Association of tea consumption and the risk of thyroid cancer: a meta-analysis.
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Abstract:
Epidemiological studies evaluating the association of tea consumption and the risk of thyroid cancer risk have produced inconsistent results. Thus, we conducted a meta-analysis to assess the relationship between tea consumption and thyroid cancer risk.Pertinent studies were identified by a search in PubMed and Web of Knowledge. The random effect model was used based to combine the results. Publication bias was estimated using Egger's regression asymmetry test.Finally, 11 articles with 14 studies (2 cohort studies and 12 case-control studies) involving 2,955 thyroid cancer cases and 106,447 participants were included in this meta-analysis. The relative risk (95% confidence interval) of thyroid cancer for the highest versus the lowest category of tea consumption was 0.774 (95% CI = 0.619-0.967), and the associations were also significant in Europe and America, but not in the Asia. No publication bias was found.Our analysis indicated that higher tea consumption may have a protective effect on thyroid cancer, especially in Europe and America.Keywords:
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RAAS Inhibition, Mortality, and Severity in COVID-19 Patients: A Systematic Review and Meta-Analysis
Background: The effect of angiotensin-receptor blockers (ARBs) and angiotensinconverting enzyme inhibitors (ACEi) on outcome and severity in COVID-19 patients has been postulated Methods: We performed a systematic review in different databases to identify studies and research work that assessed the association of ACEi/ARBs on the severity of illness and mortality in COVID-19 subjects Inclusion criteria for our meta-analysis were all studies that included human subjects with COVID-19 infection, reported mortality and severity of the disease, and described ACEi/ARB treatment The data collected were the name of the first author, journal title, the country of the study, sample size, relative risk and confidence intervals for association of ACEi/ARB treatment and mortality and severity We used the random-effects model for the meta-analysis and the funnel plot analysis to assess potential publication bias Results: Out of 4,702 records reviewed in different databases, 11 papers were included in our meta-analysis Altogether, 8,643 patients were included in the final analysis Random effects model (REM) for the relationship between ACEi/ARB and survival showed that ACEi/ARB does not affect survival (relative risk [RR]=0 81, confidence interval ranges [CIR] from 0 53 to 1 23) There was no evidence of heterogeneity with I-squared =25 5% and p<0 235 By applying Egger's test, there was no evidence of small studies effect with P=0 64 REM for the relationship between ACEi/ARB and disease severity showed that ACEi/ARB are not related to disease severity (RR=0 90, CIR from 0 70 to 1 15) There was evidence of heterogeneity with I-squared =56 2% and p=0 01 By applying Egger's test, there was no evidence of small studies effect with P=0 93 Conclusions: Based on the results of this meta-analysis, ACEi/ARB are not associated with increased mortality or severity in COVID-19 subjects
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Ovarian cancer (OC) accounts for 4% of female malignancies worldwide, and its prognosis is unfavorable. Currently available epidemiologic data suggest that non-herbal tea consumption may reduce OC risk, but these evidences are inconsistent. A comprehensive literature search for observational epidemiologic studies reporting associations between non-herbal tea consumption and OC risk was conducted in electronic databases. A random-effects model was used to synthesize effect measures in binary meta-analysis, and adjusted indirect comparison was used to compare whether there was a difference in effects between green tea (GT) and black tea (BT). Both linear and non-linear models were used to explore the dose–response relationship. Fourteen studies were included, and we obtained an inverse and significant pooled estimate in binary meta-analysis [risk ratio (RR)pool = 0.76, 95% confidence interval (CI) 0.61–0.95, PCochran < 0.001, I2 = 81.5%]. No publication bias was identified in binary meta-analysis. In binary meta-analysis stratified by tea types, we observed a significant association for GT (RRpool = 0.64, 95% CI 0.45–0.90, PCochran = 0.071, I2 = 53.6%), but not BT (RRpool = 0.85, 95% CI 0.65–1.12, PCochran = 0.007, I2 = 65.9%). Indirect comparison, which treated BT as the reference, showed an inverse but non-significant association (RRGT versus BT = 0.74, 95% CI 0.48–1.15). Both linear and non-linear models found that OC risk decreased as the consumption levels of total non-herbal tea increased. However, the dose–response relationship was stronger for GT when compared with BT. Our results suggest that non-herbal tea, especially GT, is associated with a reduced risk of OC. Future studies should explore biochemical evidence regarding the variation in chemopreventive effects between different types of non-herbal tea.
