Optimal Strategies for Reporting Pain in Clinical Trials and Systematic Reviews: Recommendations from an OMERACT 12 Workshop Subgroup Analysis of Trials Is Rarely Easy (SATIRE): a study protocol for a systematic review to characterize the analysis, reporting, and claim of subgroup effects in randomized trials Seeing the forests and the trees—innovative approaches to exploring heterogeneity in systematic reviews of complex interventions to enhance health system decision-making: a protocol Reports of clinical trials should begin and end with up-to-date systematic reviews of other relevant evidence: a status report. A systematic review of shared decision making interventions in chronic conditions: a review protocol A methodological survey of the analysis, reporting and interpretation of Absolute Risk ReductiOn in systematic revieWs (ARROW): a study protocol Systematic reviews in public health: old chestnuts and new challenges. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision-maker-researcher partnership systematic review Three challenges described for identifying participants with missing data in trials reports, and potential solutions suggested to systematic reviewers. Towards systematic reviews that inform health care management and policy-making Systematic Reviews: Synthesis of Best Evidence for Clinical Decisions Mapping the Cochrane evidence for decision making in health care. How Quickly Do Systematic Reviews Go Out of Date? A Survival Analysis Effectiveness of education in evidence-based healthcare: the current state of outcome assessments and a framework for future evaluations. Rayyan—a web and mobile app for systematic reviews Using Numerical Results from Systematic Reviews in Clinical Practice Systematic comparison of study quality criteria. Evidence-based medicine and the challenge of low back pain: where are we now? From evidence to best practice in the management of fractures of the distal radius in adults: working towards a research agenda Can you believe what you read in the papers? Systematic review of outcome measures in pediatric eosinophilic esophagitis treatment trials Balancing the strengths of systematic and narrative reviews. Systematic Reviews of Diagnostic Test Accuracy
Objective . Pain is a patient-important outcome , but current reporting in r and omized controlled trials and systematic review s is often suboptimal , impeding clinical interpretation and decision making . Methods . A working group at the 2014 Outcome Measures in Rheumatology ( OMERACT 12 ) was convened to provide guidance for reporting treatment effects regarding pain for individual studies and systematic review s. Results For individual trials , authors should report , in addition to mean change , the proportion of patients achieving 1 or more thresholds of improvement from baseline pain ( e.g. , ≥ 20 % , ≥ 30 % , ≥ 50 % ) , achievement of a desirable pain state ( e.g. , no worse than mild pain ) , and /or a combination of change and state . Effects on pain should be accompanied by other patient-important outcomes to facilitate interpretation . When pooling data for meta analysis , authors should consider converting all continuous measures for pain to a 100 mm visual analog scale ( VAS ) for pain and use the established , minimally important difference ( MID ) of 10 mm , and the conventionally used , appreciably important differences of 20 mm , 30 mm , and 50 mm , to facilitate interpretation . Effects ≤ 0.5 units suggest a small or very small effect . To further increase interpretability , the pooled estimate on the VAS should also be transformed to a binary outcome and expressed as a relative risk and risk difference . This transformation can be achieved by calculating the probability of experiencing a treatment effect greater than the MID and the thresholds for appreciably important differences in pain reduction in the control and intervention groups . Conclusion . Presentation of relative effects regarding pain will facilitate interpretation of treatment effects Background Subgroup analyses in r and omized trials examine whether effects of interventions differ between subgroups of study population s according to characteristics of patients or interventions . However , findings from subgroup analyses may be misleading , potentially result ing in suboptimal clinical and health decision making . Few studies have investigated the reporting and conduct of subgroup analyses and a number of important questions remain unanswered . The objectives of this study are : 1 ) to describe the reporting of subgroup analyses and cl aims of subgroup effects in r and omized controlled trials , 2 ) to assess study characteristics associated with reporting of subgroup analyses and with cl aims of subgroup effects , and 3 ) to examine the analysis , and interpretation of subgroup effects for each study 's primary outcome . Methods We will conduct a systematic review of 464 r and omized controlled human trials published in 2007 in the 118 Core Clinical Journals defined by the National Library of Medicine . We will r and omly select journal articles , stratified in a 1:1 ratio by higher impact versus lower impact journals . According to 2007 ISI total citations , we consider the New Engl and Journal of Medicine , JAMA , Lancet , Annals of Internal Medicine , and BMJ as higher impact journals . Teams of two review ers will independently screen full texts of reports for eligibility , and abstract data , using st and ardized , pilot-tested extraction forms . We will conduct univariable and multivariable logistic regression analyses to examine the association of pre-specified study characteristics with reporting of subgroup analyses and with cl aims of subgroup effects for the primary and any other outcomes . Discussion A clear underst and ing of subgroup analyses , as currently conducted and reported in published r and omized controlled trials , will reveal both strengths and weaknesses of this practice . Our findings will contribute to a set of recommendations to optimize the conduct and reporting of subgroup analyses , and cl aim and interpretation of subgroup effects in r and omized trials Background To improve quality of care and patient outcomes , health system decision-makers need to identify and implement effective interventions . An increasing number of systematic review s document the effects of quality improvement programs to assist decision-makers in developing new initiatives . However , limitations in the reporting of primary studies and current meta- analysis methods ( including approaches for exploring heterogeneity ) reduce the utility of existing syntheses for health system decision-makers . This study will explore the role of innovative meta- analysis approaches and the added value of enriched and up date d data for increasing the utility of systematic review s of complex interventions . Methods / Design We will use the data set from our recent systematic review of 142 r and omized trials of diabetes quality improvement programs  to evaluate novel approaches for exploring heterogeneity . These will include exploratory methods , such as multivariate meta-regression analyses and all-subsets combinatorial meta- analysis . We will then up date our systematic review to include new trials and enrich the data set by surveying authors of all included trials . In doing so , we will explore the impact of variables not , reported in previous publications , such as details of study context , on the effectiveness of the intervention . We will use innovative analytical methods on the enriched and up date d data set to identify key success factors in the implementation of  quality improvement interventions  for diabetes . Decision-makers will be involved throughout to help identify and prioritize variables to be explored and to aid in the interpretation and dissemination of results . Discussion This study will inform future systematic review s of complex interventions and describe the value of enriching and updating data for exploring heterogeneity in meta- analysis . It will also result in an up date d comprehensive systematic review of diabetes quality improvement interventions that will be useful to health system decision-makers in developing interventions to improve outcomes for people with diabetes . Systematic review registration PROSPERO registration no. OBJECTIVE Scientific and ethical justification for new clinical trials requires them to have been design ed in the light of scientifically defensible assessment s of relevant previous research . Reliable interpretation of the results of new clinical trials entails setting them in the context of up date s of the review s upon which they were deemed scientifically and ethically justifiable . We have shown previously that most reports of r and omized trials published in five general medical journals in May 1997 and in May 2001 failed to set their results in the context of the findings from similar research . In the current study , we assess whether there had been progress in this respect in 2005 and also investigate the extent to which reports begin by referring to systematic review s providing the justification for the new research reported . DESIGN Assessment of the Introduction and Discussion sections in all reports of r and omized trials published during May 2005 in five general medical journals . SETTING Reports of r and omized trials in five general medical journals . PARTICIPANTS Annals of Internal Medicine , BMJ , JAMA , Lancet and New Engl and Journal of Medicine . INTERVENTIONS None . MAIN OUTCOME MEASURES The inclusion or mention of one or more systematic review s in the Introduction or Discussion section of each report assessed . RESULTS We found 18 reports of r and omized trials . The Introduction sections referred to systematic review s in five ( 27 % ) of these reports . None of the discussion sections of the 15 reports of trials that were not the first published trials to address the question studied placed the results of the new trial in the context of an up date d systematic review of other research . Although reference was made to relevant systematic review s in five of these 15 reports , there was no integration - quantitative or qualitative - of the results of the new trials in an up date of these review s. In the remaining ten reports there was no evidence that any systematic attempt had been made to set the new results in the context of previous trials . CONCLUSIONS There is no evidence of progress between 1997 and 2005 in the proportion of reports of trials published in general medical journals which discussed new results within the context of up-to- date systematic review s of relevant evidence from other controlled trials . Although the proportion of trials referring to systematic review s in Discussion sections has increased , the majority of reports continued to fail even to do this . Similarly , most research ers appear not to have considered a systematic review when design ing their trial . Research ers and journal editors do a disservice to the interests of the public and others involved in healthcare decision-making by acquiescing in this situation