scispace - formally typeset
Search or ask a question
Author

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.


Papers
More filters
Journal ArticleDOI
TL;DR: The existing literature fails to provide clear guidance regarding use of composite end points for competing risks and is recommended only if the competing risk is plausible and if it occurs with sufficiently high frequency to influence the interpretation of the effect of intervention on the end point of interest.

26 citations

Journal ArticleDOI
TL;DR: It is confirmed that PPIs and H2RAs are most likely to have a similar effect on mortality compared to each other and compared to no prophylaxis; however, the possibility thatPPIs may slightly increase mortality cannot be excluded (low certainty evidence).
Abstract: Motivated by a new randomized trial (the PEPTIC trial) that raised the issue of an increase in mortality with proton pump inhibitors (PPIs) relative to histamine-2 receptor antagonists (H2RAs), we updated our prior systematic review and network meta-analysis (NMA) addressing the impact of pharmacological gastrointestinal bleeding prophylaxis in critically ill patients. We searched for randomized controlled trials that examined the efficacy and safety of gastrointestinal bleeding prophylaxis with PPIs, H2RAs, or sucralfate versus one another or placebo or no prophylaxis in adult critically ill patients. We performed Bayesian random-effects NMA and conducted analyses using all PEPTIC data as well as a restricted analysis using only PEPTIC data from high compliance centers. We used the GRADE approach to quantify absolute effects and assess the certainty of evidence. Seventy-four trials enrolling 39 569 patients proved eligible. Both PPIs (risk ratio (RR) 1.03, 95% credible interval 0.93 to 1.14, moderate certainty) and H2RAs (RR 0.98, 0.89 to 1.08, moderate certainty) probably have little or no impact on mortality compared with no prophylaxis. There may be no important difference between PPIs and H2RAs on mortality (RR 1.05, 0.97 to 1.14, low certainty), the 95% credible interval of the complete analysis has not excluded an important increase in mortality with PPIs. Both PPIs (RR 0.46, 0.29 to 0.66) and H2RAs (RR 0.67, 0.48 to 0.94) probably reduce clinically important gastrointestinal bleeding; the magnitude of reduction is probably greater in PPIs than H2RAs (RR 0.69, 0.45 to 0.93), and the difference may be important in higher, but not lower bleeding risk patients. PPIs (RR 1.08, 0.88 to 1.45, low certainty) and H2RAs (RR 1.07, 0.85 to 1.37, low certainty) may have no important impact on pneumonia compared with no prophylaxis. This updated NMA confirmed that PPIs and H2RAs are most likely to have a similar effect on mortality compared to each other and compared to no prophylaxis; however, the possibility that PPIs may slightly increase mortality cannot be excluded (low certainty evidence). PPIs and H2RAs probably achieve important reductions in clinically important gastrointestinal bleeding; for higher bleeding risk patients, the greater benefit of PPIs over H2RAs may be important. PPIs or H2RAs may not result in important increases in pneumonia but the certainty of evidence is low.

26 citations

Journal ArticleDOI
TL;DR: A computer-based interactive DA for COPD patients considering inhaled steroids serving as a model for other DAs in COPD, in particular related to inhaled therapies, is developed.
Abstract: Decision aids (DA) are tools designed to help patients make specific and deliberative choices among disease management options. DAs can improve the quality of decision-making and reduce decisional conflict. An area not covered by a DA is the decision of a patient with chronic obstructive pulmonary disease (COPD) to use inhaled steroids which requires balancing the benefits and downsides of therapy. We developed a DA for COPD patients considering inhaled steroid therapy using the Ottawa Decision Support Framework, the best available evidence for using inhaled steroid in COPD and the expected utility model. The development process involved patients, pulmonologists, DA developers and decision making experts. We pilot tested the DA with 8 COPD patients who completed an evaluation questionnaire, a knowledge scale, and a validated decisional conflict scale. The DA is a computer-based interactive tool incorporating four different decision making models. In the first part, the DA provides information about COPD as a disease, the different treatment options, and the benefits and downsides of using inhaled steroids. In the second part, it coaches the patient in the decision making process through clarifying values and preferences. Patients evaluated 10 out of 13 items of the DA positively and showed significant improvement on both the knowledge scale (p = 0.008) and the decisional conflict scale (p = 0.008). We have developed a computer-based interactive DA for COPD patients considering inhaled steroids serving as a model for other DAs in COPD, in particular related to inhaled therapies. Future research should assess the DA effectiveness.

26 citations

Journal ArticleDOI
TL;DR: Though adjudication of outcomes such as VAP is time-consuming, consistent decision-making requires strict criteria, training, and calibration and patients should be assigned to adjudication teams through random allocation.

26 citations

Journal ArticleDOI
TL;DR: When RD is estimated from relative association measures that are nonsignificant and this counterintuitive situation occurs, it may be more appropriate to pool RD across studies, particularly valid when baseline risks across studies are homogeneous.

26 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: Moher et al. as mentioned in this paper introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses, which is used in this paper.
Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

62,157 citations

Journal Article
TL;DR: The QUOROM Statement (QUality Of Reporting Of Meta-analyses) as mentioned in this paper was developed to address the suboptimal reporting of systematic reviews and meta-analysis of randomized controlled trials.
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

46,935 citations

Journal ArticleDOI
04 Sep 2003-BMJ
TL;DR: A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.
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 …

45,105 citations

Journal ArticleDOI
13 Sep 1997-BMJ
TL;DR: Funnel plots, plots of the trials' 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.
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

37,989 citations

Journal ArticleDOI
TL;DR: The GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer (IARC) as mentioned in this paper show that 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 cancer, colorectal (11 4.4%), liver (8.3%), stomach (7.7%) and female breast (6.9%), and cervical cancer (5.6%) cancers.
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.

35,190 citations