Robust analysis of stepped wedge trials using composite likelihood models.

Stepped wedge trials (SWTs) are a type of cluster randomized trial that involve repeated measures on clusters and design-induced confounding between time and treatment. Although mixed models are commonly used to analyze SWTs, they are susceptible to misspecification particularly for cluster-longitudinal designs such as SWTs. Mixed model estimation leverages both "horizontal" or within-cluster information and "vertical" or between-cluster information. To use horizontal information in a mixed model, both the mean model and correlation structure must be correctly specified or accounted for, since time is confounded with treatment and measurements are likely correlated within clusters. Alternative non-parametric methods have been proposed that use only vertical information; these are more robust because between-cluster comparisons in a SWT preserve randomization, but these non-parametric methods are not very efficient. We propose a composite likelihood method that focuses on vertical information, but has the flexibility to recover efficiency by using additional horizontal information. We compare the properties and performance of various methods, using simulations based on COVID-19 data and a demonstration of application to the LIRE trial. We found that a vertical composite likelihood model that leverages baseline data is more robust than traditional methods, and more efficient than methods that use only vertical information. We hope that these results demonstrate the potential value of model-based vertical methods for SWTs with a large number of clusters, and that these new tools are useful to researchers who are concerned about misspecification of traditional models.

Statistical Analysis Methods and Reporting of Patient-Reported Outcomes in Randomized Controlled Trials for Cancer Conducted in Japan: A Systematic Review.

The Setting International Standards in Analyzing Patient-Reported Outcomes and Quality of Life Endpoints Data (SISAQOL) initiative was established in 2016 to assess the quality and standardization of patient-reported outcomes (PRO) data analysis in randomized controlled trials (RCTs) on advanced breast cancer. The initiative identified deficiencies in PRO data reporting, including nonstandardized methods for handling missing data. This study evaluated the reporting of health-related quality of life (HRQOL) in Japanese cancer RCTs to provide insights into the state of PRO reporting in Japan. The study reviewed PubMed articles published from 2010 to 2018. Eligible studies included Japanese cancer RCTs with ≥50 adult patients (≥50% were Japanese) with solid tumors receiving anticancer treatments. The evaluation criteria included clarity of the HRQOL hypotheses, multiplicity testing, primary analysis methods, and reporting of clinically meaningful differences. Twenty-seven HRQOL trials were identified. Only 15% provided a clear HRQOL hypothesis, and 63% examined multiple HRQOL domains without adjusting for multiplicity. Model-based methods were the most common statistical methods for the primary HRQOL analysis. Only 22% of the trials explicitly reported clinically meaningful differences in HRQOL. Baseline assessments were reported in most trials, but only 26% reported comparisons between the treatment groups. HRQOL analysis was based on the intention-to-treat population in 19% of the trials, and 74% reported compliance at follow-up; however, 41% did not specify how missing values were handled. Although the rates of reporting clinical hypotheses and clinically meaningful differences were relatively low, the current state of HRQOL evaluation in the Japanese cancer RCT appears comparable to that of previous studies.

Efficacy and safety of omega-3 fatty acids supplementation for anxiety symptoms: a systematic review and dose-response meta-analysis of randomized controlled trials.

BACKGROUND/OBJECTIVES: There is uncertainty about the optimum dose of omega-3 fatty acids for anxiety symptoms. We aimed to find the dose-dependent effect of omega-3 supplementation on anxiety symptoms. METHODS: We systematically reviewed PubMed, Scopus, and Web of Science until December 2022 to find randomized trials that assessed the effects of omega-3 fatty acids supplementation on anxiety symptoms in adults. Investigators performed the literature search and screened the titles/abstracts and full-texts and between-reviewer agreement was assessed as Cohen's kappa coefficient. We conducted a random-effects dose-response meta-analysis to estimate standardized mean differences (SMD) and 95% confidence intervals (CIs) and assessed the certainty of evidence using the GRADE framework. RESULTS: A total of 23 trials with 2189 participants were included. Each 1 gram per day supplementation with omega-3 fatty acids resulted in a moderate decrease in anxiety symptoms (SMD: -0.70, 95%CI: -1.17, -0.22; GRADE = low). The non-linear dose-response analysis indicated the greatest improvement at 2 g/d (SMD: -0.93, 95%CI: -1.85, -0.01), and that supplementation in a dose lower than 2 g/d did not affect anxiety symptoms. Omega-3 fatty acids did not increase adverse events (odds ratio: 1.20, 95%CI: 0.89, 1.61; GRADE = moderate). CONCLUSIONS: The present dose-response meta-analysis suggested evidence of very low certainty that supplementation with omega-3 fatty acids may significantly improve anxiety symptoms, with the greatest improvements at 2 g/d. More trials with better methodological quality are needed to reach more robust evidence. PROTOCOL REGISTRATION: PROSPERO (CRD42022309636).

