracy of assembly. These pieces of information provide guidance toward a better de novo genome assembly in the presence of GC bias.
A number of authors have attempted to defend ecologic (aggregate) studies by claiming that the goal of those studies is estimation of ecologic (contextual or group-level) effects rather than individual-level effects. Critics of these attempts point out that ecologic effect estimates are inevitably used as estimates of individual effects, despite disclaimers. A more subtle problem is that ecologic variation in the distribution of individual effects can bias ecologic estimates of contextual effects. The conditions leading to this bias are plausible and perhaps even common in studies of ecosocial factors and health outcomes because social context is not randomized across typical analysis units (administrative regions). By definition, ecologic data contain only marginal observations on the joint distribution of individually defined confounders and outcomes, and so identify neither contextual nor individual-level effects. While ecologic studies can still be useful given appropriate caveats, their problems are better addressed by multilevel study designs, which obtain and use individual as well as group-level data. Nonetheless, such studies often share certain special problems with ecologic studies, including problems due to inappropriate aggregation and problems due to temporal changes in covariate distributions.
OBJECTIVE To assess the robustness of patient responses to a new national survey of patient experience as a basis for providing financial incentives to doctors. DESIGN Analysis of the representativeness of the respondents to the GP Patient Survey compared with those who were sampled (5.5 million patients registered with 8273 general practices in England in January 2009) and with the general population. Analysis of non-response bias looked at the relation between practice response rates and scores on the survey. Analysis of the reliability of the survey estimated the proportion of the variance of practice scores attributable to true differences between practices. RESULTS The overall response rate was 38.2% (2.2 million responses), which is comparable to that in surveys using similar methodology in the UK. Men, young adults, and people living in deprived areas were under-represented among respondents. However, for questions related to pay for performance, there was no systematic association between response rates and questionnaire scores. Two questions which triggered payments to general practitioners were reliable measures of practice performance, with average practice-level reliability coefficients of 93.2% and 95.0%. Less than 3% and 0.5% of practices had fewer than the number of responses required to achieve conventional reliability levels of 90% and 70%. A change to the payment formula in 2009 resulted in an increase in the average impact of random variation in patient scores on payments to general practitioners compared with payments made in 2007 and 2008. CONCLUSIONS There is little evidence to support the concern of some general practitioners that low response rates and selective non-response bias have led to systematic unfairness in payments attached to questionnaire scores. The study raises issues relating to the validity and reliability of payments based on patient surveys and provides lessons for the UK and for other countries considering the use of patient experience as part of pay for performance schemes.
The remarkable gene knockdown technique of RNAi has opened exciting new avenues for genetic screens in model organisms and human cells. Here we describe the current state of the art for RNAi screening, and stress the importance of well-designed assays and of analytical approaches for large-scale screening experiments, from high-throughput screens using simplified homogenous assays to microscopy and whole-animal experiments. Like classical genetic screens in the past, the success of large-scale RNAi surveys depends on a careful development of phenotypic assays and their interpretation in a relevant biological context.
The objective of the present study was to examine consumer preference and consumption behaviour with respect to the health benefits of wine for two contextually and culturally diverse consumer groups, namely Koreans and Australians. Participants were required to be wine consumers over the age of 18. Responses were collected by means of an online questionnaire. The results indicated that perceived health benefits of red wine were higher in the Australian sample than the Korean sample. Similarly, Australian consumers had more health related wine knowledge than Korean consumers. Red wine was the preferred wine style for both Korean and Australian consumers; however, the proportion of preference for red wine was significantly higher in the Korean sample. With respect to the expenditure on wine products, AUD$11–$19 was the preferred price range for both groups. The results also indicated that health-oriented wine is more attractive to Korean consumers than Australian consumers. In relation to gender, Korean women preferred red wine as much as men, but Australian women consumed significantly more white wine than men. Such findings inform winemakers and wine marketers on the appropriateness of weighting wine production and marketing to health aspects in order to maximize consumer
I present methods for assessing the relative effectiveness of two treatments when they have not been compared directly in a randomized trial but have each been compared to other treatments. These network meta-analysis techniques allow estimation of both heterogeneity in the effect of any given treatment and inconsistency ('incoherence') in the evidence from different pairs of treatments. A simple estimation procedure using linear mixed models is given and used in a meta-analysis of treatments for acute myocardial infarction.
