Background: Based on randomized controlled trials, a network meta-analysis was conducted to compare treatment effects across varenicline and related smoking interventions. Methods: English databases were screened for randomized controlled trials reporting the effect of varenicline as treatment for smoking. The risk of bias in included trials was assessed using the Cochrane Handbook tool. Stata 15.1 software was used to perform network meta-analysis, and the GRADE approach was used to assess the evidence credibility on the tobacco treatment effects of different interventions. Results: Thirty-four studies involving 26,130 smokers were included in the network meta-analysis. Varenicline and 11 other interventions were reported, yielding 66 pairs of comparisons. Network meta-analysis showed that varenicline monotherapy or its combination with other interventions were superior in achieving smoking cessation compared to bupropion, nicotine replacement therapy, counselling, and placebo. Furthermore, compared to the varenicline, evident abstinence superiority was found in varenicline + bupropion (odds ratio = 1.49, 95% confidence interval [1.02, 2.18]). Finally, the surface under the cumulative ranking curve value indicated that varenicline + bupropion has the highest probability to become the best intervention. Conclusions: Varenicline monotherapy increased the odds of smoking cessation further than bupropion monotherapy, nicotine replacement therapy, counselling, and placebo, while varenicline combined with other interventions may even achieve a better abstinence effect. More credible evidence has been reported indicating that the combination of varenicline and bupropion is a superior treatment for smoking.

Objective To evaluate the reporting quality of single-patient (N-of-1) trials and protocols based on the CONSORT Extension for N-of-1 trials (CENT) statement and the standard protocol items: recommendations for interventional trials (SPIRIT) extension and elaboration for N-of-1 trials (SPENT) checklist to examine the factors that influenced reporting quality. Methods Four electronic databases were searched to identify N-of-1 trials and protocols from 2015 to 2020. Quality was assessed by two reviewers. We calculated the overall scores based on binary responses in which "Yes" was scored as 1 (if the item was fully reported), and "No" was scored as 0 (if the item was not clearly reported or not definitely stated). Results A total of 78 publications (55 N-of-1 trials and 23 protocols) were identified. The mean reporting score (SD) of the N-of-1 trials and protocols were 29.24 (0.89) and 29.61 (1.83), respectively. For the items related to outcomes, sample size, allocation concealment protocol, and informed consent materials, the reporting quality was low. Our results showed that the year of publication (t = -0.793, p = 0.872 for the trials and t = 1.352, p = 0.623 for the protocols) and the impact factor of the journal (t = 1.416, p = 0.619 for the trials and t = 0.359, p = 0.667 for the protocols) were not factors associated with better reporting quality. Conclusion With the publication of the CENT 2015 statement and the SPENT 2019 checklist, authors should adhere to the relevant reporting guidelines and improve the reporting quality of N-of-1 trials and protocols.

Objective: A network meta-analysis (NMA) was conducted to investigate the effect of varenicline (VAR), bupropion (BUP), and nicotine replacement therapy (NRT) on smoking cessation. Methods: Eight databases were searched in May 2021, and only randomized controlled trials (RCTs) using varenicline, bupropion, or NRT (single or combined) for smoking cessation were included. The risk of bias in the included RCTs was assessed using the Cochrane Handbook tool. Stata 15.1 software was used to perform NMA, and the quality of the evidence was evaluated using Confidence in Network Meta-analysis (CINeMA). Findings: Twenty RCTs involving 16,702 smokers were included. The risk of bias results showed that 10 RCTs were rated as high, three were low, and seven were unclear. A total of 21 pairs were compared based on seven interventions. The NMA showed that, compared to the placebo (PLA), the other six interventions had significant efficacy in smoking cessation, where VAR + BUP showed the best effect of all treatments (odds ratio (OR) = 6.08, 95% confidence interval (CI) [3.47, 10.66]). Moreover, VAR + BUP was superior to VAR + NRT (OR = 1.66, 95% CI [1.07, 2.59]) and the three monotherapies (VAR, BUP, and NRT). In the monotherapies, the results of pairwise comparisons of VAR, BUP, and NRT did not show significant differences. Finally, the surface under the cumulative ranking curve (SUCRA) value indicated that VAR + BUP had the greatest probability of becoming the best intervention. Conclusions: The efficacy of VAR, BUP, and NRT alone increased the odds of smoking abstinence better than the placebo, combined interventions were superior to monotherapy, and VAR combined with other interventions had a better smoking cessation effect.

Since the outbreak of coronavirus disease in 2019, the controversy over the effectiveness, safety, and enforceability of masks used by the public has been prominent. This study aims to identify, describe, and organize the currently available high-quality design evidence concerning mask use during the spread of respiratory viruses and find evidence gaps. Databases including PubMed, Cochrane Library, Web of Science, EMBASE, WHO International Clinical Trials Registry Platform (ICTRP), clinical trial registry, gray literature database, and reference lists of articles were searched for relevant randomized controlled trials (RCTs) and systematic reviews (SRs) in April 2020. The quality of the studies was assessed using the risk of bias tool recommended by the Cochrane Handbook Version 5.1.0 and the Assessment of Multiple Systematic Reviews (AMSTAR 2) tool. A bubble plot was designed to display information in four dimensions. Finally, twenty-one RCTs and nine SRs met our inclusion criteria. Most studies were of "Low quality" and focused on healthcare workers. Six RCTs reported adverse effects, with one implying that the cloth masks reuse may increase the infection risk. When comparing masks with usual practice, over 70% RCTs and also SRs showed that masks were "beneficial" or "probably beneficial"; however, when comparing N95 respirators with medical masks, 75% of SRs showed "no effect", whereas 50% of RCTs showed "beneficial effect". Overall, the current evidence provided by high-quality designs may be insufficient to deal with a second impact of the pandemic. Masks may be effective in interrupting or reducing the spread of respiratory viruses; however, the effect of an N95 respirator or cloth masks versus medical masks is unclear. Additional high-quality studies determining the impact of prolonged mask use on vulnerable populations (such as children and pregnant women), the possible adverse effects (such as skin allergies and shortness of breath) and optimal settings and exposure circumstances for populations to use masks are needed.