How often can meta-analyses of individual-level data individualize treatment? A meta-epidemiologic study

Magnetic resonance-guided laser interstitial thermal therapy for drug-resistant epilepsy: A systematic review and individual participant data meta-analysis

Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) has emerged as a popular minimally invasive alternative to open resective surgery for drug-resistant epilepsy (DRE). We sought to perform a systematic review and individual participant data meta-analysis to identify independent predictors of seizure outcome and complications following MRgLITT for DRE. Eleven databases were searched from January 1, 2010 to February 6, 2021 using the terms "MR-guided ablation therapy" and "epilepsy". Multivariable mixed-effects Cox and logistic regression identified predictors of time to seizure recurrence, seizure freedom, operative complications, and postoperative neurological deficits. From 8705 citations, 46 studies reporting on 450 MRgLITT DRE patients (mean age = 29.5 ± 18.1 years, 49.6% female) were included. Median postoperative seizure freedom and follow-up duration were 15.5 and 19.0 months, respectively. Overall, 240 (57.8%) of 415 patients (excluding palliative corpus callosotomy) were seizure-free at last follow-up. Generalized seizure semiology (hazard ratio [HR] = 1.78, p = .020) and nonlesional magnetic resonance imaging (MRI) findings (HR = 1.50, p = .032) independently predicted shorter time to seizure recurrence. Cerebral cavernous malformation (CCM; odds ratio [OR] = 7.97, p < .001) and mesial temporal sclerosis/atrophy (MTS/A; OR = 2.21, p = .011) were independently associated with greater odds of seizure freedom at last follow-up. Operative complications occurred in 28 (8.5%) of 330 patients and were independently associated with extratemporal ablations (OR = 5.40, p = .012) and nonlesional MRI studies (OR = 3.25, p = .017). Postoperative neurological deficits were observed in 53 (15.1%) of 352 patients and were independently predicted by hypothalamic hamartoma etiology (OR = 5.93, p = .006) and invasive electroencephalographic monitoring (OR = 4.83, p = .003). Overall, MRgLITT is particularly effective in treating patients with well-circumscribed lesional DRE, such as CCM and MTS/A, but less effective in nonlesional cases or lesional cases with a more diffuse epileptogenic network associated with generalized seizures. This study identifies independent predictors of seizure freedom and complications following MRgLITT that may help further guide patient selection.

Reporting quality and risk of bias of Cochrane individual participant data meta-analyses: A cross-sectional study

OBJECTIVES

This study aimed to assess the reporting quality and risk of bias of Cochrane individual participant data meta-analyses (IPD-MAs).

METHODS

We searched the Cochrane Library and identified the Cochrane IPD-MAs. We used the Preferred Reporting Items for Systematic Review and Meta-Analyses of individual participant data (PRISMA-IPD) assessed the reporting quality of included Cochrane IPD- MAs, and the Risk Of Bias In Systematic reviews (ROBIS) tool was used to assess the risk of bias. We performed stratified and correlation analyses to explore factors affecting the quality.

RESULTS

Forty-six Cochrane IPD-MAs were included in our study. Twenty-six Cochrane IPD-MAs (56.5%) had statistical or epidemiological authors involved, and 31 (67.4%) contained only IPD data. Thirty-five studies (76.1%) did not report whether they used 1-stage or 2-stage methods, and forty (87.0%) did not report the statistical techniques used for missing participant data. We found that the entire compliance reported PRISMA-IPD items of Cochrane IPD-MAs published after 2015 (n = 18; Mean ± SD: 26.61 ± 2.75) was higher than those studies published in 2015 and before (n = 28; Mean ± SD: 22.61 ± 4.73), the difference was statistically significant (p = 0.002). A strong positive correlation was found between the fully reported PRISMA-IPD items and fully accordance ROBIS items (Spearman's: ρ = 0.653, p < 0.001).

CONCLUSIONS

The quality of Cochrane IPD-MAs is not high, especially in the reporting of statistical methods. There was room for further improvement in IPD retrieval, IPD integrity and statistical analyses.