Studying harms of interventions with an equity lens in randomized trials.

Equity and health equity are fundamental pillars in fostering a just and inclusive society. While equity underscores fairness in resource allocation and opportunity, health equity aims to eradicate avoidable health disparities among social groups. The concept of harms in interventions-undesirable consequences associated with the use of interventions-often varies across populations due to biological and social factors, necessitating a nuanced understanding. An equity lens reveals disparities in harm distribution, urging researchers and policymakers to address these differences in their decision-making processes. Furthermore, interventions, even well-intentioned ones, can inadvertently exacerbate disparities, emphasizing the need for comprehensive harm assessment. Integrating equity considerations in research practices and trial methodologies, through study design or through practices such as inclusive participant recruitment, is pivotal in advancing health equity. By prioritizing interventions that address disparities and ensuring inclusivity in research, we can foster a more equitable healthcare system.

Integrating Alcohol Biosensors With Ecological Momentary Intervention (EMI) for Alcohol Use: a Synthesis of the Latest Literature and Directions for Future Research.

Purpose of Review: Excessive alcohol use is a major public health concern. With increasing access to mobile technology, novel mHealth approaches for alcohol misuse, such as ecological momentary intervention (EMI), can be implemented widely to deliver treatment content in real time to diverse populations. This review summarizes the state of research in this area with an emphasis on the potential role of wearable alcohol biosensors in future EMI/just-in-time adaptive interventions (JITAI) for alcohol use. Recent Findings: JITAI emerged as an intervention design to optimize the delivery of EMI for various health behaviors including substance use. Alcohol biosensors present an opportunity to augment JITAI/EMI for alcohol use with objective information on drinking behavior captured passively and continuously in participants' daily lives, but no prior published studies have incorporated wearable alcohol biosensors into JITAI for alcohol-related problems. Several methodological advances are needed to accomplish this goal and advance the field. Future research should focus on developing standardized data processing, analysis, and interpretation methods for wrist-worn biosensor data. Machine learning algorithms could be used to identify risk factors (e.g., stress, craving, physical locations) for high-risk drinking and develop decision rules for interpreting biosensor-derived transdermal alcohol concentration (TAC) data. Finally, advanced trial design such as micro-randomized trials (MRT) could facilitate the development of biosensor-augmented JITAI. Summary: Wrist-worn alcohol biosensors are a promising potential addition to improve mHealth and JITAI for alcohol use. Additional research is needed to improve biosensor data analysis and interpretation, build new machine learning models to facilitate integration of alcohol biosensors into novel intervention strategies, and test and refine biosensor-augmented JITAI using advanced trial design.

Pooled-analysis of tadalafil and tamsulosin for ureteral calculi.

Objective: Urolithiasis is a common urological diseases and affects the daily life of patients. Medical expulsive therapy has become acceptable for many parents. We conducted a meta-analysis to determine the efficacy and safety of tadalafil compared with tamsulosin for treating distal ureteral stones less than 10 mm in length. Methods: Related studies were identified via searches of the PubMed, Embase, and Cochrane Library databases. All the articles that described the use of tadalafil and tamsulosin for treating distal ureteral stones were collected. Results: A total of 14 studies were included in our meta-analysis. Our results revealed that tadalafil enhanced expulsion rate [odds ratio (OR) = 0.68, 95% confidence interval (CI): 0.47 to 0.98, p = 0.04]; reduced expulsion time [mean difference (MD) = 1.22, 95% CI (0.13, 2.30), p = 0.03]; lowered analgesia use [MD = 38.66, 95% CI (7.56, 69.77), p = 0.01] and hospital visits [MD = 0.14, 95% CI (0.06, 0.22), p = 0.0006]. According to our subgroup analysis, either tadalafil 5 mg or 10 mg did not promote expulsion rate and accelerate expulsion time compared with tamsulosin. But patients receiving 5 mg tadalafil decreased analgesia usage [MD = 101.04, 95% CI (67.56, 134.01), p < 0.00001]. Conclusion: Compared with tamsulosin, tadalafil demonstrates a higher expulsion rate and less expulsion time for patients with distal ureteral stones less than 10 mm with a favorable safety profile.

