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PubMed2005

Is the meta-analysis of correlation coefficients accurate when population correlations vary?

One conceptualization of meta-analysis is that studies within the meta-analysis are sampled from populations with mean effect sizes that vary (random-effects models). The consequences of not applying such models and the comparison of different methods have been hotly debated. A Monte Carlo study compared the efficacy of Hedges and Vevea's random-effects methods of meta-analysis with Hunter and Schmidt's, over a wide range of conditions, as the variability in population correlations increases. (a) The Hunter-Schmidt method produced estimates of the average correlation with the least error, although estimates from both methods were very accurate; (b) confidence intervals from Hunter and Schmidt's method were always slightly too narrow but became more accurate than those from Hedges and Vevea's method as the number of studies included in the meta-analysis, the size of the true correlation, and the variability of correlations increased; and (c) the study weights did not explain the differences between the methods.

Humans↗
PubMed2005

Enteral nutritional support in prevention and treatment of pressure ulcers: a systematic review and meta-analysis.

BACKGROUND: There have been few systematic reviews and no meta-analyses of the clinical benefits of nutritional support in patients with, or at risk of developing, pressure ulcers. Therefore, this systematic review and meta-analysis was undertaken to address the impact of enteral nutritional support on pressure ulcer incidence and healing and a range of other clinically relevant outcome measures in this group. METHODS: Fifteen studies (including eight randomised controlled trials (RCTs)) of oral nutritional supplements (ONS) or enteral tube feeding (ETF), identified using electronic databases (including Pub Med and Cochrane) and bibliography searches, were included in the systematic review. Outcomes including pressure ulcer incidence, pressure ulcer healing, quality of life, complications, mortality, anthropometry and dietary intake were recorded, with the aim of comparing nutritional support versus routine care (e.g. usual diet and pressure ulcer care) and nutritional formulas of different composition. Of these 15 studies, 5 RCTs comparing ONS (4 RCTs) and ETF (1 RCT) with routine care could be included in a meta-analysis of pressure ulcer incidence. RESULTS: Meta-analysis showed that ONS (250-500 kcal, 2-26 weeks) were associated with a significantly lower incidence of pressure ulcer development in at-risk patients compared to routine care (odds ratio 0.75, 95% CI 0.62-0.89, 4 RCTs, n=1224, elderly, post-surgical, chronically hospitalised patients). Similar results were obtained when a combined meta-analysis of ONS (4 RCT) and ETF (1 RCT) trials was performed (OR 0.74, 95% CI 0.62-0.88, 5 RCTs, n=1325). Individual studies showed a trend towards improved healing of existing pressure ulcers with disease-specific (including high protein) versus standard formulas, although robust RCTs are required to confirm this. Although some studies indicate that total nutritional intake is improved, data on other outcome measures (quality of life) are lacking. CONCLUSIONS: This systematic review shows enteral nutritional support, particularly high protein ONS, can significantly reduce the risk of developing pressure ulcers (by 25%). Although studies suggest ONS and ETF may improve healing of PU, further research to confirm this trend is required.

Aged↗
PubMed2026

Evidence for the prognostic value of TP53 mutations in circulating tumor DNA across solid malignancies: a systematic review and meta-analysis.