Project rebuild the evidence base (REB): A method to interpret randomised clinical trials and their meta-analysis to present solid benefit-risk assessments to patients

Evidence-based medicine is the cornerstone of shared-decision making in healthcare today. The public deserves clear, transparent and trust-worthy information on drug efficacy. Yet today, many drugs are prescribed and used without solid evidence of efficacy. Clinical trials and randomised clinical trials (RCTs) are the best method to evaluate drug efficacy and side effects. In a shared medical decision-making approach, general practitioners need drug assessment based on patient-important outcomes. The aim of project rebuild the evidence base (REB) is to bridge the gap between the data needed in clinical practice and the data available from clinical research. The drugs will be assessed on clinical patient important outcomes and for a population. Using the Cochrane tools, we propose to analyse for each population and outcome: 1) a meta-analysis based on RCTs with a low risk of bias overall; 2) an evaluation of results of confirmatory RCTs; 3) a statistical analysis of heterrogeneity between RCTs and 4) an analysis of publication bias. Depending on the results of these analyses, the evidence will be categorized in 4 different levels: firm evidence, evidence (to be confirmed), signal or absence of evidence. Project REB proposes a method for reading and interpreting RCTs and their meta-analysis to produce quality data for general practitioners to focus on risk-benefit assessment in the interest of patients. If this data does not exist, it could enable clinical research to better its aim.

Prespecification of subgroup analyses and examination of treatment-subgroup interactions in cancer individual participant data meta-analyses are suboptimal

OBJECTIVES

This study aimed to explore the prespecification and conduct of subgroup analyses in cancer individual participant data meta-analyses (IPDMAs).

STUDY DESIGN AND SETTING

We searched PubMed, Embase.com, Cochrane Library, and Web of Science to identify IPDMAs of randomized controlled trials evaluating intervention effects for cancer. We evaluated how often cancer IPDMAs prespecify subgroup analyses and statistical approaches for examining treatment-subgroup interactions and handling continuous subgroup variables.

RESULTS

We included 89 IPDMAs, of which 41 (46.1%) reported a statistically significant treatment-subgroup interaction (P < 0.05) in at least one subgroup analysis. 47 (52.8%) IPDMAs prespecified methods for conducting subgroup analyses and the remaining 42 (47.2%) did not prespecify subgroup analyses. Of the 47 IPDMAs prespecified subgroup analyses, 19 performed the planned subgroup analyses, 21 added subgroup analyses, 7 reduced subgroup analyses. Eighty IPDMAs examined treatment-subgroup interactions, but 72 IPDMAs did not provide enough information to determine whether an appropriate approach that avoided aggregation bias was used. 85 IPDMAs that used continuous variables in subgroup analyses categorized continuous variables and only 1 IPDMA examined non-linear relationships.

CONCLUSION

Many cancer IPDMAs did not prespecify subgroup analyses, nor did they fully perform planned subgroup analyses. Lack of details for the test of treatment-subgroup interactions and examination of non-linear interactions was suboptimal.

Preventive psychiatry: a blueprint for improving the mental health of young people

