What are network meta-analyses (NMAs)? A primer with four tips for clinicians who read NMAs and who perform them (methods matter series)

For a proper use of frequentist inferential statistics in public health

As widely noted in the literature and by international bodies such as the American Statistical Association, severe misinterpretations of P-values, confidence intervals, and statistical significance are sadly common in public health. This scenario poses serious risks concerning terminal decisions such as the approval or rejection of therapies. Cognitive distortions about statistics likely stem from poor teaching in schools and universities, overly simplified interpretations, and - as we suggest - the reckless use of calculation software with predefined standardized procedures. In light of this, we present a framework to recalibrate the role of frequentist-inferential statistics within clinical and epidemiological research. In particular, we stress that statistics is only a set of rules and numbers that make sense only when properly placed within a well-defined scientific context beforehand. Practical examples are discussed for educational purposes. Alongside this, we propose some tools to better evaluate statistical outcomes, such as multiple compatibility or surprisal intervals or tuples of various point hypotheses. Lastly, we emphasize that every conclusion must be informed by different kinds of scientific evidence (e.g., biochemical, clinical, statistical, etc.) and must be based on a careful examination of costs, risks, and benefits.

Comparing the Efficacy and Adverse Events of Available COVID-19 Vaccines Through Randomized Controlled Trials: Updated Systematic Review and Network Meta-analysis

BACKGROUND

Different vaccines have so far been developed and approved to cope with COVID-19 in the world. The aim of this updated network meta-analysis (NMA) was to compare and rank all available vaccines in terms of efficacy and complications simultaneously. Study Design: A systematic review.

METHODS

Three major international databases, including Web of Science, Medline via PubMed, and Scopus, were searched through September 2023. The transitivity assumption was evaluated qualitatively in terms of epidemiologic effect modifiers. The exposure of interest in this study was receiving any available COVID-19 vaccine, and the primary outcome of interest was the incidence of symptomatic COVID-19. In this NMA, the relative risk of symptomatic COVID-19 was used to summarize the efficacy of vaccines in preventing COVID-19. The data were analyzed using the frequentist-based approach, and the results were reported using a random-effects model. Finally, the vaccines were ranked using a P-score.

RESULTS

In total, 34 randomized controlled trials (RCTs) met the eligibility criteria for this systematic review and NMA out of 3682 retrieved references. Based on the results of the NMA, mRNA-1273 was the most effective vaccine in preventing COVID-19 and demonstrated the highest P-score (0.93). The relative risk (RR) for mRNA-1273 versus placebo was 0.07 (95% confidence interval [CI]: 0.03, 0.17). The second and third-ranked vaccines were BNT-162b2 (RR=0.08; 95% CI: 0.04, 0.15; P-score=0.93) and Gam-COVID-Vac (0.09; 95% CI: 0.03, 0.25; 0.88).

CONCLUSION

Based on the results of this NMA, it seems that all available vaccines were effective in COVID-19 prevention. However, the top three ranked vaccines were mRNA-1273, BNT-162b2, and Gam-COVID-Vac, respectively.

Comparison of corticosteroids types, dexamethasone, and methylprednisolone in patients hospitalized with COVID-19: A systematic review and network meta-analysis

Background

COVID-19 is associated with severe pneumonia lung damage, acute respiratory distress syndrome (ARDS), and mortality. In this study, we aimed to compare corticosteroids' effect on the mortality risk in patients hospitalized with COVID-19.

Methods

PubMed, Web of Science, Scopus, Cochrane Library, and Embase, were searched using a predesigned search strategy. Randomized controlled trials (RCTs) that had compared the corticosteroid drugs were included. The hazard ratio (HR) with a 95% confidence interval (CI) was used to summarize the effect size from the network meta-analysis (NMA).

Results

Out of 329 retrieved references, 12 RCTs with 11,455 participants met the eligibility criteria in this review. The included RCTs formed one network with six treatments. In addition, five treatments in two RCTs were not connected to the network. Methylprednisolone + usual care (UC) versus UC decreased the risk of death by 0.65 (95% CI: 0.47, 0.90). Among treatments in the network the highest P-score (0.89) was related to Methylprednisolone + UC.

Conclusion

Based on the results of this NMA it seems Methylprednisolone + UC to be the best treatment option in patients with COVID-ARDS and COVID pneumonia.

Diet Therapeutics Interventions for Obesity: A Systematic Review and Network Meta-Analysis

Background: Up to now, different diet therapeutics interventions have been introduced for the treatment of obesity. The present study aimed to compare the diet therapeutics interventions for obesity simultaneously.

Study design: Systematic review and network meta-analysis

Methods: The major international databases, including Medline (via PubMed), Web of Science, Scopus, Cochrane Library, and Embase, were searched using a predesigned search strategy. Randomized controlled trials (RCTs) that had compared the diet therapy interventions were included. The mean difference with a 95% confidence interval was used to summarize the effect size in the network meta-analysis. The frequentist approach was used for data analysis.

Results: In total, 36 RCTs out of 9335 retrieved references met the inclusion criteria in this review. The included RCTs formed nine independent networks. Based on the results, Hypocaloricdiet+Monoselect Camellia (MonCam, P=0.99), energy restriction, behavior modification+exercise (LED) (P=0.99), sweetener at 20% of total calories (HFCS20)+Ex (P=0.67), catechin-richgreentea(650)+inulin (P=0.68), very low calorie diet (VLCD) (P=1.00), normal protein diet+resistance exercise (NPD+RT) (P=0.80), low-calorie diets+exercise (Hyc+Ex) (P=0.85), high-soy-protein low-fat diet (SD) (P=0.75), calorie restriction+behavioral weight loss (Hyc+BWL) (P=0.99) were the better treatments for weight loss in the networks one to nine, respectively.

Conclusion: Based on the results of network meta-analysis, it seems that Hypocaloricdiet+MonCam, LED, HFCS20+Ex, catechin-rich green tea +inulin, VLCD, NPD+RT, Hyc+Ex, SD, Hyc+BWL, are the better treatments for weight loss in patients with overweight and obesity.

A CHecklist for statistical Assessment of Medical Papers (the CHAMP statement): explanation and elaboration

Misuse of statistics in medical and sports science research is common and may lead to detrimental consequences to healthcare. Many authors, editors and peer reviewers of medical papers will not have expert knowledge of statistics or may be unconvinced about the importance of applying correct statistics in medical research. Although there are guidelines on reporting statistics in medical papers, a checklist on the more general and commonly seen aspects of statistics to assess when peer-reviewing an article is needed. In this article, we propose a CHecklist for statistical Assessment of Medical Papers (CHAMP) comprising 30 items related to the design and conduct, data analysis, reporting and presentation, and interpretation of a research paper. While CHAMP is primarily aimed at editors and peer reviewers during the statistical assessment of a medical paper, we believe it will serve as a useful reference to improve authors' and readers' practice in their use of statistics in medical research. We strongly encourage editors and peer reviewers to consult CHAMP when assessing manuscripts for potential publication. Authors also may apply CHAMP to ensure the validity of their statistical approach and reporting of medical research, and readers may consider using CHAMP to enhance their statistical assessment of a paper.