Background Chronic conditions are a major source of morbidity , mortality and cost worldwide . Shared decision making is one way to improve care for patients with chronic conditions . Although it has been widely studied , the effect of shared decision making in the context of chronic conditions is unknown . Methods / Design We will perform a systematic review with the objective of determining the effectiveness of  shared decision making interventions  for persons diagnosed with chronic conditions . We will search the following data bases for relevant articles : PubMed , Scopus , Ovid MEDLINE , Ovid EMBASE , Ovid EBM Review s CENTRAL , CINAHL , and Ovid PsycInfo . We will also search clinical trial registries and contact experts in the field to identify additional studies . We will include r and omized controlled trials study ing shared decision making interventions in patients with chronic conditions who are facing an actual decision . Shared decision making interventions will be defined as any intervention aim ing to facilitate or improve patient and /or clinician engagement in a decision making process . We will describe all studies and assess their quality . After adjusting for missing data , we will analyze the effect of shared decision making interventions  on outcomes in chronic conditions overall and stratified by condition . We will evaluate outcomes according to an importance ranking informed by a variety of stakeholders . We will perform several exploratory analyses including the effect of author contact on the estimates of effect . Discussion We anticipate that this systematic review may have some limitations such as heterogeneity and imprecision ; however , the results will contribute to improving the quality of care for individuals with chronic conditions and facilitate a process that allows decision making that is most consistent with their own values and preferences . Trial registration PROSPERO Registration Number : Background Clinicians , providers and guideline panels use absolute effects to weigh the advantages and downsides of treatment alternatives . Relative measures have the potential to mislead readers . However , little is known about the reporting of absolute measures in systematic review s. The objectives of our study are to determine the proportion of systematic review s that report absolute measures of effect for the most important outcomes , and ascertain how they are analyzed , reported and interpreted . Methods / design We will conduct a method ological survey of systematic review s published in 2010 . We will conduct a 1:1 stratified r and om sampling of Cochrane vs. non-Cochrane systematic review s. We will calculate the proportion of systematic review s reporting at least one absolute estimate of effect for the most patient-important outcome for the comparison of interest . We will conduct multivariable logistic regression analyses with the reporting of an absolute estimate of effect as the dependent variable and pre-specified study characteristics as the independent variables . For systematic review s reporting an absolute estimate of effect , we will document the methods used for the analysis , reporting and interpretation of the absolute estimate . Discussion Our method ological survey will inform current practice s regarding reporting of absolute estimates in systematic review s. Our findings may influence recommendations on reporting , conduct and interpretation of absolute estimates . Our results are likely to be of interest to systematic review authors , funding agencies , clinicians , guideline developers and journal editors The Bulletin ’s editorial team has decided to encourage systematic review s. This is an important decision and is to be welcomed . However it is possible that it will not be received positively by all . Some may feel that systematic review s are not suitable for answering wider public health questions , and that the new section will simply result in the publication of systematic review s addressing narrowly focused , clinical questions with a focus on r and omized controlled trials alone.1 There is no reason why this should be so , and there are far too many examples of systematic review s of non- clinical interventions ( including government policies ) , which include non-r and omized studies , to list.2 Systematic review s of qualitative research are also becoming more common.3 Nonetheless misconceptions about the scope and flexibility of systematic review s still surface occasionally and it never fails to surprise me when I stumble across one of these hoary old chestnuts . If it really were true that systematic review s were only for simple , individual-level interventions , systematic review ers working in public health would be very concerned . After all , public health problems require us to draw on complex sets of qualitative as well as quantitative evidence ; and some policy interventions have never been subjected to r and omized controlled trials ( RCTs ) but have been evaluated using other approaches ; everything from controlled and uncontrolled before- and -after studies , to time series analyses , to qualitative methods . In such cases , systematic review s that focused on RCTs alone would have little to say and we would end up producing many “ empty review s ” , which contain no studies at all . These would be undoubtedly quicker to do and quicker to read than the typical systematic review , but would be of limited use for making policy . However this is not the case . In public health we already have a wealth of review s that prioritize RCTs where they are available , but which draw upon a range of other evidence where they are appropriate to answering the review question .2 Take , as an example , transport policies , an important social determinant of health.4 Public health decision-makers have been interested in the effects on health of building new roads for decades , but there has never been a r and omized controlled trial , for obvious reasons . Yet it would make no sense to cl aim that there is no evidence to be review ed ; rather , there have been many controlled and uncontrolled studies that have examined the effects of new roads on respiratory symptoms , injuries , community severance , disturbance and a variety of other outcomes of public health importance . These studies have in fact been systematic ally review ed.5 Many other examples of review s of complex interventions that impact on public health could be given , which appear on the Cochrane Data base and elsewhere,6,7 and such review s are the main focus of the recently-established Cochrane Public Health Review Group . It is also worth noting that both the Cochrane and Campbell Collaboration include increasing numbers of review s that are relevant to low- and middle- income countries,8 though there is a particular need for more systematic review s that consider the effects on equity of the interventions that they include.9 Currently systematic review s have a “ utilitarian bias ” – they tend to be concerned more with the effects on population s and average effects than with distributional effects and impacts in disadvantaged subgroups . It is to be hoped that systematic review s su bmi tted to the Bulletin will routinely consider the effects of interventions on health inequities . The Cochrane Health Equity Field ( http://equity.cochrane.org/en/index.html ) was set up explicitly to further this agenda , to encourage systematic review authors to explicitly assess the effects of interventions not only on the whole population , but on the disadvantaged . So where does this leave non- systematic review s ? Should every review be a systematic review ? This is a difficult question to answer in a short editorial . My own view is that not all review s need to be systematic review s ; there is still a place for review papers that provide a broad overview , and that discuss a range of evidence and make a contribution to wider debates about what might work in particular setting s. However , while such discussion s help place evidence in context and suggest how it may be used , they should not be confused with the evidence -based conclusions of a transparent , scientific review , which systematic ally attempts to find all the relevant evidence , appraises its strengths and limitations in a transparent fashion , and draws that evidence together in such a way that the more robust studies are given greater weight . Finally , the challenges are many . Evidence on interventions to improve public health is in short supply , particularly evidence on social determinants . Systematic review ers therefore face a real challenge in making best use of the sometimes poor , often sparse and usually heterogeneous evidence available to them . It is easy to set narrow inclusion criteria for a review and then sift through the evidence before concluding that there is n’t enough – and what there is , is n’t very good anyway . Such “ evidential nihilism ” is probably not helpful to decision-makers , and public health systematic review ers need to continue to develop new methods and better frameworks within which different types of research evidence can be integrated to inform decision-making . Publishing systematic review s in the Bulletin should give an added impetus to this ongoing work . Background Computerized clinical decision support systems are information technology-based systems design ed to improve clinical decision-making . As with any healthcare intervention with cl aims to improve process of care or patient outcomes , decision support systems should be rigorously evaluated before widespread dissemination into clinical practice . Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake . The objective of this research was to form a partnership of healthcare providers , managers , and research ers to review r and omized controlled trials assessing the effects of computerized decision support for six clinical application areas : primary preventive care , therapeutic drug monitoring and dosing , drug prescribing , chronic disease management , diagnostic test ordering and interpretation , and acute care management ; and to identify study characteristics that predict benefit . Methods The review was undertaken by the Health Information Research Unit , McMaster University , in partnership with Hamilton Health Sciences , the Hamilton , Niagara , Haldim and , and Brant Local Health Integration Network , and pertinent healthcare service teams . Following agreement on information needs and interests with decision-makers , our earlier systematic review was up date d by search ing Medline , EMBASE , EBM Review data bases , and Inspec , and review ing reference lists through 6 January 2010 . Data extraction items were exp and ed according to input from decision-makers . Authors of primary studies were contacted to confirm data and to provide additional information . Eligible trials were organized according to clinical area of application . We included r and omized controlled trials that evaluated the effect on practitioner performance or patient outcomes of patient care provided with a  computerized clinical decision support system compared with patient care without such a system . Results Data will be summarized using descriptive summary measures , including proportions for categorical variables and means for continuous variables . Univariable and multivariable logistic regression models will be used to investigate associations between outcomes of interest and study specific covariates . When reporting results from individual studies , we will cite the measures of association and p-values reported in the studies . If appropriate for groups of studies with similar features , we will conduct meta-analyses . Conclusion A decision-maker- research er partnership provides a model for systematic review s that may foster knowledge translation and uptake OBJECTIVE To categorize the challenges in determining the extent of missing participant data in r and omized trials and suggest potential solutions for systematic review authors . STUDY DESIGN AND SETTING During the process of updating a series of Cochrane systematic review s on the topic of anticoagulation in patients with cancer , we identified challenges and used an iterative approach to improve , and a consensus process to agree on the challenges identified , and to suggest potential ways of dealing with them . The five systematic review s included 58 trials and 75 meta-analyses for patient-important dichotomous outcomes with 27,037 r and omized participants . RESULTS We identified three categories of challenges : ( 1 ) Although systematic review ers require information about missing data to be reported by outcome , trialists typically report the information by participant ; ( 2 ) It is not always clear whether the trialists followed up participants in certain categories ( e.g. , noncompliers ) , that is , whether some categories of participants did or did not have missing data ; ( 3 ) It is not always clear how the trialists dealt with missing data in their analysis ( e.g. , exclusion from the denominator vs. assumptions made for the numerator ) . We discuss potential solutions for each one of these challenges and suggest further research work . CONCLUSION Current reporting of missing data is often not explicit and transparent , and although our potential solutions to problems of suboptimal reporting may be helpful , reliable and valid characterization of the extent and nature of missing data remains elusive . Reporting of missing data in trials needs further improvement Objectives To identify ways to improve the usefulness of systematic review s for health care managers and policy-makers that could then be evaluated prospect ively . Methods We systematic ally review ed studies of decision-making by health care managers and policy-makers , conducted interviews with a purposive sample of them in Canada and the United Kingdom ( n=29 ) , and review ed the websites of research funders , producers/purveyors of research , and journals that include them among their target audiences ( n=45 ) . Results Our systematic review identified that factors such as interactions between research ers and health care policy-makers and timing/timeliness appear to increase the prospect s for research use among policy-makers . Our interviews with health care managers and policy-makers suggest that they would benefit from having information that is relevant for decisions highlighted for them ( e.g. context ual factors that affect a review 's local applicability and information about the benefits , harms/risks and costs of interventions ) and having review s presented in a way that allows for rapid scanning for relevance and then grade d entry ( such as one page of take-home messages , a three-page executive summary and a 25-page report ) . Managers and policy-makers have mixed views about the helpfulness of recommendations . Our analysis of websites found that context ual factors were rarely highlighted , recommendations were often provided and grade d entry formats were rarely used . Conclusions Research ers could help to ensure that the future flow of systematic review s will better inform health care management and policy-making by involving health care managers and policy-makers in their production and better highlighting information that is relevant for decisions . Research funders could help to ensure that the global stock of systematic review s will better inform health care management and policy-making by supporting and evaluating local adaptation processes such as developing and making available online more user-friendly ‘ front ends ’ for potentially relevant systematic review At the end of a long week in the office , you sink back into your chair , reflecting on some of the more memorable patients you cared for and counseled . Through gentle history taking , you discovered that urinary incontinence is the underlying cause of an elderly patient 's increasing social isolation . During a careful physical examination , you detected bruising on the torso of a woman with chronic headaches and began to explore the longst and ing abusive relationship between the woman and her alcoholic partner . You discontinued procainamide therapy in a 72-year-old man who had asymptomatic premature ventricular contractions after myocardial infa rct ion . To prevent bleeding from esophageal varices , you started -blocker therapy in a woman with long-st and ing cryptogenic cirrhosis and portal hypertension . In couples ' therapy , discussing the future quality of life of a middle-aged gay man with human immunodeficiency virus infection , you journeyed through emotionally intense dialogue about advance directives . You presented the risk factors for major and minor bleeding to a 39-year-old woman who was considering warfarin therapy because of recently diagnosed atrial fibrillation and valvular heart disease . You listened to , made diagnoses for , treated , advised , and comforted many patients . Yet there were some hiccoughs in your practice along the way . You stumbled while debating the pros and cons of breast cancer screening with a healthy 48-year-old woman who has been staying current with information on the Internet . You question ed the merits of a personalized walking program suggested to you by a motivated 66-year-old man with severe claudication . Explaining that you wanted to review the best current evidence on these issues , you resolved to address your uncertainties before these patients made their next office visits , in a week 's time . Sighing deeply , you acknowledge that you have little time to read . You subscribe to three journals , which you browse months after they arrive-either when your journal stack becomes precariously high or when your guilt is sufficiently motivational . You sometimes find the conclusions of individual articles conflicting or confusing . You know that some of the decisions and suggestions you made this week , specifically your decisions about stopping procainamide therapy and starting -blocker therapy and your advice about bleeding risks from anticoagulant therapy , were based on the best current research evidence [ 1 - 3 ] . On the other h and , your patients ' inquiries about breast cancer screening and exercise treatment for claudication highlight your need for a concise , current , rigorous synthesis of the best available evidence on each of these topics : in brief , a systematic review [ 4 , 5 ] . Incorporating Research Evidence into Clinical Decision Making The foregoing scenario is familiar to practitioners . In a typical week , we encounter patients with diverse problems ; exercise numerous clinical , interpersonal , and technical skills ; and make many decisions . The factors that affect these decisions and their outcomes are complex . For instance , each patient has unique sociodemographic characteristics , cultural circumstances , and personal preferences . Each physician has unique knowledge , experiences , and values . Moreover , practitioners and their patients make decisions within the context of a rapidly changing health care system that influences the availability , accessibility , and cost of diagnostic tests and therapies [ 6 ] . Timely , useful evidence from the biomedical literature should be an integral component of clinical decision making . If one treatment has been shown to be better than another , we need to know , so that we can recommend the treatment to the appropriate patients . The worldwide effort to develop new tests and treatments , and to determine their usefulness , has never been stronger , and our patients and their families expect us to be fonts of the knowledge that results from this effort [ 7 ] . Unfortunately , it is easy for current best research evidence to pass us by [ 8 ] . We may lack the time , motivation , and basic skills needed to find , critically appraise , and synthesize information , all of which we must do if we are to integrate the results of original studies into our practice . Fortunately , several potent methods are emerging that can greatly enhance our ability to interpret and apply research evidence ; foremost among them is the systematic review . This article begins a series in Annals that will examine systematic review s in detail and explore their many applications . Systematic review s represent the best chance that most practitioners will have to underst and and accurately apply the key signals arising from the robust and increasingly productive search for solutions to medical problems . A properly conducted systematic review faithfully summarizes the evidence from all relevant studies on the topic of interest , and it does so concisely and transparently . What Is a Systematic Review ? Systematic review s are scientific investigations in themselves , with pre-planned methods and an assembly of original studies as their subjects . They synthesize the results of multiple primary investigations by using strategies that limit bias and r and om error [ 9 , 10 ] . These strategies include a comprehensive search of all potentially relevant articles and the use of explicit , reproducible criteria in the selection of articles for review . Primary research design s and study characteristics are appraised , data are synthesized , and results are interpreted . When the results of primary studies are summarized but not statistically combined , the review may be called a qualitative systematic review . A quantitative systematic review , or meta- analysis , is a systematic review that uses statistical methods to combine the results of two or more studies . The term overview is sometimes used to denote a systematic review , whether quantitative or qualitative . Summaries of research that lack explicit descriptions of systematic methods are often called narrative review s. Review articles are one type of integrative publication ; practice guidelines , economic evaluations , and clinical decision analyses are others . These other types of integrative articles often incorporate the results of systematic review s. For example , practice guidelines are systematic ally developed statements intended to assist practitioners and patients with decisions about appropriate health care for specific clinical