The mediating role of health behaviors in the association between depression, anxiety and cancer incidence: an individual participant data meta-analysis

BACKGROUND

Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers).

METHODS

Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs).

RESULTS

Smoking (HRs range 1.04-1.10) and physical inactivity (HRs range 1.01-1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03-1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01).

CONCLUSIONS

Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.

Anti-Vascular Endothelial Growth Factor Drugs Compared With Panretinal Photocoagulation for the Treatment of Proliferative Diabetic Retinopathy: A Cost-Effectiveness Analysis

OBJECTIVES

This study aimed to evaluate the cost-effectiveness of anti-vascular endothelial growth factor drugs (anti-VEGFs) compared with panretinal photocoagulation (PRP) for treating proliferative diabetic retinopathy (PDR) in the United Kingdom.

METHODS

A discrete event simulation model was developed, informed by individual participant data meta-analysis. The model captures treatment effects on best corrected visual acuity in both eyes, and the occurrence of diabetic macular edema and vitreous hemorrhage. The model also estimates the value of undertaking further research to resolve decision uncertainty.

RESULTS

Anti-VEGFs are unlikely to generate clinically meaningful benefits over PRP. The model predicted anti-VEGFs be more costly and similarly effective as PRP, generating 0.029 fewer quality-adjusted life-years at an additional cost of £3688, with a net health benefit of -0.214 at a £20 000 willingness-to-pay threshold. Scenario analysis results suggest that only under very select conditions may anti-VEGFs offer potential for cost-effective treatment of PDR. The consequences of loss to follow-up were an important driver of model outcomes.

CONCLUSIONS

Anti-VEGFs are unlikely to be a cost-effective treatment for early PDR compared with PRP. Anti-VEGFs are generally associated with higher costs and similar health outcomes across various scenarios. Although anti-VEGFs were associated with lower diabetic macular edema rates, the number of cases avoided is insufficient to offset the additional treatment costs. Key uncertainties relate to the long-term comparative effectiveness of anti-VEGFs, particularly considering the real-world rates and consequences of treatment nonadherence. Further research on long-term visual acuity and rates of vision-threatening complications may be beneficial in resolving uncertainties.

Does Social and Economic Disadvantage Predict Lower Engagement with Parenting Interventions? An Integrative Analysis Using Individual Participant Data

There is a social gradient to the determinants of health; low socioeconomic status (SES) has been linked to reduced educational attainment and employment prospects, which in turn affect physical and mental wellbeing. One goal of preventive interventions, such as parenting programs, is to reduce these health inequalities by supporting families with difficulties that are often patterned by SES. Despite these intentions, a recent individual participant data (IPD) meta-analysis of the Incredible Years (IY) parenting program found no evidence for differential benefit by socioeconomic disadvantage (Gardner et al. in Public Health Resesearch 5, 1-144, 2017). However, it did not examine whether this was influenced by engagement in the intervention. Using intervention arm data from this pooled dataset (13 trials; N = 1078), we examined whether there was an SES gradient to intervention attendance (an indicator of engagement). We ran mixed-effects Poisson regression models to estimate incidence rate ratios (IRRs) for program attendance for each of five (binary) markers of SES: low income; unemployment; low education status; teen parent; and lone parent status. The multilevel structure of the data allowed for comparison of within-trial and between-trial effects, including tests for contextual effects. We found evidence that low SES was associated with reduced attendance at parenting programs-an 8-19% reduction depending on the SES marker. However, there was no evidence that this association is impacted by differences in SES composition between trials or by the attendance levels of higher-SES families. The findings underscore the importance of developing and prioritizing strategies that enable engagement in parenting interventions and encourage program attendance by low-SES families.

Umbrella review and meta-analysis of reconstructed individual patient data of mortality following conventional endovascular and open surgical repair of infrarenal abdominal aortic aneurysm

OBJECTIVES

This umbrella review aims to quality assess published meta-analyses, conduct a de-novo meta-analysis of the available randomized control trials (RCTs), and test the hypothesis that there is a long-term difference in mortality between OSR and EVAR.

METHODS

A systematic search was conducted in MEDLINE and EMBASE's bibliographic databases (June 2022). Data were extracted using standardized extraction forms. The methodological quality of publications was assessed using the ROBIS tool. Data were analyzed with 'one-stage' and 'two-stage' approaches.

RESULTS

According to two-stage analysis, EVAR has significantly favorable mortality for up to four years (increasing evidence). Subsequently, until the longest available time period, there is no difference between EVAR and OSR; all the results are statistically non-significant.In one stage analysis, the Cox model demonstrated a non-significant (weak evidence) hazard ratio of 1.03 (95% confidence interval [CI]: 0.94-1.12) in favor of OSR. The best-fitting parametric model (generalized gamma), leads to an hazard ratio of 0.97 (95% CI: 0.93-1.01) in favor of EVAR, with the results approaching significance (weak evidence).

CONCLUSION

The results of this umbrella systematic review and meta-analysis failed to demonstrate any difference in long-term mortality following planned EVAR, compared with OSR of infrarenal AAA.

Harmonization of maternal balanced energy-protein supplementation studies for individual participant data (IPD) meta-analyses - finding and creating similarities in variables and data collection

BACKGROUND

Public health and clinical recommendations are established from systematic reviews and retrospective meta-analyses combining effect sizes, traditionally, from aggregate data and more recently, using individual participant data (IPD) of published studies. However, trials often have outcomes and other meta-data that are not defined and collected in a standardized way, making meta-analysis problematic. IPD meta-analysis can only partially fix the limitations of traditional, retrospective, aggregate meta-analysis; prospective meta-analysis further reduces the problems.

METHODS

We developed an initiative including seven clinical intervention studies of balanced energy-protein (BEP) supplementation during pregnancy and/or lactation that are being conducted (or recently concluded) in Burkina Faso, Ethiopia, India, Nepal, and Pakistan to test the effect of BEP on infant and maternal outcomes. These studies were commissioned after an expert consultation that designed recommendations for a BEP product for use among pregnant and lactating women in low- and middle-income countries. The initiative goal is to harmonize variables across studies to facilitate IPD meta-analyses on closely aligned data, commonly called prospective meta-analysis. Our objective here is to describe the process of harmonizing variable definitions and prioritizing research questions. A two-day workshop of investigators, content experts, and advisors was held in February 2020 and harmonization activities continued thereafter. Efforts included a range of activities from examining protocols and data collection plans to discussing best practices within field constraints. Prior to harmonization, there were many similar outcomes and variables across studies, such as newborn anthropometry, gestational age, and stillbirth, however, definitions and protocols differed. As well, some measurements were being conducted in several but not all studies, such as food insecurity. Through the harmonization process, we came to consensus on important shared variables, particularly outcomes, added new measurements, and improved protocols across studies.

