Interval breast cancer rates for tomosynthesis vs mammography population screening: a systematic review and meta-analysis of prospective studies.

OBJECTIVES: We aimed to synthesise evidence from prospective studies of digital breast tomosynthesis (DBT) screening to assess its effectiveness compared to digital mammography (DM). Specifically, we examined whether DBT reduces interval cancer rates (ICRs) in population breast cancer screening. MATERIALS AND METHODS: We performed a systematic review and meta-analysis of DBT screening studies (identified from January 2013 to March 2024). We included both RCTs and non-randomised prospective studies that used an independent comparison for our primary outcome ICRs. The risk of bias was assessed with QUADAS-2. We compared the ICR, cancer detection rate (CDR), and recall rate of DBT and DM screening using random effects meta-analysis models. Subgroup analyses estimated outcomes by study design. Sensitivity analyses estimated absolute effects from relative effects. RESULTS: Ten prospective studies (three RCTs, seven non-randomised) were eligible; all had a low risk of bias. There were 205,245 DBT-screened and 306,476 DM-screened participants with follow-up for interval cancer data. The pooled absolute ICR did not significantly differ between DBT and DM: -2.92 per 10,000 screens (95% CI: -6.39 to 0.54); however subsequent subgroup analysis indicated certain study designs may have biased this ICR estimate. Pooled ICR from studies that only sampled groups from the same time and region indicated DBT led to 5.50 less IC per 10,000 screens (95% CI: -9.47 to -1.54). Estimates from subgroup analysis that compared randomised and non-randomised trials did not significantly differ. CONCLUSION: This meta-analysis provides suggestive evidence that DBT decreases ICR relative to DM screening; further evidence is needed to reduce uncertainty regarding ICR differences between DBT and DM. KEY POINTS: Question Does DBT have long-term benefits over standard DM? Finding We find suggestive evidence in our primary analysis and stronger evidence in a follow-up analysis that DBT reduces interval cancers. Clinical relevance This meta-analysis provides the first indication that DBT may detect additional cancers that are clinically meaningful, based on suggestive evidence of a reduction in ICR. This finding does not preclude the simultaneous possibility of overdiagnosis.

Data sharing policies across health research globally: Cross-sectional meta-research study.

BACKGROUND: Data sharing improves the value, synthesis, and integrity of research, but rates are low. Data sharing might be improved if data sharing policies were prominent and actionable at every stage of research. We aimed to systematically describe the epidemiology of data sharing policies across the health research lifecycle. METHODS: This was a cross-sectional analysis of the data sharing policies of the largest health research funders, all national ethics committees, all clinical trial registries, the highest-impact medical journals, and all medical research data repositories. Stakeholders' official websites, online reports, and other records were reviewed up to May 2022. The strength and characteristics of their data sharing policies were assessed, including their policies on data sharing intention statements (a.k.a. data accessibility statements) and on data sharing specifically for coronavirus disease studies. Data were manually extracted in duplicate, and policies were descriptively analysed by their stakeholder and characteristics. RESULTS: Nine hundred and thirty-five eligible stakeholders were identified: 110 funders, 124 ethics committees, 18 trial registries, 273 journals, and 410 data repositories. Data sharing was required by 41% (45/110) of funders, no ethics committees or trial registries, 19% (52/273) of journals and 6% (24/410) of data repositories. Among funder types, a higher proportion of private (63%, 35/55) and philanthropic (67%, 4/6) funders required data sharing than public funders (12%, 6/49). CONCLUSION: Data sharing requirements, and even recommendations, were insufficient across health research. Where data sharing was required or recommended, there was limited guidance on implementation. We describe multiple pathways to improve the implementation of data sharing. Public funders and ethics committees are two stakeholders with particularly important untapped opportunities.

A survey of experts to identify methods to detect problematic studies: stage 1 of the INveStigating ProblEmatic Clinical Trials in Systematic Reviews project.