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Background: Growing evidence has demonstrated that Ki-67/MIB-1 has an effect on the clinical progression and prognosis in cancers. However, the diagnostic and prognostic values of Ki-67/MIB-1 in thyroid cancer remain unclear. Materials and methods: The meta-analysis was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies were retrieved from PubMed, EBSCO, EMBASE, ISI Web of Science, China National Knowledge Infrastructure, WanFang and Chinese VIP databases. MetaDiSc and STATA12.0 were used to analyze the meta-analysis. Fixed-effect analysis and random-effect analysis were applied to pool the relative ratio based on heterogeneity in this meta-analysis. Results: In the meta-analysis, 51 eligible studies were included. The pooled sensitivity of Ki-67/MIB-1 was 0.61 (95% confidence interval [CI]: 0.59–0.63) and specificity was 0.75 (95% CI: 0.74–0.77) in thyroid cancer. The pooled positive likelihood ratio was 3.19 (95% CI: 2.30–4.42) and negative likelihood ratio was 0.43 (95% CI: 0.35–0.54). In the diagnosis of thyroid cancer, the pooled diagnostic odds ratio of Ki-67/MIB-1 was 8.54 (95% CI: 5.03–14.49). The area under the symmetric receiver operating characteristic curve was 0.804 (standard error =0.031). Our results showed that there were statistical associations between Ki-67/MIB-1 and age (odds ratio [OR] =1.71, 95% CI: 1.14–2.57, P =0.010), tumor size (OR =1.86, 95% CI: 1.17–2.96, P =0.008), lymph node metastasis (OR =2.49, 95% CI: 1.42–4.39, P =0.002), metastasis status (OR =6.96, 95% CI: 2.46–19.69, P <0.001), tumor node metastasis stage (OR =6.56, 95% CI: 3.80–11.34, P <0.001) and extrathyroid extension (OR =1.91, 95% CI: 1.27–2.87, P =0.002). Furthermore, thyroid cancer patients with a high level of Ki-67/MIB-1 had a worse disease-free survival as compared to patients with a low level of Ki-67/MIB-1 (hazard ratio =5.19, 95% CI: 3.18–8.46, P <0.001). Also, Ki-67/MIB-1 was found to be associated with increased risk of mortality (hazard ratio =3.56, 95% CI: 1.17–10.83, P =0.025). Conclusion: Our results demonstrated that Ki-67/MIB-1 might act as a potential factor in diagnosing thyroid cancer in Chinese. Also, the meta-analysis indicated that Ki-67/MIB-1 might have an effect on prognosis in non-Chinese thyroid cancer patients. Keywords: thyroid cancer, Ki-67/MIB-1, diagnosis, progression, prognosis, meta-analysis
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Fat consumption has been hypothesized to influence pancreatic cancer risk, but the results of epidemiologic studies have been controversial. We conducted a systematic review and meta-analysis of case–control and cohort studies to investigate this issue. Relevant published studies were identified by searching MEDLINE (PubMed) through February 2014. Two authors (Q.-W.S. and Q.-Y.Y.) independently assessed eligibility and the extracted data. Study-specific relative risks (RRs) were pooled using a random-effects model. We also carried out heterogeneity and publication bias analyses. Six cohort and 13 case–control studies with 6159 pancreatic cancer cases and 1 068 476 noncases were included in this meta-analysis. The summary RR for pancreatic cancer for the highest versus lowest intake was 1.04 [95% confidence interval (CI)=0.90–1.20, I2=57.3%, P for heterogeneity=0.001] for total fat. In addition, when separately analyzed by study design, case–control (RR=1.03, 95% CI=0.83–1.27, I2=55.8%, P for heterogeneity=0.007) and cohort studies (RR=1.05, 95% CI=0.85–1.29, I2=66.7%, P for heterogeneity=0.010) yielded similar results. Furthermore, no statistically significant associations were observed in the subgroup analyses on the basis of fat source, geographic location, whether using energy-adjusted models, and whether adjusted for several potential confounders and important risk factors. There was no evidence of publication bias or significant heterogeneity between subgroups on meta-regression analyses. The results of this meta-analysis do not support an independent association between diets high in total fat and pancreatic cancer risk.
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To conduct a meta-analysis from published studies to evaluate the relationship between long working hours and the risk of cardiovascular disease (CVD).Among a total of 341 published studies found from publicly accessible databases, five cohort studies and six case-control studies were analyzed for the study.Statistically significant heterogeneity has been observed (P = 0.037). The effect of longer working hours was significantly associated with the risk of CVD in the random-effects model of all 11 studies (odds ratio, 1.37; 95% confidence interval, 1.11 to 1.70). On the basis of meta-regression analysis, the result was not affected by the mean age, region, or the study year. The P value using Eager test was 0.701 suggesting this analysis was unlikely to have any publication bias.These findings provide evidence of increased CVD with long working hours.
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Objective
To compare the performance of the bias-adjusted meta-analysis to the conventional meta-analysis assessing seasonal influenza vaccine effectiveness among community-dwelling elderly aged 60 years and older.Study Design and Setting
Systematic literature search revealed 14 cohort studies that met inclusion and exclusion criteria. Laboratory-confirmed influenza, influenza-like illness, hospitalization from influenza and/or pneumonia, and all-cause mortality were study outcomes. Potential biases were identified using bias checklists. The magnitude and uncertainty of biases were assessed by expert opinion. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using random effects model.Results
After incorporating biases, overall effect estimates regressed slightly toward no effect, with the largest relative difference between conventional and bias-adjusted ORs for laboratory-confirmed influenza (OR, 0.18; 95% CI: 0.01, 3.00 vs. OR, 0.23; 95% CI: 0.03, 2.04). In most of the studies, CIs widened reflecting uncertainties about the biases. The between-study heterogeneity reduced considerably with the largest reduction for all-cause mortality (I2 = 4%, P = 0.39 vs. I2 = 91%, P < 0.01).Conclusion
This case study showed that after addressing potential biases influenza vaccine was still estimated effective in preventing hospitalization from influenza and/or pneumonia and all-cause mortality. Increasing the number of assessors and incorporating empirical evidence might improve the new bias-adjustment method.Seasonal influenza
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