DISCUSSION

We have fostered extensive communication between investigators from different studies, and importantly, created a large set of harmonized variable definitions within a prospective meta-analysis framework. We expect this initiative will improve reporting within each study in addition to providing opportunities for a series of IPD meta-analyses.

Multivariate meta-analysis of multiple outcomes: characteristics and predictors of borrowing of strength from Cochrane reviews

OBJECTIVES

Multivariate meta-analysis allows the joint synthesis of multiple outcomes accounting for their correlation. This enables borrowing of strength (BoS) across outcomes, which may lead to greater efficiency and even different conclusions compared to separate univariate meta-analyses. However, multivariate meta-analysis is complex to apply, so guidance is needed to flag (in advance of analysis) when the approach is most useful.

STUDY DESIGN AND SETTING

We use 43 Cochrane intervention reviews to empirically investigate the characteristics of meta-analysis datasets that are associated with a larger BoS statistic (from 0 to 100%) when applying a bivariate meta-analysis of binary outcomes.

RESULTS

Four characteristics were identified as strongly associated with BoS: the total number of studies, the number of studies with the outcome of interest, the percentage of studies missing the outcome of interest, and the largest absolute within-study correlation. Using these characteristics, we then develop a model for predicting BoS in a new dataset, which is shown to have good performance (an adjusted R² of 50%). Applied examples are used to illustrate the use of the BoS prediction model.

CONCLUSIONS

Cochrane reviewers mainly use univariate meta-analysis methods, but the identified characteristics associated with BoS and our subsequent prediction model for BoS help to flag when a multivariate meta-analysis may also be beneficial in Cochrane reviews with multiple binary outcomes. Extension to non-Cochrane reviews and other outcome types is still required.

Concurrent chemoradiotherapy with cisplatin + S-1 versus cisplatin + other third-generation agents for locally advanced non-small-cell lung cancer: a meta-analysis of individual participant data

BACKGROUND

For decades, concurrent chemo-radiotherapy with cisplatin-based regimen has been a standard therapy for locally advanced stage III non-small-cell lung cancer (NSCLC). We conducted individual-participant-data (IPD) meta-analyses to compare S-1/cisplatin versus other third-generation anti-cancer medications plus cisplatin regimens with the goal of determining whether or not S-1/cisplatin was the ideal choice for treatment accompanied by radiotherapy (RT).

METHODS

A thorough search was performed using multiple electronic databases. We integrated the IPD of each trial and analyzed the resulting meta-database. The primary endpoint was the overall survival (OS), and the secondary endpoints included the progression-free survival (PFS), objective response rate (ORR), toxicities, and treatment delivery. Subgroup analyses were conducted based on baseline characteristics. Statistical analyses were stratified by trials.

RESULTS

Three randomized control trials (WJOG5008L study, SPECTRA study, and TORG1018 study) were found. Of the 316 patients enrolled in those studies, 159 received S-1/cisplatin (SP), and 157 were assigned to other combination chemotherapy. The median OS for the SP arm was 48.2 months, and that of the non-SP arm was 42.4 months. The combined hazard ratio (HR) for the OS was 0.895 (95% confidence interval [CI] 0.638-1.256), and no heterogeneity was noted among the trials (test for heterogeneity, p = 0.87; I² = 0). The median PFS for the SP and non-SP arms was 12.8 and 14.0 months, respectively. The corresponding HR for the PFS was 1.022 (95% CI 0.776-1.347), and there was evidence of moderate heterogeneity among the trials (test for heterogeneity, p = 0.16; I² = 0.46). The ORRs were 69.7% (95% CI 62.1-76.7%) and 70.9% (95% CI 63.7-78.1%) in the SP and non-SP arms, respectively. The toxicity profile showed that SP caused significantly fewer instances of grade 3-4 leukopenia and neutropenia than non-SP regimens.

CONCLUSION

No marked differences were detected in the OS, PFS, or ORR between the SP and non-SP arms. SP had significantly less myelosuppression and better treatment compliance as a chemotherapy regimen for concurrent chemoradiation in locally advanced NSCLC than non-SP regimens.

Weight loss interventions on health-related quality of life in those with moderate to severe obesity: Findings from an individual patient data meta-analysis of randomized trials

The relationship between BMI and health-related quality of life (HRQoL) critically affects regulatory approval of interventions for weight loss, but evidence of the association is inconsistent. A higher standard of evidence than that available was sought with an IPD meta-analysis of 10,884 people enrolled in five randomized controlled trials of intentional weight loss interventions. Cross-sectional and longitudinal associations of BMI and HRQoL were estimated in mixed effects models specifying a latent variable for HRQoL. Spline regressions captured nonlinear associations across the range of BMI. In cross-sectional spline regressions, BMI was not associated with HRQoL for people with a BMI < 30 kg/m² but was for those with a higher BMI. In longitudinal spline regressions, decreases in BMI were positively associated with HRQoL for people with a BMI ≥ 25 kg/m² . The impact of change in BMI was larger for people with higher BMIs than for those with BMIs under 30 kg/m² . Lower BMI and decreases in BMI were related to higher HRQoL for people living with obesity but not in the population without excess weight. HRQoL gains from weight loss are greater for more severe obesity. Commissioners should use these estimates for future decision making.

Zika Brazilian Cohorts (ZBC) Consortium: Protocol for an Individual Participant Data Meta-Analysis of Congenital Zika Syndrome after Maternal Exposure during Pregnancy

Despite great advances in our knowledge of the consequences of Zika virus to human health, many questions remain unanswered, and results are often inconsistent. The small sample size of individual studies has limited inference about the spectrum of congenital Zika manifestations and the prognosis of affected children. The Brazilian Zika Cohorts Consortium addresses these limitations by bringing together and harmonizing epidemiological data from a series of prospective cohort studies of pregnant women with rash and of children with microcephaly and/or other manifestations of congenital Zika. The objective is to estimate the absolute risk of congenital Zika manifestations and to characterize the full spectrum and natural history of the manifestations of congenital Zika in children with and without microcephaly. This protocol describes the assembly of the Consortium and protocol for the Individual Participant Data Meta-analyses (IPD Meta-analyses). The findings will address knowledge gaps and inform public policies related to Zika virus. The large harmonized dataset and joint analyses will facilitate more precise estimates of the absolute risk of congenital Zika manifestations among Zika virus-infected pregnancies and more complete descriptions of its full spectrum, including rare manifestations. It will enable sensitivity analyses using different definitions of exposure and outcomes, and the investigation of the sources of heterogeneity between studies and regions.

