Metformin has heterogeneous effects on model organism lifespans and is beneficial when started at an early age in Caenorhabditis elegans: A systematic review and meta-analysis.

There is growing interest in the use of metformin to extend lifespan and prevent the onset of age-related disorders in non-diabetic individuals. The impact of metformin on lifespan and aging has been studied in several model organisms, with varying effects. We conducted a systematic review of studies that performed laboratory experiments investigating the effect of metformin on overall lifespan in healthy Mus musculus mice and in Caenorhabditis elegans nematodes. Lifespan results for mice and nematodes were analyzed in separate meta-analyses, and there was a significant amount of heterogeneity across experiments within each species. We found that metformin was not significantly associated with an overall lifespan-prolonging effect in either mice or nematodes. For nematodes, however, there was a lifespan-prolonging effect in experiments using live OP50 Escherichia coli as a food source, an effect that was larger when metformin was started earlier in life. Our work highlights the importance of testing compounds in a diversity of model organisms. Moreover, in all species, including humans, it may be necessary to study the effect of metformin on aging in both younger and older cohorts.

2,109 randomized oncology trials map continuous, meager improvements in progression-free and overall survival over 50 years.

OBJECTIVES: To assess the patterns and time trends in overall survival and progression-free survival treatment effects across randomized controlled trials (RCTs) in oncology. STUDY DESIGN AND SETTING: A PubMed search for oncology network meta-analyses (NMAs) was carried (to September 30, 2021). Relevant hazard ratios were extracted for systemic treatments from RCTs in the NMAs. After removing duplicate results, relationships between treatment effects, year of publication, trial design, and other features were explored. RESULTS: From 241 oncology NMAs, 2,109 unique eligible RCTs provided analyzable data. On average, there was a 12%-14% reduction in hazard for overall survival and 27%-30% reduction for progression-free survival, with substantial heterogeneity across different malignancies. Correlation between overall survival and progression-free survival treatment effects was modest (r = 0.60, 95% confidence interval, 0.56-0.64). Over time, there was a suggestive trend of increased progression-free survival treatment effect, although overall survival treatment effects remained steady. Only one in five trials met criteria for clinically meaningful improvements in overall survival. Among 300 randomly selected trials, mean absolute improvement was 1.6 months for median progression-free survival and 1.4 months for median overall survival. CONCLUSION: Broad patterns across the past 50 years of oncology research suggest continuous progress has been made, but few results meet clinically meaningful thresholds for overall survival improvement.

Identification of threshold for large (dramatic) effects that would obviate randomized trials is not possible.

OBJECTIVE: To analyze distribution of "dramatic", large treatment effects. STUDY DESIGN & SETTING: Pareto distribution modeling of previously reported cohorts of 3,486 randomized trials (RCTs) that enrolled 1,532,459 patients and 730 non-randomized studies (NRS) enrolling 1,650,658 patients. RESULTS: We calculated the Pareto α parameter, which determines the tail of the distribution for various starting points of distribution [odds ratiomin (ORmin)]. In default analysis using all data at ORmin ≥1, Pareto distribution fit well to the treatment effects of RCTs favoring the new treatments (P = 0.21, Kolmogorov-Smirnov test) with best α = 2.32. For NRS, Pareto fit for ORmin ≥2 with best α = 1.91. For RCTs, theoretical 99th percentile OR was 32.7. The actual 99th percentile OR was 25; which converted into relative risk (RR) = 7.1. The maximum observed effect size was OR = 121 (RR = 11.45). For NRS, theoretical 99th percentile was OR = 315. The actual 99th percentile OR was 294 (RR = 13). The maximum observed effect size was OR = 1473 (RR = 66). CONCLUSIONS: The effects sizes observed in RCTs and NRS considerably overlap. Large effects are rare and there is no clear threshold for dramatic effects that would obviate future RCTs.

Bacterial Vaginosis and Its Association With Incident Trichomonas vaginalis Infections: A Systematic Review and Meta-Analysis.

