Gordon H. Guyatt

Bio: Gordon H. Guyatt is an academic researcher from McMaster University. The author has contributed to research in topics: Randomized controlled trial & Evidence-based medicine. The author has an hindex of 231, co-authored 1620 publications receiving 228631 citations. Previous affiliations of Gordon H. Guyatt include Memorial Sloan Kettering Cancer Center & Cayetano Heredia University.

Is This Patient Having a Myocardial Infarction

Abstract: When faced with a patient with acute chest pain, clinicians must distinguish myocardial infarction (MI) from all other causes of acute chest pain. If MI is suspected, current therapeutic practice includes deciding whether to administer thrombolysis or primary percutaneous transluminal coronary angioplasty and whether to admit patients to a coronary care unit. The former decision is based on electrocardiographic (ECG) changes, including ST-segment elevation or left bundle-branch block, the latter on the likelihood of the patient’s having unstable high-risk ischemia or MI without ECG changes. Despite advances in investigative modalities, a focused history and physical examination followed by an ECG remain the key tools for the diagnosis of MI. The most powerful features that increase the probability of MI, and their associated likelihood ratios (LRs), are new ST-segment elevation (LR range, 5.7-53.9); new Q wave (LR range, 5.3-24.8); chest pain radiating to both the left and right arm simultaneously (LR, 7.1); presence of a third heart sound (LR, 3.2); and hypotension (LR, 3.1). The most powerful features that decrease the probability of MI are a normal ECG result (LR range, 0.1-0.3), pleuritic chest pain (LR, 0.2), chest pain reproduced by palpation (LR range, 0.2-0.4), sharp or stabbing chest pain (LR, 0.3), and positional chest pain (LR, 0.3). Computer-derived algorithms that depend on clinical examination and ECG findings might improve the classification of patients according to the probability that an MI is causing their chest pain. JAMA. 1998;280:1256-1263

The MacNew Heart Disease health-related quality of life instrument: A summary

Abstract: Background: The measurement of health, the effects of disease, and the impact of health care include not only an indication of changes in disease frequency and severity but also an estimate of patients' perception of health status before and after treatment. One of the more important developments in health care in the past decade may be the recognition that the patient's perspective is as legitimate and valid as the clinician's in monitoring health care outcomes. This has lead to the development of instruments to quantify the patients' perception of their health status before and after treatment. Methods: We review evidence supporting the measurement properties of the MacNew Heart Disease Health-related Quality of Life [MacNew] Questionnaire which was designed to evaluate how daily activities and physical, emotional, and social functioning are affected by coronary heart disease and its treatment. Results: Reliability was demonstrated by using internal consistency and the intraclass correlation coefficients for the three domains in the Dutch, English, Farsi, German, and Spanish versions of the MacNew. With internal consistency and intraclass correlation coefficients =>0.73, reliability is high. Validity of the MacNew was examined with factor analysis and three core underlying factors, physical, emotional, and social, were identified, explaining 63.0 – 66.5% of the observed variance and replicated in the translations with psychometric data. Construct validity of the MacNew was further demonstrated by extensive substantiation of the logical relationships, defined a priori, between items and other comparison tools. The MacNew is responsive and sensitive to changes in HRQL following various interventions for patients with heart disease with 11 of 13 effect size statistics >0.80. Taking an average of 10 minutes or less to complete, the respondent-burden for the MacNew is low and its acceptability is demonstrated by response rates of over 90%. Normative data are available for patients with myocardial infarction, angina, and heart failure in the English version. Conclusion: The MacNew may be a valuable tool for assessing and evaluating health related quality of life in patients with heart disease.

Percutaneous transluminal coronary angioplasty versus medical treatment for non-acute coronary heart disease: meta-analysis of randomised controlled trials

Abstract: Objective: To determine whether percutaneous transluminal coronary angioplasty (angioplasty) is superior to medical treatment in non-acute coronary artery disease. Design: Meta-analysis of randomised controlled trials. Setting: Randomised controlled trials conducted worldwide and published between 1979 and 1998. Participants: 953 patients treated with angioplasty and 951 with medical treatment from six randomised controlled trials, three of which included patients with multivessel disease and pre-existing myocardial infarction. Main outcome measures: Angina, fatal and non-fatal myocardial infarction, death, repeated angioplasty, and coronary artery bypass grafting. Results: In patients treated with angioplasty compared with medical treatment the risk ratios were 0.70 (95% confidence interval 0.50 to 0.98; heterogeneity P Conclusions: Percutaneous transluminal coronary angioplasty may lead to a greater reduction in angina in patients with coronary heart disease than medical treatment but at the cost of more coronary artery bypass grafting. Trials have not included enough patients for informative estimates of the effect of angioplasty on myocardial infarction, death, or subsequent revascularisation, though trends so far do not favour angioplasty.

