Prediction intervals for random-effects meta-analysis: A confidence distribution approach

Prediction intervals are commonly used in meta-analysis with random-effects models. One widely used method, the Higgins–Thompson–Spiegelhalter prediction interval, replaces the heterogeneity parameter with its point estimate, but its validity strongly depends on a large sample approximation. This is a weakness in meta-analyses with few studies. We propose an alternative based on bootstrap and show by simulations that its coverage is close to the nominal level, unlike the Higgins–Thompson–Spiegelhalter method and its extensions. The proposed method was applied in three meta-analyses.

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Prognostic Role of Matrix Metalloproteinases in Cervical Cancer: A Meta-Analysis

Cancer Control ◽

10.1177/10732748211033743 ◽

2021 ◽

Vol 28 ◽

pp. 107327482110337

Author(s):

Weiwei Chen ◽

Shenjiao Huang ◽

Kun Shi ◽

Lisha Yi ◽

Yaqiong Liu ◽

...

Keyword(s):

Cervical Cancer ◽

Matrix Metalloproteinases ◽

Random Effects ◽

Fixed Effects ◽

Prognostic Value ◽

Meta Analysis ◽

Free Survival ◽

Random Effects Models ◽

Registration Number ◽

Meta Analyses

Objective Studies have published the association between the expression of matrix metalloproteinases (MMPs) and the outcome of cervical cancer. However, the prognostic value in cervical cancer remains controversial. This meta-analysis was conducted to evaluate the prognostic functions of MMP expression in cervical cancer. Methods A comprehensive search of PubMed, Embase, and Web of Science databases was conducted to identify the eligible studies according to defined selection and excluding criteria and analyzed according to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Fixed and random effects models were evaluated through the hazard ratios (HRs) and 95% confidence intervals (CIs) to estimate the overall survival (OS), recurrence-free survival (RFS), and progress-free survival (PFS). Results A total of 18 eligible studies including 1967 patients were analyzed for prognostic value. Totally 16 selected studies including 21 tests were relevant to the cervical cancer OS, 4 studies focused on RFS, and 1 study on PFS. The combined pooled HRs and 95% CIs of OS were calculated with random-effects models (HR = 1.64, 95% CI = 1.01–2.65, P = .000). In the subgroup analysis for OS, there was no heterogeneity in MMP-2 (I2 = .0%, P = .880), MMP-1 (I2 = .0%, P = .587), and MMP-14 (I2 = 28.3%, P = .248). In MMP-7 and MMP-9, the heterogeneities were obvious (I2 = 99.2% ( P = .000) and I2 = 77.9% ( P = .000), respectively). The pooled HRs and 95% CIs of RFS were calculated with fixed-effects models (HR = 2.22, 95% CI = 1.38–3.58, P = .001) and PFS (HR = 2.29, 95% CI = 1.14–4.58, P = .035). Conclusions The results indicated that MMP overexpression was associated with shorter OS and RFS in cervical cancer patients. It suggested that MMP overexpression might be a poor prognostic marker in cervical cancer. Research Registry Registration Number: reviewregistry 1159.

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Triclosan-Coated Sutures Reduce the Risk of Surgical Site Infections: A Systematic Review and Meta-analysis

Infection Control and Hospital Epidemiology ◽

10.1017/ice.2014.22 ◽

2015 ◽

Vol 36 (2) ◽

pp. 169-179 ◽

Cited By ~ 24

Author(s):

Anucha Apisarnthanarak ◽

Nalini Singh ◽

Aila Nica Bandong ◽

Gilbert Madriaga

Keyword(s):

