scholarly journals Revisiting Statistics and Evidence-Based Medicine: On the Fallacy of the Effect Size Based on Correlation and Misconception of Contingency Tables

2021 ◽  
Author(s):  
Sergey Roussakow
Keyword(s):  
Effect Size ◽  
Evidence Based Medicine ◽  
Binary Data ◽  
Contingency Tables ◽  
Evidence Based ◽  
Mean Square ◽  
Bias Analysis ◽  
Contingency Coefficient ◽  
Meta Analyses ◽  
Based Medicine

Abstract BACKGROUND: Evidence-based medicine (EBM) is in crisis, in part due to bad methods, which are understood as misuse of statistics that is considered correct in itself. The correctness of the basic statistics related to the effect size (ES) based on correlation (CBES) was questioned. METHODS: Monte Carlo simulation of two paired binary samples, mathematical analysis, conceptual analysis, bias analysis. RESULTS: Actual effect size and CBES are not related. CBES is a fallacy based on misunderstanding of correlation and ES and confusion with 2 × 2 tables that makes no distinction between gross crosstabs (GCTs) and contingency tables (CTs). This leads to misapplication of Pearson’s Phi, designed for CTs, to GCTs and confusion of the resulting gross Pearson Phi, or mean-square effect half-size, with the implied Pearson mean square contingency coefficient. Generalizing this binary fallacy to continuous data and the correlation in general (Pearson’s r) resulted in flawed equations directly expressing ES in terms of the correlation coefficient, which is impossible without including covariance, so these equations and the whole CBES concept are fundamentally wrong. misconception of contingency tables (MCT) is a series of related misconceptions due to confusion with 2 × 2 tables and misapplication of related statistics. Problems arising from these fallacies are discussed and the necessary changes to the corpus of statistics are proposed resolving the problem of correlation and ES in paired binary data. CONCLUSIONS: Two related common misconceptions in statistics have been exposed, CBES and MCT. The misconceptions are threatening because most of the findings from contingency tables, including meta-analyses, can be misleading. Since exposing these fallacies casts doubt on the reliability of the statistical foundations of EBM in general, we urgently need to revise them.

scholarly journals Revisiting Statistics and Evidence-Based Medicine: On the Fallacy of the Effect Size Based on Correlation and Misconception of Contingency Tables

2021 ◽  
Author(s):  
Sergey Roussakow
Keyword(s):  
Effect Size ◽  
Evidence Based Medicine ◽  
Binary Data ◽  
Contingency Tables ◽  
Evidence Based ◽  
Mean Square ◽  
Contingency Coefficient ◽  
Meta Analyses ◽  
Based Medicine ◽  
Common Misconceptions

Evidence-based medicine (EBM) is in crisis, in part due to bad methods, which are understood as misuse of statistics that is considered correct in itself. This article exposes two related common misconceptions in statistics, the effect size (ES) based on correlation (CBES) and a misconception of contingency tables (MCT). CBES is a fallacy based on misunderstanding of correlation and ES and confusion with 2 × 2 tables, which makes no distinction between gross crosstabs (GCTs) and contingency tables (CTs). This leads to misapplication of Pearson’s Phi, designed for CTs, to GCTs and confusion of the resulting gross Pearson Phi, or mean-square effect half-size, with the implied Pearson mean square contingency coefficient. Generalizing this binary fallacy to continuous data and the correlation in general (Pearson’s r) resulted in flawed equations directly expressing ES in terms of the correlation coefficient, which is impossible without including covariance, so these equations and the whole CBES concept are fundamentally wrong. MCT is a series of related misconceptions due to confusion with 2 × 2 tables and misapplication of related statistics. The misconceptions are threatening because most of the findings from contingency tables, including CBES-based meta-analyses, can be misleading. Problems arising from these fallacies are discussed and the necessary changes to the corpus of statistics are proposed resolving the problem of correlation and ES in paired binary data. Since exposing these fallacies casts doubt on the reliability of the statistical foundations of EBM in general, we urgently need to revise them.