BACKGROUND: The purpose of this meta-analysis study is to provide evidence for the clinical utility of TP53 mutations in circulating tumor DNA (ctDNA) as a prognostic biomarker. METHODS: We searched the PubMed, Embase, Cochrane, and Web of Science databases (last update May 2025) for studies on TP53 mutations in ctDNA or cfDNA as prognosis overall survival and in solid tumors. A total of 21 studies that met the criteria were utilized and data was collected regarding the authors, year of publication, study design, site of the study, number of patients, detection, mutation sample size and outcome measures were collected. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the study, and meta-analysis was done by using STATA 16.0. Effect sizes were in the form of hazard ratios (HR) that had 95% confidence intervals (CI). The models used were fixed-effects and random-effects based on heterogeneity. Funnel plots, and Egger's test was used to measure publication bias, and sensitivity analysis conducted through a leave-one-out method. RESULTS: A total of 21 studies (2,685 TP53-mutated patients, one unreported) showed: Mutated patients had worse progression-free survival (PFS) (HR=2.10, p=0.000; 12 studies, heterogeneity resolved after excluding Yoshida 2023), shorter OS (HR=1.74, p=0.014; 9 studies), and reduced DFS (HR=1.73, p=0.007; 3 studies), but RFS (2 items) showed no statistically significant differences. Subgroup analyses revealed: Prospective studies showed stronger PFS (HR=2.14 vs retrospective 1.90) with Japanese subgroup HR=4.90; Lung/liver cancers had higher HRs than breast. Prospective OS HR=2.25 (lung 3.14, endometrial 0.75). Retrospective DFS HR=1.89 vs Japanese breast RFS HR=4.00. Heterogeneity originated from study design, region, and cancer type variations, with no significant publication bias (Egger's test p>0.05). CONCLUSION: Current evidence suggests that TP53 mutations detected in ctDNA are significantly associated with poor prognosis in various solid tumors, particularly lung cancer. The association is robust for PFS and OS, though high heterogeneity and biological complexity warrant cautious interpretation. These findings support the potential incorporation of ctDNA-based TP53 mutation status into clinical prognostic assessment systems as an adjunctive parameter; however, further standardization of detection protocols, functional annotation of mutation types (e.g., LOF vs. GOF), incorporation of VAF and clonality analysis, and validation in large prospective multicenter cohorts are needed before routine clinical implementation. PROSPERO REGISTRATION NUMBER: CRD420251021095.

Humans↗
PubMed2006

Hepatitis C virus and risk of lymphoma and other lymphoid neoplasms: a meta-analysis of epidemiologic studies.

The present meta-analysis was conducted to evaluate the strength and the consistency of the association between hepatitis C virus (HCV) infection and non-Hodgkin lymphoma (NHL) and other lymphoid neoplasms. Only studies with >or=100 cases which were also adjusted for sex and age were included. Fifteen case-control studies and three prospective studies contributed to present analysis, nine of which had not been included in previous meta-analyses. We calculated the pooled relative risks (RR) with corresponding 95% confidence intervals (95% CI), as a weighted average of the estimated RRs by random-effect models. The pooled RR of all NHL among HCV-positive individuals was 2.5 (95% CI, 2.1-3.0), but substantial heterogeneity was found between studies and by study design. Pooled RRs were 2.5 (95% CI, 2.1-3.1) in case-control studies and 2.0 (95% CI, 1.8-2.2) in cohort ones. The strongest source of heterogeneity seemed to be the prevalence of HCV among NHL-free study subjects (RR for NHL among HCV-positive individuals 3.0 and 1.9, respectively, for >or=5% and <5% HCV prevalence). RRs were consistently increased for all major B-NHL subtypes, T-NHL, and primary sites of NHL presentation. Thus, previous suggestions that the RRs for HCV differed by NHL subtype were not confirmed in our meta-analysis. Associations weaker than with NHL were found between HCV infection and Hodgkin's lymphoma (RR, 1.5; 95% CI, 1.0-2.1) and multiple myeloma (RR, 1.6; 95% CI, 0.7-3.6), but they were based on much fewer studies than NHL. The etiologic fraction of NHL attributable to HCV varies greatly by country, and may be upward of 10% in areas where HCV prevalence is high.

Case-Control Studies↗
PubMed1993

Meta-analysis as a guide to clinical practice.

BACKGROUND: Meta-analysis is now widely used in order to increase the power of individual clinical studies. Important far-reaching conclusions have been derived by pooling the results of studies which in isolation would not be large enough to reach definitive conclusions. While the statistical power is thereby amplified, so is the potential for error. OBJECTIVE: To assess the potential and the pitfalls of meta-analysis as a guide to clinical practice. CONCLUSIONS: Conclusions derived from meta-analysis may be influenced by unrecognized selection bias and heterogeneity of studies included. Publication of the results may be in a form which does not lend itself readily to critical analysis and misleading results may therefore be accepted.

Antihypertensive Agents↗
PubMed1993

Meta-analysis of clinical trials based on censored end-points: simplified theory and implementation of the statistical algorithms on a microcomputer.