A heart failure phenotype stratified model for predicting 1-year mortality in patients admitted with acute heart failure: results from an individual participant data meta-analysis of four prospective European cohorts

BACKGROUND

Prognostic models developed in general cohorts with a mixture of heart failure (HF) phenotypes, though more widely applicable, are also likely to yield larger prediction errors in settings where the HF phenotypes have substantially different baseline mortality rates or different predictor-outcome associations. This study sought to use individual participant data meta-analysis to develop an HF phenotype stratified model for predicting 1-year mortality in patients admitted with acute HF.

METHODS

Four prospective European cohorts were used to develop an HF phenotype stratified model. Cox model with two rounds of backward elimination was used to derive the prognostic index. Weibull model was used to obtain the baseline hazard functions. The internal-external cross-validation (IECV) approach was used to evaluate the generalizability of the developed model in terms of discrimination and calibration.

RESULTS

3577 acute HF patients were included, of which 2368 were classified as having HF with reduced ejection fraction (EF) (HFrEF; EF < 40%), 588 as having HF with midrange EF (HFmrEF; EF 40-49%), and 621 as having HF with preserved EF (HFpEF; EF ≥ 50%). A total of 11 readily available variables built up the prognostic index. For four of these predictor variables, namely systolic blood pressure, serum creatinine, myocardial infarction, and diabetes, the effect differed across the three HF phenotypes. With a weighted IECV-adjusted AUC of 0.79 (0.74-0.83) for HFrEF, 0.74 (0.70-0.79) for HFmrEF, and 0.74 (0.71-0.77) for HFpEF, the model showed excellent discrimination. Moreover, there was a good agreement between the average observed and predicted 1-year mortality risks, especially after recalibration of the baseline mortality risks.

CONCLUSIONS

Our HF phenotype stratified model showed excellent generalizability across four European cohorts and may provide a useful tool in HF phenotype-specific clinical decision-making.

Predicting response to topical non-steroidal anti-inflammatory drugs in osteoarthritis: an individual patient data meta-analysis of randomized controlled trials

Objectives

To identify predictors of the specific (difference between treatment and placebo) and overall (change from baseline in treatment arm) treatment effects of topical NSAIDs in OA.

Methods

Randomized controlled trials (RCTs) of topical NSAIDs in OA were identified through systematic literature searching and inquiry to pharmaceutical companies. The raw, de-identified data were analysed in one-stage individual patient data meta-analysis (IPD-MA). Negative values for treatment effects (0–100 scale) indicate pain reduction.

Results

Of 63 eligible RCTs, 15 provided IPD (n = 1951 on topical NSAID), including 11 placebo-controlled RCTs (n = 1587 on topical NSAIDs, 1553 on placebo). Seven potential predictors of response were examined. Topical NSAIDs were superior to placebo [−6 (95% CI −9, −4)], with a small, but statistically significant greater effect in women than men [difference −4 (95% CI −8, −1)]. The overall treatment effect was 4-fold larger than the specific effect [−25 (95% CI −31, −19)] and increased with greater baseline pain severity (P < 0.001). No differences in efficacy were observed for age, BMI, features of inflammation, duration of complaints or radiographic OA severity.

Conclusion

Topical NSAIDs are effective for OA pain relief. Greater overall pain relief in individuals with more baseline pain might be due to contextual and non-specific effects, including regression to the mean. Additional factors that have been linked either mechanistically or through empirical evidence to outcomes should be selected for inclusion across future RCTs in order to facilitate the identification of response predictors through IPD-MA.

Steroid treatment for the first episode of childhood nephrotic syndrome: comparison of the 8 and 12 weeks regimen using an individual patient data meta-analysis

Steroids are the cornerstone of the treatment of childhood nephrotic syndrome. The optimal duration for the first episode remains a matter of debate. The aim of this study is to determine whether the 8 weeks International Study of Kidney Disease in Children (ISKDC) regimen is equally effective as the 12 weeks steroid regimen from the German society of pediatric nephrology (Arbeitsgemeinschaft für Pädiatrische Nephrologie [APN]). An individual patient data (IPD) meta-analysis of randomized controlled trials reporting on prednisolone treatment for a first episode of childhood nephrotic syndrome was conducted. European trials aimed at investigating the ISKDC and/or APN steroid regimen were selected. The lead investigators of the selected trials were requested to provide the IPD of the specific treatment groups. Four trials included European cohorts using dosing schedules according to the regimens studied. IPD of two trials were available. A significant difference was found in time to first relapse after cessation of steroid treatment between the 8 and 12 weeks treatment group with a median time to relapse of 29 and 63 days, respectively. Moreover, relapse rate ratios during total follow-up were 51% higher for the 8 weeks regimen. Finally, younger children have a significantly lower time to first relapse and frequently relapsing nephrotic syndrome.Conclusions: The results of this IPD meta-analysis suggest that the 8 weeks steroid regimen for a first episode of steroid-sensitive nephrotic syndrome may not be equally effective as the 12 weeks steroid regimen. Moreover, this study highlights the importance of using uniform definitions to enable accurate comparison and interpretation of trial results.Trial registration: Registration number: CRD42020199244, date of registration 16-08-2020 What is Known: • Steroids are the cornerstone of the treatment of childhood nephrotic syndrome, however the optimal duration for the first episode remains a matter of debate. • Currently, the 8 weeks ISKDC protocol and 12 weeks APN protocol are among the most frequently used protocols in Europe. What is New: • The 8 weeks steroid regimen for a first episode of steroid-sensitive nephrotic syndrome may not be equally effective as the 12 weeks steroid regimen for the treatment of a first episode of nephrotic syndrome. • Younger children have a significantly shorter time to first relapse and time to frequent relapsing nephrotic syndrome.