scholarly journals THERAPEUTIC METHODS IN CEREBRAL PALSY FROM THE STANDPOINT OF EVIDENCE-BASED MEDICINE

2019 ◽  
Vol 21 (3) ◽  
pp. 168-174
Author(s):  
Leila A. Pak ◽  
K. V. Zherdev ◽  
L. M. Kuzenkova ◽  
A. L. Kurenkov ◽  
B. I. Bursagova
Keyword(s):  
Cerebral Palsy ◽  
Stem Cell ◽  
Evidence Based Medicine ◽  
Vagal Stimulation ◽  
Clinical Manifestations ◽  
Evidence Based ◽  
Complementary Treatment ◽  
Epidural Stimulation ◽  
Meta Analyses ◽  
Based Medicine

In the article the authors consider such methods of the alternative/complementary treatment of the cerebral palsy (CP), presented in the modern domestic and foreign literature, as metabolic (amino acid composites), metamer (I.A. Skvortsov), intravenous administration of baclofen, antiepileptic (vagal stimulation, levetiracetam), acupuncture, transcranial cerebral micropolarization, epidural stimulation, modified motion-induced restriction therapy (MMIRT), stem cell therapy, as well as some other complementary/palliative approaches to the correction of clinical manifestations of various forms of CP. The final part of the article presents the attitude of modern evidence-based medicine to the main methods of the alternative/complementary treatment of cerebral palsy. These data are based almost exclusively on international systematic reviews and relevant meta-analyses.

scholarly journals Pearls for Interpreting Neurosurgical Systematic Reviews and Meta-Analyses: Lessons From a Collaborative Effort

Neurosurgery ◽  
2020 ◽  
Vol 87 (3) ◽  
pp. 435-441 ◽  
Author(s):  
Victor M Lu ◽  
Christopher S Graffeo ◽  
Avital Perry ◽  
Michael J Link ◽  
Fredric B Meyer ◽  
...  
Keyword(s):  
Systematic Reviews ◽  
Evidence Based Medicine ◽  
Lessons Learned ◽  
Evidence Based ◽  
Cranial Neuralgia ◽  
The Individual ◽  
Meta Analyses ◽  
Based Medicine ◽  
Over Time

Abstract Systematic reviews and meta-analyses in the neurosurgical literature have surged in popularity over the last decade. It is our concern that, without a renewed effort to critically interpret and appraise these studies as high or low quality, we run the risk of the quality and value of evidence-based medicine in neurosurgery being misinterpreted. Correspondingly, we have outlined 4 major domains to target in interpreting neurosurgical systematic reviews and meta-analyses based on the lessons learned by a collaboration of clinicians and academics summarized as 4 pearls. The domains of (1) heterogeneity, (2) modeling, (3) certainty, and (4) bias in neurosurgical systematic reviews and meta-analyses were identified as aspects in which the authors’ approaches have changed over time to improve robustness and transparency. Examples of how and why these pearls were adapted were provided in areas of cranial neuralgia, spine, pediatric, and neuro-oncology to demonstrate how neurosurgical readers and writers may improve their interpretation of these domains. The incorporation of these pearls into practice will empower neurosurgical academics to effectively interpret systematic reviews and meta-analyses, enhancing the quality of our evidence-based medicine literature while maintaining a critical focus on the needs of the individual patients in neurosurgery.

scholarly journals Current Status of Cell-Based Therapy in Patients with Critical Limb Ischemia

2020 ◽  
Vol 21 (23) ◽  
pp. 8999
Author(s):  
Frantisek Jaluvka ◽  
Peter Ihnat ◽  
Juraj Madaric ◽  
Adela Vrtkova ◽  
Jaroslav Janosek ◽  
...  
Keyword(s):  
Cell Therapy ◽  
Critical Limb Ischemia ◽  
Evidence Based Medicine ◽  
Odds Ratio ◽  
Limb Ischemia ◽  
Current Evidence ◽  
Evidence Based ◽  
Cell Based Therapy ◽  
Meta Analyses ◽  
Based Medicine