Meta-analysis is increasingly being used in clinical research. While the meta-analytical algorithms for pooling the results of studies using non-censored end-points are now sufficiently standardized, the management of trials based on censored end-points is still controversial, and specific algorithms of meta-analysis are still needed (for example, censored end-points are commonly used in survival studies of cancer patients). In the present article we review the various algorithms that have thus far been utilized to perform a meta-analysis based on censored end-points, and we propose a new and original approach that combines two of the existing algorithms. Our approach is designed to formulate any meta-analysis of survival studies in terms of the calculation of an odds ratio. The meta-analytical odds ratio proposed here is called the 'log-rank' odds ratio of meta-analysis. A microcomputer program is described that implements the various methods of meta-analysis that can handle clinical trials based on censored end-points. Some examples are presented to illustrate the use of the program.

Algorithms↗
PubMed1990

Meta-analysis for the refinement of gerontological nursing research and theory.

A meta-analysis review of literature addresses concerns such as inclusion and exclusion criteria for articles in the meta-analysis and seeks potentially biasing effects of sample size and characteristics, measurement of variables, type of design, and analytic techniques. Whereas the narrative review of literature provides direction by identifying potential variables and relationships of concern, meta-analysis quantifies those relationships by integrating findings and providing explicit direction for research, practice, and theory development. Despite its strengths for quantitatively integrating study results, meta-analysis is time consuming, labor intensive, and may omit other sources such as case studies, historical and qualitative research, and clinical decision making.

Geriatric Nursing↗
PubMedDate not supplied

[Meta-analysis: the science of review in Neurology].

INTRODUCTION: The review and continuous analysis of the present knowledge have always been necessary for scientific and clinical practice advance. This study presents the difference between narrative and systematic reviews, the most important points of meta-analysis, and finishes with detailed description of its phases. Our objective was to explain, in simple terms, the technique of meta-analysis and this could permit its application and use in the clinical practice and neurological investigations. DEVELOPMENT: The term meta-analysis was described for the first time by the psychologist Glass in 1967. Since then, the meta-analysis was utilized by many investigators as a technique to combine the results of different studies. The steps of a meta-analysis are: 1. Hypothesis of the study; 2. Localization of the studies of investigation; 3. Selection of the localized studies; 4. Qualitative meta-analysis; 5. Quantitative meta-analysis. Basically, It refers to the numeric combination of data, which were extracted by the reviewers. The mathematical method which will be used to evaluate the effect size should be chosen, also homogeneity and sensibility tests should be done. CONCLUSIONS: Well-designed meta-analysis is accepted as the optimum form to present the results of different studies. The meta-analysis could be of great importance for clinical practice and neurological research.

Humans↗
PubMedDate not supplied

[Impact of meta-analysis in clinical practice: the example of psychiatry].

BACKGROUND: To analyze the features of the studies on meta-analysis in psychiatry and assess the effect of these papers on the psychiatric reference textbooks. METHODS: Two researchers reviewed electronic databases Medline and Embase during the period 1977-98, using the key words: clinical trial, randomized observational trial, metaanalysis, systematic review. To confirm the validity of the searching strategy inter and intra-raters reliability was studied with satisfactory kappa figures. RESULTS: Psychiatry is the medical specialty in which more studies on meta-analysis have been carried out (N= 179, 11,79% out of the total), followed by cardiology and oncology. The increase in this kind of research during 1977-98 has been very high in all medical fields and, specifically, in psychiatry. There is no correlation between impact factor of a scientifical journal and number of meta-analysis published in it. Only 0.002% of the references of one of the most important textbook in psychiatry (Kaplan) are related to meta-analysis. There is no studies on meta-analysis developed by Spanish researchers. CONCLUSIONS: Studies on meta-analysis are not referred by psychiatric reference textbooks. As a consequence, their impact on clinical practice is scarce.

Meta-Analysis as Topic↗
PubMed2006

Meta-analysis: Methods, strengths, weaknesses, and political uses.

The general methodology, strengths and weaknesses, and political uses of meta-analysis are examined. As a systematic study of all studies that have been conducted to answer a specific question or hypothesis, meta-analysis is strong in revealing structural flaws and sources of bias in primary research and in posing promising research questions for future study. It cannot exceed, however, the limits of what is reported by primary researchers. Meta-analysis is particularly challenged to quantify the size of a common effect of treatment across reported trials because of (1) the clinical diversity of the trials and (2) the myriad of potential differences among patients with varying characteristics within the trials. Without access to the original data of reported trials, meta-analysis cannot overcome the bias of underpowered trials toward overstatement of the size of main treatment effects, nor the tendency for such trials to falsely conclude there were no statistically significant adverse events. Although severely compromised by ghost-written or honorary-authored reports of primary research, meta-analysis can make use of its methods to focus on the conflicts of interest and likely sources of bias of such research and make known what precautions should be taken by would-be consumers. Examples show how meta-analysis has clarified thinking about the off-label use of selective serotonin reuptake inhibitors for treating child and adolescent depression, use of low-tidal volume respirator assistance for acute lung injury and acute respiratory distress syndrome patients, and the long-term use of COX-2 inhibitors for relieving arthritic pain. Recommendations are made for Congressional action.