BACKGROUND AND OBJECTIVE: Randomized controlled trials (RCTs) inform health-care decisions. Unfortunately, some published RCTs contain false data, and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesize all RCTs which have been conducted on a given topic. This means that any of these 'problematic studies' are likely to be included, but there are no agreed methods for identifying them. The INveStigating ProblEmatic Clinical Trials in Systematic Reviews (INSPECT-SR) project is developing a tool to identify problematic RCTs in systematic reviews of health care-related interventions. The tool will guide the user through a series of 'checks' to determine a study's authenticity. The first objective in the development process is to assemble a comprehensive list of checks to consider for inclusion. METHODS: We assembled an initial list of checks for assessing the authenticity of research studies, with no restriction to RCTs, and categorized these into five domains: Inspecting results in the paper; Inspecting the research team; Inspecting conduct, governance, and transparency; Inspecting text and publication details; Inspecting the individual participant data. We implemented this list as an online survey, and invited people with expertise and experience of assessing potentially problematic studies to participate through professional networks and online forums. Participants were invited to provide feedback on the checks on the list, and were asked to describe any additional checks they knew of, which were not featured in the list. RESULTS: Extensive feedback on an initial list of 102 checks was provided by 71 participants based in 16 countries across five continents. Fourteen new checks were proposed across the five domains, and suggestions were made to reword checks on the initial list. An updated list of checks was constructed, comprising 116 checks. Many participants expressed a lack of familiarity with statistical checks, and emphasized the importance of feasibility of the tool. CONCLUSION: A comprehensive list of trustworthiness checks has been produced. The checks will be evaluated to determine which should be included in the INSPECT-SR tool. PLAIN LANGUAGE SUMMARY: Systematic reviews draw upon evidence from randomized controlled trials (RCTs) to find out whether treatments are safe and effective. The conclusions from systematic reviews are often very influential, and inform both health-care policy and individual treatment decisions. However, it is now clear that the results of many published RCTs are not genuine. In some cases, the entire study may have been fabricated. It is not usual for the veracity of RCTs to be questioned during the process of compiling a systematic review. As a consequence, these "problematic studies" go unnoticed, and are allowed to contribute to the conclusions of influential systematic reviews, thereby influencing patient care. This prompts the question of how these problematic studies could be identified. In this study, we created an extensive list of checks that could be performed to try to identify these studies. We started by assembling a list of checks identified in previous research, and conducting a survey of experts to ask whether they were aware of any additional methods, and to give feedback on the list. As a result, a list of 116 potential "trustworthiness checks" was created. In subsequent research, we will evaluate these checks to see which should be included in a tool, INveStigating ProblEmatic Clinical Trials in Systematic Reviews, which can be used to detect problematic studies.

Protocol for the application of single-cell damage in murine intestinal organoid models.

Spatially defined organoid damage enables the study of cellular repair processes. However, capturing dynamic events in living tissues is technically challenging. Here, we present a protocol for the application of single-cell damage in intestinal organoid models. We describe steps for isolating and cultivating murine colon organoids, lentivirus generation and transduction of organoids, single-cell ablation by a femtosecond laser, and follow-up imaging analysis. We provide examples for the image acquisition pipeline of dynamic processes in organoids using a confocal microscope. For complete details on the use and execution of this protocol, please refer to Donath et al.1,2.

Development of the individual participant data integrity tool for assessing the integrity of randomised trials using individual participant data.

Increasing integrity concerns in medical research have prompted the development of tools to detect untrustworthy studies. Existing tools primarily assess published aggregate data (AD), though scrutiny of individual participant data (IPD) is often required to detect trustworthiness issues. Thus, we developed the IPD Integrity Tool for detecting integrity issues in randomised trials with IPD available. This manuscript describes the development of this tool. We conducted a literature review to collate and map existing integrity items. These were discussed with an expert advisory group; agreed items were included in a standardised tool and automated where possible. We piloted this tool in two IPD meta-analyses (including 116 trials) and conducted preliminary validation checks on 13 datasets with and without known integrity issues. We identified 120 integrity items: 54 could be conducted using AD, 48 required IPD, and 18 were possible with AD, but more comprehensive with IPD. An initial reduced tool was developed through consensus involving 13 advisors, featuring 11 AD items across four domains, and 12 IPD items across eight domains. The tool was iteratively refined throughout piloting and validation. All studies with known integrity issues were accurately identified during validation. The final tool includes seven AD domains with 13 items and eight IPD domains with 18 items. The quality of evidence informing healthcare relies on trustworthy data. We describe the development of a tool to enable researchers, editors, and others to detect integrity issues using IPD. Detailed instructions for its application are published as a complementary manuscript in this issue.