Neuraminidase Inhibitors and Hospital Length of Stay: A Meta-analysis of Individual Participant Data to Determine Treatment Effectiveness Among Patients Hospitalized With Nonfatal 2009 Pandemic Influenza A(H1N1) Virus Infection

Background

The effect of neuraminidase inhibitor (NAI) treatment on length of stay (LoS) in patients hospitalized with influenza is unclear.

Methods

We conducted a one-stage individual participant data (IPD) meta-analysis exploring the association between NAI treatment and LoS in patients hospitalized with 2009 influenza A(H1N1) virus (A[H1N1]pdm09) infection. Using mixed-effects negative binomial regression and adjusting for the propensity to receive NAI, antibiotic, and corticosteroid treatment, we calculated incidence rate ratios (IRRs) and 95% confidence intervals (CIs). Patients with a LoS of <1 day and those who died while hospitalized were excluded.

Results

We analyzed data on 18 309 patients from 70 clinical centers. After adjustment, NAI treatment initiated at hospitalization was associated with a 19% reduction in the LoS among patients with clinically suspected or laboratory-confirmed influenza A(H1N1)pdm09 infection (IRR, 0.81; 95% CI, .78–.85), compared with later or no initiation of NAI treatment. Similar statistically significant associations were seen in all clinical subgroups. NAI treatment (at any time), compared with no NAI treatment, and NAI treatment initiated <2 days after symptom onset, compared with later or no initiation of NAI treatment, showed mixed patterns of association with the LoS.

Conclusions

When patients hospitalized with influenza are treated with NAIs, treatment initiated on admission, regardless of time since symptom onset, is associated with a reduced LoS, compared with later or no initiation of treatment.

Efficacy and Safety of Polaprezinc (Zinc Compound) on Zinc Deficiency: A Systematic Review and Dose-Response Meta-Analysis of Randomized Clinical Trials Using Individual Patient Data

Zinc intake is recommended for zinc deficiency. In clinical practice, polaprezinc has been used as a zinc replacement therapy for zinc deficiency. However, the efficacy of polaprezinc has not been established. To confirm the efficacy on zinc deficiency of polaprezinc and provide additional information on an appropriate regimen, we conducted a systematic review using individual patient data (IPD). We searched PubMed, the Japanese database Ichushi, and the database owned by the marketing authorization holder of polaprezinc. Randomized placebo-controlled trials that reported the serum zinc concentration were eligible. The mean difference of the change from baseline in serum zinc concentration was estimated using a fixed-effects model. The linear dose-response relationship and the subgroup effects were also assessed. Out of 54 unique randomized clinical trials (RCTs), four studies met the eligibility criteria, and we could access IPD for all of them. All three doses of polaprezinc (75 mg, 150 mg, and 300 mg) and the placebo group were examined. The dose-combined overall polaprezinc increased the change from baseline by a mean of 9.08 µg/dL (95% confidence interval: 5.46, 12.70; heterogeneity: I2 = 0.61%) compared to the placebo. A significant dose-response relationship was confirmed (p < 0.001). Baseline serum zinc concentration was considered an effect modifier in polaprezinc 300 mg. All doses of polaprezinc were tolerable, but a dose-response relationship with adverse events (AEs) was observed in gastrointestinal disorders. The dose of 300 mg may be useful among patients with baseline serum zinc concentration of less than 70 µg/dL, and 150 mg for 70 µg/dL or more.

Meta-analysis of clinical trials with competing time-to-event endpoints

Recommendations for the analysis of competing risks in the context of randomized clinical trials are well established. Meta-analysis of individual patient data (IPD) is the gold standard for synthesizing evidence for clinical interpretation based on multiple studies. Surprisingly, no formal guidelines have been yet proposed to conduct an IPD meta-analysis with competing risk endpoints. To fill this gap, this work details (i) how to handle the heterogeneity between trials via a stratified regression model for competing risks and (ii) that the usual metrics of inconsistency to assess heterogeneity can readily be employed. Our proposal is illustrated by the re-analysis of a recently published meta-analysis in nasopharyngeal carcinoma, aiming at quantifying the benefit of the addition of chemotherapy to radiotherapy on each competing endpoint.

The effect of dose on the antimalarial efficacy of artesunate-mefloquine against Plasmodium falciparum malaria: a protocol for systematic review and individual patient data (IPD) meta-analysis

INTRODUCTION

Antimalarial posology based on weight bands leaves patients at the margins vulnerable to receiving either lower or higher weight-adjusted (mg/kg) dosages. This article aims to describe the protocol for systematic review and individual patient meta-analysis (MA) for a study of the distribution of artesunate and mefloquine dosage administered in patients with uncomplicated Plasmodium falciparum malaria treated with an artesunate-mefloquine (AS-MQ) regimen. Relationship between mg/kg dose and therapeutic outcomes will be assessed through a one-stage individual participant data (IPD) MA.

METHODS AND ANALYSIS

Therapeutic efficacy studies with the AS-MQ regimen will be identified by searching the following databases: PUBMED, EMBASE and Web of Science. The corresponding authors of the relevant studies will be requested to share the IPD for the purpose of this MA to a secured repository. All available studies will be standardised using a common data management protocol and pooled into a single database. The relationship between mg/kg dosage and treatment failures will be assessed using a Cox regression model with study sites considered as a shared frailty term. Safety parameters will be explored where available.

ETHICS AND DISSEMINATION

This IPD MA met the criteria for waiver of ethical review as defined by the Oxford Tropical Research Ethics Committee as the research consisted of secondary analysis of existing anonymous data. The results of this analysis will be disseminated at conferences, WorldWide Antimalarial Resistance Network website and any peer-reviewed publication arising will be made open source.

PROSPERO REGISTRATION NUMBER

CRD42018103776.

Virulence-driven trade-offs in disease transmission: A meta-analysis

The virulence-transmission trade-off hypothesis proposed more than 30 years ago is the cornerstone in the study of host-parasite co-evolution. This hypothesis rests on the premise that virulence is an unavoidable and increasing cost because the parasite uses host resources to replicate. This cost associated with replication ultimately results in a deceleration in transmission rate because increasing within-host replication increases host mortality. Empirical tests of predictions of the hypothesis have found mixed support, which cast doubt about its overall generalizability. To quantitatively address this issue, we conducted a meta-analysis of 29 empirical studies, after reviewing over 6000 published papers, addressing the four core relationships between (1) virulence and recovery rate, (2) within-host replication rate and virulence, (3) within-host replication and transmission rate, and (4) virulence and transmission rate. We found strong support for an increasing relationship between replication and virulence, and replication and transmission. Yet, it is still uncertain if these relationships generally decelerate due to high within-study variability. There was insufficient data to quantitatively test the other two core relationships predicted by the theory. Overall, the results suggest that the current empirical evidence provides partial support for the trade-off hypothesis, but more work remains to be done.

