A brief note on the random-effects meta-analysis model and its relationship to other models.

Meta-analysis is a statistical method for combining quantitative results across studies. A fundamental decision in undertaking a meta-analysis is choosing an appropriate model for analysis. This is the second of two companion articles which have the joint aim of describing the different meta-analysis models. In the first article, we focused on the common-effect (also known as fixed-effect [singular]) model, and in this article, we focus on the random-effects model. We describe the key assumptions underlying the random-effects model, how it is related to the common-effect and fixed-effects [plural] models, and present some of the arguments for selecting one model over another. We outline some of the methods for fitting a random-effects model. Finally, we present an illustrative example to demonstrate how the results can differ depending on the chosen model and method. Understanding the assumptions of the different meta-analysis models, and the questions they address, is critical for meta-analysis model selection and interpretation.

Exploring decision-makers' challenges and strategies when selecting multiple systematic reviews: insights for AI decision support tools in healthcare.

BACKGROUND: Systematic reviews (SRs) are being published at an accelerated rate. Decision-makers may struggle with comparing and choosing between multiple SRs on the same topic. We aimed to understand how healthcare decision-makers (eg, practitioners, policymakers, researchers) use SRs to inform decision-making and to explore the potential role of a proposed artificial intelligence (AI) tool to assist in critical appraisal and choosing among SRs. METHODS: We developed a survey with 21 open and closed questions. We followed a knowledge translation plan to disseminate the survey through social media and professional networks. RESULTS: Our survey response rate was lower than expected (7.9% of distributed emails). Of the 684 respondents, 58.2% identified as researchers, 37.1% as practitioners, 19.2% as students and 13.5% as policymakers. Respondents frequently sought out SRs (97.1%) as a source of evidence to inform decision-making. They frequently (97.9%) found more than one SR on a given topic of interest to them. Just over half (50.8%) struggled to choose the most trustworthy SR among multiple. These difficulties related to lack of time (55.2%), or difficulties comparing due to varying methodological quality of SRs (54.2%), differences in results and conclusions (49.7%) or variation in the included studies (44.6%). Respondents compared SRs based on the relevance to their question of interest, methodological quality, and recency of the SR search. Most respondents (87.0%) were interested in an AI tool to help appraise and compare SRs. CONCLUSIONS: Given the identified barriers of using SR evidence, an AI tool to facilitate comparison of the relevance of SRs, the search and methodological quality, could help users efficiently choose among SRs and make healthcare decisions.

Two decades of network meta-analysis: Roadmap to their applications and challenges.

Recently, Ades and colleagues discussed the controversies and advancements in network meta-analysis (NMA) over the past two decades, discussing its reliability, assumptions, novel approaches, and provided some useful recommendations for the conduction of NMAs. The present discussion paper builds on the insights by Ades and colleagues, providing a roadmap for NMA applications, advancements in software and tools, and approaches designed to facilitate the assessment and interpretation of NMA findings. It also discusses the impact of NMA across disciplines, particularly for policymakers and guideline developers. Despite 20 years of NMA history, challenges remain in understanding and assessing assumptions, communicating and interpreting findings, and applying common approaches like network meta-regression and NMA involving non-randomized studies in readily available software. NMA has proven particularly valuable in clinical decision-making, which highlights the need for additional training and interdisciplinary collaboration of knowledge users, including patient engagement, to enhance its adoption and address real-world problems.

A systematic survey of 200 systematic reviews with network meta-analysis (published 2020-2021) reveals that few reviews report structured evidence summaries.