circumstances [ 11 ] . Evidence -based practice guidelines are based on systematic review s of the literature , appropriately adapted to local circumstances and values . Economic evaluations compare both the costs and the consequences of different courses of action ; the knowledge of consequences that are considered in these evaluations is often generated by systematic review s of primary studies . Decision analyses quantify both the likelihood and the valuation of the expected outcomes associated with competing alternatives . Differences between Systematic and Narrative Review s All review s , narrative and systematic alike , are retrospective , observational research studies and are therefore subject to systematic and r and om error . Accordingly , the quality of a review - and thus its worth-depends on the extent to which scientific review methods have been used to minimize error and bias . This is the key feature that distinguishes traditional narrative review s from systematic review s ( Table 1 ) . If a review is prepared according to the steps outlined in the right column of Table 1 , it is more likely to be systematic and to provide unbiased conclusions . If review methods approximate those found in the middle column of Table 1 , the article is more likely to be a narrative review , and the conclusions are less likely to be based on an unbiased summary of all relevant evidence . Table 1 . Differences between Narrative Review s and Systematic Review s Systematic review s are generated to answer specific , often narrow , clinical questions in depth . These questions can be formulated explicitly according to four variables : a specific population and setting ( such as elderly out patients ) , the condition of interest ( for example , hypertension ) , an exposure to a test or treatment ( such as pharmacologic management ) , and one or more specific outcomes ( such as cardiovascular and cerebrovascular events and mortality ) [ 12 ] . Thus , an example of a well-formulated , clinical ly relevant question is , Does pharmacologic treatment of hypertension in the elderly prevent strokes and myocardial infa rct ions or delay death ? If the question that is driving the review is not clear from the title , abstract , or introduction , or if no methods section is included , the paper is more likely to be a narrative review than a systematic review [ 13 ] . Most narrative review articles deal with a broad range of issues related to a given topic rather than addressing a particular issue in depth [ 9 ] . For example , a narrative review on diabetes ( such as that which might be found in a textbook chapter ) might include sections on the physiology and pathophysiology of carbohydrate , lipid , and protein metabolism ; the epidemiology of and prognosis associated with diabetes ; diagnostic and screening approaches ; and preventive , therapeutic , rehabilitative , and palliative interventions . Thus , narrative review s may be most useful for obtaining a broad perspective on a topic ; they are less often useful in furnishing quantitative answers to specific clinical questions . Narrative review s are appropriate for describing the history or development of a problem and its management . Narrative review s may better describe cutting-edge developments if research is scant or preliminary or if studies are very limited by flawed design or execution [ 13 ] . They may be particularly useful for discussing data in light of underlying theory and context . Narrative review s can draw analogies and can conceptually integrate two independent fields of research , such as RATIONALE AND AIM Over the past 12 years , thous and s of authors working with the Cochrane Collaboration around the world have produced systematic review s to reduce uncertainty in health care decision making . We evaluated the conclusions from Cochrane systematic review s of r and omized controlled trials in terms of their recommendations for clinical practice and research . METHODS In our cross-sectional study of systematic review s published in the Cochrane Library , we r and omly selected and analysed completed systematic review s published across all 50 Cochrane Collaborative Review Groups . RESULTS We analysed 1016 completed systematic review s. Of these , 44 % concluded that the interventions studied were likely to be beneficial , of which 1 % recommended no further research and 43 % recommended additional research . Also , 7 % of the review s concluded that the interventions were likely to be harmful , of which 2 % did not recommend further studies and 5 % recommended additional studies . In total , 49 % of the review s reported that the evidence did not support either benefit or harm , of which 1 % did not recommend further studies and 48 % recommended additional studies . Overall , 96 % of the review s recommended further research . CONCLUSIONS Cochrane systematic review s were about evenly split between those in which the authors concluded that at least one of the interventions was beneficial and those in which the evidence neither supported nor refuted the intervention tested . The Cochrane Collaboration needs to include clinical trial protocol summaries with a study design optimized to answer the relevant research questions Context Clinicians rely on systematic review s for current , evidence -based information . Contribution This survival analysis of 100 meta-analyses indexed in ACP Journal Club from 1995 to 2005 found that new evidence that substantively changed conclusions about the effectiveness or harms of therapies arose frequently and within relatively short time periods . The median survival time without substantive new evidence for the meta-analyses was 5.5 years . Significant new evidence was already available for 7 % of the review s at the time of publication and became available for 23 % within 2 years . Implication Clinical ly important evidence that alters conclusions about the effectiveness and harms of treatments can accumulate rapidly . The Editors Systematic review s have become increasingly common in recent years ( 1 ) and are recommended by many as the best sources of evidence to guide both clinical decisions ( 2 ) and health care policy ( 3 ) . For systematic review s to fulfill these roles , their findings must remain relatively stable for at least several years or effective mechanisms must exist for alerting end users to important changes in evidence . Yet , surprisingly little research has assessed the extent to which systematic review s become out of date or the rate at which this occurs ( 47 ) . Some organizations , such as the Cochrane Collaboration , recommend updating systematic review s every 2 years , but few empirical data guide this or other recommendations about updating . We sought to determine how quickly systematic review s meet explicitly defined criteria for changes in evidence of sufficient importance to warrant updating . We also sought to identify predictors of survival time , the time to such important changes in evidence . Survival time might vary depending on many factors , including the type of question posed by the original review ( for example , therapeutic or diagnostic ) , the types of studies included ( for example , r and omized trials or observational studies ) , and whether the systematic review provided quantitative synthesis . To limit such variation , we focused on systematic review s of r and omized , controlled trials that evaluated therapeutic benefit or harm by providing quantitative synthesis ( meta- analysis ) for at least 1 outcome . Methods Study Design and Sample We used a quasi-r and om process ( alphabetical sort order by author ) to select 100 systematic review s that were indexed in ACP Journal Club with an accompanying commentary between January 1995 and December 2005 ( with a search date no later than 31 December 2004 to ensure at least 1 full year for new evidence to appear ) . We chose this sampling frame because ACP Journal Club selects systematic review s that meet explicit quality st and ards and are deemed directly relevant to clinical practice ( 8) . We regarded the sample size of 100 as sufficiently large to achieve suitably narrow confidence intervals and to permit evaluation of up to 5 potential predictors of survival . Eligibility Criteria Eligible review s evaluated the benefit or harm of a specific drug , class of drug , device , or procedure ( invasive procedure or surgery ) and included r and omized or quasi-r and omized , controlled trials . We excluded evaluations of alternative and complementary medicines because the stability of review s of such therapies might differ substantially from review s of conventional therapies . We required that review s provide a point estimate and 95 % confidence interval for at least 1 outcome in the form of a relative risk , odds ratio , or absolute risk difference for binary outcomes and weighted mean differences for continuous outcomes . We excluded meta-analyses of individual-patient data , meta-regressions , and indirect meta-analyses because of the difficulty of determining whether new data would alter previous quantitative results . Two team members independently assessed eligibility , with disagreements resolved by consensus involving a third review er . When more than 1 review on the same topic was identified , only the earliest was included . Search ing For each review , search es for new trials included identifying new systematic review s on the same topic , su bmi tting relevant content terms to the Clinical Queries function in Ovid , applying the Related Articles function in PubMed to the 3 largest and the 3 most recent trials in the original review ( up to 6 trials in total ) , and using Scopus ( www . scopus .com/ scopus /home.url ) to identify new r and omized trials that cited the original review . When these search strategies yielded no eligible new trials , we conducted more comprehensive electronic search es and review ed relevant chapters in such sources as Clinical Evidence and UpTo Date to ensure that we had not missed new trials . Team members who had background s in both medicine and clinical research screened citations retrieved by the preceding methods to identify trials that would have met the inclusion criteria in the original review . Retrieved articles were screened in chronological order to ascertain quantitative or qualitative signals for the need for updating . The review protocol stopped when any criteria for updating were met . Each systematic review was discussed in detail , with the final statussignal for updating was or was not detectedadjudicated by consensus ( Figure 1 ) . Figure 1 . Overall process for determining updating status . ACP Journal Club Signals for the Need to Up date Systematic Review s In design ing criteria for comparing new findings with those in a previous review , we adapted methods used by other investigators to address similar problems with comparing 2 sets of results relating to the same question ( 913 ) , such as r and omized and nonr and omized studies of the same intervention . These investigators identified conflicting findings among different publications using a