What Affects the Completion of Ecological Momentary Assessments in Chronic Pain Research? An Individual Patient Data Meta-Analysis

Background

Ecological momentary assessment (EMA) involves repeated sampling of people’s current experiences in real time in their natural environments, which offers a granular perspective on patients’ experience of pain and other symptoms. However, EMA can be burdensome to patients, and its benefits depend upon patients’ engagement in the assessments.

Objective

The goal of this study was to investigate factors affecting EMA-completion rates among patients with chronic pain.

Methods

This individual patient data meta-analysis was based on 12 EMA datasets that examined patients with chronic noncancer-related pain (n=701). The EMA-completion rates were calculated on a daily basis for each patient. Multilevel models were used to test the following predictors of completion rates at different levels: within-patient factors (days into the study and daily pain level), between-patient factors (age, sex, pain diagnosis, and average pain level per person), and between-study EMA design factors (study duration, sampling density, and survey length).

Results

Across datasets, an EMA-completion rate of 85% was observed. The strongest results were found for the between-patient factor age: Younger respondents reported lower completion rates than older respondents (P=.002). One within-patient factor, study day, was associated with completion rates (P<.001): over the course of the studies, the completion rates declined. The two abovementioned factors interacted with each other (P=.02) in that younger participants showed a more rapid decline in EMA completion over time. In addition, none of the other hypothesized factors including gender, chronic pain diagnoses, pain intensity levels, or measures of study burden showed any significant effects.

Conclusion

Many factors thought to influence the EMA-completion rates in chronic pain studies were not confirmed. However, future EMA research in chronic pain should note that study length and young age can impact the quality of the momentary data and devise strategies to maximize completion rates across different age groups and study days.

The use of one-stage meta-analytic method based on individual participant data for binary adverse events under the rule of three: a simulation study

Objective

In evidence synthesis practice, dealing with binary rare adverse events (AEs) is a challenging problem. The pooled estimates for rare AEs through traditional inverse variance (IV), Mantel-Haenszel (MH), and Yusuf-Peto (Peto) methods are suboptimal, as the biases tend to be large. We proposed the “one-stage” approach based on multilevel variance component logistic regression (MVCL) to handle this problem.

Methods

We used simulations to generate trials of individual participant data (IPD) with a series of predefined parameters. We compared the performance of the MVCL “one-stage” approach and the five classical methods (fixed/random effect IV, fixed/random effect MH, and Peto) for rare binary AEs under different scenarios, which included different sample size setting rules, effect sizes, between-study heterogeneity, and numbers of studies in each meta-analysis. The percentage bias, mean square error (MSE), coverage probability, and average width of the 95% confidence intervals were used as performance indicators.

Results

We set 52 scenarios and each scenario was simulated 1,000 times. Under the rule of three (a sample size setting rule to ensure a 95% chance of detecting at least one AE case), the MVCL “one-stage” IPD method had the lowest percentage bias in most of the situations and the bias remained at a very low level (<10%), when compared to IV, MH, and Peto methods. In addition, the MVCL “one-stage” IPD method generally had the lowest MSE and the narrowest average width of 95% confidence intervals. However, it did not show better coverage probability over the other five methods.

Conclusions

The MVCL “one-stage” IPD meta-analysis is a useful method to handle binary rare events and superior compared to traditional methods under the rule of three. Further meta-analyses may take account of the “one-stage” IPD method for pooling rare event data.

The Role of COL5A2 in Patients With Muscle-Invasive Bladder Cancer: A Bioinformatics Analysis of Public Datasets Involving 787 Subjects and 29 Cell Lines

Bladder cancer (BC) is one of the most common malignancies. Two previous studies identified collagen type V alpha 2 (COL5A2) as a potential biomarker in BC, both are simple reanalysis of a single transcriptomic dataset without subgroup analysis for muscle-invasive BC (MIBC). We focused in MIBC patients and explored the role of COL5A2 from an integration perspective, using refined methodology covering individual participant data meta-analysis and bioinformatics analysis. Eight transcriptomic datasets of 787 MIBC patients (including one dataset containing genomic mutation information) and two drug sensitivity datasets of 29 cell lines in which more than 250 compounds were analyzed. We found subjects with increased COL5A2 gene expression exhibited poorer prognosis, and the power analysis confirmed adequate sample size. FGFR3 was the only gene differential mutated between the COL5A2 high and low expression groups. Differential expression and co-expression network analysis suggested potential association between COL5A2 expression and essential pathways involved in cancer invasion and dissemination, including cell adhesion, extracellular matrix organization, and epithelial-mesenchymal transition. Coordinately, analysis of drug screening datasets and gene-drug interaction also revealed COL5A2 expression linked to cell morphogenesis, angiogenesis, blood vessel development, and urogenital development. The utility and feasibility of COL5A2 for clinically applicable prognosis prediction and risk classification and the exact underlying molecular mechanism should be further investigated in subsequent studies.

An Empirical Comparison of Meta- and Mega-Analysis With Data From the ENIGMA Obsessive-Compulsive Disorder Working Group

Objective: Brain imaging communities focusing on different diseases have increasingly started to collaborate and to pool data to perform well-powered meta- and mega-analyses. Some methodologists claim that a one-stage individual-participant data (IPD) mega-analysis can be superior to a two-stage aggregated data meta-analysis, since more detailed computations can be performed in a mega-analysis. Before definitive conclusions regarding the performance of either method can be drawn, it is necessary to critically evaluate the methodology of, and results obtained by, meta- and mega-analyses.

Methods: Here, we compare the inverse variance weighted random-effect meta-analysis model with a multiple linear regression mega-analysis model, as well as with a linear mixed-effects random-intercept mega-analysis model, using data from 38 cohorts including 3,665 participants of the ENIGMA-OCD consortium. We assessed the effect sizes and standard errors, and the fit of the models, to evaluate the performance of the different methods.