OBJECTIVES: To map whether and how systematic reviews (SRs) with network meta-analysis (NMA) use presentation formats to report (a) structured evidence summaries - here defined as reporting of effects estimates in absolute effects with certainty ratings and with a method to rate interventions across one or more outcome(s) - and (b) NMA results in general. STUDY DESIGN AND SETTING: We conducted a systematic survey, searching MEDLINE (Ovid) for SRs with NMA published between January 1, 2020, and December 31, 2021. We planned to include a random sample of publications, with predefined mechanisms in place for saturation, and included SRs that met prespecified quality criteria and extracted data on presentation formats that reported: (a) estimates of effects, (b) certainty of the evidence, or (c) rating of interventions. RESULTS: The 200 eligible SRs, from 158 unique Journals, utilized 1133 presentation formats. We found structured evidence summaries in 10 publications (5.0%), with 3 (1.5%) reporting structured evidence summaries across all outcomes, including benefits and harms. Sixteen of the 133 SRs (11.7%) reporting dichotomous outcomes included estimates of absolute effects. Seventy-six SRs (38.0%) reported both benefits and harms and 26 SRs (13.0%) reported certainty ratings in presentation formats, 20 (76.9%) used Grading of Recommendations Assessment, Development and Evaluation and 6 (23.1%) used Confidence In Network Meta-analysis. Surface Under the Cumulative Ranking Curve was the most common method to rate interventions (69 SRs, 34.5%). NMA results were most often reported using forest plots (108 SRs, 54.0%) and league tables (93 SRs, 46.5%). CONCLUSION: Most SRs with NMA do not report structured evidence summaries and only rarely do such summaries include reporting of both benefits and harms; those that do offer effective user-friendly communication and provide models for optimal NMA presentation practice.

Treatment methods for cervical intraepithelial neoplasia in England: A cost-effectiveness analysis.

OBJECTIVE: To compare the cost-effectiveness of different treatments for cervical intraepithelial neoplasia (CIN). DESIGN: A cost-effectiveness analysis based on data available in the literature and expert opinion. SETTING: England. POPULATION: Women treated for CIN. METHODS: We developed a decision-analytic model to simulate the clinical course of 1000 women who received local treatment for CIN and were followed up for 10 years after treatment. In the model we considered surgical complications as well as oncological and reproductive outcomes over the 10-year period. The costs calculated were those incurred by the National Health Service (NHS) of England. MAIN OUTCOME MEASURES: Cost per one CIN2+ recurrence averted (oncological outcome); cost per one preterm birth averted (reproductive outcome); overall cost per one adverse oncological or reproductive outcome averted. RESULTS: For young women of reproductive age, large loop excision of the transformation zone (LLETZ) was the most cost-effective treatment overall at all willingness-to-pay thresholds. For postmenopausal women, LLETZ remained the most cost-effective treatment up to a threshold of £31,500, but laser conisation became the most cost-effective treatment above that threshold. CONCLUSIONS: LLETZ is the most cost-effective treatment for both younger and older women. However, for older women, more radical excision with laser conisation could also be considered if the NHS is willing to spend more than £31,500 to avert one CIN2+ recurrence.

Trivalent and quadrivalent seasonal influenza vaccine in adults aged 60 and older: a systematic review and network meta-analysis.