combination of quantitative thresholds for differences in effect magnitude and qualitative judgments about the language used to describe the results . We have similarly conceptualized quantitative and qualitative signals of potential changes in evidence that are sufficiently important to warrant updating previous systematic review s. Quantitative Signals Quantitative signals consisted of a change in statistical significance or relative change in effect magnitude of at least 50 % . We restricted these changes to those involving 1 of the primary outcomes of the original review or any mortality outcome . We also ignored trivial changes in statistical significance when the original and up date d meta-analytic results both had P values between 0.04 and 0.06so that quantitative signals of changes in evidence would represent robust indicators of the need to up date previous review s. Quantitative signals were detected by combining data from eligible new trials with the previous results using a fixed-effects approach . Use of fixed-effect models allowed pooling of the new trials with the previous meta-analytic result , as opposed to having to obtain original data from all of the included trials in each of 100 systematic review s. Although r and om-effects models are usually preferred to avoid spurious precision in the face of heterogeneity , our goal was to detect potential changes in evidence that would warrant a formal up date , not produce exact estimates of the up date d results . Qualitative Signals Qualitative signals included new information about harm sufficient to affect clinical decision making , important caveats to the original results , emergence of a superior alternate therapy , and important changes in certainty or direction of effect . Qualitative signals were detected by using explicit criteria for comparing the language in the original review with descriptions of findings in new systematic review s that addressed the same topic , pivotal trials , clinical practice guidelines , or recent editions of major textbooks ( for example , UpTo Date ) . Pivotal trials were defined as trials that had a sample size at least 3 times larger than that of the previous largest trial or were published in 1 of the 5 highest-impact general medical journals ( The New Engl and Journal of Medicine , Lancet , Journal of the American Medical Association , Annals of Internal Medicine , and the British Medical Journal ) . We defined 2 levels of importance for qualitative signals : potentially invalidating changes in evidence , which would make one no longer want clinicians or policymakers to base decisions on the original findings ( such as a pivotal trial that characterized treatment effectiveness in terms opposite of those in the original systematic review ) , and major changes in evidence , which would affect clinical decision making in important ways without invalidating the previous results ( such as the identification of patient population s for whom treatment is more or less beneficial ) . Major changes also included differing characterizations of effectiveness that were less extreme than those for potentially invalidating signals but that would still affect clinical decision making ( for example , a change from possibly beneficial to definitely beneficial ) . Of importance , such characterizations as possibly effective , probably effective , and promising , were all categorized as possibly effective . Thus , qualitative signals for changes in evidence captured substantive differences in the characterization of treatment effects , not merely semantic differences . Full definitions for each of the specific signals can be found at www.ohri.ca/UpdatingSystRevs . Data Collection For each review , we characterized the clinical content area , eligibility criteria for included trials , definitions of reported outcomes , number of included trials and participants , meta-analytic result for each outcome , identification of statistical heterogeneity , and excerpted quotations of the authors ' characterizations of the main results . We also abstract ed whether a given outcome was explicitly identified as 1 of the primary or main outcomes . We discounted identification of more than 3 such outcomes as inconsistent with the Background A discipline which critically looks at the evidence for practice should itself be critically examined . Credible evidence for the effectiveness of training in evidence -based healthcare ( EBHC ) is essential . We attempted to summarise the current knowledge on evaluating the effectiveness of training in EBHC while identifying the gaps . Methods A working group of EBHC teachers developed a conceptual framework of key areas of EBHC teaching and practice in need of evidence mapped to appropriate methods and outcomes . A literature search was conducted to review the current state of research in these key areas . Studies of training interventions that evaluated effectiveness by considering learner , patient or health system outcomes in terms of knowledge , skills , attitude , judgement , competence , decision-making , patient satisfaction , quality of life , clinical indicators or cost were included . There was no language restriction . Results Of 55 articles review ed , 15 met the inclusion criteria : six systematic review s , three r and omised controlled trials and six before-after studies . We found weak indications that undergraduate training in EBHC improves knowledge but not skills , and that clinical ly integrated postgraduate teaching improves both knowledge and skills . Two r and omised controlled trials reported no impact on attitudes or behaviour . One before-after study found a positive impact on decision-making , while another suggested change in learners ' behaviour and improved patient outcome . We found no studies assessing the impact of EBHC training on patient satisfaction , health-related quality of life , cost or population -level indicators of health . Conclusions Literature evaluating the effectiveness of training in EBHC has focused on short-term acquisition of knowledge and skills . Evaluation design s were method ologically weak , controlled trials appeared inadequately powered and systematic review s could not provide conclusive evidence owing to weakness of study design Background Synthesis of multiple r and omized controlled trials ( RCTs ) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions . Filtering of search es is time consuming , and no single method fulfills the principal requirements of speed with accuracy . Automation of systematic review s is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making . We developed Rayyan ( http://rayyan.qcri.org ) , a free web and mobile app , that helps expedite the initial screening of abstract s and titles using a process of semi-automation while incorporating a high level of usability . For the beta testing phase , we used two published Cochrane review s in which included studies had been selected manually . Their search es , with 1030 records and 273 records , were uploaded to Rayyan . Different features of Rayyan were tested using these two review s. We also conducted a survey of Rayyan ’s users and collected feedback through a built-in feature . Results Pilot testing of Rayyan focused on usability , accuracy against manual methods , and the added value of the prediction feature . The “ taster ” review ( 273 records ) allowed a quick overview of Rayyan for early comments on usability . The second review ( 1030 records ) required several iterations to identify the previously identified 11 trials . The “ suggestions ” and “ hints , ” based on the “ prediction model , ” appeared as testing progressed beyond five included studies . Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements . The survey respondents reported 40 % average time savings when using Rayyan compared to others tools , with 34 % of the respondents reporting more than 50 % time savings . In addition , around 75 % of the respondents mentioned that screening and labeling studies as well as collaborating on review s to be the two most important features of Rayyan . As of November 2016 , Rayyan users exceed 2000 from over 60 countries conducting hundreds of review s totaling more than 1.6 M citations . Feedback from users , obtained mostly through the app web site and a recent survey , has highlighted the ease in exploration of search es , the time saved , and simplicity in sharing and comparing include-exclude decisions . The strongest features of the app , identified and reported in user feedback , were its ability to help in screening and collaboration as well as the time savings it affords to users . Conclusions Rayyan is responsive and intuitive in use with significant potential to lighten the load of review ers As professionals , we want to use the best treatments ; as patients , we want to be given them . Knowing whether an intervention works ( or does not work ) is fundamental to clinical decision making . However , clinical decision making involves more than simply taking published results of research directly to the bedside . Physicians need to consider how similar their patients are to those in the published studies , to take the values and preferences of their patients into account , and to consider their own experience with a given test or treatment . Evidence from clinical research is becoming increasingly important in medical- practice decisions as more and better evidence is published . But when is the evidence strong enough to justify changing a practice ? Individual studies that involve only small numbers of patients may have results that are distorted by the r and om play of chance and thus lead to less than optimal decisions . As is clear from other papers in this series , systematic review s identify , critically appraise , and review all the relevant studies on a clinical question and are more likely to give a valid answer . They use explicit methods and quality st and ards to reduce bias . Their results are the closest we can come to reaching the truth given our current state of knowledge . The questions about an intervention that a systematic review should answer are the following : 1 . Does it work ? 2 . If it works , how well does it work in general and compared with placebo , no treatment , or other interventions that are currently in use ? 3 . Is it safe ? 