Preventive approaches have latterly gained traction for improving mental health in young people. In this paper, we first appraise the conceptual foundations of preventive psychiatry, encompassing the public health, Gordon's, US Institute of Medicine, World Health Organization, and good mental health frameworks, and neurodevelopmentally-sensitive clinical staging models. We then review the evidence supporting primary prevention of psychotic, bipolar and common mental disorders and promotion of good mental health as potential transformative strategies to reduce the incidence of these disorders in young people. Within indicated approaches, the clinical high-risk for psychosis paradigm has received the most empirical validation, while clinical high-risk states for bipolar and common mental disorders are increasingly becoming a focus of attention. Selective approaches have mostly targeted familial vulnerability and non-genetic risk exposures. Selective screening and psychological/psychoeducational interventions in vulnerable subgroups may improve anxiety/depressive symptoms, but their efficacy in reducing the incidence of psychotic/bipolar/common mental disorders is unproven. Selective physical exercise may reduce the incidence of anxiety disorders. Universal psychological/psychoeducational interventions may improve anxiety symptoms but not prevent depressive/anxiety disorders, while universal physical exercise may reduce the incidence of anxiety disorders. Universal public health approaches targeting school climate or social determinants (demographic, economic, neighbourhood, environmental, social/cultural) of mental disorders hold the greatest potential for reducing the risk profile of the population as a whole. The approach to promotion of good mental health is currently fragmented. We leverage the knowledge gained from the review to develop a blueprint for future research and practice of preventive psychiatry in young people: integrating universal and targeted frameworks; advancing multivariable, transdiagnostic, multi-endpoint epidemiological knowledge; synergically preventing common and infrequent mental disorders; preventing physical and mental health burden together; implementing stratified/personalized prognosis; establishing evidence-based preventive interventions; developing an ethical framework, improving prevention through education/training; consolidating the cost-effectiveness of preventive psychiatry; and decreasing inequalities. These goals can only be achieved through an urgent individual, societal, and global level response, which promotes a vigorous collaboration across scientific, health care, societal and governmental sectors for implementing preventive psychiatry, as much is at stake for young people with or at risk for emerging mental disorders.

Development of the Instrument to assess the Credibility of Effect Modification Analyses (ICEMAN) in randomized controlled trials and meta-analyses

BACKGROUND

Most randomized controlled trials (RCTs) and meta-analyses of RCTs examine effect modification (also called a subgroup effect or interaction), in which the effect of an intervention varies by another variable (e.g., age or disease severity). Assessing the credibility of an apparent effect modification presents challenges; therefore, we developed the Instrument for assessing the Credibility of Effect Modification Analyses (ICEMAN).

METHODS

To develop ICEMAN, we established a detailed concept; identified candidate credibility considerations in a systematic survey of the literature; together with experts, performed a consensus study to identify key considerations and develop them into instrument items; and refined the instrument based on feedback from trial investigators, systematic review authors and journal editors, who applied drafts of ICEMAN to published claims of effect modification.

RESULTS

The final instrument consists of a set of preliminary considerations, core questions (5 for RCTs, 8 for meta-analyses) with 4 response options, 1 optional item for additional considerations and a rating of credibility on a visual analogue scale ranging from very low to high. An accompanying manual provides rationales, detailed instructions and examples from the literature. Seventeen potential users tested ICEMAN; their suggestions improved the user-friendliness of the instrument.

INTERPRETATION

The Instrument for assessing the Credibility of Effect Modification Analyses offers explicit guidance for investigators, systematic reviewers, journal editors and others considering making a claim of effect modification or interpreting a claim made by others.

Vaccines to prevent COVID-19: a protocol for a living systematic review with network meta-analysis including individual patient data (The LIVING VACCINE Project)

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19) which has rapidly spread worldwide. Several human randomized clinical trials assessing potential vaccines are currently underway. There is an urgent need for a living systematic review that continuously assesses the beneficial and harmful effects of all available vaccines for COVID-19.

METHODS/DESIGN

We will conduct a living systematic review based on searches of major medical databases (e.g., MEDLINE, EMBASE, CENTRAL) and clinical trial registries from their inception onwards to identify relevant randomized clinical trials. We will update the literature search once a week to continuously assess if new evidence is available. Two review authors will independently extract data and conduct risk of bias assessments. We will include randomized clinical trials comparing any vaccine aiming to prevent COVID-19 (including but not limited to messenger RNA; DNA; non-replicating viral vector; replicating viral vector; inactivated virus; protein subunit; dendritic cell; other vaccines) with any comparator (placebo; "active placebo;" no intervention; standard care; an "active" intervention; another vaccine for COVID-19) for participants in all age groups. Primary outcomes will be all-cause mortality; a diagnosis of COVID-19; and serious adverse events. Secondary outcomes will be quality of life and non-serious adverse events. The living systematic review will include aggregate data meta-analyses, trial sequential analyses, network meta-analyses, and individual patient data meta-analyses. Within-study bias will be assessed using Cochrane risk of bias tool. The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) and Confidence in Network Meta-Analysis (CINeMA) approaches will be used to assess certainty of evidence. Observational studies describing harms identified during the search for trials will also be included and described and analyzed separately.