Systematic Review ◽

Abdominal Surgery ◽

Random Effects ◽

Meta Analysis ◽

Surgical Site Infections ◽

Sensitivity Analyses ◽

Publication Type ◽

Random Effects Models ◽

Meta Regression ◽

Meta Analyses

OBJECTIVETo analyze available evidence on the effectiveness of triclosan-coated sutures (TCSs) in reducing the risk of surgical site infection (SSI).DESIGNSystematic review and meta-analysis.METHODSA systematic search of both randomized (RCTs) and nonrandomized (non-RCT) studies was performed on PubMed Medline, OVID, EMBASE, and SCOPUS, without restrictions in language and publication type. Random-effects models were utilized and pooled estimates were reported as the relative risk (RR) ratio with 95% confidence interval (CI). Tests for heterogeneity as well as meta-regression, subgroup, and sensitivity analyses were performed.RESULTSA total of 29 studies (22 RCTs, 7 non-RCTs) were included in the meta-analysis. The overall RR of acquiring an SSI was 0.65 (95% CI: 0.55–0.77; I2=42.4%, P=.01) in favor of TCS use. The pooled RR was particularly lower for the abdominal surgery group (RR: 0.56; 95% CI: 0.41–0.77) and was robust to sensitivity analysis. Meta-regression analysis revealed that study design, in part, may explain heterogeneity (P=.03). The pooled RR subgroup meta-analyses for randomized controlled trials (RCTs) and non-RCTs were 0.74 (95% CI: 0.61–0.89) and 0.53 (95% CI: 0.42–0.66), respectively, both of which favored the use of TCSs.CONCLUSIONThe random-effects meta-analysis based on RCTs suggests that TCSs reduced the risk of SSI by 26% among patients undergoing surgery. This effect was particularly evident among those who underwent abdominal surgery.Infect Control Hosp Epidemiol 2015;36(2): 1–11

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USING PREDICTION INTERVALS FROM RANDOM-EFFECTS META-ANALYSES IN AN ECONOMIC MODEL

International Journal of Technology Assessment in Health Care ◽

10.1017/s0266462313000676 ◽

2014 ◽

Vol 30 (1) ◽

pp. 44-49 ◽

Cited By ~ 11

Author(s):

Conor Teljeur ◽

Michelle O'Neill ◽

Patrick Moran ◽

Linda Murphy ◽

Patricia Harrington ◽

...

Keyword(s):

Random Effects ◽

Treatment Effect ◽

Meta Analysis ◽

Clinical Effectiveness ◽

Cost Utility ◽

Prediction Intervals ◽

Confidence Bounds ◽

Robot Assisted ◽

Meta Analyses ◽

Robot Assisted Surgery

Objectives: When incorporating treatment effect estimates derived from a random-effect meta-analysis it is tempting to use the confidence bounds to determine the potential range of treatment effect. However, prediction intervals reflect the potential effect of a technology rather than the more narrowly defined average treatment effect. Using a case study of robot-assisted radical prostatectomy, this study investigates the impact on a cost-utility analysis of using clinical effectiveness derived from random-effects meta-analyses presented as confidence bounds and prediction intervals, respectively.Methods: To determine the cost-utility of robot-assisted prostatectomy, an economic model was developed. The clinical effectiveness of robot-assisted surgery compared with open and conventional laparoscopic surgery was estimated using meta-analysis of peer-reviewed publications. Assuming treatment effect would vary across studies due to both sampling variability and differences between surgical teams, random-effects meta-analysis was used to pool effect estimates.Results: Using the confidence bounds approach the mean and median ICER was €24,193 and €26,731/QALY (95%CI: €13,752 to €68,861/QALY), respectively. The prediction interval approach produced an equivalent mean and median ICER of €26,920 and €26,643/QALY (95%CI: -€135,244 to €239,166/QALY), respectively. Using prediction intervals, there is a probability of 0.042 that robot-assisted surgery will result in a net reduction in QALYs.Conclusions: Using prediction intervals rather than confidence bounds does not affect the point estimate of the treatment effect. In meta-analyses with significant heterogeneity, the use of prediction intervals will produce wider ranges of treatment effect, and hence result in greater uncertainty, but a better reflection of the effect of the technology.

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Stereotactic radiosurgery for non-functioning pituitary adenomas: meta-analysis and International Stereotactic Radiosurgery Society practice opinion

Neuro-Oncology ◽

10.1093/neuonc/noz225 ◽

2019 ◽

Vol 22 (3) ◽

pp. 318-332 ◽

Cited By ~ 4

Author(s):

Rupesh Kotecha ◽

Arjun Sahgal ◽

Muni Rubens ◽

Antonio De Salles ◽

Laura Fariselli ◽

...