Reliability of study endpoint adjudication in a pragmatic trial on brain arteriovenous malformations.

BACKGROUND: The results of a clinical trial are given in terms of primary and secondary outcomes that are obtained for each patient. Just as an instrument should provide the same result when the same object is measured repeatedly, the agreement of the adjudication of a clinical outcome between various raters is fundamental to interpret study results. The reliability of the adjudication of study endpoints determined by examination of the electronic case report forms of a pragmatic trial has not previously been tested. METHODS: The electronic case report forms of 62/434 (14%) patients selected to be observed in a study on brain AVMs were independently examined twice (4 weeks apart) by 8 raters who judged whether each patient had reached the following study endpoints: (1) new intracranial hemorrhage related to AVM or to treatment; (2) new non-hemorrhagic neurological event; (3) increase in mRS ≥1; (4) serious adverse events (SAE). Inter and intra-rater reliability were assessed using Gwet's AC1 (κG) statistics, and correlations with mRS score using Cramer's V test. RESULTS: There was almost perfect agreement for intracranial hemorrhage (92% agreement; κG = 0.84 (95%CI: 0.76-0.93), and substantial agreement for SAEs (88% agreement; κG = 0.77 (95%CI: 0.67-0.86) and new non-hemorrhagic neurological event (80% agreement; κG = 0.61 (95%CI: 0.50-0.72). Most endpoints correlated (V = 0.21-0.57) with an increase in mRS of ≥1, an endpoint which was itself moderately reliable (76% agreement; κG = 0.54 (95%CI: 0.43-0.64). CONCLUSION: Study endpoints of a pragmatic trial were shown to be reliable. More studies on the reliability of pragmatic trial endpoints are needed.

Systematic Review of Women Leading and Participating in Nephrology Randomized Clinical Trials.

Introduction: Women are underrepresented in the leadership of and participation in randomized controlled trials (RCTs). We conducted a bibliometric review of nephrology RCTs to examine trial leadership by women and participation of women in nephrology RCTs. Methods: A bibliometric review of RCTs published in top medical, surgical, or nephrology journals was conducted using MEDLINE and EMBASE from January 2011 to December 2021. Leadership by women as corresponding authors, women trial participation, and trial characteristics were examined with duplicate independent data extraction. Logistic regression was used to examine associations between trial characteristics and women leadership and trial participation. Results: A total of 1770 studies were screened and 395 RCTs met eligibility criteria. The number (%) of women in corresponding, first, and last authorship positions were as follows: 89 (22%), 109 (28%), and 74 (19%), respectively, without change over time (P = 0.94). The median percentage (interquartile range [IQR]) of women trial participants was 39.0% (13.5%) with no difference between women or men lead authors (P = 0.15). Men lead authors were statistically less likely to enroll women in RCTs. Women lead authors were less likely to be funded by industry (odds ratio [OR]: 0.30; 95% confidence interval [CI]: 0.14-0.63; P = 0.002) or lead international trials (OR: 0.11; 95% CI: 0.01-0.83; P = 0.03). Trials with sex-specific eligibility criteria were more likely to have women leaders (OR: 2.56; 95% CI: 1.19-5.49; P = 0.02) than those without. Discussion: Gender inequalities in RCT leadership and RCT participation exist in nephrology and did not improve over time. Strategies to improve inequalities need to be implemented and evaluated.

Multilevel Intervention Stepped Wedge Designs (MLI-SWDs).

Multilevel interventions (MLIs) hold promise for reducing health inequities by intervening at multiple types of social determinants of health consistent with the socioecological model of health. In spite of their potential, methodological challenges related to study design compounded by a lack of tools for sample size calculation inhibit their development. We help address this gap by proposing the Multilevel Intervention Stepped Wedge Design (MLI-SWD), a hybrid experimental design which combines cluster-level (CL) randomization using a Stepped Wedge design (SWD) with independent individual-level (IL) randomization. The MLI-SWD is suitable for MLIs where the IL intervention has a low risk of interference between individuals in the same cluster, and it enables estimation of the component IL and CL treatment effects, their interaction, and the combined intervention effect. The MLI-SWD accommodates cross-sectional and cohort designs as well as both incomplete (clusters are not observed in every study period) and complete observation patterns. We adapt recent work using generalized estimating equations for SWD sample size calculation to the multilevel setting and provide an R package for power and sample size calculation. Furthermore, motivated by our experiences with the ongoing NC Works 4 Health study, we consider how to apply the MLI-SWD when individuals join clusters over the course of the study. This situation arises when unemployment MLIs include IL interventions that are delivered while the individual is unemployed. This extension requires carefully considering whether the study interventions will satisfy additional causal assumptions but could permit randomization in new settings.