DISCUSSION

COVID-19 has become a pandemic with substantial mortality. A living systematic review assessing the beneficial and harmful effects of different vaccines is urgently needed. This living systematic review will regularly inform best practice in vaccine prevention and clinical research of this highly prevalent disease.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020196492.

Nutrition in times of Covid-19, how to trust the deluge of scientific information

PURPOSE OF REVIEW

The Covid-19 pandemic has daunted the world with its enormous impact on healthcare, economic recession, and psychological distress. Nutrition is an integral part of every person life care, and should also be mandatorily integrated to patient care under the Covid-19 pandemic. It is crucial to understand how the Covid-19 does develop and which risk factors are associated with negative outcomes and death. Therefore, it is of utmost importance to have studies that respect the basic tenets of the scientific method in order to be trusted. The goal of this review is to discuss the deluge of scientific data and how it might influence clinical reasoning and practice.

RECENT FINDINGS

A large number of scientific manuscripts are daily published worldwide, and the Covid-19 makes no exception. Up to now, data on Covid-19 have come from countries initially affected by the disease and mostly pertain either epidemiological observations or opinion papers. Many of them do not fulfil the essential principles characterizing the adequate scientific method.

SUMMARY

It is crucial to be able to critical appraise the scientific literature, in order to provide adequate nutrition therapy to patients, and in particular, to Covid-19 infected individuals.

Statistical analyses and quality of individual participant data network meta-analyses were suboptimal: a cross-sectional study

BACKGROUND

Network meta-analyses using individual participant data (IPD-NMAs) have been increasingly used to compare the effects of multiple interventions. Although there have been many studies on statistical methods for IPD-NMAs, it is unclear whether there are statistical defects in published IPD-NMAs and whether the reporting of statistical analyses has improved. This study aimed to investigate statistical methods used and assess the reporting and methodological quality of IPD-NMAs.

METHODS

We searched four bibliographic databases to identify published IPD-NMAs. The methodological quality was assessed using AMSTAR-2 and reporting quality assessed based on PRISMA-IPD and PRISMA-NMA. We performed stratified analyses and correlation analyses to explore the factors that might affect quality.

RESULTS

We identified 21 IPD-NMAs. Only 23.8% of the included IPD-NMAs reported statistical techniques used for missing participant data, 42.9% assessed the consistency, and none assessed the transitivity. None of the included IPD-NMAs reported sources of funding for trials included, only 9.5% stated pre-registration of protocols, and 28.6% assessed the risk of bias in individual studies. For reporting quality, compliance rates were lower than 50.0% for more than half of the items. Less than 15.0% of the IPD-NMAs reported data integrity, presented the network geometry, or clarified risk of bias across studies. IPD-NMAs with statistical or epidemiological authors often better assessed the inconsistency (P = 0.017). IPD-NMAs with a priori protocol were associated with higher reporting quality in terms of search (P = 0.046), data collection process (P = 0.031), and syntheses of results (P = 0.006).

CONCLUSIONS

The reporting of statistical methods and compliance rates of methodological and reporting items of IPD-NMAs were suboptimal. Authors of future IPD-NMAs should address the identified flaws and strictly adhere to methodological and reporting guidelines.

Characteristics and interpretation of subgroup analyses based on tumour characteristics in randomised trials testing target-specific anticancer drugs: design of a systematic survey

BACKGROUND

Target-specific anticancer drugs are under rapid development. Little is known, however, about the risk of administering target-specific drugs to patients who have tumours with molecular alterations or other characteristics that can make the drug ineffective or even harmful. An increasing number of randomised clinical trials (RCTs) investigating target-specific anticancer drugs include subgroup analyses based on tumour characteristics. Such subgroup analyses have the potential to be more credible and influential than subgroup analyses based on traditional factors such as sex or tumour stage. In addition, they may more frequently lead to qualitative subgroup effects, that is, show benefit in one but harm in another subgroup of patients (eg, if the tumour characteristic makes the drug ineffective or even enhance tumour growth). If so, subgroup analyses based on tumour characteristics would be highly relevant for patient safety. The aim of this study is to systematically assess the frequency and characteristics of subgroup analyses based on tumour characteristics, the frequency of qualitative subgroup effects, their credibility, and the interpretations that investigators and guidelines developers report.