OBJECTIVES: To compare the efficacy of influenza vaccines of any valency for adults 60 years and older. DESIGN AND SETTING: Systematic review with network meta-analysis (NMA) of randomised controlled trials (RCTs). MEDLINE, EMBASE, JBI Evidence-Based Practice (EBP) Database, PsycINFO, and Cochrane Evidence -Based Medicine database were searched from inception to 20 June 20, 2022. Two reviewers screened, abstracted, and appraised articles (Cochrane Risk of Bias (ROB) 2.0 tool) independently. We assessed certainty of findings using Confidence in Network Meta-Analysis and Grading of Recommendations, Assessment, Development and Evaluations approaches. We performed random-effects meta-analysis and network meta-analysis (NMA), and estimated odds ratios (ORs) for dichotomous outcomes and incidence rate ratios (IRRs) for count outcomes along with their corresponding 95% confidence intervals (CIs) and prediction intervals. PARTICIPANTS: Older adults (≥60 years old) receiving an influenza vaccine licensed in Canada or the USA (vs placebo, no vaccine, or any other licensed vaccine), at any dose. MAIN OUTCOME MEASURES: Laboratory-confirmed influenza (LCI) and influenza-like illness (ILI). Secondary outcomes were the number of vascular adverse events, hospitalisation for acute respiratory infection (ARI) and ILI, inpatient hospitalisation, emergency room (ER) visit for ILI, outpatient visit, and mortality, among others. RESULTS: We included 41 RCTs and 15 companion reports comprising 8 vaccine types and 206 032 participants. Vaccines may prevent LCI compared with placebo, with high-dose trivalent inactivated influenza vaccine (IIV3-HD) (NMA: 9 RCTs, 52 202 participants, OR 0.23, 95% confidence interval (CI) (0.11 to 0.51), low certainty of evidence) and recombinant influenza vaccine (RIV) (OR 0.25, 95%CI (0.08 to 0.73), low certainty of evidence) among the most efficacious vaccines. Standard dose trivalent IIV3 (IIV3-SD) may prevent ILI compared with placebo, but the result was imprecise (meta-analysis: 2 RCTs, 854 participants, OR 0.39, 95%CI (0.15 to 1.02), low certainty of evidence). Any HD was associated with prevention of ILI compared with placebo (NMA: 9 RCTs, 65 658 participants, OR 0.38, 95%CI (0.15 to 0.93)). Adjuvanted quadrivalent IIV (IIV4-Adj) may be associated with the least vascular adverse events, but the results were very uncertain (NMA: eight 8 RCTs, 57 677 participants, IRR 0.18, 95%CI (0.07 to 0.43), very low certainty of evidence). RIV on all-cause mortality may be comparable to placebo (NMA: 20 RCTs, 140 577 participants, OR 1.01, 95%CI (0.23 to 4.49), low certainty of evidence). CONCLUSIONS: This systematic review demonstrated efficacy associated with IIV3-HD and RIV vaccines in protecting older persons against LCI. RIV vaccine may reduce all-cause mortality when compared with other vaccines, but the evidence is uncertain. Differences in efficacy between influenza vaccines remain uncertain with very low to moderate certainty of evidence. PROSPERO REGISTRATION NUMBER: CRD42020177357.

A multiprovincial retrospective analysis of the incidence of myocarditis or pericarditis after mRNA vaccination compared to the incidence after SARS-CoV-2 infection.

Objective: To compare myocarditis/pericarditis risk after COVID-19 mRNA vaccination versus SARS-CoV-2 infection, and to assess if myocarditis/pericarditis risk varies by vaccine dosing interval. Methods: In this retrospective cohort study, we used linked databases in Quebec, Ontario, and British Columbia between January 26, 2020, and September 9, 2021. We included individuals aged 12 or above who received an mRNA vaccine as the second dose or were SARS-CoV-2-positive by RT-PCR. The outcome was hospitalization/emergency department visit for myocarditis/pericarditis within 21 days of exposure. We calculated age- and sex-stratified incidence ratios (IRs) of myocarditis/pericarditis following mRNA vaccination versus SARS-CoV-2 infection. We also calculated myocarditis/pericarditis incidence by vaccine type, homologous/heterologous schedule, and dosing interval. We pooled province-specific estimates using meta-analysis. Results: Following 18,860,817 mRNA vaccinations and 860,335 SARS-CoV-2 infections, we observed 686 and 160 myocarditis/pericarditis cases, respectively. Myocarditis/pericarditis incidence was lower after vaccination than infection (IR [BNT162b2/SARS-CoV-2], 0.14; 95%CI, 0.07-0.29; IR [mRNA-1273/SARS-CoV-2], 0.28; 95%CI, 0.20-0.39). Within the vaccinated cohort, myocarditis/pericarditis incidence was lower with longer dosing intervals; IR (56 or more days/15-30 days) was 0.28 (95%CI, 0.19-0.41) for BNT162b2 and 0.26 (95%CI, 0.18-0.38) for mRNA-1273. Conclusion: Myocarditis/pericarditis risk was lower after mRNA vaccination than SARS-CoV-2 infection, and with longer intervals between primary vaccine doses.

