A systematic review and meta-regression analysis to examine the ‘timing hypothesis’ of hormone replacement therapy on mortality, coronary heart disease, and stroke
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The 'Timing Hypothesis' states that the benefits and harms of hormone replacement therapy (HRT) are related to the proximity with which it is begun following the onset of menopause. The primary aim of this analysis was to test for heterogeneity of treatment effect for HRT using Chi2 and I2 tests for younger versus older initiators of HRT. The secondary aim was to perform a meta-regression with mean age at trial baseline as the covariate for various outcomes. Younger initiation trials were defined as those with mean age of participants <60 years and older initiation trials were those with mean age >60 years. The primary endpoints included all-cause mortality, cardiac mortality, coronary heart disease (CHD) events (a composite of cardiac mortality and nonfatal myocardial (MI)), and a composite of stroke, transient ischemic attack (TIA) and systemic embolism. Thirty-one RCTs were identified comparing HRT users to nonusers (n = 40,521). There was significant heterogeneity of treatment effect between younger versus older HRT initiators for all-cause mortality (Chi2 = 9.74, p = 0.002, I2 = 89.7%), cardiac mortality (Chi2 = 4.04, p = 0.04, I2 = 75.2%), and CHD events (Chi2 = 3.06, p = 0.08, I2 = 67.3%). Both groups experienced an increase in stroke, TIA and systemic embolism (1112/18,774 in the HRT group versus 734/18,070 in the control group; OR = 1.52; 95% confidence interval (CI) = 1.38–1.67). When performing the meta-regression, as age increased the treatment effect of HRT was increased for stroke, TIA and systemic embolism (point estimate 0.006 with a standard error of 0.002) (p = 0.0003). Younger initiation of HRT may be effective in reducing death and cardiac events. However, younger HRT initiators remained at an increased risk of stroke, TIA and systemic embolism and this risk increased as average age increased. Younger menopausal women using HRT to treat vasomotor symptoms do not appear to be at an increased risk of dying or experiencing CHD events.Keywords:
Stroke
Hormone Therapy
Meta-regression
Su, Han; Dreesmann, Nathan; Hough, Catherine (Terri); Bridges, Elizabeth; Thompson, Hilaire Author Information
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To explore the role and application of Meta-regression and subgroup analyses to recognize and control the heterogeneity in Meta-analysis, Meta-regression models were established by secondary data to screen the factors resulting heterogeneity,and subgroup analyses were used to compare the change of heterogeneity before and after.The heterogeneity was found in the Meta-analysis(Q=44.71,df=27,P=0.017).Sample size and region were selected(P=0.012 and P=0.091,respectively)by Meta-regression from many possible factors such as sample size,year,region and case/contml ratio.The Q values were lowered from 44.71 to 32.11 after subgroup analyses.Thus,Metaregression method was convenient and reliable to screen the affected factors of heterogeneity,and subgroup analyses based on the hypothesis that could significantly lower the heterogeneity.It was recommended to a combined use when an obvious heterogeneity existed but was in need to get an overall result in Metaanalysis.We could correctly judge and lower the heterogeneity to increase the robustness and rationality of results from Meta-analysis.