METHODS AND ANALYSIS

We will perform a systematic survey of 433 RCTs testing the effect of target-specific anticancer drugs. Teams of methodologically trained investigators and oncologists will identify eligible studies, extract relevant data and assess the credibility of putative subgroup effects using a recently developed formal instrument. We will systematically assess how trial investigators interpret apparent subgroup effects based on tumour characteristics and the extent to which they influence subsequent practice guidelines. Our results will provide empirical data characterising an increasingly used type of subgroup analysis in cancer trials and its potential impact on precision medicine to predict benefit or harm.

ETHICS AND DISSEMINATION

Formal ethical approval is not required for this study. We will disseminate the findings in a peer-reviewed and open-access journal publication.

Individual participant data meta-analysis to examine interactions between treatment effect and participant-level covariates: Statistical recommendations for conduct and planning

Precision medicine research often searches for treatment‐covariate interactions, which refers to when a treatment effect (eg, measured as a mean difference, odds ratio, hazard ratio) changes across values of a participant‐level covariate (eg, age, gender, biomarker). Single trials do not usually have sufficient power to detect genuine treatment‐covariate interactions, which motivate the sharing of individual participant data (IPD) from multiple trials for meta‐analysis. Here, we provide statistical recommendations for conducting and planning an IPD meta‐analysis of randomized trials to examine treatment‐covariate interactions. For conduct, two‐stage and one‐stage statistical models are described, and we recommend: (i) interactions should be estimated directly, and not by calculating differences in meta‐analysis results for subgroups; (ii) interaction estimates should be based solely on within‐study information; (iii) continuous covariates and outcomes should be analyzed on their continuous scale; (iv) nonlinear relationships should be examined for continuous covariates, using a multivariate meta‐analysis of the trend (eg, using restricted cubic spline functions); and (v) translation of interactions into clinical practice is nontrivial, requiring individualized treatment effect prediction. For planning, we describe first why the decision to initiate an IPD meta‐analysis project should not be based on between‐study heterogeneity in the overall treatment effect; and second, how to calculate the power of a potential IPD meta‐analysis project in advance of IPD collection, conditional on characteristics (eg, number of participants, standard deviation of covariates) of the trials (potentially) promising their IPD. Real IPD meta‐analysis projects are used for illustration throughout.

The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement: Explanation and Elaboration

The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed to promote the conduct of, and provide guidance for, predictive analyses of heterogeneity of treatment effects (HTE) in clinical trials. The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risk with versus without the intervention, taking into account all relevant patient attributes simultaneously, to support more personalized clinical decision making than can be made on the basis of only an overall average treatment effect. The authors distinguished 2 categories of predictive HTE approaches (a "risk-modeling" and an "effect-modeling" approach) and developed 4 sets of guidance statements: criteria to determine when risk-modeling approaches are likely to identify clinically meaningful HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. They discuss limitations of these methods and enumerate research priorities for advancing methods designed to generate more personalized evidence. This explanation and elaboration document describes the intent and rationale of each recommendation and discusses related analytic considerations, caveats, and reservations.

Age-treatment subgroup analyses in Cochrane intervention reviews: a meta-epidemiological study

BACKGROUND

There is growing interest in evaluating differences in healthcare interventions across routinely collected demographic characteristics. However, individual subgroup analyses in randomized controlled trials are often not prespecified, adjusted for multiple testing, or conducted using the appropriate statistical test for interaction, and therefore frequently lack credibility. Meta-analyses can be used to examine the validity of potential subgroup differences by collating evidence across trials. Here, we characterize the conduct and clinical translation of age-treatment subgroup analyses in Cochrane reviews.