Effectiveness and Cost-Effectiveness of Self-Management Interventions for Adults Living with Heart Failure to Improve Patient-Important Outcomes: An Evidence Map of Randomized Controlled Trials.

Self-management interventions (SMIs) may enhance heart failure (HF) outcomes and address challenges associated with disease management. This study aims to review randomized evidence and identify knowledge gaps in SMIs for adult HF patients. Within the COMPAR-EU project, from 2010 to 2018, we conducted searches in the databases MEDLINE, CINAHL, Embase, Cochrane, and PsycINFO. We performed a descriptive analysis using predefined categories and developed an evidence map of randomized controlled trials (RCTs). We found 282 RCTs examining SMIs for HF patients, comparing two to four interventions, primarily targeting individual patients (97%) globally (34 countries, only 31% from an European country). These interventions involved support techniques such as information sharing (95%) and self-monitoring (62%), often through a mix of in-person and remote sessions (43%). Commonly assessed outcomes included quality of life, hospital admissions, mortality, exercise capacity, and self-efficacy. Few studies have focused on lower socio-economic or minority groups. Nurses (68%) and physicians (30%) were the primary providers, and most studies were at low risk of bias in generating a random sequence for participant allocation; however, the reporting was noticeably unclear of methods used to conceal the allocation process. Our analysis has revealed prevalent support techniques and delivery methods while highlighting methodological challenges. These findings provide valuable insights for researchers, clinicians, and policymakers striving to optimize SMIs for individuals living with HF.

A brief note on the common (fixed)-effect meta-analysis model.

Meta-analysis is a statistical method used to combine results from multiple studies, providing a quantitative summary of their findings. One of the fundamental decisions in conducting a meta-analysis is choosing an appropriate model to estimate the overall effect size and its CI. In this article, we focus on the common-effect (also referred to as the fixed-effect) model, and in a companion article, the random-effects model. These models are the two prevailing meta-analysis models employed in the literature. In this article, we outline the key assumption underlying the common-effect model, describe different common-effect methods (ie, inverse variance, Peto, and Mantel-Haenszel), and highlight characteristics of the meta-analysis that should be considered when selecting a method. Furthermore, we demonstrate the application of these methods to a dataset. Understanding the common-effect model is important for knowing when to use the model and how to interpret the overall effect size and its CI.

Methodological review of NMA bias concepts provides groundwork for the development of a list of concepts for potential inclusion in a new risk of bias tool for network meta-analysis (RoB NMA Tool).

INTRODUCTION: Network meta-analyses (NMAs) have gained popularity and grown in number due to their ability to provide estimates of the comparative effectiveness of multiple treatments for the same condition. The aim of this study is to conduct a methodological review to compile a preliminary list of concepts related to bias in NMAs. METHODS AND ANALYSIS: We included papers that present items related to bias, reporting or methodological quality, papers assessing the quality of NMAs, or method papers. We searched MEDLINE, the Cochrane Library and unpublished literature (up to July 2020). We extracted items related to bias in NMAs. An item was excluded if it related to general systematic review quality or bias and was included in currently available tools such as ROBIS or AMSTAR 2. We reworded items, typically structured as questions, into concepts (i.e. general notions). RESULTS: One hundred eighty-one articles were assessed in full text and 58 were included. Of these articles, 12 were tools, checklists or journal standards; 13 were guidance documents for NMAs; 27 were studies related to bias or NMA methods; and 6 were papers assessing the quality of NMAs. These studies yielded 99 items of which the majority related to general systematic review quality and biases and were therefore excluded. The 22 items we included were reworded into concepts specific to bias in NMAs. CONCLUSIONS: A list of 22 concepts was included. This list is not intended to be used to assess biases in NMAs, but to inform the development of items to be included in our tool.