Prevalence, characteristics, and publication of discontinued randomized trials.

Abstract: Importance The discontinuation of randomized clinical trials (RCTs) raises ethical concerns and often wastes scarce research resources. The epidemiology of discontinued RCTs, however, remains unclear. Objectives To determine the prevalence, characteristics, and publication history of discontinued RCTs and to investigate factors associated with RCT discontinuation due to poor recruitment and with nonpublication. Design and Setting Retrospective cohort of RCTs based on archived protocols approved by 6 research ethics committees in Switzerland, Germany, and Canada between 2000 and 2003. We recorded trial characteristics and planned recruitment from included protocols. Last follow-up of RCTs was April 27, 2013. Main Outcomes and Measures Completion status, reported reasons for discontinuation, and publication status of RCTs as determined by correspondence with the research ethics committees, literature searches, and investigator surveys. Results After a median follow-up of 11.6 years (range, 8.8-12.6 years), 253 of 1017 included RCTs were discontinued (24.9% [95% CI, 22.3%-27.6%]). Only 96 of 253 discontinuations (37.9% [95% CI, 32.0%-44.3%]) were reported to ethics committees. The most frequent reason for discontinuation was poor recruitment (101/1017; 9.9% [95% CI, 8.2%-12.0%]). In multivariable analysis, industry sponsorship vs investigator sponsorship (8.4% vs 26.5%; odds ratio [OR], 0.25 [95% CI, 0.15-0.43]; P P = .04) were associated with lower rates of discontinuation due to poor recruitment. Discontinued trials were more likely to remain unpublished than completed trials (55.1% vs 33.6%; OR, 3.19 [95% CI, 2.29-4.43]; P Conclusions and Relevance In this sample of trials based on RCT protocols from 6 research ethics committees, discontinuation was common, with poor recruitment being the most frequently reported reason. Greater efforts are needed to ensure the reporting of trial discontinuation to research ethics committees and the publication of results of discontinued trials.

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement

Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.

Abstract: Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews. Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in 4 leading medical journals in 1985 and 1986 and found that none met all 8 explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in 6 domains. Reporting was generally poor; between 1 and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement.7 In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1). Box 1 Conceptual issues in the evolution from QUOROM to PRISMA

Measuring inconsistency in meta-analyses

Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice? Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis. Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4 Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted? A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …

Bias in meta-analysis detected by a simple, graphical test

Abstract: Objective: Funnel plots (plots of effect estimates against sample size) may be useful to detect bias in meta-analyses that were later contradicted by large trials. We examined whether a simple test of asymmetry of funnel plots predicts discordance of results when meta-analyses are compared to large trials, and we assessed the prevalence of bias in published meta-analyses. Design: Medline search to identify pairs consisting of a meta-analysis and a single large trial (concordance of results was assumed if effects were in the same direction and the meta-analytic estimate was within 30% of the trial); analysis of funnel plots from 37 meta-analyses identified from a hand search of four leading general medicine journals 1993-6 and 38 meta-analyses from the second 1996 issue of the Cochrane Database of Systematic Reviews . Main outcome measure: Degree of funnel plot asymmetry as measured by the intercept from regression of standard normal deviates against precision. Results: In the eight pairs of meta-analysis and large trial that were identified (five from cardiovascular medicine, one from diabetic medicine, one from geriatric medicine, one from perinatal medicine) there were four concordant and four discordant pairs. In all cases discordance was due to meta-analyses showing larger effects. Funnel plot asymmetry was present in three out of four discordant pairs but in none of concordant pairs. In 14 (38%) journal meta-analyses and 5 (13%) Cochrane reviews, funnel plot asymmetry indicated that there was bias. Conclusions: A simple analysis of funnel plots provides a useful test for the likely presence of bias in meta-analyses, but as the capacity to detect bias will be limited when meta-analyses are based on a limited number of small trials the results from such analyses should be treated with considerable caution. Key messages Systematic reviews of randomised trials are the best strategy for appraising evidence; however, the findings of some meta-analyses were later contradicted by large trials Funnel plots, plots of the trials9 effect estimates against sample size, are skewed and asymmetrical in the presence of publication bias and other biases Funnel plot asymmetry, measured by regression analysis, predicts discordance of results when meta-analyses are compared with single large trials Funnel plot asymmetry was found in 38% of meta-analyses published in leading general medicine journals and in 13% of reviews from the Cochrane Database of Systematic Reviews Critical examination of systematic reviews for publication and related biases should be considered a routine procedure

Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries.

Abstract: This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.