Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): summary of findings and assessment of existing guidelines.

BACKGROUND: The SAVVY project aims to improve the analyses of adverse events (AEs) in clinical trials through the use of survival techniques appropriately dealing with varying follow-up times and competing events (CEs). This paper summarizes key features and conclusions from the various SAVVY papers. METHODS: Summarizing several papers reporting theoretical investigations using simulations and an empirical study including randomized clinical trials from several sponsor organizations, biases from ignoring varying follow-up times or CEs are investigated. The bias of commonly used estimators of the absolute (incidence proportion and one minus Kaplan-Meier) and relative (risk and hazard ratio) AE risk is quantified. Furthermore, we provide a cursory assessment of how pertinent guidelines for the analysis of safety data deal with the features of varying follow-up time and CEs. RESULTS: SAVVY finds that for both, avoiding bias and categorization of evidence with respect to treatment effect on AE risk into categories, the choice of the estimator is key and more important than features of the underlying data such as percentage of censoring, CEs, amount of follow-up, or value of the gold-standard. CONCLUSIONS: The choice of the estimator of the cumulative AE probability and the definition of CEs are crucial. Whenever varying follow-up times and/or CEs are present in the assessment of AEs, SAVVY recommends using the Aalen-Johansen estimator (AJE) with an appropriate definition of CEs to quantify AE risk. There is an urgent need to improve pertinent clinical trial reporting guidelines for reporting AEs so that incidence proportions or one minus Kaplan-Meier estimators are finally replaced by the AJE with appropriate definition of CEs.

Patient information leaflets for placebo-controlled surgical trials: a review of current practice and recommendations for developers.

INTRODUCTION: Informed consent for participation in an RCT is an important ethical and legal requirement. In placebo surgical trials, further issues are raised, and to date, this has not been explored. Patient information leaflets (PILs) are a core component of the informed consent process. This study aimed to investigate the key content of PILs for recently completed placebo-controlled trials of invasive procedures, including surgery, to highlight areas of good practice, identify gaps in information provision for trials of this type and provide recommendations for practice. METHODS: PILs were sought from trials included in a recent systematic review of placebo-controlled trials of invasive procedures, including surgery. Trial characteristics and data on surgical and placebo interventions under evaluation were extracted. Directed content analysis was applied, informed by published regulatory and good practice guidance on PIL content and existing research on placebo-controlled surgical trials. Results were analysed using descriptive statistics and presented as a narrative summary. RESULTS: Of the 62 eligible RCTs, authors of 59 trials were contactable and 14 PILs were received for analysis. At least 50% of all PILs included content on general trial design. Explanations of how the placebo differs or is similar to the surgical intervention (i.e. fidelity) were reported in 6 (43%) of the included PILs. Over half (57%) of the PILs included information on the potential therapeutic benefits of the surgical intervention. One (7%) included information on potential indirect therapeutic benefits from invasive components of the placebo. Five (36%) presented the known risks of the placebo intervention, whilst 8 (57%) presented information on the known risks of the surgical intervention. A range of terms was used across the PILs to describe the placebo component, including 'control', 'mock' and 'sham'. CONCLUSION: Developers of PILs for placebo-controlled surgical trials should carefully consider the use of language (e.g. sham, mock), be explicit about how the placebo differs (or is similar) to the surgical intervention and provide balanced presentations of potential benefits and risks of the surgical intervention separately from the placebo. Further research is required to determine optimal approaches to design and deliver this information for these trials.

Considerations for using potential surrogate endpoints in cancer screening trials.

The requirement of large-scale expensive cancer screening trials spanning decades creates considerable barriers to the development, commercialisation, and implementation of novel screening tests. One way to address these problems is to use surrogate endpoints for the ultimate endpoint of interest, cancer mortality, at an earlier timepoint. This Review aims to highlight the issues underlying the choice and use of surrogate endpoints for cancer screening trials, to propose criteria for when and how we might use such endpoints, and to suggest possible candidates. We present the current landscape and challenges, and discuss lessons and shortcomings from the therapeutic trial setting. It is hugely challenging to validate a surrogate endpoint, even with carefully designed clinical studies. Nevertheless, we consider whether there are candidates that might satisfy the requirements defined by research and regulatory bodies.

The reporting quality and spin of randomized controlled trials of endometriosis pain: Methodological study based on CONSORT extension on abstracts.