Keyword(s):

Systematic Review ◽

Stereotactic Radiosurgery ◽

Random Effects ◽

Local Control ◽

Pituitary Adenomas ◽

Meta Analysis ◽

Random Effects Models ◽

Review Reports ◽

Meta Analyses ◽

Non Functioning Pituitary Adenomas

Abstract Background This systematic review reports on outcomes and toxicities following stereotactic radiosurgery (SRS) for non-functioning pituitary adenomas (NFAs) and presents consensus opinions regarding appropriate patient management. Methods Using the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, a systematic review was performed from articles of ≥10 patients with NFAs published prior to May 2018 from the Medline database using the key words “radiosurgery” and “pituitary” and/or “adenoma.” Weighted random effects models were used to calculate pooled outcome estimates. Results Of the 678 abstracts reviewed, 35 full-text articles were included describing the outcomes of 2671 patients treated between 1971 and 2017 with either single fraction SRS or hypofractionated stereotactic radiotherapy (HSRT). All studies were retrospective (level IV evidence). SRS was used in 27 studies (median dose: 15 Gy, range: 5–35 Gy) and HSRT in 8 studies (median total dose: 21 Gy, range: 12–25 Gy, delivered in 3–5 fractions). The 5-year random effects local control estimate after SRS was 94% (95% CI: 93.0–96.0%) and 97.0% (95% CI: 93.0–98.0%) after HSRT. The 10-year local control random effects estimate after SRS was 83.0% (95% CI: 77.0–88.0%). Post-SRS hypopituitarism was the most common treatment-related toxicity observed, with a random effects estimate of 21.0% (95% CI: 15.0–27.0%), whereas visual dysfunction or other cranial nerve injuries were uncommon (range: 0–7%). Conclusions SRS is an effective and safe treatment for patients with NFAs. Encouraging short-term data support HSRT for select patients, and mature outcomes are needed before definitive recommendations can be made. Clinical practice opinions were developed on behalf of the International Stereotactic Radiosurgery Society (ISRS).

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Meta-Analysis of Sensorimotor Gating Deficits in Patients With Schizophrenia Evaluated by Prepulse Inhibition Test

Schizophrenia Bulletin ◽

10.1093/schbul/sbaa059 ◽

2020 ◽

Vol 46 (6) ◽

pp. 1482-1497

Author(s):

Rodrigo San-Martin ◽

Leonardo Andrade Castro ◽

Paulo Rossi Menezes ◽

Francisco José Fraga ◽

Priscyla Waleska Simões ◽

...

Keyword(s):

Prepulse Inhibition ◽

Random Effects ◽

Effect Size ◽

Meta Analysis ◽

Sensorimotor Gating ◽

Control Group ◽

Random Effects Models ◽

Meta Regression Analysis ◽

High Level ◽

Meta Analyses

Abstracts Prepulse inhibition (PPI) of startle is an operational measure of sensorimotor gating that is often impaired in patients with schizophrenia. Despite the large number of studies, there is considerable variation in PPI outcomes reported. We conducted a systematic review and meta-analysis investigating PPI impairment in patients with schizophrenia compared with healthy control subjects, and examined possible explanations for the variation in results between studies. Major databases were screened for observational studies comparing healthy subjects and patients with schizophrenia for the prepulse and pulse intervals of 60 and 120 ms as primary outcomes, ie, PPI-60 and PPI-120. Standardized mean difference (SMD) and 95% confidence intervals (CI) were extracted and pooled using random effects models. We then estimated the mean effect size of these measures with random effects meta-analyses and evaluated potential PPI heterogeneity moderators, using sensitivity analysis and meta-regressions. Sixty-seven primary studies were identified, with 3685 healthy and 4290 patients with schizophrenia. The schizophrenia group showed reduction in sensorimotor gating for both PPI-60 (SMD = −0.50, 95% CI = [−0.61, −0.39]) and PPI-120 (SMD = −0.44, 95% CI = [−0.54, −0.33]). The sensitivity and meta-regression analysis showed that sample size, gender proportion, imbalance for gender, source of control group, and study continent were sources of heterogeneity (P < .05) for both PPI-60 and PPI-120 outcomes. Our findings confirm a global sensorimotor gating deficit in schizophrenia patients, with overall moderate effect size for PPI-60 and PPI-120. Methodological consistency should decrease the high level of heterogeneity of PPI results between studies.

