Facilitating meta-analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category.
ABSTRACT Epidemiological studies relating a particular exposure to a specified disease may present their results in a variety of ways. Often, results are presented as estimated odds ratios (or relative risks) and confidence intervals (CIs) for a number of categories of exposure, for example, by duration or level of exposure, compared with a single reference category, often the unexposed. For systematic literature review, and particularly meta-analysis, estimates for an alternative comparison of the categories, such as any exposure versus none, may be required. Obtaining these alternative comparisons is not straightforward, as the initial set of estimates is correlated. This paper describes a method for estimating these alternative comparisons based on the ideas originally put forward by Greenland and Longnecker, and provides implementations of the method, developed using Microsoft Excel and SAS. Examples of the method based on studies of smoking and cancer are given. The method also deals with results given by categories of disease (such as histological types of a cancer). The method allows the use of a more consistent comparison when summarizing published evidence, thus potentially improving the reliability of a meta-analysis.
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ABSTRACT: MicroRNA-21 (miRNA-21 or miR-21) may act as a prognostic biomarker of cancer. However, the available evidence is controversial. Therefore, the present meta-analysis summarizes this evidence and evaluates the prognostic role of this gene in breast cancer. The meta-analysis was conducted by searching the databases of PubMed, EMBASE, Web of Science and Chinese database-China National Knowledge Infrastructure (CNKI). Data were extracted from studies that investigated the association between miR-21 expression and survival outcomes in breast cancer patients. With respect to survival outcomes, the pooled hazard ratios (HRs) of miR-21 were calculated given a 95% confidence interval (CI). Our meta-analysis identified a total of 10 studies involving 1,439 cases. Further investigation demonstrated that a high miR-21 expression can predict poor overall survival (OS) (HR = 2.57, 95% CI: 1.37-4.81, P = 0.003) and shortened disease-free/recurrence-free survival (DFS/RFS) (HR = 1.45, 95% CI: 1.16-1.82, P = 0.001) in breast cancer patients. Moreover, high miR-21 expression was significantly correlated with lowered OS in the Asian group (HR = 5.07, 95% CI: 2.89-8.92, P < 0.001), but not in the Caucasian cohort (HR = 1.44, 95% CI: 0.99-2.10, P = 0.058). Furthermore, odds ratios (ORs) showed that up-regulated miR-21 levels were associated with multiple clinical characteristics. Our results indicated that miR-21 can predict unfavorable prognoses in breast cancer patients, especially in Asians.PLoS ONE 01/2015; 10(2):e0118647. DOI:10.1371/journal.pone.0118647 · 3.53 Impact Factor
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ABSTRACT: Published data on the relationship of hormone replacement therapy (HRT) with Parkinson's disease (PD) were inconclusive. Thus, a systematic meta-analysis of observational studies was performed to clarify this topic. The databases of PubMed and EMBASE were searched for case-control or cohort studies published up till June 2, 2014. Meta-analysis of the relative risks (RRs) with 95% confidence intervals (CIs) was estimated using random-effects models. A final total of ten case-control and four cohort studies were included in our meta-analysis. The overall combined RR of PD for ever users versus never users of HRT was 1.00 (95% CI: 0.84-1.20). Limited to those subjects who only use estrogen, a similar trend was detected (RR: 0.95, 95% CI: 0.69-1.30). In the subgroup analysis by study design, no significant association was observed in case-control studies (RR: 0.79, 95% CI: 0.62-1.02), whereas a positive association was found in cohort studies (RR: 1.24, 95% CI: 1.10-1.40). In further analysis according to study quality, an inverse association was found in the low-quality group (RR: 0.58, 95% CI: 0.40-0.82), whereas a positive association was found in the high-quality group (RR: 1.16, 95% CI: 1.02-1.31). In summary, our results of meta-analysis do not support a protective role of HRT in female PD development.Neuropsychiatric Disease and Treatment 01/2015; 11:59-66. DOI:10.2147/NDT.S69918 · 2.00 Impact Factor
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ABSTRACT: The obesity paradox is often attributed to fat acting as a buffer to protect individuals in fragile metabolic states. If this was the case, one would predict that the reverse epidemiology would be apparent across all causes of mortality including that of the particular disease state. We performed a dose-response meta-analysis to assess the impact of body mass index (BMI) on all-cause and stroke-specific mortality among stroke patients. Data from relevant studies were identified by systematically searching PubMed, OVID and Scopus databases and were analysed using a random-effects dose-response model. Eight cohort studies on all-cause mortality (with 20,807 deaths of 95,651 stroke patients) and nine studies of mortality exclusively because of stroke (with 8,087 deaths of 28,6270 patients) were evaluated in the meta-analysis. Non-linear associations of BMI with all-cause mortality (P < 0.0001) and mortality by stroke (P = 0.05) were observed. Among overweight and obese stroke patients, the risk of all-cause mortality increased, while the risk of mortality by stroke declined, with an increase in BMI. Increasing BMI had opposite effects on all-cause mortality and stroke-specific mortality in stroke patients. Further investigations are needed to examine how mortality by stroke is influenced by a more accurate indicator of obesity than BMI. © 2015 World Obesity.Obesity Reviews 04/2015; DOI:10.1111/obr.12272 · 7.86 Impact Factor