OBJECTIVE: To assess the reporting quality of published RCT abstracts regarding patients with endometriosis pelvic pain and investigate the prevalence and characteristics of spin in these abstracts. METHODS: PubMed and Scopus were searched for RCT abstracts addressing endometriosis pelvic pain published from January 1st, 2010 to December 1st, 2023.The reporting quality of RCT abstracts was assessed using the CONSORT statement for abstracts. Additionally, spin was evaluated in the results and conclusions section of the abstracts, defined as the misleading reporting of study findings to emphasize the perceived benefits of an intervention or to confound readers from statistically non-significant results. Assessing factors affecting the reporting quality and spin existence, linear and logistic regression was used, respectively. RESULTS: A total of 47 RCT abstracts were included. Out of 16 checklist items, only three items including objective, intervention and conclusions were sufficiently reported in the most abstracts (more than 95%), and none of the abstracts presented precise data as required by the CONSORT-A guidelines. In the reporting quality of material and method section, trial design, type of randomization, the generation of random allocation sequences, the allocation concealment and blinding were most items identified that were suboptimal. The total score for the quality varied between 5 and 15 (mean: 9.59, SD: 3.03, median: 9, IQR: 5). Word count (beta = 0.015, p-value = 0.005) and publishing in open-accessed journals (beta = 2.023, p-value = 0.023) were the significant factors that affecting the reporting quality. Evaluating spin within each included paper, we found that 18 (51.43%) papers had statistically non-significant results. From these studies, 12 (66.66%) had spin in both results and conclusion sections. Furthermore, the spin intensity increased during 2010-2023 and 38.29% of abstracts had spin in both results and conclusion sections. CONCLUSION: Overall poor adherence to CONSORT-A was observed, with spin detected in several RCTs featuring non-significant primary endpoints in obstetrics and gynecology literature.

Using Bayesian statistics in confirmatory clinical trials in the regulatory setting: a tutorial review.

Bayesian statistics plays a pivotal role in advancing medical science by enabling healthcare companies, regulators, and stakeholders to assess the safety and efficacy of new treatments, interventions, and medical procedures. The Bayesian framework offers a unique advantage over the classical framework, especially when incorporating prior information into a new trial with quality external data, such as historical data or another source of co-data. In recent years, there has been a significant increase in regulatory submissions using Bayesian statistics due to its flexibility and ability to provide valuable insights for decision-making, addressing the modern complexity of clinical trials where frequentist trials are inadequate. For regulatory submissions, companies often need to consider the frequentist operating characteristics of the Bayesian analysis strategy, regardless of the design complexity. In particular, the focus is on the frequentist type I error rate and power for all realistic alternatives. This tutorial review aims to provide a comprehensive overview of the use of Bayesian statistics in sample size determination, control of type I error rate, multiplicity adjustments, external data borrowing, etc., in the regulatory environment of clinical trials. Fundamental concepts of Bayesian sample size determination and illustrative examples are provided to serve as a valuable resource for researchers, clinicians, and statisticians seeking to develop more complex and innovative designs.

Transparency, reproducibility, and replicability of pharmacoepidemiology studies in a distributed network environment.

PURPOSE: Our objective is to describe how the U.S. Food and Drug Administration (FDA)'s Sentinel System implements best practices to ensure trust in drug safety studies using real-world data from disparate sources. METHODS: We present a stepwise schematic for Sentinel's data harmonization, data quality check, query design and implementation, and reporting practices, and describe approaches to enhancing the transparency, reproducibility, and replicability of studies at each step. CONCLUSIONS: Each Sentinel data partner converts its source data into the Sentinel Common Data Model. The transformed data undergoes rigorous quality checks before it can be used for Sentinel queries. The Sentinel Common Data Model framework, data transformation codes for several data sources, and data quality assurance packages are publicly available. Designed to run against the Sentinel Common Data Model, Sentinel's querying system comprises a suite of pre-tested, parametrizable computer programs that allow users to perform sophisticated descriptive and inferential analysis without having to exchange individual-level data across sites. Detailed documentation of capabilities of the programs as well as the codes and information required to execute them are publicly available on the Sentinel website. Sentinel also provides public trainings and online resources to facilitate use of its data model and querying system. Its study specifications conform to established reporting frameworks aimed at facilitating reproducibility and replicability of real-world data studies. Reports from Sentinel queries and associated design and analytic specifications are available for download on the Sentinel website. Sentinel is an example of how real-world data can be used to generate regulatory-grade evidence at scale using a transparent, reproducible, and replicable process.

The quality of reporting in case reports of permanent neonatal diabetes mellitus: a cross-sectional study.