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Random-effects meta-analysis: the number of studies matters

Statistical Methods in Medical Research ◽

10.1177/0962280215583568 ◽

2015 ◽

Vol 26 (3) ◽

pp. 1500-1518 ◽

Cited By ~ 70

Author(s):

Annamaria Guolo ◽

Cristiano Varin

Keyword(s):

Random Effects ◽

Type I Error ◽

Meta Analysis ◽

Practical Interest ◽

Error Rates ◽

Type I ◽

Model Framework ◽

Random Effects Models ◽

Meta Analyses ◽

The Impact

This paper investigates the impact of the number of studies on meta-analysis and meta-regression within the random-effects model framework. It is frequently neglected that inference in random-effects models requires a substantial number of studies included in meta-analysis to guarantee reliable conclusions. Several authors warn about the risk of inaccurate results of the traditional DerSimonian and Laird approach especially in the common case of meta-analysis involving a limited number of studies. This paper presents a selection of likelihood and non-likelihood methods for inference in meta-analysis proposed to overcome the limitations of the DerSimonian and Laird procedure, with a focus on the effect of the number of studies. The applicability and the performance of the methods are investigated in terms of Type I error rates and empirical power to detect effects, according to scenarios of practical interest. Simulation studies and applications to real meta-analyses highlight that it is not possible to identify an approach uniformly superior to alternatives. The overall recommendation is to avoid the DerSimonian and Laird method when the number of meta-analysis studies is modest and prefer a more comprehensive procedure that compares alternative inferential approaches. R code for meta-analysis according to all of the inferential methods examined in the paper is provided.

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Moment and Least-Squares Based Approaches to Meta-analytic Inference

Handbook of Meta-analysis in Ecology and Evolution ◽

10.23943/princeton/9780691137285.003.0009 ◽

2013 ◽

Author(s):

Michael S. Rosenberg

Keyword(s):

Least Squares ◽

Random Effects ◽

Meta Analysis ◽

Structural Models ◽

Sums Of Squares ◽

Random Effects Models ◽

Weighted Means ◽

The Moment ◽

The One ◽

Meta Analyses

Chapter 8 introduced variance and structural models and various statistical inference approaches used in meta-analysis. This chapter describes the basic details behind the moment and least-squares approach to meta-analysis. This approach represents “classic” meta-analysis; it is the one most frequently found in meta-analytic introductions and used in ecological meta-analyses to date. This approach to meta-analytic inference has the advantage of using fairly simple formulas (for basic structural models) that can be easily calculated, and it is clearly and directly comparable to common statistical concepts, such as weighted means and sums of squares. The disadvantages of this approach is that it is less amenable to more complex modeling, particularly when considering features such as interaction effects; it also has certain limitations that in some cases reduce the applicability of random-effects models.

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The Application of Meta-Analytic Models with Multiple Random Effects: A Systematic Review

10.31234/osf.io/ugwn8 ◽

2019 ◽

Author(s):

Belén Fernández ◽

Laleh Jamshidi ◽

Lies Declercq ◽

S. Natasha Beretvas ◽

Patrick Onghena ◽

...

Keyword(s):

Systematic Review ◽

Data Structure ◽

Random Effects ◽

Multilevel Models ◽

Meta Analysis ◽

Simulation Studies ◽

Random Effects Models ◽

Sophisticated Model ◽

Meta Analyses ◽

Study Participants

In meta-analysis, study participants are nested within studies, leading to a multilevel data structure. The traditional random effects model can be considered as a model with a random study effect, but additional random effects can be added in order to account for dependent effects sizes within or across studies. The goal of this systematic review is three-fold. First, we will describe how multilevel models with multiple random effects (i.e., hierarchical three-, four-, five-level models or cross-classified random effects models) are applied in meta-analysis. Second, we will illustrate how in some specific three-level meta-analyses, a more sophisticated model could have been used to deal with additional dependencies in the data. Third and last, we will describe the distribution of the characteristics of three-level meta-analyses (e.g., distribution of the number of outcomes across studies or which dependencies are typically modeled) so that future simulation studies can simulate more realistic conditions. Results showed that four- or five-level or cross-classified random effects models are not often used although they might account better for the meta-analytic data structure of the analyzed datasets. Also, we have found that the simulation studies done on multilevel meta-analysis with multiple random factors could have used more realistic simulation factor conditions. The implications of these results are discussed and further suggestions are given.