BACKGROUND: Bacterial vaginosis (BV) has been associated with an increased risk for acquisition of human immunodeficiency virus and sexually transmitted infections. We evaluated the association between BV and incident Trichomonas vaginalis (TV) infection in women. METHODS: MEDLINE and ClinicalTrials.gov were searched for articles published between January 1, 1980, and May 7, 2021. Observational studies in women that evaluated the relationship between having/not having BV and the risk for acquiring TV were included. RESULTS: Fourteen studies were included in the systematic review; 12 studies were included in meta-analyses involving 18,424 participants. Most studies used Nugent scoring to diagnose BV. For TV diagnosis, 12 studies used wet mount microscopy or culture, and 2 used nucleic acid amplification tests. There was diversity in the measures of association used, so an overall effect size could not be calculated. The majority of studies reported odds ratios, which showed an increased risk of incident TV among women with BV versus without BV (adjusted odds ratio, 1.87; 95% confidence interval, 1.45-2.40; P = 0.007). However, there were heterogeneity and potential confounding factors (eg, age, sexual partners) reported among studies. CONCLUSIONS: This systematic review and meta-analysis provide evidence for a nearly 2-fold higher risk for acquiring TV among women with BV compared with women without BV.

An umbrella review of effect size, bias, and power across meta-analyses in emergency medicine.

OBJECTIVES: The objective of this study was to conduct an umbrella review of therapeutic studies relevant to emergency medicine, analyzing patterns in effect size, power, and signals of potential bias across an entire field of clinical research. METHODS: We combined topic- and journal-driven searches of PubMed and Google Scholar for published articles of systematic reviews and meta-analyses (SRMA) relevant to emergency medicine (last search in November 2020). Data were screened and extracted by six investigators. Redundant meta-analyses were removed. Whenever possible for each comparison we extracted one meta-analysis on mortality with the most events and one meta-analysis on a nonmortality outcome with the most studies. From each meta-analysis we extracted all individual study effects; outcomes were converted to odds ratios (ORs) and placed on a common scale where an OR < 1.0 represents a reduction in a harmful outcome with an experimental treatment versus control. Outcomes were analyzed at the level of individual studies and at the level of summary effects across meta-analyses. RESULTS: A total of 332 articles contained 431 eligible meta-analyses with a total of 3,129 individual study outcomes; of these, 2,593 (83%) were from randomized controlled trials. The median OR across all studies was 0.70. Within each meta-analysis, the earliest study effect on average demonstrated larger benefit compared to the overall summary effect. Only 57 of 431 meta-analyses (13%) both favored the experimental intervention and did not show any signal of small study effects or excess significance, and of those only 12 had at least one study with 80% or higher power to detect an OR of 0.70. Of these, no interventions significantly decreased mortality in well-powered trials. Although the power of studies increased somewhat over time, the majority of studies were underpowered. CONCLUSIONS: Few interventions studied within SRMAs relevant to emergency medicine seem to have strong and unbiased evidence for improving outcomes. The field would benefit from more optimally powered trials.

Early Intubation and Increased Coronavirus Disease 2019 Mortality: A Propensity Score-Matched Retrospective Cohort Study.

OBJECTIVES: There has been controversy about the timing and indications for intubation and mechanical ventilation in novel coronavirus disease 2019. This study assessed the effect of early intubation and mechanical ventilation on all-cause, inhospital mortality for coronavirus disease 2019 patients. DESIGN: Multicenter retrospective cohort study. SETTING: Eleven municipal hospitals in New York City from March 1, 2020, to December 1, 2020. PATIENTS: Adult patients who tested positive for coronavirus disease 2019 in the emergency department were subsequently admitted. Patients with do-not-intubate orders at admission were excluded. INTERVENTIONS: Intubation within 48 hours of triage and intubation at any point during hospital stay. MEASUREMENTS AND MAIN RESULTS: Data from 7,597 coronavirus disease 2019 patients were included; of these, 1,628 (21%) were intubated overall and 807 (11%) were intubated within 48 hours of triage. After controlling for available confounders, intubation rates for coronavirus disease 2019 patients varied significantly across hospitals and decreased steadily as the pandemic progressed. After nearest neighbor propensity score matching, intubation within 48 hours of triage was associated with higher all-cause mortality (hazard ratio, 1.30 [1.15-1.48]; p < 0.0001), as was intubation at any time point (hazard ratio, 1.62 [1.45-1.80]; p < 0.0001). Among intubated patients, intubation within 48 hours of triage was not significantly associated with differences in mortality (hazard ratio, 1.09 [0.94-1.26]; p = 0.26). These results remained robust to multiple sensitivity analyses. CONCLUSIONS: Intubation within 48 hours of triage, as well as at any time point in the hospital course, was associated with increased mortality in coronavirus disease 2019 patients in this observational study.