(1) Background: The treatment of peripheral arterial disease (PAD) is focused on improving perfusion and oxygenation in the affected limb. Standard revascularization methods include bypass surgery, endovascular interventional procedures, or hybrid revascularization. Cell-based therapy can be an alternative strategy for patients with no-option critical limb ischemia who are not eligible for endovascular or surgical procedures. (2) Aims: The aim of this narrative review was to provide an up-to-date critical overview of the knowledge and evidence-based medicine data on the position of cell therapy in the treatment of PAD. The current evidence on the cell-based therapy is summarized and future perspectives outlined, emphasizing the potential of exosomal cell-free approaches in patients with critical limb ischemia. (3) Methods: Cochrane and PubMed databases were searched for keywords “critical limb ischemia and cell therapy”. In total, 589 papers were identified, 11 of which were reviews and 11 were meta-analyses. These were used as the primary source of information, using cross-referencing for identification of additional papers. (4) Results: Meta-analyses focusing on cell therapy in PAD treatment confirm significantly greater odds of limb salvage in the first year after the cell therapy administration. Reported odds ratio estimates of preventing amputation being mostly in the region 1.6–3, although with a prolonged observation period, it seems that the odds ratio can grow even further. The odds of wound healing were at least two times higher when compared with the standard conservative therapy. Secondary endpoints of the available meta-analyses are also included in this review. Improvement of perfusion and oxygenation parameters in the affected limb, pain regression, and claudication interval prolongation are discussed. (5) Conclusions: The available evidence-based medicine data show that this technique is safe, associated with minimum complications or adverse events, and effective.

scholarly journals What is a multiple treatments meta-analysis?

2012 ◽  
Vol 21 (2) ◽  
pp. 151-153 ◽  
Author(s):  
A. Cipriani ◽  
C. Barbui ◽  
C. Rizzo ◽  
G. Salanti
Keyword(s):  
Evidence Based Medicine ◽  
Treatment Effects ◽  
Meta Analysis ◽  
Evidence Based ◽  
Relative Efficacy ◽  
Analytical Technique ◽  
Multiple Treatments ◽  
Meta Analyses ◽  
Based Medicine ◽  
Indirect Comparisons

Standard meta-analyses are an effective tool in evidence-based medicine, but one of their main drawbacks is that they can compare only two alternative treatments at a time. Moreover, if no trials exist which directly compare two interventions, it is not possible to estimate their relative efficacy. Multiple treatments meta-analyses use a meta-analytical technique that allows the incorporation of evidence from both direct and indirect comparisons from a network of trials of different interventions to estimate summary treatment effects as comprehensively and precisely as possible.

‘Evidence-based’, ‘Cost-Effective’ and ‘Preference-Driven’ Medicine: Decision Analysis Based Medical Decision Making is the Pre-Requisite

1996 ◽  
Vol 1 (2) ◽  
pp. 104-113 ◽  
Author(s):  
Jack Dowie
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Evidence Based Medicine ◽  
Medical Decision Making ◽  
Clinical Effectiveness ◽  
Cost Effective ◽  
Medical Decision ◽  
Evidence Based ◽  
Meta Analyses ◽  
Based Medicine

Three broad movements are seeking to change the world of medicine. The proponents of ‘evidence-based medicine’ are mainly concerned with ensuring that strategies of proven clinical effectiveness are adopted. Health economists are mainly concerned to establish that ‘cost-effectiveness’ and not ‘clinical effectiveness’ is the criterion used in determining option selection. A variety of patient support and public interest groups, including many health economists, are mainly concerned with ensuring that patient and public preferences drive clinical and policy decisions. This paper argues that decision analysis based medical decision making (DABMDM) constitutes the pre-requisite for the widespread introduction of the main principles embodied in evidence-based medicine, cost-effective medicine and preference-driven medicine; that, in the light of current modes of practice, seeking to promote these principles without a prior or simultaneous move to DABMDM is equivalent to asking the cart to move without the horse; and that in fact DABMDM subsumes and enjoins the valuable aspects of all three. Particular attention is paid to differentiating between DABMDM and EBM, by way of analysis of various expositions of EBM and examination of two recent empirical studies. EBM, as so far expounded, reflects a problem-solving attitude that results in a heavy concentration on RCTs and meta-analyses, rather than a broad decision making focus that concentrates on meeting all the requirements of a good clinical decision. The latter include: Ensuring that inferences from RCTs and meta-analyses to individual patients (or patient groups) are made explicitly; paying equally serious attention to evidence on values and costs as to clinical evidence; and accepting the inadequacy of ‘taking into account and bearing in mind’ as a way of integrating the multiple and distinct elements of a decision.

