Thomas Agoritsas

How to Read a Systematic Review and Meta-analysis and Apply the Results to Patient Care: Users’ Guides to the Medical Literature

Clinical decisions should be based on the totality of the best evidence and not the results of individual studies. When clinicians apply the results of a systematic review or meta-analysis to patient care, they should start by evaluating the credibility of the methods of the systematic review, ie, the extent to which these methods have likely protected against misleading results. Credibility depends on whether the review addressed a sensible clinical question; included an exhaustive literature search; demonstrated reproducibility of the selection and assessment of studies; and presented results in a useful manner. For reviews that are sufficiently credible, clinicians must decide on the degree of confidence in the estimates that the evidence warrants (quality of evidence). Confidence depends on the risk of bias in the body of evidence; the precision and consistency of the results; whether the results directly apply to the patient of interest; and the likelihood of reporting bias. Shared decision making requires understanding of the estimates of magnitude of beneficial and harmful effects, and confidence in those estimates.

How to Use a Subgroup Analysis: Users’ Guide to the Medical Literature

Clinicians, when trying to apply trial results to patient care, need to individualize patient care and, potentially, manage patients based on results of subgroup analyses. Apparently compelling subgroup effects often prove spurious, and guidance is needed to differentiate credible from less credible subgroup claims. We therefore provide 5 criteria to use when assessing the validity of subgroup analyses: (1) Can chance explain the apparent subgroup effect; (2) Is the effect consistent across studies; (3) Was the subgroup hypothesis one of a small number of hypotheses developed a priori with direction specified; (4) Is there strong preexisting biological support; and (5) Is the evidence supporting the effect based on within- or between-study comparisons. The first 4 criteria are applicable to individual studies or systematic reviews, the last only to systematic reviews of multiple studies. These criteria will help clinicians deciding whether to use subgroup analyses to guide their patient care.

Performance of logistic regression modeling: beyond the number of events per variable, the role of data structure

OBJECTIVE Logistic regression is commonly used in health research, and it is important to be sure that the parameter estimates can be trusted. A common problem occurs when the outcome has few events; in such a case, parameter estimates may be biased or unreliable. This study examined the relation between correctness of estimation and several data characteristics: number of events per variable (EPV), number of predictors, percentage of predictors that are highly correlated, percentage of predictors that were non-null, size of regression coefficients, and size of correlations. STUDY DESIGN Simulation studies. RESULTS In many situations, logistic regression modeling may pose substantial problems even if the number of EPV exceeds 10. Moreover, the number of EPV is not the only element that impacts on the correctness of parameter estimation. High regression coefficients and high correlations between the predictors may cause large problems in the estimation process. Finally, power is generally very low, even at 20 EPV. CONCLUSION There is no single rule based on EPV that would guarantee an accurate estimation of logistic regression parameters. Instead, the number of predictors, probable size of the regression coefficients based on previous literature, and correlations among the predictors must be taken into account as guidelines to determine the necessary sample size.

Decision aids that really promote shared decision making: the pace quickens

Decision aids can help shared decision making, but most have been hard to produce, onerous to update, and are not being used widely. Thomas Agoritsas and colleagues explore why and describe a new electronic model that holds promise of being more useful for clinicians and patients to use together at the point of care

Patient reports of undesirable events during hospitalization

BACKGROUND: Thus far, incident reporting in health care has relied on health professionals. However, patients too may be able to signal the occurrence of undesirable events. OBJECTIVE: To estimate the frequency of undesirable events reported by recently discharged patients, and to identify correlates of undesirable events. DESIGN: Mailed patient survey. SETTING: Swiss public teaching hospital. PARTICIPANTS: Adult patients (N=1,518) discharged from hospital. MEASUREMENTS: Self-reports of 27 undesirable events during hospitalization, including 9 medical complications, 9 interpersonal problems, and 9 incidents related to the health care process. RESULTS: Most survey respondents (1,433, 94.4%) completed the section about undesirable events, and 725 (50.6%) reported at least 1 event. The most frequent events were phlebitis (11.0%), unavailable medical record (9.5%), failure to respect confidentiality (8.4%), and hospital-acquired infection (8.2%). The odds of an unfavorable rating increased with each additional interpersonal problem (odds ratio [OR] 1.6, 95% confidence interval [CI] 1.3 to 1.8), each additional process-related problem (OR 1.5, 95% CI 1.3 to 1.9), but not with each additional medical complication (OR 1.0, 95% CI 0.9 to 1.2). Longer duration of stay, poor health, and depressed mood were all related to a greater reported frequency of undesirable events. CONCLUSION: Patients are able to report undesirable events that occur during hospital care. Such events occur in about a half of the hospitalizations, and have a negative impact on satisfaction with care.