Key words:
Meta-analysis; Heterogeneity; Meta-regression; Subgroup analyses
Meta-regression
Subgroup analysis
Study heterogeneity
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Coronavirus disease 2019 (COVID-19) is spreading rapidly around the world. There are many published studies exploring the risk factors of severe and mortal COVID-19 patients. Huang et al reported that the elevated leukocyte counts and decreased lymphocyte counts were significantly associated with the severity of COVID-19. Although neutrophil counts were not uniformly reported in that study, they thought that neutrophilia was more specific to severe patients than leukocytosis.1 To our knowledge, a number of studies have investigated the association of neutrophil counts with the mortality of COVID-19; however, the conclusions among studies are inconsistent.2-6 On this basis, we explored the relationship between neutrophil counts and mortality of COVID-19 by quantitative meta-analysis and meta-regression. We completed our meta-analysis by strictly following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Table S1).7 We conducted an electronic search of PubMed, Web of Science, and EMBASE to identify potential studies published between January 1, 2020, and May 22, 2020, using the following terms: ("clinical" OR "laboratory" OR "neutrophil") AND ("coronavirus" OR "2019-nCoV" OR "SARS-CoV-2" OR "COVID-19") AND ("outcome" OR "mortality"). In addition, the references of included studies were also reviewed to screen out additional eligible studies by two researchers (Li Shi and Ying Wang), respectively. Extracted data included authors, study design, locations, number of cases, percentages of male, the median or mean of age, and neutrophil counts and corresponding units in the non-survival and survival groups. The Agency for Healthcare Research and Quality (AHRQ) score checklist was used for assessing the quality of included studies in this meta-analysis.8 The quality assessment of the studies was divided into low (0-3), moderate (4-7), or high (8-11). The inclusion criteria involved (a) studies presented in English; (b) patients with laboratory-confirmed and clinically diagnosed COVID-19 pneumonia; and (c) clear report about neutrophil counts in the non-survival and survival groups. Case reports, meta-analysis, review, and studies with overlapping data were excluded. Considering the inherent differences among studies, we calculated the pooled standardized mean difference (SMD) and corresponding 95% confidence interval (CI) for continuous variables by using random-effects model to evaluate the relationship between changes in neutrophil counts and mortality of COVID-19 patients. When the mean and standard deviation could not be extracted directly from studies, we estimated them according to Wan et al's9 method by utilizing sample size, median and interquartile range (IQR), or median and range. The I2 statistic and Cochran's Q statistic were used to quantify the heterogeneity across studies.10 For the Cochran's Q statistic, significant heterogeneity across studies was deemed as a P-value <.10. For the I2 statistic, significant heterogeneity across studies was regarded as I2> 50%. In addition, we also provided the prediction interval, which was helpful for assessing whether the variation across studies was clinically significant.11, 12 We used age and gender as covariates to conduct a restricted-maximum likelihood random-effects meta-regression. Sensitivity analysis was used not only to identify sources of heterogeneity but also to assess the robustness of the results. For assessing small-study effects, we chose Begg's test and regression-based Egger's test. All calculations were performed in Stata 16.0. Two-tailed P-values <.05 were considered statistically significant. At the beginning, there were 648 records in the search results, 100 duplicates were deleted, and the remaining 548 studies were screened. Finally, 10 observational studies2-6, 13-17 including nine retrospective studies and one prospective study were enrolled in this meta-analysis through careful screening of titles, abstracts, and full texts. There were a total of 1473 COVID-19 cases including 372 nonsurvivors and 1101 survivors. Baseline characteristics of the included studies are shown in Table 1. Neutrophil counts were clearly reported upon admission in most studies except for Du et al, He et al and Wang et al. Objectively speaking, their studies presumably reported neutrophil counts on admission. In addition, all included studies were of high or moderate quality with an AHRQ score ≥6 (Table S2). Chen T et al. PMID: 32217556 Chen Tielong et al. PMID: 32279081 Du R et al. PMID: 32269088 He W et al. PMID: 32332856 Wang D et al. PMID: 32354360 Wang K et al. PMID: 32361723 Wang L et al. PMID: 32240670 Wu C et al. PMID: 32167524 Yan Y et al. PMID: 32345579 Martín-Moro F et al. PMID: 32379921 The combined results revealed that higher neutrophil counts were detected in the non-survival COVID-19 patients compared with the survival COVID-19 patients (SMD = 0.93, 95% CI = 0.63-1.24; I2 = 76.3%, Q = 42.12, P < 0.001; prediction interval = −0.12-1.99) (Figure. 1A). The results of sensitivity analysis suggested that removing any individual study of the included studies had no significant effect on the association between changes in neutrophil counts and mortality of COVID-19-infected patients (Figure. 1B). Due to the limitations of the data reported in the included studies, we only used age and gender as covariates for meta-regression. The results of meta-regression analysis indicated that the relationship between changes in neutrophil counts and increased risk of mortality in COVID-19-infected patients was not obviously affected by age (P = 0.628) (Figure. 1C) and gender (P = 0.222) (Figure. 