4 . Will it be safe and effective for my patients ? Whereas the critical appraisal and qualitative synthesis provided by review articles can be interpreted directly , the numerical products of quantitative review s can be more difficult to underst and and apply in daily clinical practice . This paper provides guidance on how to interpret the numerical and statistical results of systematic review s , translate these results into more underst and able terms , and apply them directly to individual patients . Many of these principles can also be used to interpret the numerical results of individual clinical studies . They are particularly relevant to systematic review s , however , because such review s contain more information than do primary studies and often exert greater influence than do individual studies . Making Sense of the Numerical Results of Clinical Studies Although the results of clinical studies can be expressed in intuitively meaningful ways , such results do not always easily translate into clinical decision making . For example , results are frequently expressed in terms of risk , which is an expression of the frequency of a given outcome . ( Risks are probabilities , which can vary between 0.0 and 1.0 . A probability of 0.0 means that the event will never happen , and a probability of 1.0 means that it always happens . ) Consider a hypothetical study of the recurrence of migraine headaches in a control group receiving placebo and a treatment group receiving a new antimigraine preparation , drug M ( a secondary prevention trial ) . Suppose that at the end of the trial , migraines recurred in 30 % of the control group ( the risk for recurrence was 0.30 ) but in only 5 % of the drug M group ( risk of 0.05 ) ( Table 1 ) . Table 1 . Numerical Expression of Hypothetical Clinical Trial Results The outcomes of the study are clear enough for the two groups when they are examined separately . But clinicians and patients are more interested in the comparative results , that is , the outcome in one group relative to the outcome in the other group . This overall ( comparative ) result can be expressed in various ways . For example , the relative risk , which is the risk in the treatment group relative to that in the control group , is simply the ratio of the risks in the two groups . In other words , relative risk is the risk in the treatment group divided by that in the control group , 0.05 0.30 , or 0.17 . The comparison can also be expressed as the reduction in relative risk , which is the ratio between the decrease in risk ( in the treatment group ) and the risk in the control group , 0.25 0.30 , or 0.83 ( Table 1 ) . ( The relative risk reduction can also be calculated as 1 relative risk ) . Although the clinical meaning of relative risk ( and relative risk reduction ) is reasonably clear , relative risk has the distinct disadvantage that a given value ( for example , 0.17 ) is the same whether the risk with treatment decreases from 0.80 to 0.14 , from 0.30 to 0.05 , from 0.001 to 0.00017 , and so forth . The clinical implication s of these changes clearly differ from one another enormously and depend on the specific disease and intervention . An important alternate expression of comparative results , therefore , is the absolute risk reduction . Absolute risk reduction is determined by subtracting the risk in one group from the risk in the other ( for example , the risk in the treatment group is subtracted from the risk in the placebo group ) . In the case of our migraine study , the absolute risk reduction would be 0.30 0.05 , which equals 0.25 , or 25 percentage points . In contrast , for a study in which the risk decreased from 0.001 to 0.00017 , the absolute risk reduction would be only 0.00083 , or 0.083 percentage points , which is a trivial change in comparison ( Table 1 ) . This arithmetic emphasizes the difficulty of expressing the results of clinical studies in meaningful ways . Relative risk and relative risk reduction clearly give a quantitative sense of the effects of an intervention in proportional terms but provide no clue about the size of an effect on an absolute scale . In contrast , although it tells less about proportional effects , absolute risk says a great deal about whether an effect is likely to be clinical ly meaningful . Despite this benefit , even absolute risk is problematic because it is a dimensionless , abstract number ; that is , it lacks a direct connection with the clinical situation in which the patient and physician exist . However , another way of expressing clinical research results can provide that clinical link : the number needed to treat ( NNT ) . Number Needed To Treat The NNT for a given therapy is simply the reciprocal of the absolute risk reduction for that treatment [ 1 , 2 ] . In the case of our hypothetical migraine study ( in which risk decreased from 0.30 without treatment with drug M to 0.05 with treatment with drug M , for a relative risk of 0.17 , a relative risk reduction of 0.83 , and an absolute risk reduction of 0.25 ) , the NNT would be 1 0.25 , or 4 . In concrete clinical terms , an NNT of 4 means that you would need to treat four patients with drug M to prevent migraine from recurring in one patient . To emphasize the difference between the concepts embodied in NNT and relative risk , recall the various situations mentioned above , in all of which the relative risk was 0.17 but in which the absolute risk decreased from 0.80 to 0.14 in one case and from 0.001 to 0.00017 in another . Note that the corresponding NNTs in these two other cases are 1.5 and 1204 , respectively : that is , you would need to treat 1.5 and 1204 patients to obtain a therapeutic result in these two situations compared with 4 patients with drug M ( Table 1 ) . The NNT can be calculated easily and kept as a single numerical reminder of the effectiveness ( or , as we will see , the potential for harm ) of a particular therapy . As we suggested , the NNT has the crucial advantage of direct applicability to clinical practice because it shows the effort that is required to achieve a particular therapeutic target . The NNT has the additional advantage that it can be applied to any beneficial outcome or any adverse event ( when it becomes the number needed to harm [ NNH ] ) . The concept of NNT always refers to a comparison group ( in which patients receive placebo , no treatment , or some other treatment ) , a particular treatment outcome , and a defined period of treatment . In other words , the NNT is the number of patients that you will need to treat with drug or treatment A to achieve an improvement in outcome compared with drug or treatment B for a treatment period of C weeks ( or other unit of time ) . To be fully specified , NNT and NNH must always specify the comparator , the therapeutic outcome , and the duration of treatment that is necessary to achieve the outcome . Important Qualities of the Number Needed To Treat The NNT is treatment specific . It describes the difference between treatment and control in achieving a particular clinical outcome . Table 2 shows NNTs from a selection of systematic review s and large r and omized , controlled trials . Table 2 . Numbers Needed To Treat from Systematic Review s and R and omized , Controlled Trials A very small NNT ( that is , one that approaches 1 ) means that a favorable outcome occurs in nearly every patient who receives the treatment and in few patients in a comparison group . Although NNTs close to 1 are theoretically possible , they are almost never found in practice . However , small NNTs do occur in some therapeutic trials , such as those comparing antibiotics with placebo in the eradication of Helicobacter pylori infection or those examining the use of insecticide for head lice ( Table 2 ) . An NNT of 2 or 3 indicates that a treatment is quite effective . In contrast , such prophylactic interventions as adding aspirin to streptokinase to reduce 5-week vascular mortality rates after myocardial infa rct ion may have NNTs as high as 20 to 40 and still be considered clinical ly effective . Limitations of the Number Needed To Treat Although NNTs are powerful instruments for interpreting clinical effects , they also have important limitations . First , an NNT is generally expressed as a single number , which is known as its point estimate . As with all experimental measurements , however , the true value of the NNT can be higher or lower than the point estimate determined through clinical studies . The 95 % CIs of the NNT are useful in this regard because they provide an indication that Approaches for the systematic review and evaluation of chemical toxicity are currently being reconsidered , with a specific focus on the evaluation of individual studies and their integration into the overall body of evidence . This renewed interest has arisen , in part , as a result of several prominent review s of these approaches by special committees of the National Research Council ( NRC ) , among others . We conducted a critical evaluation of several available frameworks for evaluating study quality . We assessed the criteria separately for human , animal , and in vitro studies as well as for systematic review s. We then evaluated commonalities across disciplines . We also considered the potential implication s of applying criteria frameworks and how they bear on fundamental risk assessment questions . We found that the available frameworks within each discipline differed in terms of their intended purpose and level of guidance for decision making . All the frameworks across disciplines shared common themes , however , including the adequate reporting of specific details of study conditions and design / protocol , selection and r and omization of study groups ( where applicable ) , outcome assessment methods and applicability ( e.g. , validity and reliability ) , avoidance of selective reporting , and the consideration of potential confounders or bias . We identified the most informative study quality considerations , which will enable research ers to implement more objective and st and ardized methods for evaluating studies and , ultimately , improve risk assessment methods Low  back pain  has long been described as a challenge for both primary care physicians and specialists . Management of  low back pain  has also been criticized as frequently arbitrary , inappropriate , or ineffective . Contributing factors have been an inadequate evidence base and a need for more rigorous appraisal s of the available literature . Evidence -based medicine , an approach to clinical problem solving , is predicated on the premise that high- quality health care will result from practice s consistent with the best evidence . In contrast to the traditional medical paradigm that placed a heavy reliance on expert opinion , authority , and un systematic clinical observations , evidence -based medicine emphasizes the need for rigorous critical appraisal s of the scientific literature to inform medical decision making . Evidence -based medicine places strong weight on the requirement for valid studies , particularly r and omized controlled trials , to appropriately evaluate the effectiveness of health care interventions . Because of the rapidly increasing volume of medical literature , however , most clinicians are unable to keep up-to- date with all the new data . Two types of preprocessed evidence that can aid busy clinicians in medical decision making are systematic review s and evidence -based clinical practice guidelines . Like primary studies , systematic review s and clinical practice guidelines must adhere to high method ologic st and ards to reduce error and bias . As in other areas of medicine , the approach to the management of low back pain has been positively affected by the availability of more clinical trials and better use of critical appraisal techniques to evaluate and apply research findings . In addition to more