The Individual Participant Data Integrity Tool for assessing the integrity of randomised trials.

Increasing concerns about the trustworthiness of research have prompted calls to scrutinise studies' Individual Participant Data (IPD), but guidance on how to do this was lacking. To address this, we developed the IPD Integrity Tool to screen randomised controlled trials (RCTs) for integrity issues. Development of the tool involved a literature review, consultation with an expert advisory group, piloting on two IPD meta-analyses (including 73 trials with IPD), preliminary validation on 13 datasets with and without known integrity issues, and evaluation to inform iterative refinements. The IPD Integrity Tool comprises 31 items (13 study-level, 18 IPD-specific). IPD-specific items are automated where possible, and are grouped into eight domains, including unusual data patterns, baseline characteristics, correlations, date violations, patterns of allocation, internal and external inconsistencies, and plausibility of data. Users rate each item as having either no issues, some/minor issue(s), or many/major issue(s) according to decision rules, and justification for each rating is recorded. Overall, the tool guides decision-making by determining whether a trial has no concerns, some concerns requiring further information, or major concerns warranting exclusion from evidence synthesis or publication. In our preliminary validation checks, the tool accurately identified all five studies with known integrity issues. The IPD Integrity Tool enables users to assess the integrity of RCTs via examination of IPD. The tool may be applied by evidence synthesists, editors and others to determine whether an RCT should be considered sufficiently trustworthy to contribute to the evidence base that informs policy and practice.

Initial Oxygen Concentration for the Resuscitation of Infants Born at Less Than 32 Weeks' Gestation: A Systematic Review and Individual Participant Data Network Meta-Analysis.

Importance: Resuscitation with lower fractional inspired oxygen (FiO2) reduces mortality in term and near-term infants but the impact of this practice on very preterm infants is unclear. Objective: To evaluate the relative effectiveness of initial FiO2 on reducing mortality, severe morbidities, and oxygen saturations (SpO2) in preterm infants born at less than 32 weeks' gestation using network meta-analysis (NMA) of individual participant data (IPD). Data Sources: MEDLINE, Embase, CENTRAL, CINAHL, ClinicalTrials.gov, and WHO ICTRP from 1980 to October 10, 2023. Study Selection: Eligible studies were randomized clinical trials enrolling infants born at less than 32 weeks' gestation comparing at least 2 initial oxygen concentrations for delivery room resuscitation, defined as either low (≤0.3), intermediate (0.5-0.65), or high (≥0.90) FiO2. Data Extraction and Synthesis: Investigators from eligible studies were invited to provide IPD. Data were processed and checked for quality and integrity. One-stage contrast-based bayesian IPD-NMA was performed with noninformative priors and random effects and adjusted for key covariates. Main Outcomes and Measures: The primary outcome was all-cause mortality at hospital discharge. Secondary outcomes were morbidities of prematurity and SpO2 at 5 minutes. Results: IPD were provided for 1055 infants from 12 of the 13 eligible studies (2005-2019). Resuscitation with high (≥0.90) initial FiO2 was associated with significantly reduced mortality compared to low (≤0.3) (odds ratio [OR], 0.45; 95% credible interval [CrI], 0.23-0.86; low certainty) and intermediate (0.5-0.65) FiO2 (OR, 0.34; 95% CrI, 0.11-0.99; very low certainty). High initial FiO2 had a 97% probability of ranking first to reduce mortality. The effects on other morbidities were inconclusive. Conclusions and Relevance: High initial FiO2 (≥0.90) may be associated with reduced mortality in preterm infants born at less than 32 weeks' gestation compared to low initial FiO2 (low certainty). High initial FiO2 is possibly associated with reduced mortality compared to intermediate initial FiO2 (very low certainty) but more evidence is required.