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Effects of dutasteride on prostate cancer incidence: A systematic review and meta-analysis

International Journal of Research in Pharmaceutical Sciences ◽

10.26452/ijrps.v11i4.3860 ◽

2020 ◽

Vol 11 (4) ◽

pp. 7266-7270

Author(s):

Gyeong-Eun Min ◽

Haesoo Kim ◽

Da Eun Lee ◽

Kisok Kim

Keyword(s):

Prostate Cancer ◽

Random Effects ◽

Fixed Effects ◽

Meta Analysis ◽

Adult Males ◽

Fixed Effects Model ◽

Random Effects Models ◽

Benign Prostate Hypertrophy ◽

Fixed And Random Effects ◽

Meta Analyses

5-Alpha-reductase inhibitors (5-ARIs) are used in the treatment of benign prostate hypertrophy (BPH). 5-ARIs, such as finasteride and dutasteride, suppress the biosynthesis of dihydrotestosterone (DHT), a precursor of androgen, which is closely related to the incidence of prostate cancer (PCa). A previous meta-analysis demonstrated a relationship between finasteride use and the incidence of PCA. However, there have been no meta-analyses on the relationship between PCa and dutasteride alone. This meta-analysis was performed to examine the prevalence of PCa in adult males taking dutasteride. We searched PubMed for reports regarding PCa risk and dutasteride use. The study was conducted according to the PRISMA guidelines for systematic reviews and meta-analyses. The analytic hierarchy process (AHP) method was used to weight the studies. Odds ratios (ORs), 95% confidence intervals (CIs), and P-values were calculated using fixed- and random-effects models. A total of eight articles were included in the meta-analysis. The overall OR for both the fixed- and random-effects models was 0.669 and the 95% CI for the random-effects model (0.526–0.851; P = 0.006) was wider than that for the fixed effects model (0.548–0.817; P < 0.001). This study confirmed that the incidence of PCa was significantly reduced by taking dutasteride.

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Incidence and Prevalence of Drug-Resistant Epilepsy

Neurology ◽

10.1212/wnl.0000000000011839 ◽

2021 ◽

Vol 96 (17) ◽

pp. 805-817

Author(s):

Bushra Sultana ◽

Marie-Andrée Panzini ◽

Ariane Veilleux Carpentier ◽

Jacynthe Comtois ◽

Bastien Rioux ◽

...

Keyword(s):

Random Effects ◽

Observational Studies ◽

Focal Epilepsy ◽

Meta Analysis ◽

Drug Resistant ◽

Eligibility Criteria ◽

Random Effects Models ◽

Arcsine Transformation ◽

Drug Resistant Epilepsy ◽

Meta Analyses

ObjectiveTo evaluate the incidence and prevalence of drug-resistant epilepsy (DRE) as well as its predictors and correlates, we conducted a systematic review and meta-analysis of observational studies.MethodsOur protocol was registered with PROSPERO, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Meta-analysis of Observational Studies in Epidemiology reporting standards were followed. We searched MEDLINE, Embase, and Web of Science. We used a double arcsine transformation and random-effects models to perform our meta-analyses. We performed random-effects meta-regressions using study-level data.ResultsOur search strategy identified 10,794 abstracts. Of these, 103 articles met our eligibility criteria. There was high interstudy heterogeneity and risk of bias. The cumulative incidence of DRE was 25.0% (95% confidence interval [CI]: 16.8–34.3) in child studies but 14.6% (95% CI: 8.8–21.6) in adult/mixed age studies. The prevalence of DRE was 13.7% (95% CI: 9.2–19.0) in population/community-based populations but 36.3% (95% CI: 30.4–42.4) in clinic-based cohorts. Meta-regression confirmed that the prevalence of DRE was higher in clinic-based populations and in focal epilepsy. Multiple predictors and correlates of DRE were identified. The most reported of these were having a neurologic deficit, an abnormal EEG, and symptomatic epilepsy. The most reported genetic predictors of DRE were polymorphisms of the ABCB1 gene.ConclusionsOur observations provide a basis for estimating the incidence and prevalence of DRE, which vary between populations. We identified numerous putative DRE predictors and correlates. These findings are important to plan epilepsy services, including epilepsy surgery, a crucial treatment option for people with disabling seizures and DRE.

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