GNAS, GNAQ, and GNA11 alterations in patients with diverse cancers.

BACKGROUND: Advances in deep sequencing technology have uncovered a widespread, protumorigenic role of guanine nucleotide-binding (G protein) α (GNA) subunits, particularly GNA subunits Gs (GNAS), Gq (GNAQ), and G11 (GNA11) (GNA*), in a diverse collection of malignancies. The objectives of the current study were: 1) to determine GNA* aberration status in a cohort of 1348 patients with cancer and 2) to examine tumor mutational burden, overall survival rates, and treatment outcomes in patients with GNA*-positive tumors versus those with tumors that had wild-type GNA*. METHODS: For each patient, clinical and genomic data were collected from medical records. Next-generation sequencing was performed for each patient (range, 182-236 genes). RESULTS: Aberrations of GNA* genes were identified in a subset of patients who had 8 of the 12 cancer types examined, and a significant association was observed for appendiceal cancer and ocular melanoma (P < .0001 for both; multivariate analysis). Overall, 4.1% of the cancer population was affected. GNA* abnormalities were associated with higher numbers of co-alterations in univariate (but not multivariate) analysis and were most commonly accompanied by Aurora kinase A (AURKA), Cbl proto-oncogene (CBL), and LYN proto-oncogene (LYN) co-alterations (all P < .0001; multivariate analysis). GNA* alterations were correlated with a trend toward lower median overall survival (P = .085). The median tumor mutational burden was 4 mutations per megabase in both GNA*-altered and GNA* wild-type tumors. For this limited sample of GNA*-positive patients, longer survival was not correlated with any specific treatment regimens. CONCLUSIONS: In the current sample, the genes GNAS, GNAQ, and GNA11 were widely altered across cancer types, and these alterations often were accompanied by specific genomic abnormalities in AURKA, CBL, and LYN. Therefore, targeting GNA* alterations may require drugs that address the GNA* signal and important co-alterations. Cancer 2018;00:000-000. © 2018 American Cancer Society.

Dynamics of co-authorship and productivity across different fields of scientific research.

We aimed to assess which factors correlate with collaborative behavior and whether such behavior associates with scientific impact (citations and becoming a principal investigator). We used the R index which is defined for each author as log(Np)/log(I1), where I1 is the number of co-authors who appear in at least I1 papers written by that author and Np are his/her total papers. Higher R means lower collaborative behavior, i.e. not working much with others, or not collaborating repeatedly with the same co-authors. Across 249,054 researchers who had published ≥30 papers in 2000-2015 but had not published anything before 2000, R varied across scientific fields. Lower values of R (more collaboration) were seen in physics, medicine, infectious disease and brain sciences and higher values of R were seen for social science, computer science and engineering. Among the 9,314 most productive researchers already reaching Np ≥ 30 and I1 ≥ 4 by the end of 2006, R mostly remained stable for most fields from 2006 to 2015 with small increases seen in physics, chemistry, and medicine. Both US-based authorship and male gender were associated with higher values of R (lower collaboration), although the effect was small. Lower values of R (more collaboration) were associated with higher citation impact (h-index), and the effect was stronger in certain fields (physics, medicine, engineering, health sciences) than in others (brain sciences, computer science, infectious disease, chemistry). Finally, for a subset of 400 U.S. researchers in medicine, infectious disease and brain sciences, higher R (lower collaboration) was associated with a higher chance of being a principal investigator by 2016. Our analysis maps the patterns and evolution of collaborative behavior across scientific disciplines.