Meta-analysis: Fixed-effect model

Seasonal peak and the role of local weather in schizophrenia occurrence: A global analysis of epidemiological evidence

BACKGROUND

Many studies have shown that the onset of schizophrenia peaked in certain months within a year and the local weather conditions could affect the morbidity risk of schizophrenia. This study aimed to conduct a systematic analysis of schizophrenia seasonality in different countries of the world and to explore the effects of weather factors globally.

METHODS

We searched three databases (PubMed, Web of Science, and China National Knowledge Infrastructure) for eligible studies published up to September 2022. Schizophrenia seasonality was compared between hemispheres and within China. A meta-analysis was conducted to pool excess risk (ER, absolute percentage increase in risk) of the onset of schizophrenia associated with various weather factors including temperature (an increase or decrease of temperature as a reflection of high or low temperature; heatwave; temperature variation), precipitation, etc. RESULTS: We identified 84 relevant articles from 22 countries, mainly in China. The seasonality analysis found that the onset of schizophrenia mostly peaked in the cold season in the southern hemisphere but in the warm season in the northern hemisphere. Interestingly in China, schizophrenia seasonality presented two peaks, respectively in the late cold and warm seasons. The meta-analysis further revealed an increased risk of schizophrenia after short-term exposure to high temperature [ER%: 0.45 % (95 % confidence interval (CI): 0.14 % to 0.76 %)], low temperature [ER%: 0.52 % (95%CI: 0.29 % to 0.75 %)], heatwave [ER%: 7.26 % (95%CI: 4.45 % to 10.14 %)], temperature variation [ER%: 1.02 % (95%CI: 0.55 % to 1.50 %)], extreme precipitation [ER%: 3.96 % (95%CI: 2.29 % to 5.67 %)]. The effect of other weather factors such as sunlight on schizophrenia was scarcely investigated with inconsistent findings.

CONCLUSION

This study provided evidence of intra- and inter-country variations in schizophrenia seasonality, especially the double-peak seasons in China. Exposure to local weather conditions mainly temperature changes and precipitation could affect the onset risk of schizophrenia.

The effect of selenium therapy in critically ill patients: an umbrella review of systematic reviews and meta-analysis of randomized controlled trials

BACKGROUND

Selenium is an essential nutrient with antioxidant, anti-inflammatory, and immuno-regulatory properties. Studies have displayed that in critically ill patients, selenium supplementation may be a potentially promising adjunctive therapy.

OBJECTIVE

We aimed to present an overview of the effects of selenium supplementation in adult critically ill patients based on published systematic reviews and meta-analyses (SRMAs) of randomized controlled trials (RCTs).

METHODS

A literature search in three electronic databases, PubMed, Scopus, and Web of Science, was performed to find eligible SRMAs until July 2022. For each outcome, the risk ratios (RRs) or mean differences (MDs) and 95% confidence intervals (CIs) were recalculated using either random or fixed effect models. The methodological quality and quality of evidence of the SRMAs were assessed by applying "A Measurement Tool to Assess Systematic Reviews" (AMSTAR2) and Grading of Recommendations Assessment, Development, and Evaluation(GRADE) tools, respectively.

RESULTS

We included 17 meta-analyses containing 24 RCTs based on inclusion criteria. Selenium supplementation can reduce the incidence of mortality (RR: 0.83, 95% CI 0.71, 0.98, P = 0.024) and incidence of acute renal failure (RR: 0.67, 95% CI 0.46, 0.98, P: 0.038) significantly; however, the certainty of evidence was low. Moreover, with moderate to very low certainty of evidence, no significant effects were found for risk of infection (RR: 0.92, 95% CI 0.80, 1.05, P: 0.207), pneumonia (RR: 1.11, 95% CI 0.72, 1.72, P: 0.675), as well as the length of ICU (MD: 0.15, 95% CI - 1.75, 2.05, P: 0.876) and hospital stay (MD: - 0.51, 95% CI - 3.74, 2.72, P: 0.757) and days on ventilation (MD: - 0.98, 95% CI - 2.93, 0.98, P: 0.329).

CONCLUSIONS

With low quality of evidence, the use of selenium supplementation could improve the risk of mortality and acute renal failure, but not other outcomes in critically ill patients.

Impact of New Systemic Therapies in Overall Survival in Non-Metastatic Castration Resistant Prostate Cancer: Systematic Review and Meta-Analysis

There was a high medical need for patients with non-metastatic castration-resistant prostate cancer (nmCRPC) when several next-generation anti-androgens (apalutamide, enzalutamide, and darolutamide) demonstrated clinically relevant delays in metastasis onset. However, to date, few publications have assessed the pooled effect of these treatments on overall survival (OS). We performed a systematic review and meta-analysis of all randomized, placebo-controlled studies investigating a systemic treatment in nmCRPC. Publications were identified by searching several databases on April 7, 2021. The primary objective of this analysis was to determine the OS benefit. Secondary outcomes included the relative risk (RR) of adverse events (AEs) and grade 3-4 AEs. A sensitivity analysis with simulated data was also conducted to examine the influence of the study designs on the results. Three randomized controlled studies (SPARTAN, PROSPER, ARAMIS) met our inclusion criteria. Pooled meta-analyses showed a significant benefit in OS with the active agents versus placebo (hazard ratio [HR] 0.74, 95% confidence interval [CI] 0.65-0.83), as well as increased risk of any grade (RR 1.09, 95% CI 1.01-1.17) and grade 3-4 AEs (RR 1.50, 95% CI 1.23-1.83). The sensitivity analysis with SPARTAN-like simulated populations demonstrated that when using ARAMIS statistical design, OS would be statistically significant in 98.1% of the cases, at a shorter follow-up and with lower number of events. First-line treatment of nmCRPC patients with anti-androgens increased OS with an acceptable safety profile. In light of the different study designs and follow-up, results should be interpreted separately.

Meta-computational techniques' for managing spare data: An application in off-pump heart surgery

BACKGROUND AND OBJECTIVES

This research looked at the key considerations to remember when selecting a model for working with sparse data. In the presence of sparse evidence, it proposes ideal conditions for conducting meta-analysis.

METHODS

Monte Carlo simulations were used to produce study results, and three forms of continuity correction were used in the research. Besides, meta-analytical approaches were used to measure the cumulative effect of treatment and estimate each method's efficiency. A clinical trial in off-pump surgery met the main objectives of this research. Meta-analysis methods were used to determine the outcome of postoperative risk results. After that, with a total population of 3030, Monte Carlo simulations were used to produce research data to run fixed and random-effect models with three continuity correction forms. The type of consistency adjustment used, group imbalances, statistical analysis used, and variance values between studies all affect meta-analytical methods' results.

RESULTS

MSE values for balanced groups are normally zero. While the Arc-sine variation approach does a decent job of coping with inconsistent results on the effect of treatment, it has concerns with boundary estimates of variance between tests. Furthermore, using continuity correction methods introduces bias and imprecise medication outcome calculations. The spectrum of statistical analysis, such as fixed effects and random effects, can be inferred as completely based on data in samples. The sensitivity analysis of correction decisions could increase the reliability of meta-analysis approaches by enabling researchers to analyze various effect estimation findings.

CONCLUSION

This research study can be expanded upon by identifying alternative approaches to continuity correction methods and resolving boundary estimate problems. The range of statistical analysis, such as fixed effects and random effects, can be entirely dependent on the samples' type of data. The sensitivity analysis of correction decisions could improve the efficiency of meta-analysis methods by allowing researchers to investigate a wide range of effect estimation results.