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.
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
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 .