scholarly journals Evidence-Based Medicine, Systematic Reviews, and Guidelines in Interventional Pain Management: Part 6. Systematic Reviews and Meta-Analyses of Observational Studies

2008 ◽  
Vol 5;12 (5;9) ◽  
pp. 819-850
Author(s):  
Laxmaiah Manchikanti
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Evidence Based Medicine ◽  
Observational Studies ◽  
Meta Analysis ◽  
Evidence Based ◽  
Confounding Bias ◽  
Meta Analyses ◽  
Based Medicine

Observational studies provide an important source of information when randomized controlled trials (RCTs) cannot or should not be undertaken, provided that the data are analyzed and interpreted with special attention to bias. Evidence-based medicine (EBM) stresses the examination of evidence from clinical research and describes it as a shift in medical paradigm, in contrast to intuition, unsystematic clinical experience, and pathophysiologic rationale. While the importance of randomized trials has been created by the concept of the hierarchy of evidence in guiding therapy, much of the medical research is observational. The reporting of observational research is often not detailed and clear enough with insufficient quality and poor reporting, which hampers the assessment of strengths and weaknesses of the study and the generalizability of the mixed results. Thus, in recent years, progress and innovations in health care are measured by systematic reviews and meta-analyses. A systematic review is defined as, “the application of scientific strategies that limit bias by the systematic assembly, clinical appraisal, and synthesis of all relevant studies on a specific topic.” Meta-analysis usually is the final step in a systematic review. Systematic reviews and meta-analyses are labor intensive, requiring expertise in both the subject matter and review methodology, and also must follow the rules of EBM which suggests that a formal set of rules must complement medical training and common sense for clinicians to integrate the results of clinical research effectively. While expertise in the review methods is important, the expertise in the subject matter and technical components is also crucial. Even though, systematic reviews and meta-analyses, specifically of RCTs, have exploded, the quality of the systematic reviews is highly variable and consequently, the opinions reached of the same studies are quite divergent. Numerous deficiencies have been described in methodologic assessment of the quality of the individual articles. Consequently, observational studies can provide an important complementary source of information, provided that the data are analyzed and interpreted in the context of confounding bias to which they are prone. Appropriate systematic reviews of observational studies, in conjunction with RCTs, may provide the basis for elimination of a dangerous discrepancy between the experts and the evidence. Steps in conducting systematic reviews of observational studies include planning, conducting, reporting, and disseminating the results. MOOSE, or Meta-analysis of Observational Studies in Epidemiology, a proposal for reporting contains specifications including background, search strategy, methods, results, discussion, and conclusion. Use of the MOOSE checklist should improve the usefulness of meta-analysis for authors, reviewers, editors, readers, and decision-makers. This manuscript describes systematic reviews and meta-analyses of observational studies. Authors frequently utilize RCTs and observational studies in one systematic review; thus, they should also follow the reporting standards of the Quality of Reporting of Meta-analysis (QUOROM) statement, which also provides a checklist. A combined approach of QUOROM and MOOSE will improve reporting of systematic reviews and lead to progress and innovations in health care. Key words: Observational studies, evidence-based medicine, systematic reviews, metaanalysis, randomized trials, case-control studies, cross-sectional studies, cohort studies, confounding bias, QUOROM, MOOSE

Evidence-based medicine

2017 ◽  
Author(s):  
Philip Wiffen ◽  
Marc Mitchell ◽  
Melanie Snelling ◽  
Nicola Stoner
Keyword(s):  
Evidence Based Medicine ◽  
Binary Data ◽  
Statistical Significance ◽  
Number Needed To Treat ◽  
Evidence Based ◽  
High Quality ◽  
Relative Risks ◽  
High Quality Evidence ◽  
Based Medicine ◽  
Quality Evidence

This chapter provides a brief overview to the concept of evidence-based medicine (EBM) starting with a well-accepted definition. The importance of clinical significance over statistical significance is discussed. A number of useful tools are presented and described to enable the practitioner to become competent in recognizing high-quality evidence and to have the skills to critically appraise evidence that is potentially important to their practice. There is a brief description of some of the statistical tools commonly used in EBM including binary data tools such as odds ratios, number needed to treat, and relative risks.

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