Likelihood ratios are one of the best measures of diagnostic accuracy, although they are seldom used, because interpreting them requires a calculator to convert back and forth between “probability” and “odds” of disease. This article describes a simpler method of interpreting likelihood ratios, one that avoids calculators, nomograms, and conversions to “odds” of disease. Several examples illustrate how the clinician can use this method to refine diagnostic decisions at the bedside.
Receiver operating characteristic (ROC) curves are used to describe and compare the performance of diagnostic technology and diagnostic algorithms. This paper refines the statistical comparison of the areas under two ROC curves derived from the same set of patients by taking into account the correlation between the areas that is induced by the paired nature of the data. The correspondence between the area under an ROC curve and the Wilcoxon statistic is used and underlying Gaussian distributions (binormal) are assumed to provide a table that converts the observed correlations in paired ratings of images into a correlation between the two ROC areas. This between-area correlation can be used to reduce the standard error (uncertainty) about the observed difference in areas. This correction for pairing, analogous to that used in the paired t-test, can produce a considerable increase in the statistical sensitivity (power) of the comparison. For studies involving multiple readers, this method provides a measure of a component of the sampling variation that is otherwise difficult to obtain.
OBJECTIVES To examine the effect of routinely administered psychiatric questionnaires on the recognition, management, and outcome of psychiatric disorders in non-psychiatric settings. DATA SOURCES Embase, Medline, PsycLIT, Cinahl, Cochrane Controlled Trials Register, and hand searches of key journals. METHODS A systematic review of randomised controlled trials of the administration and routine feedback of psychiatric screening and outcome questionnaires to clinicians in non-psychiatric settings. Narrative overview of key design features and end points, together with a random effects quantitative synthesis of comparable studies. MAIN OUTCOME MEASURES Recognition of psychiatric disorders after feedback of questionnaire results; interventions for psychiatric disorders; and outcome of psychiatric disorders. RESULTS Nine randomised studies were identified that examined the use of common psychiatric instruments in primary care and general hospital settings. Studies compared the effect of the administration of these instruments followed by the feedback of the results to clinicians, with administration with no feedback. Meta-analytic pooling was possible for four of these studies (2457 participants), which measured the effect of feedback on the recognition of depressive disorders. Routine administration and feedback of scores for all patients (irrespective of score) did not increase the overall rate of recognition of mental disorders such as anxiety and depression (relative risk of detection of depression by clinician after feedback 0.95, 95% confidence interval 0.83 to 1.09). Two studies showed that routine administration followed by selective feedback for only high scorers increased the rate of recognition of depression (relative risk of detection of depression after feedback 2.64, 1.62 to 4.31). This increased recognition, however, did not translate into an increased rate of intervention. Overall, studies of routine administration of psychiatric measures did not show an effect on patient outcome. CONCLUSIONS The routine measurement of outcome is a costly exercise. Little evidence shows that it is of benefit in improving psychosocial outcomes of those with psychiatric disorder managed in non-psychiatric settings.
© Joanna Moncrieff 2013. All rights reserved. A challenging reappraisal of the history of antipsychotics, revealing how they were transformed from neurological poisons into magical cures, their benefits exaggerated and their toxic effects minimized or ignored.
QUESTION Do clinical tests accurately diagnose rotator cuff pathology? DESIGN A systematic review of investigations into the diagnostic accuracy of clinical tests for rotator cuff pathology. PARTICIPANTS People with shoulder pain who underwent clinical testing in order to diagnose rotator cuff pathology. OUTCOME MEASURES The diagnostic accuracy of clinical tests was determined using likelihood ratios. RESULTS Thirteen studies met the inclusion criteria. The 13 studies evaluated 14 clinical tests in 89 separate evaluations of diagnostic accuracy. Only one evaluation, palpation for supraspinatus ruptures, resulted in significant positive and negative likelihood ratios. Eight of the 89 evaluations resulted in either significant positive or negative likelihood ratios. However, none of these eight positive or negative likelihood ratios were found in other studies. Of the 89 evaluations of clinical tests 71 (80%) did not result in either significant positive or negative likelihood ratio evaluations across different studies. CONCLUSION Overall, most tests for rotator cuff pathology were inaccurate and cannot be recommended for clinical use. At best, suspicion of a rotator cuff tear may be heightened by a positive palpation, combined Hawkins/painful arc/infraspinatus test, Napoleon test, lift-off test, belly-press test, or drop-arm test, and it may be reduced by a negative palpation, empty can test or Hawkins-Kennedy test.