rigorous primary studies , an increasing number of high- quality systematic review s and evidence -based clinical practice guidelines for low back pain are also available . Although some research gaps and method ologic shortcomings persist , the richer evidence base has greatly improved our underst and ing of what does and does not work for low back pain . Despite these advances , the best available evidence often does not inform everyday clinical decisions for low back pain . Nonetheless , there is widespread agreement that adherence to evidence -based practice will help improve low back pain patient outcomes and reduce arbitrary variations in care . This article review s basic principles of evidence -based medicine , discusses evidence -based medicine in the context of low back pain management , and summarizes some useful evidence -based medicine re sources Background Fracture of the distal radius is a common clinical problem , particularly in older white women with osteoporosis . We report our work towards evidence -based and patient-centred care for adults with these injuries . Methods We developed a systematic programme of research that built on our systematic review of the evidence of effectiveness of treatment interventions for these fractures . We devised schemata showing ' typical ' care pathways and identified over 100 patient management questions . These depicted the more important decisions taken when progressing along each care pathway . We compiled a comprehensive document summarising the evidence available for each decision point from our review s of r and omised trials of treatment interventions . Using these documents , we undertook a formal and structured consultation process involving key players , including a patient representative , to obtain their views on the available evidence and to establish a research agenda . The result ing feedback was then processed and interpreted , using systematic methods . Results Some evidence from 114 r and omised trials was available for 31 of the 117 patient management questions . However , there was sufficient evidence to base some conclusions of effectiveness for particular interventions in only five of these . Though only 60 % of those approached responded , the responses received from the consultation group were often comprehensive and provided important insights into treatment practice and policy . There was a clear acceptance of the aims of the project and , aside from some suggestions for the more explicit inclusion of secondary prevention and management of complications , of the care pathways scheme . Though some respondents stressed that r and omised trials were not always appropriate , there was no direct overall criticism of the evidence document and underlying processes . We were able to identify important core themes that underpin management decisions and research from the feedback of the consultation exercise . Conclusions Overall , this project is an important advance towards evidence -based and patient-centred management of adults with distal radial fractures . It exposes the serious deficiency in the available evidence but also provides a template for further action . As well as being a valuable basis for viewing and informing current practice , the insights gained from this project should inform a future research agenda The number of reports of clinical trials grows by hundreds every week . However , this does not mean that people making decisions about healthcare are finding it easier to obtain reliable knowledge for these decisions . Some of the information is unreliable . Systematic review s are helping to resolve this by bringing together the research on a topic , appraising and summarising it . But the quality of these review s depends greatly on the quality of the studies , and this usually means the quality of their reports . If there are fundamental flaws within a study , such as the use of inappropriate ' r and omisation ' techniques in the context of review s of the effects of interventions , the review ers will not be able to fix these . Worse still , if they are not aware of underlying flaws , they might make incorrect judgements about the quality of the research in their review . A study by Wu and colleagues of ' r and omised trials ' from China provides a reminder of the cautious approach needed by users of scientific articles . They contacted the authors of more than 2000 research articles , which purported to be reports of r and omised trials ; and concluded that ten of every 11 studies cl aim ing to be a r and omised trial probably did not use r and om allocation . Better education of research ers , peer review ers and editors about what is , and is not , a properly r and omised trial is needed ; along with better reporting of the details for how participants were allocated to the different interventions . Systematic review ers must be cautious in making assumptions about the conduct of trials based on simple phrases about the trial methodology , rather than a full description of the methods actually used . It 's not that you ca n't believe anything that you read in the papers , just that you can not believe everything Abstract Background Heterogeneity has been noted in the selection and reporting of disease-specific , pediatric outcomes in r and omized controlled trials ( RCTs ) . The consequence is invalid results or difficulty comparing results across trials . The primary objective of this systematic review was to assess primary outcome and outcome measure selection and reporting , in pediatric eosinophilic esophagitis ( EoE ) treatment trials . As secondary objectives , we compared trial disease definition to established concensus guidelines , and the efficacy of current EoE treatments . Methods We search ed MEDLINE , EMBASE , The Cochrane Library , Cochrane Central Register of Controlled Trials ( CENTRAL ) , and CINAHL since 2001 . We also search ed clinical trial registries ( portal.nihr.ac.uk ; clinical trials.gov ; is rct n.com ; and anzctr.org.au ) and references of included studies . We included RCTs of EoE treatment in patients 0–18 years . Two authors independently assessed articles . Results Eleven studies met inclusion criteria . All identified primary outcomes , however , of 9 unique primary outcomes , only 2 were used in more than one study . In total , 25 unique primary and secondary outcome measures were employed for pediatric EoE treatment trials . Measurement properties and rationale for their selection was rarely provided . Uptake of consensus-based diagnostic criteria was 25 % in trials initiated after 2011 . Due to the small number and heterogeneity of studies obtained , no meta- analysis of treatment efficacy could be undertaken . This SR was limited to exclusively pediatric RCTs . Conclusions The results of this study confirm the need for a st and ardized set of core outcomes that are universally reported in pediatric EoE trials . Consistent disease definition and st and ardized outcome reporting will facilitate meta-analyses across similar trials and inform future clinical decision-making . Systematic review registration number The m and ate of Human Reproduction Up date involves several roles : ( i ) to provide a synthesis of evidence that can aid scientists and clinicians in their daily work ; ( ii ) to help reproductive specialists underst and concepts from related disciplines ; and ( iii ) to summarize current knowledge generated by basic science as the foundation of future scientific and clinical advancement . Given that review and synthesis are central to good scientific and clinical practice , and that a grasp of the current state of knowledge is a prerequisite to design ing new studies , it is pertinent to ask which review s are most likely to fulfil the needs of readers . A related question concerns whether systematic review s meet the needs of all review topics and all readers . Summarizing evidence or knowledge is a difficult problem in reproductive medicine , as in other branches of science and medical care ( Eddy et al. , 1992 ) . For each question there may be multiple studies that use different design s and inclusion criteria . For clinical questions , the interventions , outcomes and measures of effect may vary : the effect measures in treatment studies include odds ratios , relative risks and absolute differences . For scientific questions , the experimental species , models and design s may differ . Moreover , it is always uncertain whether all of the relevant evidence has been evaluated . Even when the search has been exhaustive , there are no simple guides on how to interpret conflicting results and whether to accept apparently outlying studies . The choices that the review er makes to address the variable conditions and uncertainties may be conservative , strict and exclusive , or liberal , open and inclusive . The decisions made by the review er may not be consistent throughout and these choices may or may not satisfy the reader who seeks out the review to address a clinical or research question . Faced with uncertainty and doubt , readers nonetheless must form an impression of the evidence and synthesize the state of knowledge in order to address the clinical or research question that stimulated their interest in the review . We argue that the reader is better served when the choices made in the review , regardless of whether they are strict or open , should be explicit , transparent , clearly stated and reproducible by interested readers . This list of objectives for review s is more easily satisfied by systematic review s , which use explicit methods to method ically search , critically appraise and synthesize the available literature on a specific issue . The question or issue need not be clinical : indeed , the concept evolved primarily in psychology studies ( Light and Pillemer , 1984 ) . The systematic review attempts to reduce review er bias through the use of objective , reproducible criteria to select relevant individual publications and assess their validity . A systematic review may include a meta- analysis or statistical summary of the individual study results : the aggregate of effects from several studies yields an average treatment effect that is more precise than the individual study results ( Schlesselman and Collins , 2003 ) . Thus , the systematic review involves explicit , transparent methods which are clearly stated , and reproducible by others . Whether a systematic review of r and omized controlled trials adheres to the guidelines can easily be evaluated by means of a widely used checklist ( the QUORUM statement ) ( Moher et al. , 1999 ) . The strengths of the systematic review include the narrow focus of the question , the comprehensive search for evidence , the criterion-based selection of relevant evidence , the rigorous appraisal of validity , the objective or quantitative summary , and the evidence -based inferences ( Cook et al. , 1997 ) . For some review topics , however , the strengths of the systematic review may turn into weaknesses . The primary problem is that the narrow focus and prescribed methods of the systematic review do not allow for comprehensive coverage . For example , the historical review is an irreplaceable means of tracing the development of a scientific principle or clinical concept , but the narrative thread could be lost in the strict rules of systematic review . As other examples , it would be burdensome to apply systematic methods to a survey on  aneuploidy and fertility in the aging female or to an assessment of mouse knockout models and polycystic ovarian phenotype . Such topics would require the wider scope of a traditional narrative review , in Human Reproduction Up date , Vol.11 , No.2 pp . 