HIGHLIGHTS: • Our research aimed to develop a preliminary list of concepts related to bias with the goal of developing the first tool for assessing the risk of bias in the results and conclusions of a network meta-analysis (NMA).• We followed the methodology proposed by Whiting (2017) and Sanderson (2007) for creating systematically developed lists of quality items, as a first step in the development of a risk of bias tool for network meta-analysis (RoB NMA Tool).• We included items related to biases in NMAs and excluded items that are equally applicable to all systematic reviews as they are covered by other tools (e.g. ROBIS, AMSTAR 2).• Fifty-seven studies were included generating 99 items, which when screened, yielded 22 included items. These items were then reworded into concepts in preparation for a Delphi process for further vetting by external experts.• A limitation of our study is the challenge in retrieving methods studies as methods collections are not regularly updated.

Accessibility of clinical study reports supporting medicine approvals: a cross-sectional evaluation.

OBJECTIVES: Clinical study reports (CSRs) are highly detailed documents that play a pivotal role in medicine approval processes. Though not historically publicly available, in recent years, major entities including the European Medicines Agency (EMA), Health Canada, and the US Food and Drug Administration (FDA) have highlighted the importance of CSR accessibility. The primary objective herein was to determine the proportion of CSRs that support medicine approvals available for public download as well as the proportion eligible for independent researcher request via the study sponsor. STUDY DESIGN AND SETTING: This cross-sectional study examined the accessibility of CSRs from industry-sponsored clinical trials whose results were reported in the FDA-authorized drug labels of the top 30 highest-revenue medicines of 2021. We determined (1) whether the CSRs were available for download from a public repository, and (2) whether the CSRs were eligible for request by independent researchers based on trial sponsors' data sharing policies. RESULTS: There were 316 industry-sponsored clinical trials with results presented in the FDA-authorized drug labels of the 30 sampled medicines. Of these trials, CSRs were available for public download from 70 (22%), with 37 available at EMA and 40 at Health Canada repositories. While pharmaceutical company platforms offered no direct downloads of CSRs, sponsors confirmed that CSRs from 183 (58%) of the 316 clinical trials were eligible for independent researcher request via the submission of a research proposal. Overall, 218 (69%) of the sampled clinical trials had CSRs available for public download and/or were eligible for request from the trial sponsor. CONCLUSION: CSRs were available from 69% of the clinical trials supporting regulatory approval of the 30 medicines sampled. However, only 22% of the CSRs were directly downloadable from regulatory agencies, the remaining required a formal application process to request access to the CSR from the study sponsor.

Self-Management Interventions for Adults Living with Type II Diabetes to Improve Patient-Important Outcomes: An Evidence Map.

Self-management interventions (SMIs) may be promising in the treatment of Diabetes Mellitus Type 2 (T2DM). However, accurate comparisons of their relative effectiveness are challenging, partly due to a lack of clarity and detail regarding the intervention content being evaluated. This study summarizes intervention components and characteristics in randomized controlled trials (RCTs) related to T2DM using a taxonomy for SMIs as a framework and identifies components that are insufficiently incorporated into the design of the intervention or insufficiently reported. Following evidence mapping methodology, we searched MEDLINE, CINAHL, Embase, Cochrane, and PsycINFO from 2010 to 2018 for randomized controlled trials (RCTs) on SMIs for T2DM. We used the terms 'self-management', 'adult' and 'T2DM' for content. For data extraction, we used an online platform based on the taxonomy for SMIs. Two independent reviewers assessed eligible references; one reviewer extracted data, and a second checked accuracy. We identified 665 RCTs for SMIs (34% US, 21% Europe) including 164,437 (median 123, range 10-14,559) adults with T2DM. SMIs highly differed in design and content, and characteristics such as mode of delivery, intensity, location and providers involved were poorly described. The majority of interventions aimed to improve clinical outcomes like HbA1c (83%), weight (53%), lipid profile (45%) or blood pressure (42%); 27% (also) targeted quality of life. Improved knowledge, health literacy, patient activation or satisfaction with care were hardly used as outcomes (<16%). SMIs most often used education (98%), self-monitoring (56%), goal-setting (48%) and skills training (42%) to improve outcomes. Management of emotions (17%) and shared decision-making (5%) were almost never mentioned. Although diabetes is highly prevalent in some minority groups, in only 13% of the SMIs, these groups were included. Our findings highlight the large heterogeneity that exists in the design of SMIs for T2DM and the way studies are reported, making accurate comparisons of their relative effectiveness challenging. In addition, SMIs pay limited attention to outcomes other than clinical, despite the importance attached to these outcomes by patients. More standardized and streamlined research is needed to better understand the effectiveness and cost-effectiveness of SMIs of T2DM and benefit patient care.