BACKGROUND: Although randomized trials and systematic reviews provide the best evidence to guide medical practice, many permanent neonatal diabetes mellitus (PNDM) studies have been published as case reports. However, the quality of these studies has not been assessed. The purpose of this study was to assess the extent to which the current case reports for PNDM comply with the Case Report (CARE) guidelines and to explore variables associated with the reporting. METHOD: Six English and four Chinese databases were searched from their inception to December 2022 for PNDM case reports. The 23 items CARE checklist was used to measure reporting quality. Primary outcome was the adherence rate of each CARE item and second outcome was total reporting score for each included PNDM case report. Linear and logistic regression analyses were used to examine the connection between five pre-specified predictor variables and the reporting quality. The predictor variables were impact factor of the published journal (<3.4 vs. ≥3.4, categorized according to the median), funding (yes vs. no), language (English vs. other language), published journal type (general vs. special) and year of publication (>2013 vs. ≤ 2013). RESULT: In total, 105 PNDM case reports were included in this study. None of the 105 PNDM case reports fulfilled all 23 items of the CARE checklist. The response rate of 11 items were under 50%, including prognostic characteristics presentation (0%), patient perspective interpretation (0%), diagnostic challenges statement (2.9%), clinical course summary (21.0%), diagnostic reasoning statement (22.9%), title identification (24.8%), case presentation (33.3%), disease history description (34.3%), strengths and limitations explanation (41.0%), informed consent statement (45.7%), and lesson elucidation (47.6%). This study identified that the PNDM case reports published in higher impact factor journals were statistically associated with a higher reporting quality. CONCLUSION: The reporting of case reports for PNDM is generally poor. As a result, this information may be misleading to providers, and the clinical applications may be detrimental to patient care. To improve reporting quality, journals should encourage strict adherence to the CARE guidelines.

Reporting Standards for Complication Studies of Radiation Therapy for Pediatric Cancer: Lessons From PENTEC.

The major aim of Pediatric Normal Tissue Effects in the Clinic (PENTEC) was to synthesize quantitative published dose/-volume/toxicity data in pediatric radiation therapy. Such systematic reviews are often challenging because of the lack of standardization and difficulty of reporting outcomes, clinical factors, and treatment details in journal articles. This has clinical consequences: optimization of treatment plans must balance between the risks of toxicity and local failure; counseling patients and their parents requires knowledge of the excess risks encountered after a specific treatment. Studies addressing outcomes after pediatric radiation therapy are particularly challenging because: (a) survivors may live for decades after treatment, and the latency time to toxicity can be very long; (b) children's maturation can be affected by radiation, depending on the developmental status of the organs involved at time of treatment; and (c) treatment regimens frequently involve chemotherapies, possibly modifying and adding to the toxicity of radiation. Here we discuss: basic reporting strategies to account for the actuarial nature of the complications; the reporting of modeling of abnormal development; and the need for standardized, comprehensively reported data sets and multivariate models (ie, accounting for the simultaneous effects of radiation dose, age, developmental status at time of treatment, and chemotherapy dose). We encourage the use of tools that facilitate comprehensive reporting, for example, electronic supplements for journal articles. Finally, we stress the need for clinicians to be able to trust artificial intelligence models of outcome of radiation therapy, which requires transparency, rigor, reproducibility, and comprehensive reporting. Adopting the reporting methods discussed here and in the individual PENTEC articles will increase the clinical and scientific usefulness of individual reports and associated pooled analyses.

Misstatements, misperceptions, and mistakes in controlling for covariates in observational research.

We discuss 12 misperceptions, misstatements, or mistakes concerning the use of covariates in observational or nonrandomized research. Additionally, we offer advice to help investigators, editors, reviewers, and readers make more informed decisions about conducting and interpreting research where the influence of covariates may be at issue. We primarily address misperceptions in the context of statistical management of the covariates through various forms of modeling, although we also emphasize design and model or variable selection. Other approaches to addressing the effects of covariates, including matching, have logical extensions from what we discuss here but are not dwelled upon heavily. The misperceptions, misstatements, or mistakes we discuss include accurate representation of covariates, effects of measurement error, overreliance on covariate categorization, underestimation of power loss when controlling for covariates, misinterpretation of significance in statistical models, and misconceptions about confounding variables, selecting on a collider, and p value interpretations in covariate-inclusive analyses. This condensed overview serves to correct common errors and improve research quality in general and in nutrition research specifically.

Retrospective and prospective study designs.

The labels "retrospective" and "prospective" strongly connote study quality, often favouring prospective studies. However, three definitions of these terms exist, each suggesting distinct methodological limitations. In this review, we summarize and evaluate these definitions. Caution is warranted when labeling a study "retrospective": This label should only be used when implying a risk of recall bias, which can only occur in retrospective data collection. Generally, assessing random and systematic errors is necessary to appraise study quality rather than relying on ambiguous labels.

Using Qualitative Questionnaires in Medical Education Research.