Clinical Trials as Topic↗
PubMed2000

Predictors of sexual recidivism: did meta-analysis clarify the role and relevance of denial?

Seven studies selected for meta-analysis of the denial variable in a large-scale meta-analysis of predictors of sexual recidivism are briefly reviewed and a number of methodologic issues are identified that relate to interpretation of the failure of meta-analysis to find an effect for the denial variable. These include variability in definition of the denial variable, variation in treatment access and exclusion for deniers, low base rates of recidivism, small sample sizes, low power, and high probability of type II error across individual studies. Despite the apparent objectivity and power of this methodology, a careful examination of the individual studies suggests that meta-analysis did not clarify the role and relevance of denial as a predictor of sexual recidivism. Further work is necessary to clarify the role and relevance of denial in treatment success, risk assessment, and risk prediction.

Adolescent↗
PubMed1994

[Meta-analysis and its application in epidemiology].

Meta-analysis provides a powerful statistical tool for epidemiological study. The basic principle of meta-analysis is introduced in this paper, and some problems about its application in epidemiology are discussed. This method was used by the authors to study the relationship between exposure to extreme low frequency electromagnetic fields (ELF) and childhood leukemia, and the result showed that there is a significant association between them.

Electromagnetic Fields↗
PubMed1990

Meta-analysis: its importance in cost-effectiveness studies.

Meta-analysis can be used in cost-effectiveness studies when evidence from several studies is combined to identify which therapies are effective; to estimate the degree of effectiveness between alternative choices; and to estimate cost-related outcomes as part of the costing of therapies and their sequelae. When meta-analysis is performed it is essential that the research protocol include a clear definition of the research question, a description of the studies to be included, inclusion/exclusion criteria for selecting trials, and the methods of trial selection. Issues of bias, and statistical methods and sensitivity analyses used should also be assessed. Meta-analysis, particularly of randomized trials, can provide a rigorous and sound approach to treatment evaluation and should be an integral part of any major cost-effectiveness analysis.

Cost-Benefit Analysis↗
PubMed1999

Resolving discrepancies between a meta-analysis and a subsequent large controlled trial.

CONTEXT: A recent meta-analysis found calcium supplementation to be highly effective in preventing preeclampsia but a large National Institutes of Health trial (Calcium for Preeclampsia Prevention [CPEP]) found no risk reduction due to calcium in healthy nulliparous women. OBJECTIVES: To resolve discrepancies between the results of the meta-analysis and the CPEP trial and to assess the role of effect heterogeneity in the discrepancies. DATA SOURCES: Literature search of English-language articles published prior to July 10, 1997, the date of publication of the CPEP trial, using MEDLINE and by a manual search of bibliographies of published articles. STUDY SELECTION: Trials were included if they reported data on preeclampsia and calcium supplementation. Fourteen trials were systematically evaluated for differences in study design and patient populations. One trial was excluded because its results were reported after publication of the major CPEP results. DATA EXTRACTION: The sample size and number of subjects who developed preeclampsia in the calcium supplementation group vs a control group were recorded and analyzed on an intent-to-treat basis. Each author independently extracted the data. DATA SYNTHESIS: Substantial heterogeneity existed across trials (P = .001). After stratifying studies by the presence of a placebo-controlled group and by high-risk and low-risk populations, the conclusions of the meta-analysis of placebo-controlled trials enrolling a low-risk population (relative risk, 0.79; 99% confidence interval, 0.44-1.42; P = .30) were compatible with the conclusions of the CPEP trial that calcium supplementation does not prevent preeclampsia in healthy nulliparous women. In contrast, the data implied a strong beneficial calcium effect (relative risk, 0.19; 99% confidence interval, 0.08-0.46; P = .001) in healthy high-risk subject populations. However, only 225 women were analyzed and because of inconsistent data, these results remain equivocal. CONCLUSIONS: Further studies are needed to establish the efficacy of calcium for preeclampsia prevention in healthy high-risk populations. A single summary measure does not adequately describe the findings of a meta-analysis when the observed effects in individual studies differ substantially. In such settings the primary focus should be to identify and incorporate pertinent covariates that reduce heterogeneity and allow for optimum treatment strategies.