A collaborative network trial to evaluate the effectiveness of implementation strategies to maximize adoption of a school-based healthy lunchbox program: a study protocol.

Introduction: An important impediment to the large-scale adoption of evidence-based school nutrition interventions is the lack of evidence on effective strategies to implement them. This paper describes the protocol for a "Collaborative Network Trial" to support the simultaneous testing of different strategies undertaken by New South Wales Local Health Districts to facilitate the adoption of an effective school-based healthy lunchbox program ('SWAP IT'). The primary objective of this study is to assess the effectiveness of different implementation strategies to increase school adoption of the SWAP across New South Wales Local Health Districts. Methods: Within a Master Protocol framework, a collaborative network trial will be undertaken. Independent randomized controlled trials to test implementation strategies to increase school adoption of SWAP IT within primary schools in 10 different New South Wales Local Health Districts will occur. Schools will be randomly allocated to either the intervention or control condition. Schools allocated to the intervention group will receive a combination of implementation strategies. Across the 10 participating Local Health Districts, six broad strategies were developed and combinations of these strategies will be executed over a 6 month period. In six districts an active comparison group (containing one or more implementation strategies) was selected. The primary outcome of the trial will be adoption of SWAP IT, assessed via electronic registration records captured automatically following online school registration to the program. The primary outcome will be assessed using logistic regression analyses for each trial. Individual participant data component network meta-analysis, under a Bayesian framework, will be used to explore strategy-covariate interactions; to model additive main effects (separate effects for each component of an implementation strategy); two way interactions (synergistic/antagonistic effects of components), and full interactions. Discussion: The study will provide rigorous evidence of the effects of a variety of implementation strategies, employed in different contexts, on the adoption of a school-based healthy lunchbox program at scale. Importantly, it will also provide evidence as to whether health service-centered, collaborative research models can rapidly generate new knowledge and yield health service improvements. Clinical trial registration: This trial is registered prospectively with the Australian New Zealand Clinical Trials Registry (ACTRN12623000558628).

A survey of experts to identify methods to detect problematic studies: Stage 1 of the INSPECT-SR Project.

Background: Randomised controlled trials (RCTs) inform healthcare decisions. Unfortunately, some published RCTs contain false data, and some appear to have been entirely fabricated. Systematic reviews are performed to identify and synthesise all RCTs which have been conducted on a given topic. This means that any of these 'problematic studies' are likely to be included, but there are no agreed methods for identifying them. The INSPECT-SR project is developing a tool to identify problematic RCTs in systematic reviews of healthcare-related interventions. The tool will guide the user through a series of 'checks' to determine a study's authenticity. The first objective in the development process is to assemble a comprehensive list of checks to consider for inclusion. Methods: We assembled an initial list of checks for assessing the authenticity of research studies, with no restriction to RCTs, and categorised these into five domains: Inspecting results in the paper; Inspecting the research team; Inspecting conduct, governance, and transparency; Inspecting text and publication details; Inspecting the individual participant data. We implemented this list as an online survey, and invited people with expertise and experience of assessing potentially problematic studies to participate through professional networks and online forums. Participants were invited to provide feedback on the checks on the list, and were asked to describe any additional checks they knew of, which were not featured in the list. Results: Extensive feedback on an initial list of 102 checks was provided by 71 participants based in 16 countries across five continents. Fourteen new checks were proposed across the five domains, and suggestions were made to reword checks on the initial list. An updated list of checks was constructed, comprising 116 checks. Many participants expressed a lack of familiarity with statistical checks, and emphasized the importance of feasibility of the tool. Conclusions: A comprehensive list of trustworthiness checks has been produced. The checks will be evaluated to determine which should be included in the INSPECT-SR tool.