Most students in Health Profession Education courses are new to the world of qualitative research. Faced with the challenge of designing a research project, they are often drawn towards using the questionnaire as a data collection method, commonly assuming that utilising open-ended questions alone constitutes qualitative research design. Designing questionnaires that meet the standards of rigour is challenging, and this common assumption reflects inexperience with and misunderstandings of qualitative ontology, as well as the lack of methodological literature on designing and developing qualitative questionnaires. This paper is written with research supervisors as well as students in mind, as it is aimed to help elucidate the decision-making process and the justification for using a qualitative questionnaire. Drawing upon examples of research conducted by our students, and the wider literature, we demonstrate how qualitative questionnaires can produce rich and meaningful findings when they (1) prioritise qualitative research values, and (2) follow a rigorous design process when the questionnaire is developed. We conclude by offering a simple framework for developing rigorous qualitative questionnaires to those who may consider using this approach.

Identifying Existing Guidelines, Frameworks, Checklists, and Recommendations for Implementing Patient-Reported Outcome Measures: Protocol for a Scoping Review.

BACKGROUND: Implementing patient-reported outcome measures (PROMs) to measure and evaluate health outcomes is increasing worldwide. Along with this emerging trend, it is important to identify which guidelines, frameworks, checklists, and recommendations exist, and if and how they have been used in implementing PROMs, especially in clinical quality registries (CQRs). OBJECTIVE: This review aims to identify existing publications, as well as publications that discuss the application of actual guidelines, frameworks, checklists, and recommendations on PROMs' implementation for various purposes such as clinical trials, clinical practice, and CQRs. In addition, the identified publications will be used to guide the development of a new guideline for PROMs' implementation in CQRs, which is the aim of the broader project. METHODS: A literature search of the databases MEDLINE, Embase, CINAHL, PsycINFO, and Cochrane Central Register of Controlled Trials will be conducted since the inception of the databases, in addition to using Google Scholar and gray literature to identify literature for the scoping review. Predefined inclusion and exclusion criteria will be used for all phases of screening. Existing publications of guidelines, frameworks, checklists, recommendations, and publications discussing the application of those methodologies for implementing PROMs in clinical trials, clinical practice, and CQRs will be included in the final review. Data relating to bibliographic information, aim, the purpose of PROMs use (clinical trial, practice, or registries), name of guideline, framework, checklist and recommendations, the rationale for development, and their purpose and implications will be extracted. Additionally, for publications of actual methodologies, aspects or domains of PROMs' implementation will be extracted. A narrative synthesis of included publications will be conducted. RESULTS: The electronic database searches were completed in March 2024. Title and abstract screening, full-text screening, and data extraction will be completed in May 2024. The review is expected to be completed by the end of August 2024. CONCLUSIONS: The findings of this scoping review will provide evidence on any existing methodologies and tools for PROMs' implementation in clinical trials, clinical practice, and CQRs. It is anticipated that the publications will help us guide the development of a new guideline for PROMs' implementation in CQRs. TRIAL REGISTRATION: PROSPERO CRD42022366085; https://tinyurl.com/bdesk98x. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52572.

Adaptive clinical trials in surgery: A scoping review of methodological and reporting quality.

IMPORTANCE: Adaptive surgical trials are scarce, but adopting these methods may help elevate the quality of surgical research when large-scale RCTs are impractical. OBJECTIVE: Randomized-controlled trials (RCTs) are the gold standard for evidence-based healthcare. Despite an increase in the number of RCTs, the number of surgical trials remains unchanged. Adaptive clinical trials can streamline trial design and time to trial reporting. The advantages identified for ACTs may help to improve the quality of future surgical trials. We present a scoping review of the methodological and reporting quality of adaptive surgical trials. EVIDENCE REVIEW: We performed a search of Ovid, Web of Science, and Cochrane Collaboration for all adaptive surgical RCTs performed from database inception to October 12, 2023. We included any published trials that had at least one surgical arm. All review and abstraction were performed in duplicate. Risk of bias (RoB) was assessed using the RoB 2.0 instrument and reporting quality was evaluated using CONSORT ACE 2020. All results were analyzed using descriptive methods. FINDINGS: Of the 1338 studies identified, six trials met inclusion criteria. Trials were performed in cardiothoracic, oral, orthopedic, and urological surgery. The most common type of adaptive trial was group sequential design with pre-specified interim analyses planned for efficacy, futility, and/or sample size re-estimation. Two trials did use statistical simulations. Our risk of bias evaluation identified a high risk of bias in 50% of included trials. Reporting quality was heterogeneous regarding trial design and outcome assessment and details in relation to randomization and blinding concealment. CONCLUSION AND RELEVANCE: Surgical trialists should consider implementing adaptive components to help improve patient recruitment and reduce trial duration. Reporting of future adaptive trials must adhere to existing CONSORT ACE 2020 guidelines. Future research is needed to optimize standardization of adaptive methods across medicine and surgery.

Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting.

Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aß]40, Aß42, Aß42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.