Results: The mega-analytical models showed lower standard errors and narrower confidence intervals than the meta-analysis. Similar standard errors and confidence intervals were found for the linear regression and linear mixed-effects random-intercept models. Moreover, the linear mixed-effects random-intercept models showed better fit indices compared to linear regression mega-analytical models.

Conclusions: Our findings indicate that results obtained by meta- and mega-analysis differ, in favor of the latter. In multi-center studies with a moderate amount of variation between cohorts, a linear mixed-effects random-intercept mega-analytical framework appears to be the better approach to investigate structural neuroimaging data.

Association of longitudinal alcohol consumption trajectories with coronary heart disease: a meta-analysis of six cohort studies using individual participant data

BACKGROUND

Studies have shown that alcohol intake trajectories differ in their associations with biomarkers of cardiovascular functioning, but it remains unclear if they also differ in their relationship to actual coronary heart disease (CHD) incidence. Using multiple longitudinal cohort studies, we evaluated the association between long-term alcohol consumption trajectories and CHD.

METHODS

Data were drawn from six cohorts (five British and one French). The combined analytic sample comprised 35,132 individuals (62.1% male; individual cohorts ranging from 869 to 14,247 participants) of whom 4.9% experienced an incident (fatal or non-fatal) CHD event. Alcohol intake across three assessment periods of each cohort was used to determine participants' intake trajectories over approximately 10 years. Time to onset for (i) incident CHD and (ii) fatal CHD was established using surveys and linked medical record data. A meta-analysis of individual participant data was employed to estimate the intake trajectories' association with CHD onset, adjusting for demographic and clinical characteristics.

RESULTS

Compared to consistently moderate drinkers (males: 1-168 g ethanol/week; females: 1-112 g ethanol/week), inconsistently moderate drinkers had a significantly greater risk of incident CHD [hazard ratio (HR) = 1.18, 95% confidence interval (CI) = 1.02-1.37]. An elevated risk of incident CHD was also found for former drinkers (HR = 1.31, 95% CI = 1.13-1.52) and consistent non-drinkers (HR = 1.47, 95% CI = 1.21-1.78), although, after sex stratification, the latter effect was only evident for females. When examining fatal CHD outcomes alone, only former drinkers had a significantly elevated risk, though hazard ratios for consistent non-drinkers were near identical. No evidence of elevated CHD risk was found for consistently heavy drinkers, and a weak association with fatal CHD for inconsistently heavy drinkers was attenuated following adjustment for confounding factors.

CONCLUSIONS

Using prospectively recorded alcohol data, this study has shown how instability in drinking behaviours over time is associated with risk of CHD. As well as individuals who abstain from drinking (long term or more recently), those who are inconsistently moderate in their alcohol intake have a higher risk of experiencing CHD. This finding suggests that policies and interventions specifically encouraging consistency in adherence to lower-risk drinking guidelines could have public health benefits in reducing the population burden of CHD. The absence of an effect amongst heavy drinkers should be interpreted with caution given the known wider health risks associated with such intake.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT03133689 .

B-type natriuretic peptide-guided therapy for heart failure (HF): a systematic review and meta-analysis of individual participant data (IPD) and aggregate data

BACKGROUND

We estimated the effectiveness of serial B-type natriuretic peptide (BNP) blood testing to guide up-titration of medication compared with symptom-guided up-titration of medication in patients with heart failure (HF).

METHODS

Systematic review and meta-analysis of randomised controlled trials (RCTs). We searched: MEDLINE (Ovid) 1950 to 9/06/2016; Embase (Ovid), 1980 to 2016 week 23; the Cochrane Library; ISI Web of Science (Citations Index and Conference Proceedings). The primary outcome was all-cause mortality; secondary outcomes were death related to HF, cardiovascular death, all-cause hospital admission, hospital admission for HF, adverse events, and quality of life. IPD were sought from all RCTs identified. Random-effects meta-analyses (two-stage) were used to estimate hazard ratios (HR) and confidence intervals (CIs) across RCTs, including HR estimates from published reports of studies that did not provide IPD. We estimated treatment-by-covariate interactions for age, gender, New York Heart Association (NYHA) class, HF type; diabetes status and baseline BNP subgroups. Dichotomous outcomes were analysed using random-effects odds ratio (OR) with 95% CI.

RESULTS

We identified 14 eligible RCTs, five providing IPD. BNP-guided therapy reduced the hazard of hospital admission for HF by 19% (13 RCTs, HR 0.81, 95% CI 0.68 to 0.98) but not all-cause mortality (13 RCTs; HR 0.87, 95% CI 0.75 to 1.01) or cardiovascular mortality (5 RCTs; OR 0.88, 95% CI 0.67 to 1.16). For all-cause mortality, there was a significant interaction between treatment strategy and age (p = 0.034, 11 RCTs; HR 0.70, 95% CI 0.53-0.92, patients < 75 years old and HR 1.07, 95% CI 0.84-1.37, patients ≥ 75 years old); ejection fraction (p = 0.026, 11 RCTs; HR 0.84, 95% CI 0.71-0.99, patients with heart failure with reduced ejection fraction (HFrEF); and HR 1.33, 95% CI 0.83-2.11, patients with heart failure with preserved ejection fraction (HFpEF)). Adverse events were significantly more frequent with BNP-guided therapy vs. symptom-guided therapy (5 RCTs; OR 1.29, 95% CI 1.04 to 1.60).

CONCLUSION

BNP-guided therapy did not reduce mortality but reduced HF hospitalisation. The overall quality of the evidence varied from low to very low. The relevance of these findings to unselected patients, particularly those managed by community generalists, are unclear.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42013005335.

Non-equivalence of anti-Müllerian hormone automated assays-clinical implications for use as a companion diagnostic for individualised gonadotrophin dosing

STUDY QUESTION

Can anti-Müllerian hormone (AMH) automated immunoassays (Elecsys® and Access) be used interchangeably as a companion diagnostic for individualisation of follitropin delta dosing?

SUMMARY ANSWER

The Access assay gives systematically higher AMH values than the Elecsys® assay which results in over 29% of women being misclassified to a different follitropin delta dose.

WHAT IS KNOWN ALREADY

Follitropin delta is the first gonadotrophin to be licenced with a companion diagnostic, the Roche Elecsys® AMH Plus assay. Alternative automated AMH assays including the Beckman Coulter Access immunoassay are considered to provide similar results, but clarification of their suitability as an off-licence companion diagnostic for follitropin delta is required.