METHODS

For a random sample of 928 Cochrane intervention reviews of randomized trials, we determined how often subgroup analyses of age are reported, how often these analyses have a P < 0.05 from formal interaction testing, how frequently subgroup differences first observed in an individual trial are later corroborated by other trials in the same meta-analysis, and how often statistically significant results are included in commonly used clinical management resources (BMJ Best Practice, UpToDate, Cochrane Clinical Answers, Google Scholar, and Google search).

RESULTS

Among 928 Cochrane intervention reviews, 189 (20.4%) included plans to conduct age-treatment subgroup analyses. The vast majority (162 of 189, 85.7%) of the planned analyses were not conducted, commonly because of insufficient trial data. There were 22 reviews that conducted their planned age-treatment subgroup analyses, and another 3 reviews appeared to perform unplanned age-treatment subgroup analyses. These 25 (25 of 928, 2.7%) reviews conducted a total of 97 age-treatment subgroup analyses, of which 65 analyses (in 20 reviews) had non-overlapping subgroup levels. Among the 65 age-treatment subgroup analyses, 14 (21.5%) did not report any formal interaction testing. Seven (10.8%) reported P < 0.05 from formal age-treatment interaction testing; however, none of these seven analyses were in reviews that discussed the potential biological rationale or clinical significance of the subgroup findings or had results that were included in common clinical practice resources.

CONCLUSION

Age-treatment subgroup analyses in Cochrane intervention reviews were frequently planned but rarely conducted, and implications of detected interactions were not discussed in the reviews or mentioned in common clinical resources. When subgroup analyses are performed, authors should report the findings, compare the results to previous studies, and outline any potential impact on clinical care.

Increase value and reduce waste in research on psychological therapies

A seminal Lancet series focused on increasing value and reducing waste in biomedical research, providing a transferrable template to diagnose problems in research. Our goal was to document how some of these sources of waste apply to mental health and particularly psychological treatments research. We synthesize and critically evaluate empirical findings in relation to four major sources: i) defining research priorities; ii) research design, methods and analysis; iii) accessibility of research information; iv) accuracy and usability of research reports. We demonstrate that each source of waste considered is well-represented and amply documented within this field. We describe hype and insufficient consideration of what is known in defining research priorities, persistent risk of bias, particularly due to selective outcome reporting, for psychotherapy trials across mental disorders, intellectual and financial biases, direct and indirect evidence of publication bias, largely inexistent adoption of data sharing, issues of multiplicity and fragmentation of data and findings, and insufficient adoption of reporting guidelines. We expand on a few general solutions, including supporting meta-research, properly testing interventions to increase research quality, placing open science at the center of psychological treatment research and remaining vigilant particularly regarding the strains of research currently prioritized, such as experimental psychopathology.

Personalized Pharmacotherapy for Bipolar Disorder: How to Tailor Findings From Randomized Trials to Individual Patient-Level Outcomes

The quest for "personalized medicine" in psychiatry has focused mainly on pursuing potential biomarkers such as pharmacogenetic predictors of drug response. However, the collective randomized trial database across phases of bipolar disorder allows one to identify clinical characteristics that inform the likelihood of desired treatment outcomes. In turn, those characteristics, termed moderators and mediators of drug response, enable those who administer treatment to construct clinical profiles that can help them tailor pharmacotherapies to the features of a given patient rather than simply to an overall diagnosis. Bipolar disorder typically involves more heterogeneous than uniform clinical presentations, partly because of its highly prevalent psychiatric and medical comorbid conditions. Further clinical diversity arises from characteristics such as bipolar I versus II disorder subtype, rapid cycling, mixed versus pure affective episodes, psychosis, anxiety, chronicity, cognitive dysfunction, and suicidality, among other distinguishing features. By coupling such profiles with an awareness of the psychotropic breadth of spectrum held by particular medications, clinicians can devise strategic combination therapy regimens, capitalizing on synergies and using drugs that exert multiple relevant effects, addressing comorbid conditions, incorporating medications that could offset adverse effects of other agents, and avoiding or deprescribing medication options that lack known evidence to target symptoms within the clinical profile of a given patient.