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.

Transferring evidence from research into practice: 2. Getting the evidence straight

Abstract: In Part 1 of this series (1), we considered a simple model for evidencebased clinical decision making that included 3 components: clinical expertise, patient preferences, and evidencefrom research.

Quality of life in cystic fibrosis.

Abstract: Cystic fibrosis is a chronic, multisystem genetic disease with a wide variability in clinical severity. In recent years, advances in therapy have led to improved patient survival into adulthood. New treatments are rapidly being developed and require evaluation to determine their efficacy. The measurement of health-related quality of life in cystic fibrosis provides additional information about the impact of this disease that cannot be obtained by physiological tests such as pulmonary function. An instrument to measure health-related quality of life is especially useful as an outcome measure for clinical trials. To date, only a few general quality-of-life (QOL) measures have been used in people with cystic fibrosis. There has been some demonstration of validity in 2 measures (the Quality of Well-Being Scale and the Functional Status Index) but the responsiveness of these instruments in this population has not been established. A cystic fibrosis-specific QOL instrument would be valuable as an outcome measure because of its potential for increased responsiveness, but no published measures exist as yet.

Critical-sized defect in the tibia: is it critical? Results from the SPRINT trial.

Abstract: Objectives The purpose of this study was to determine whether the SPRINT definition of a "critical-sized defect" (fracture gap at least 1 cm in length and involving over 50% of the cortical diameter) was accurate, to discern which factors predict reoperation in patients with these defects, and to compare the patient-based outcomes of these patients with patients without a critical defect. Design Therapeutic Cohort Study. Setting Level 1 and level 2 trauma centers. Patients Thirty-seven patients in the SPRINT trial with a critical-sized defect participated. We evaluated these patients for planned and unplanned secondary intervention to gain union. Additionally, we evaluated which other factors predicted the need for reoperation. Finally, the 37 patients with a critical defect were compared with the larger cohort of patients without a defect with respect to demographics, mechanism of injury, fracture characteristics, and patient-based outcome. Intervention Revision surgery for tibial nonunion. Results Of the 37 patients with a large fracture gap, 7 patients had a planned secondary procedure. Of the remaining 30 patients in whom the attending surgeon adopted a "watch and wait" strategy, 14 patients (47%) never required additional surgery to gain union. Additional surgery to gain union was less likely in patients treated with a reamed nail (P = 0.04) and in female patients (P = 0.04). Patients with a critical-sized defect were more likely to have a high-energy mechanism of injury (P = 0.001), AO-OTA fracture type 42 B or C (P Conclusions Tibial diaphyseal defects of >1 cm and >50% cortical circumference healed without additional surgery in 47% of cases. This definition of a critical-sized defect is not "critical." However, as compared with the overall cohort of tibial fractures, patients with these bone defects had a higher rate of reoperation and worse patient-based outcomes. Further investigation is required to determine which factors predict union in this challenging fracture to avoid unnecessary secondary surgery. Level of evidence Prognostic level I. See instructions for authors for a complete description of levels of evidence.

How to keep up with the medical literature: II. Deciding which journals to read regularly.

Abstract: For practitioners, one of the major objectives for reading the medical literature is to maintain clinical competence. Ideally, this task is accomplished through efficiently extracting from...

A practical approach to evidence-based dentistry: Understanding and applying the principles of EBD

Abstract: Scientific evidence is a crucial underpinning of clinical practice. Nevertheless, the first series of articles aimed at providing clinicians with guidelines for critically appraising the evidence that informs clinical practices did not appear until 1981.1 Ten years later, the term “evidence-based medicine”2 first appeared in the medical literature. Subsequently, between 1993 and 2000, a group of evidence-based medicine enthusiasts3 published a series of 25 articles that aimed at assisting clinicians in understanding and applying the medical literature to their clinical decision making in a clinical setting.4 The concept of evidence-based medicine soon expanded to other clinical areas. The first article to use the term “evidence-based dentistry” (EBD) was published in 1995 by Richards and Lawrence,5 and since then other articles have been published on the topic.6-11 There is, however, still no guide easily accessible for practicing dentists in the United States that addresses the critical appraisal and use of evidence specifically aimed at clinicians in oral health care fields. A series of articles (Box) will be published in The Journal of the American Dental Association, aimed at providing an overview of the basic concepts of EBD to assist oral health care professionals in making use of evidence to inform their clinical decisions. The series will consist of, in addition to this introductory commentary, six core articles that will address the main topics in EBD. In this introductory commentary, we will define EBD, delineate its principles and outline the main steps in the process of EBD. The first core article will describe how to state questions in a format that facilitates searching for the evidence, and where and how to search for such evidence. In the remaining articles, we will explain how to use literature about therapy and prevention, etiology and prognosis, and diagnosis as well as systematic reviews and clinical practice guidelines.

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.