STUDY DESIGN, SIZE, DURATION

We systematically searched the existing literature for studies that had measured AMH using both automated assays in the same cohort of women. Individual paired patient data were acquired from each author and combined with unpublished data.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We identified five eligible prospective published studies and one additional unpublished study. A 100% response from the authors was achieved. We collected paired AMH data on samples from 848 women. Passing-Bablok regression and Bland-Altman plots were used to compare the analytical performance of the two assays. The degree of misclassification to different treatment categories was estimated should the Access AMH be used as a companion diagnostic instead of the Elecsys AMH in determining the dosing of follitropin delta.

MAIN RESULTS AND THE ROLE OF CHANCE

The Passing-Bablok regression shows a linear relationship (Access = -0.05 + 1.10 × Elecsys). The Access assay systematically gave higher values by an average of 10% compared with the Elecsys assay (slope = 1.10, 95% CI: 1.09 to 1.12). The average of the difference between the two assays was 2.7 pmol/l. The 95% limits of agreement were -11.7 to 6.3. Overall 253 (29.3%) women would have received an inappropriate follitropin delta dose if the Beckman Coulter Access assay was used. Specifically, a substantial proportion of women (ranging from 49% to 90% depending on the AMH category) would receive a lower dose of follitropin delta based on the Access AMH assay. Up to 10% (ranging from 2.5% to 10%) of women with high ovarian reserve would have been misclassified to a greater dose of follitropin delta based on the Access AMH assay.

LIMITATIONS REASONS FOR CAUTION

We compared the values of the two principal automated assays, extrapolation of our findings to other automated AMH assays would require similar comprehensive examination.

WIDER IMPLICATIONS OF THE FINDINGS

An international standard for the calibration of the automated AMH assays is warranted to facilitate efficient use of AMH as a companion diagnostic. The variable calibration of alternative automated AMH assays may adversely impact on the performance of the follitropin delta dosing algorithm.

STUDY FUNDING/COMPETING INTEREST(S)

No formal funding has been received for this study. SI is funded by a UK Medical Research Council skills development fellowship (MR/N015177/1). SMN has received speakers fees, travel to meetings and participated in advisory Boards for Beckman Coulter, IBSA, Ferring Pharmaecuticals, Finox, Merck Serono, Merck and Roche Diagnostics. SMN has received research support from Ansh laboratories, Beckman Coulter, Ferring Pharmaceuticals and Roche Diagnostics.

TRIAL REGISTRATION NUMBER

N/A.

Handling incomplete correlated continuous and binary outcomes in meta-analysis of individual participant data

Meta‐analysis of individual participant data (IPD) is increasingly utilised to improve the estimation of treatment effects, particularly among different participant subgroups. An important concern in IPD meta‐analysis relates to partially or completely missing outcomes for some studies, a problem exacerbated when interest is on multiple discrete and continuous outcomes. When leveraging information from incomplete correlated outcomes across studies, the fully observed outcomes may provide important information about the incompleteness of the other outcomes. In this paper, we compare two models for handling incomplete continuous and binary outcomes in IPD meta‐analysis: a joint hierarchical model and a sequence of full conditional mixed models. We illustrate how these approaches incorporate the correlation across the multiple outcomes and the between‐study heterogeneity when addressing the missing data. Simulations characterise the performance of the methods across a range of scenarios which differ according to the proportion and type of missingness, strength of correlation between outcomes and the number of studies. The joint model provided confidence interval coverage consistently closer to nominal levels and lower mean squared error compared with the fully conditional approach across the scenarios considered. Methods are illustrated in a meta‐analysis of randomised controlled trials comparing the effectiveness of implantable cardioverter‐defibrillator devices alone to implantable cardioverter‐defibrillator combined with cardiac resynchronisation therapy for treating patients with chronic heart failure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Multivariable fractional polynomial interaction to investigate continuous effect modifiers in a meta-analysis on higher versus lower PEEP for patients with ARDS

OBJECTIVES

A recent individual patient data (IPD) meta-analysis suggested that patients with moderate or severe acute respiratory distress syndrome (ARDS) benefit from higher positive end-expiratory pressure (PEEP) ventilation strategies. However, thresholds for continuous variables (eg, hypoxaemia) are often arbitrary and linearity assumptions in regression approaches may not hold; the multivariable fractional polynomial interaction (MFPI) approach can address both problems. The objective of this study was to apply the MFPI approach to investigate interactions between four continuous patient baseline variables and higher versus lower PEEP on clinical outcomes.

SETTING

Pooled data from three randomised trials in intensive care identified by a systematic review.

PARTICIPANTS

2299 patients with acute lung injury requiring mechanical ventilation.

INTERVENTIONS

Higher (N=1136) versus lower PEEP (N=1163) ventilation strategy.

OUTCOME MEASURES

Prespecified outcomes included mortality, time to death and time-to-unassisted breathing. We examined the following continuous baseline characteristics as potential effect modifiers using MFPI: PaO2/FiO2 (arterial partial oxygen pressure/ fraction of inspired oxygen), oxygenation index, respiratory system compliance (tidal volume/(inspiratory plateau pressure-PEEP)) and body mass index (BMI).

RESULTS

We found that for patients with PaO2/FiO2 below 150 mm Hg, but above 100 mm Hg or an oxygenation index above 12 (moderate ARDS), higher PEEP reduces hospital mortality, but the beneficial effect appears to level off for patients with very severe ARDS. Patients with mild ARDS (PaO2/FiO2 above 200 mm Hg or an oxygenation index below 10) do not seem to benefit from higher PEEP and might even be harmed. For patients with a respiratory system compliance above 40 mL/cm H2O or patients with a BMI above 35 kg/m(2), we found a trend towards reduced mortality with higher PEEP, but there is very weak statistical confidence in these findings.

CONCLUSIONS

MFPI analyses suggest a nonlinear effect modification of higher PEEP ventilation by PaO2/FiO2 and oxygenation index with reduced mortality for some patients suffering from moderate ARDS.

STUDY REGISTRATION NUMBER

CRD42012003129.