1D). Begg's test (P = 1.839) and regression-based Egger's test (P = 0.058) demonstrated no small-study effects for the relationship between neutrophil counts and increased risk of mortality in COVID-19 patients. Our current study demonstrated that the elevated neutrophil counts were significantly correlated to the mortality of COVID-19 patients. However, there was high heterogeneity in our study. To find sources of heterogeneity, we conducted a meta-regression. Considering the relationship between age and gender and mortality in COVID-19 patients,18 we selected age and gender as covariables based on the available data provided by the included studies. Although meta-regression did not identify the sources of heterogeneity, sensitivity analysis indicated that our results were reliable and robust. Besides, the prediction interval showed that values were possible on both sides of the null (prediction interval = −0.12-1.99). Hence, interpretation of our results in some settings or different study populations should be taken with caution. There are still some other limitations to our meta-analysis. This meta-analysis was based on only 10 published studies with 1473 COVID-19 cases. Therefore, future studies with larger sample size are needed to support our results. Besides, most of the studies were from China and only one was from Spain, so the scope of our findings might be limited. In conclusion, neutrophilia is a risk factor for mortality of COVID-19 patients, and our results are required to be verified by a study analyzing the adjusted effect estimates in the future. All authors report that they have no potential conflicts of interest. Li Shi, Haiyan Yang, and Yadong Wang conceptualized the study. Li Shi, Ying Wang, Xuan Liang, and Wenwei Xiao extracted the data. Li Shi and Ying Wang analyzed the data. Li Shi, Ying Wang, Guangcai Duan, Haiyan Yang, and Yadong Wang contributed to methodology. Li Shi, Xuan Liang, and Wenwei Xiao contributed software; Li Shi, Ying Wang, Haiyan Yang, and Yadong Wang wrote and reviewed the manuscript. All the authors approved the final manuscript. This study was supported by a grant from the National Natural Science Foundation of China (No. 81973105). Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
Neutrophilia
Leukocytosis
Meta-regression
Absolute neutrophil count
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Physiological alterations in hormone levels during menopause have long been theorised to affect cognitive function and brain chemistry. The effects of oestrogen on the central nervous system may account for the neurological changes associated with menopause. Hormone replacement therapy is believed to modulate these changes and thus confer protection against age-related cognitive decline in postmenopausal women. Likewise, the development and severity of dementia is of significant concern in postmenopausal women and various therapeutic hormone replacement treatments have been postulated to be of benefit in this regard. This report will begin with an explanation of the physiological effects of oestrogen on brain function and the neurological changes resulting from fluctuations in hormone levels at the onset of menopause. An evaluation of the available medical literature will inform an exploration of the mechanisms of action of hormone replacement therapy and its efficacy in modulating cognitive decline, memory loss and the development and severity of dementia syndromes in postmenopausal women.
Hormone Therapy
Cognitive Decline
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Suggested risk of bias criteria for EPOC reviews 1. Risk of
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Metamodeling
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Low dose aspirin
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Background: Herpes simplex virus type 2 (HSV-2) infection is a prevalent sexually transmitted infection worldwide. This systematic review was conducted to characterize HSV-2 epidemiology in Asia, including the World Health Organization regions of Southeast Asia and the Western Pacific.Methods: Cochrane and PRISMA guidelines were followed to systematically review and report findings. Random-effects meta-analyses and meta-regressions were conducted.Findings: HSV-2 measures extracted from 173 publications included 15 seroconversion rates, 11 seroincidence rates, 272 overall seroprevalence measures (678 stratified), 14 proportions of HSV-2 isolation in genital ulcer disease (GUD) (15 stratified), and 28 proportions of HSV-2 isolation in genital herpes (36 stratified). Pooled mean seroprevalence was 12.1% (95% confidence interval (CI): 11.0-13.2%) among general populations, 23.6% (95% CI: 20.9-26.3%) among men who have sex with men and transgender people, 46.0% (95% CI: 39.2-52.9%) among HIV-positive individuals and individuals in HIV-discordant couples, and 62.2% (95% CI: 58.9-65.6%) among female sex workers. Among general populations, pooled mean seroprevalence increased gradually from 4.7% (95% CI: 3.3-6.3%) in <20-year-old individuals to 26.6% (95% CI: 19.2-34.7%) in >60-year-old individuals. Compared to women, men had 0.60-fold (95% CI: 54.0-67.0) lower seroprevalence. Seroprevalence declined by 0.98-fold (95% CI: 0.97-0.99) per year in the most recent three decades. Pooled mean proportions of HSV-2 isolation in GUD and in genital herpes were 48.2% (95% CI: 34.9-61.6%) and 75.9% (95% CI: 68.3-82.8%), respectively.Interpretation: Over 1 in 10 individuals is infected with HSV-2, but seroprevalence is declining by 2% per year. HSV-2 accounts for half of GUD cases and three-quarters of genital herpes cases.Funding Statement: This work was supported by the Qatar National Research Fund [NPRP 9-040-3- 008] and by pilot funding from the Biomedical Research Program at Weill Cornell Medicine in Qatar.Declaration of Interests: The authors declare no competing interests.
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