A 10-year update to the principles for clinical trial data sharing by pharmaceutical companies: perspectives based on a decade of literature and policies.

Data sharing is essential for promoting scientific discoveries and informed decision-making in clinical practice. In 2013, PhRMA/EFPIA recognised the importance of data sharing and supported initiatives to enhance clinical trial data transparency and promote scientific advancements. However, despite these commitments, recent investigations indicate significant scope for improvements in data sharing by the pharmaceutical industry. Drawing on a decade of literature and policy developments, this article presents perspectives from a multidisciplinary team of researchers, clinicians, and consumers. The focus is on policy and process updates to the PhRMA/EFPIA 2013 data sharing commitments, aiming to enhance the sharing and accessibility of participant-level data, clinical study reports, protocols, statistical analysis plans, lay summaries, and result publications from pharmaceutical industry-sponsored trials. The proposed updates provide clear recommendations regarding which data should be shared, when it should be shared, and under what conditions. The suggested improvements aim to develop a data sharing ecosystem that supports science and patient-centred care. Good data sharing principles require resources, time, and commitment. Notwithstanding these challenges, enhancing data sharing is necessary for efficient resource utilization, increased scientific collaboration, and better decision-making for patients and healthcare professionals.

Efficacy of sustained knowledge translation (KT) interventions in chronic disease management in older adults: systematic review and meta-analysis of complex interventions.

BACKGROUND: Chronic disease management (CDM) through sustained knowledge translation (KT) interventions ensures long-term, high-quality care. We assessed implementation of KT interventions for supporting CDM and their efficacy when sustained in older adults. METHODS: Design: Systematic review with meta-analysis engaging 17 knowledge users using integrated KT. ELIGIBILITY CRITERIA: Randomized controlled trials (RCTs) including adults (> 65 years old) with chronic disease(s), their caregivers, health and/or policy-decision makers receiving a KT intervention to carry out a CDM intervention for at least 12 months (versus other KT interventions or usual care). INFORMATION SOURCES: We searched MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials from each database's inception to March 2020. OUTCOME MEASURES: Sustainability, fidelity, adherence of KT interventions for CDM practice, quality of life (QOL) and quality of care (QOC). Data extraction, risk of bias (ROB) assessment: We screened, abstracted and appraised articles (Effective Practice and Organisation of Care ROB tool) independently and in duplicate. DATA SYNTHESIS: We performed both random-effects and fixed-effect meta-analyses and estimated mean differences (MDs) for continuous and odds ratios (ORs) for dichotomous data. RESULTS: We included 158 RCTs (973,074 participants [961,745 patients, 5540 caregivers, 5789 providers]) and 39 companion reports comprising 329 KT interventions, involving patients (43.2%), healthcare providers (20.7%) or both (10.9%). We identified 16 studies described as assessing sustainability in 8.1% interventions, 67 studies as assessing adherence in 35.6% interventions and 20 studies as assessing fidelity in 8.7% of the interventions. Most meta-analyses suggested that KT interventions improved QOL, but imprecisely (36 item Short-Form mental [SF-36 mental]: MD 1.11, 95% confidence interval [CI] [- 1.25, 3.47], 14 RCTs, 5876 participants, I2 = 96%; European QOL-5 dimensions: MD 0.01, 95% CI [- 0.01, 0.02], 15 RCTs, 6628 participants, I2 = 25%; St George's Respiratory Questionnaire: MD - 2.12, 95% CI [- 3.72, - 0.51] 44 12 RCTs, 2893 participants, I2 = 44%). KT interventions improved QOC (OR 1.55, 95% CI [1.29, 1.85], 12 RCTS, 5271 participants, I2 = 21%). CONCLUSIONS: KT intervention sustainability was infrequently defined and assessed. Sustained KT interventions have the potential to improve QOL and QOC in older adults with CDM. However, their overall efficacy remains uncertain and it varies by effect modifiers, including intervention type, chronic disease number, comorbidities, and participant age. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018084810.