Multiple imputation for IPD meta-analysis: allowing for heterogeneity and studies with missing covariates

Recently, multiple imputation has been proposed as a tool for individual patient data meta‐analysis with sporadically missing observations, and it has been suggested that within‐study imputation is usually preferable. However, such within study imputation cannot handle variables that are completely missing within studies. Further, if some of the contributing studies are relatively small, it may be appropriate to share information across studies when imputing. In this paper, we develop and evaluate a joint modelling approach to multiple imputation of individual patient data in meta‐analysis, with an across‐study probability distribution for the study specific covariance matrices. This retains the flexibility to allow for between‐study heterogeneity when imputing while allowing (i) sharing information on the covariance matrix across studies when this is appropriate, and (ii) imputing variables that are wholly missing from studies. Simulation results show both equivalent performance to the within‐study imputation approach where this is valid, and good results in more general, practically relevant, scenarios with studies of very different sizes, non‐negligible between‐study heterogeneity and wholly missing variables. We illustrate our approach using data from an individual patient data meta‐analysis of hypertension trials. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Imputation of systematically missing predictors in an individual participant data meta-analysis: a generalized approach using MICE

Individual participant data meta-analyses (IPD-MA) are increasingly used for developing and validating multivariable (diagnostic or prognostic) risk prediction models. Unfortunately, some predictors or even outcomes may not have been measured in each study and are thus systematically missing in some individual studies of the IPD-MA. As a consequence, it is no longer possible to evaluate between-study heterogeneity and to estimate study-specific predictor effects, or to include all individual studies, which severely hampers the development and validation of prediction models. Here, we describe a novel approach for imputing systematically missing data and adopt a generalized linear mixed model to allow for between-study heterogeneity. This approach can be viewed as an extension of Resche-Rigon's method (Stat Med 2013), relaxing their assumptions regarding variance components and allowing imputation of linear and nonlinear predictors. We illustrate our approach using a case study with IPD-MA of 13 studies to develop and validate a diagnostic prediction model for the presence of deep venous thrombosis. We compare the results after applying four methods for dealing with systematically missing predictors in one or more individual studies: complete case analysis where studies with systematically missing predictors are removed, traditional multiple imputation ignoring heterogeneity across studies, stratified multiple imputation accounting for heterogeneity in predictor prevalence, and multilevel multiple imputation (MLMI) fully accounting for between-study heterogeneity. We conclude that MLMI may substantially improve the estimation of between-study heterogeneity parameters and allow for imputation of systematically missing predictors in IPD-MA aimed at the development and validation of prediction models.

Platinum versus platinum-combination chemotherapy in platinum-sensitive recurrent ovarian cancer: a meta-analysis using individual patient data

BACKGROUND

The majority of women with ovarian cancer develop recurrent disease. For patients with a platinum-free interval of >6 months, platinum-based chemotherapy is a treatment of choice. The benefit of platinum-based combination chemotherapy in randomized trials varies, and a meta-analysis was carried out to gain more secure information on the size of the benefit of this treatment.

MATERIALS AND METHODS

We initiated a systematic review and meta-analysis following a pre-specified protocol to determine whether combination chemotherapy is superior to single-agent platinum chemotherapy in women with relapsed platinum-sensitive ovarian cancer.

RESULTS

A total of five potentially eligible randomized trials were identified that had used combination-platinum chemotherapy versus single-agent platinum chemotherapy in women with relapsed platinum-sensitive ovarian cancer. For one trial (190 patients), adequate contact with the investigators could not be established. Therefore, four trials that randomly assigned 1300 patients were included, with a median follow-up of 36.1 months. Overall survival (OS) analyses were based on 865 deaths and demonstrated evidence for the benefit of combination-platinum chemotherapy (HR = 0.80; 95% CI, 0.64-1.00; P = 0.05). Progression-free survival (PFS) analyses were based on 1167 events and demonstrated strong evidence for the benefit of combination-platinum chemotherapy (HR = 0.68; 95% CI, 0.57-0.81; P < 0.001). There was no evidence of a difference in the relative effect of combination-platinum chemotherapy on either OS or PFS in patient subgroups defined by previous paclitaxel (Taxol) treatment (OS, P = 0.49; PFS, P = 0.66), duration of treatment-free interval (OS, P = 0.86; PFS, P = 0.48) or the number of previous lines of chemotherapy (OS, P = 0.21; PFS, P = 0.27).

CONCLUSIONS

In this individual patient data (IPD) meta-analysis, we have demonstrated that combination-platinum chemotherapy improves OS and PFS across all subgroups. This provides the strongest evidence to date of the benefit of combination-platinum over single-agent platinum.

Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data

A variable is 'systematically missing' if it is missing for all individuals within particular studies in an individual participant data meta-analysis. When a systematically missing variable is a potential confounder in observational epidemiology, standard methods either fail to adjust the exposure-disease association for the potential confounder or exclude studies where it is missing. We propose a new approach to adjust for systematically missing confounders based on multiple imputation by chained equations. Systematically missing data are imputed via multilevel regression models that allow for heterogeneity between studies. A simulation study compares various choices of imputation model. An illustration is given using data from eight studies estimating the association between carotid intima media thickness and subsequent risk of cardiovascular events. Results are compared with standard methods and also with an extension of a published method that exploits the relationship between fully adjusted and partially adjusted estimated effects through a multivariate random effects meta-analysis model. We conclude that multiple imputation provides a practicable approach that can handle arbitrary patterns of systematic missingness. Bias is reduced by including sufficient between-study random effects in the imputation model.

Combining individual participant and aggregated data in a meta-analysis with correlational studies

This paper presents methods for combining individual participant data (IPD) with aggregated study level data (AD) in a meta-analysis of correlational studies. Although medical researchers have employed IPD in a wide range of studies, only a single example exists in the social sciences. New policies at the National Science Foundation requiring grantees to submit data archiving plans may increase social scientists' access to individual level data that could be combined with traditional meta-analysis. The methods presented here extend prior work on IPD to meta-analyses using correlational studies. The examples presented illustrate the synthesis of publicly available national datasets in education with aggregated study data from a meta-analysis examining the correlation of socioeconomic status measures and academic achievement. The major benefit of the inclusion of the individual level is that both within-study and between-study interactions among moderators of effect size can be estimated. Given the potential growth in data archives in the social sciences, we should see a corresponding increase in the ability to synthesize IPD and AD in a single meta-analysis, leading to a more complete understanding of how within-study and between-study moderators relate to effect size. Copyright © 2012 John Wiley & Sons, Ltd.