Risk prediction models for mortality in ambulatory patients with heart failure: a systematic review

Background—Optimal management of heart failure requires accurate assessment of prognosis. Many prognostic models are available. Our objective was to identify studies that evaluate the use of risk prediction models for mortality in ambulatory patients with heart failure and describe their performance and clinical applicability. Methods and Results—We searched for studies in Medline, Embase, and CINAHL in May 2012. Two reviewers selected citations including patients with heart failure and reporting on model performance in derivation or validation cohorts. We abstracted data related to population, outcomes, study quality, model discrimination, and calibration. Of the 9952 studies reviewed, we included 34 studies testing 20 models. Only 5 models were validated in independent cohorts: the Heart Failure Survival Score, the Seattle Heart Failure Model, the PACE (incorporating peripheral vascular disease, age, creatinine, and ejection fraction) risk score, a model by Frankenstein et al, and the SHOCKED predictors. The Heart Failure Survival Score was validated in 8 cohorts (2240 patients), showing poor-to-modest discrimination (c-statistic, 0.56–0.79), being lower in more recent cohorts. The Seattle Heart Failure Model was validated in 14 cohorts (16 057 patients), describing poor-to-acceptable discrimination (0.63–0.81), remaining relatively stable over time. Both models reported adequate calibration, although overestimating survival in specific populations. The other 3 models were validated in a cohort each, reporting poor-to-modest discrimination (0.66–0.74). Among the remaining 15 models, 6 were validated by bootstrapping (c-statistic, 0.74–0.85); the rest were not validated. Conclusions—Externally validated heart failure models showed inconsistent performance. The Heart Failure Survival Score and Seattle Heart Failure Model demonstrated modest discrimination and questionable calibration. A new model derived from contemporary patient cohorts may be required for improved prognostic performance.

Guideline for opioid therapy and chronic noncancer pain

Chronic noncancer pain includes any painful condition that persists for at least three months and is not associated with malignant disease.[1][1] According to seven national surveys conducted between 1994 and 2008, 15%–19% of Canadian adults live with chronic noncancer pain.[2][2] Chronic

Creating Clinical Practice Guidelines We Can Trust, Use, and Share : A New Era Is Imminent

Standards and guidance for developing trustworthy clinical practice guidelines are now available, and a number of leading guidelines adhere to the key standards. Even current trustworthy guidelines, however, generally suffer from a cumbersome development process, suboptimal presentation formats, inefficient dissemination to clinicians at the point of care, high risk of becoming quickly outdated, and suboptimal facilitation of shared decision-making with patients. To address these limitations, we have--in our innovative research program and nonprofit organization, MAGIC (Making GRADE the Irresistible Choice)--constructed a conceptual framework and tools to facilitate the creation, dissemination, and dynamic updating of trustworthy guidelines. We have developed an online application that constitutes an authoring and publication platform that allows guideline content to be written and structured in a database, published directly on our web platform or exported in a computer-interpretable language (eg, XML) enabling dissemination through a wide range of outputs that include electronic medical record systems, web portals, and applications for smartphones/tablets. Modifications in guidelines, such as recommendation updates, will lead to automatic alterations in these outputs with minimal additional labor for guideline authors and publishers, greatly facilitating dynamic updating of guidelines. Semiautomated creation of a new generation of decision aids linked to guideline recommendations should facilitate face-to-face shared decision-making in the clinical encounter. We invite guideline organizations to partner with us (www.magicproject.org) to apply and further improve the tools for their purposes. This work will result in clinical practice guidelines that we cannot only trust, but also easily share and use.

CommentaryCreating Clinical Practice Guidelines We Can Trust, Use, and Share: A New Era Is Imminent

Standards and guidance for developing trustworthy clinical practice guidelines are now available, and a number of leading guidelines adhere to the key standards. Even current trustworthy guidelines, however, generally suffer from a cumbersome development process, suboptimal presentation formats, inefficient dissemination to clinicians at the point of care, high risk of becoming quickly outdated, and suboptimal facilitation of shared decision-making with patients. To address these limitations, we have--in our innovative research program and nonprofit organization, MAGIC (Making GRADE the Irresistible Choice)--constructed a conceptual framework and tools to facilitate the creation, dissemination, and dynamic updating of trustworthy guidelines. We have developed an online application that constitutes an authoring and publication platform that allows guideline content to be written and structured in a database, published directly on our web platform or exported in a computer-interpretable language (eg, XML) enabling dissemination through a wide range of outputs that include electronic medical record systems, web portals, and applications for smartphones/tablets. Modifications in guidelines, such as recommendation updates, will lead to automatic alterations in these outputs with minimal additional labor for guideline authors and publishers, greatly facilitating dynamic updating of guidelines. Semiautomated creation of a new generation of decision aids linked to guideline recommendations should facilitate face-to-face shared decision-making in the clinical encounter. We invite guideline organizations to partner with us (www.magicproject.org) to apply and further improve the tools for their purposes. This work will result in clinical practice guidelines that we cannot only trust, but also easily share and use.

Meta-analysis of antibiotics versus appendicectomy for non-perforated acute appendicitis

For more than a century, appendicectomy has been the treatment of choice for appendicitis. Recent trials have challenged this view. This study assessed the benefits and harms of antibiotic therapy compared with appendicectomy in patients with non‐perforated appendicitis.