103–104 , 2005 doi:10.1093/humupd/dmh058 Advance Access publication December 23 , Diagnosis is a critical component of health care , and clinicians , policymakers , and patients routinely face a range of questions regarding diagnostic tests . They want to know whether testing improves outcome ; what test to use , purchase , or recommend in practice guidelines ; and how to interpret test results . Well- design ed  diagnostic test accuracy studies can help in making these decisions , provided that they transparently and fully report their participants , tests , methods , and results as facilitated , for example , by the STARD ( St and ards for Reporting of Diagnostic Accuracy ) statement ( 1 ) . That 25-item checklist was published in many journals and is now adopted by more than 200 scientific journals worldwide . As in other areas of science , systematic review s and meta- analysis of accuracy studies can be used to obtain more precise estimates when small studies addressing the same test and patients in the same setting are available . Review s can also be useful to establish whether and how scientific findings vary by particular subgroups , and may provide summary estimates with a stronger generalizability than estimates from a single study . Systematic review s may help identify the risk for bias that may be present in the original studies and can be used to address questions that were not directly considered in the primary studies , such as comparisons between tests . The Cochrane Collaboration is the largest international organization preparing , maintaining , and promoting systematic review s to help people make well-informed decisions about health care ( 2 ) . The Collaboration decided in 2003 to make preparations for including systematic review s of diagnostic test accuracy in their Cochrane Data base of Systematic Review s. To enable this , a working group ( Appendix ) . was formed to develop methodology , software , and a h and book The first diagnostic test accuracy review was published in the Cochrane Data base in October 2008 . In this paper , we review recent method ological developments concerning problem formulation , location of literature , quality assessment , and meta- analysis of diagnostic accuracy studies by using our experience from the work on the Cochrane H and book . The information presented here is based on the recent literature and up date s previously published guidelines by Irwig and colleagues ( 3 ) . Definition of the Objectives of the Review Diagnostic test accuracy refers to the ability of a test to distinguish between patients with disease ( or more generally , a specified target condition ) and those without . In a study of test accuracy , the results of the test under evaluation , the index test , are compared with those of the reference st and ard determined in the same patients . The reference st and ard is an agreed-on and accurate method for identifying patients who have the target condition . Test results are typically categorized as positive or negative for the target condition . By using such binary test outcomes , the accuracy is most often expressed as the test 's sensitivity ( the proportion of patients with positive results on the reference st and ard that are also positive on the index test ) and specificity ( the proportion of patients with negative results on the reference st and ard that are also negative on the index test ) . Other measures have been proposed and are in use ( 46 ) . It has long been recognized that test accuracy is not a fixed property of a test . It can vary between patient subgroups , with their spectrum of disease , with the clinical setting , or with the test interpreters and may depend on the results of previous testing . For this reason , inclusion of these elements in the study question is essential . In order to make a policy decision to promote use of a new index test , evidence is required that using the new test increases test accuracy over other testing options , including current practice , or that the new test has equivalent accuracy but offers other advantages ( 79 ) . As with the evaluation of interventions , systematic review s need to include comparative analyses between alternative testing strategies and should not focus solely on evaluating the performance of a test in isolation . In relation to the existing situation , 3 possible roles for a new test can be defined : replacement , triage , and add-on ( 7 ) . If a new test is to replace an existing test , then comparing the accuracy of both tests on the same population and with the same reference st and ard provides the most direct evidence . In triage , the new test is used before the existing test or testing pathway , and only patients with a particular result on the triage test continue the testing pathway . When a test is needed to rule out disease in patients who then need no further testing , a test that gives a minimal proportion of falsenegative results and thus a relatively high sensitivity should be used . Triage tests may be less accurate than existing ones , but they have other advantages , such as simplicity or low cost . A third possible role of a new test is add-on . The new test is then positioned after the existing testing pathway to identify false-positive or false-negative results after the existing pathway . The review should provide data to assess the incremental change in accuracy made by adding the new test . An example of a replacement question can be found in a systematic review of the diagnostic accuracy of urinary markers for primary bladder cancer ( 10 ) . Clinicians may use cytology to triage patients before they undergo invasive cystoscopy  , the reference st and ard for bladder cancer . Because cytology combines high specificity with low sensitivity ( 11 ) , the goal of the review was to identify a tumor marker with sufficient accuracy to either replace cytology or be used in addition to cytology . For a marker to replace cytology , it has to achieve equally high specificity with improved sensitivity . New markers that are sensitive but not specific may have roles as adjuncts to conventional testing . The review included studies in which the test under evaluation ( several different tumor markers and cytology ) was evaluated against cystoscopy or histopathology . Included studies compared 1 or more of the markers , cytology only , or a combination of markers and cytology . Although information on accuracy can help clinicians make decisions about tests , good diagnostic accuracy is a desirable but not sufficient condition for the effectiveness of a test ( 8) . To demonstrate that using a new test does more good than harm to patients tested , r and omized trials of test- and -treatment strategies and review s of such trials may be necessary . However , with the possible exception of screening , in most cases , such r and omized trials are not available and systematic review s of test accuracy may provide the most useful evidence available to guide clinical and health policy decision making and use as input for decision and cost-effectiveness analysis ( 12 ) . Identification and Selection of Studies Identifying test accuracy studies is more difficult than search ing for r and omized trials ( 13 ) . There is not a clear , unequivocal keyword or indexing term for an accuracy study in literature data bases comparable with the term r and omized , controlled trial . The Medical Subject Heading sensitivity and specificity may look suitable but is inconsistently applied in most electronic bibliographic data bases . Furthermore , data on diagnostic test accuracy may be hidden in studies that did not have test accuracy estimation as their primary objective . This complicates the efficient identification of diagnostic test accuracy studies in electronic data bases , such as MEDLINE . Until indexing systems properly code studies of test accuracy , search ing for them will remain challenging and may require additional manual search es , such as screening reference lists . In the development of a comprehensive search strategy , review authors can use search strings that refer to the test(s ) under evaluation , the target condition , and the patient description or a subset of these . For tests with a clear name that are used for a single purpose , search ing for publications in which those tests are mentioned may suffice . For other review s , adding the patient description may be necessary , although this is also often poorly indexed . A search strategy in MEDLINE should contain both Medical Subject Headings and free text words . A search strategy for articles about tests for bladder cancer , for example , should include as many synonyms for bladder cancer as possible in the search strategy , including neoplasm , carcinoma , transitional cell , and hematuria . Several method ological electronic search filters for diagnostic test accuracy studies have been developed , each attempting to restrict the search to articles that are most likely to be test accuracy studies ( 1316 ) . These filters rely on indexing terms for research methodology and text words used in reporting results , but they often miss relevant studies and are unlikely to decrease the number of articles one needs to screen . Therefore , they are not recommended for systematic review s ( 17 , 18 ) . The incremental value of search ing in language s other than English and in the gray literature has not yet been fully investigated . In systematic review s of intervention studies , publication bias is an important and well-studied form of bias in which the decision to report and publish studies is linked to their findings . For clinical trials , the magnitude and determinants of publication bias have been identified by tracing the publication history of cohorts of trials review ed by ethics committees and research boards ( 19 ) . A consistent observation has been that studies with significant results are more likely to be published than studies with nonsignificant findings ( 19 ) . Investigating publication bias for diagnostic tests is problematic , because many studies are done without ethical review or study registration ; therefore , identification of cohorts of studies from registration to final publication status
Presentation of relative effects regarding pain will facilitate interpretation of treatment effects
OBJECTIVE Pain is a patient-important outcome , but current reporting in r and omized controlled trials and systematic review s is often suboptimal , impeding clinical interpretation and decision making .