Can routinely collected administrative data effectively be used to evaluate and validate endpoints used in breast cancer clinical trials? Protocol for a scoping review of the literature.

BACKGROUND: Randomized controlled trials (RCTs) are a critical component of evidence-based medicine and the evolution of patient care. However, the costs of conducting a RCT can be prohibitive. A promising approach toward reduction of costs and lessening of the burden of intensive and lengthy patient follow-up is the use of routinely collected healthcare data (RCHD), commonly called real-world data. We propose a scoping review to identify existing RCHD case definitions of breast cancer progression and survival and their diagnostic performance. METHODS: We will search MEDLINE, EMBASE, and CINAHL to identify primary studies of women with either early-stage or metastatic breast cancer, managed with established therapies, that evaluated the diagnostic accuracy of one or more RCHD-based case definitions or algorithms of disease progression (i.e., recurrence, progression-free survival, disease-free survival, or invasive disease-free survival) or survival (i.e., breast-cancer-free survival or overall survival) compared with a reference standard measure (e.g., chart review or a clinical trial dataset). Study characteristics and descriptions of algorithms will be extracted along with measures of the diagnostic accuracy of each algorithm (e.g., sensitivity, specificity, positive predictive value, negative predictive value), which will be summarized both descriptively and in structured figures/tables. DISCUSSION: Findings from this scoping review will be clinically meaningful for breast cancer researchers globally. Identification of feasible and accurate strategies to measure patient-important outcomes will potentially reduce RCT budgets as well as lessen the burden of intensive trial follow-up on patients. SYSTEMATIC REVIEW REGISTRATION: Open Science Framework ( https://doi.org/10.17605/OSF.IO/6D9RS ).

Protocol for a systematic review and meta-analysis of the diagnostic test accuracy of host and HPV DNA methylation in cervical cancer screening and management.

INTRODUCTION: Human papillomavirus (HPV) is necessary but not sufficient for cervical cancer development. During cervical carcinogenesis, methylation levels increase across host and HPV DNA. DNA methylation has been proposed as a test to diagnose cervical intraepithelial neoplasia (CIN); we present a protocol to evaluate the accuracy of methylation markers to detect high-grade CIN and cervical cancer. METHODS AND ANALYSIS: We will search electronic databases (Medline, Embase and Cochrane Library), from inception, to identify studies examining DNA methylation as a diagnostic marker for CIN or cervical cancer, in a cervical screening population. The primary outcome will be to assess the diagnostic test accuracy of host and HPV DNA methylation for high-grade CIN; the secondary outcomes will be to examine the accuracy of different methylation cut-off thresholds, and accuracy in high-risk HPV positive women. Our reference standard will be histology. We will perform meta-analyses using Cochrane guidelines for diagnostic test accuracy. We will use the number of true positives, false negatives, true negatives and false positives from individual studies. We will use the bivariate mixed effect model to estimate sensitivity and specificity with 95% CIs; we will employ different bivariate models to estimate sensitivity and specificity at different thresholds if sufficient data per threshold. For insufficient data, the hierarchical summary receiver operating curve model will be used to calculate a summary curve across thresholds. If there is interstudy and intrastudy variation in thresholds, we will use a linear mixed effects model to calculate the optimum threshold. If few studies are available, we will simplify models by assuming no correlation between sensitivity and specificity and perform univariate, random-effects meta-analysis. We will assess the quality of studies using QUADAS-2 and QUADAS-C. ETHICS AND DISSEMINATION: Ethical approval is not required. Results will be disseminated to academic beneficiaries, medical practitioners, patients and the public. PROSPERO REGISTRATION NUMBER: CRD42022299760.