Calcium↗
PubMed2001

Multilevel models for meta-analysis, and their application to absolute risk differences.

Meta-analysis can be considered a multilevel statistical problem, since information within studies is combined in the presence of potential heterogeneity between studies. Here a general multilevel model framework is developed for meta-analysis to combine either summary data or individual patient outcome data from each study, and to include either study or individual level covariates that might explain heterogeneity. Classical and Bayesian approaches to estimation are contrasted. These methods are applied to a meta-analysis of trials of thrombolytic therapy after myocardial infarction. Subgroups within the trials were available, categorized by the time delay until treatment, so that a three-level random effects model that includes time delay as a covariate is proposed. In addition it was desired to represent the treatment effect as an absolute risk reduction, rather than the conventional odds ratio. We show how this can be achieved within a Bayesian analysis, while still recognizing the binary nature of the original outcome data.

Bayes Theorem↗
PubMed2004

An application of meta-analysis in food safety consumer research to evaluate consumer behaviors and practices.

Meta-analysis provides a structured method for combining results from several studies and accounting for and differentiating between study variables. Numerous food safety consumer research studies often focus on specific behaviors among different subpopulations but fail to provide a holistic picture of consumer behavior. Combining information from several studies provides a broader understanding of differences and trends among demographic subpopulations, and thus, helps in developing effective risk communication messages. In the illustrated example, raw/undercooked ground beef consumption and hygienic practices were evaluated according to gender, ethnicity, and age. Percentages of people engaging in each of the above behaviors (referred to as effect sizes) were combined using weighted averages of these percentages. Several measures, including sampling errors, random variance between studies, sample sizes of studies, and homogeneity of findings across studies, were used in the meta-analysis. The statistical significance of differences in behaviors across demographic segments was evaluated using analysis of variance. The meta-analysis identified considerable variability in effect sizes for raw/undercooked ground beef consumption and poor hygienic practices. More males, African Americans, and adults between 30 and 54 years (mid-age) consumed raw/undercooked ground beef than other demographic segments. Males, Caucasians, and Hispanics and young adults between 18 and 29 years were more likely to engage in poor hygienic practices. Compared to traditional qualitative review methods, meta-analysis quantitatively accounts for interstudy differences, allows greater consideration of data from studies with smaller sample sizes, and offers ease of analysis as newer data become available, and thus, merits consideration for its application in food safety consumer research.

Adult↗
PubMed2003

Validation of the summary ROC for diagnostic test meta-analysis: a Monte Carlo simulation.

RATIONALE AND OBJECTIVES: The author performed this study to test a technique for validating the logit regression method for summary receiver operating characteristic (ROC) meta-analysis, perform initial validation studies, and identify areas for further investigation. MATERIALS AND METHODS: Monte Carlo simulation was performed by using a custom macro program for a personal computer spreadsheet. The program creates simulated data sets based on user-specified parameters, performs a meta-analysis on the data sets, and logs the results so the accuracy and variability of the method can be measured. The program can also be used to measure the effects of changes in study design and meta-analysis parameters. RESULTS: For the base case of a small meta-analysis (10 studies) of small trials (mean, 50 patients), the meta-analysis results closely matched the input sensitivity and specificity when they were less than 80%. Systematic errors, if any, were small. At sensitivities and specificities greater than 80%, the true sensitivity or specificity was underestimated by up to 2% in the meta-analysis. Confidence intervals calculated with the summary ROC curve were reasonably conservative, although they too fell below the true results when sensitivity or specificity was greater than 80%. The underestimation was eliminated when the simulation was repeated for a much larger trial (mean, 1,000 cases per study)--even with a sensitivity and specificity of 98%. CONCLUSION: The Littenberg-Moses method for summary ROC meta-analysis is effective for obtaining an accurate summary estimate of diagnostic test performance, although the continuity correction introduces a small downward bias in the meta-analysis of small trials.

Computer Simulation↗