The relative vaccine effectiveness of high-dose vs standard-dose influenza vaccines in preventing hospitalization and mortality: A meta-analysis of evidence from randomized trials.

OBJECTIVES: To summarize current evidence of high-dose influenza vaccine (HD-IV) vs standard-dose (SD-IV) regarding severe clinical outcomes. METHODS: A prespecified meta-analysis was conducted to assess relative vaccine effectiveness (rVE) of HD-IV vs SD-IV in reducing the rates of (1) pneumonia and influenza (P&I) hospitalization, (2) all hospitalizations, and (3) all-cause death in adults ≥ 65 years in randomized controlled trials. Pooled effect sizes were estimated using fixed-effects models with the inverse variance method. RESULTS: Five randomized trials were included encompassing 105,685 individuals. HD-IV vs SD-IV reduced P&I hospitalizations (rVE: 23.5 %, [95 %CI: 12.3 to 33.2]). HD-IV vs SD-IV also reduced rate of all-cause hospitalizations (rVE: 7.3 %, [95 %CI: 4.5 to 10.0]). No significant differences were observed in death rates (rVE = 1.6 % ([95 %CI: -2.0 to 5.0]) in HD-IV vs SD-IV. Sensitivity analyses omitting trials with participants sharing the same comorbidity, trials with ≥ 100 events, and random-effects models provided comparable estimates for all outcomes. CONCLUSIONS: HD-IV reduced the incidence of P&I and all-cause hospitalization vs SD-IV in adults ≥ 65 years in randomized trials, through no significant difference was observed in all-cause death rates. These findings, supported by evidence from several randomized studies, can benefit from replication in a fully powered, individually randomized trial.

Prospective benchmarking of an observational analysis in the SWEDEHEART registry against the REDUCE-AMI randomized trial.

Prospective benchmarking of an observational analysis against a randomized trial increases confidence in the benchmarking process as it relies exclusively on aligning the protocol of the trial and the observational analysis, while the trials findings are unavailable. The Randomized Evaluation of Decreased Usage of Betablockers After Myocardial Infarction (REDUCE-AMI, ClinicalTrials.gov ID: NCT03278509) trial started recruitment in September 2017 and results are expected in 2024. REDUCE-AMI aimed to estimate the effect of long-term use of beta blockers on the risk of death and myocardial following a myocardial infarction with preserved left ventricular systolic ejection fraction. We specified the protocol of a target trial as similar as possible to that of REDUCE-AMI, then emulated the target trial using observational data from Swedish healthcare registries. Had everyone followed the treatment strategy as specified in the target trial protocol, the observational analysis estimated a reduction in the 5-year risk of death or myocardial infarction of 0.8 percentage points for beta blockers compared with no beta blockers; effects ranging from an absolute reduction of 4.5 percentage points to an increase of 2.8 percentage points in the risk of death or myocardial infarction were compatible with our data under conventional statistical criteria. Once results of REDUCE-AMI are published, we will compare the results of our observational analysis against those from the trial. If this prospective benchmarking is successful, it supports the credibility of additional analyses using these observational data, which can rapidly deliver answers to questions that could not be answered by the initial trial. If benchmarking proves unsuccessful, we will conduct a "postmortem" analysis to identify the reasons for the discrepancy. Prospective benchmarking shifts the investigator focus away from an endeavour to use observational data to obtain similar results as a completed randomized trial, to a systematic attempt to align the design and analysis of the trial and the observational analysis.

Health-related quality of life in trials with high rates of early censoring: Caution advised.

Health-related quality-of-life (HRQoL) data are central to capturing the quality of patients' life, while endpoints like overall survival (OS) focus on the quantity of life. When analyzing HRQoL data gathered from patients in a randomized trial, a key consideration is the completion rate - indicating the proportion of patients remaining in the trial and with completed questionnaires. When completion rates are disproportionately low in one treatment arm, one likely explanation is that patients who did not complete questionnaires suffered more from toxicities, negatively impacting their HRQoL. This is likely the case when low completion rates occur in the more toxic arm within a randomized trial. If the HRQoL analysis is run as a complete-case analysis - only considering patients without missing data - a decrement in HRQoL can be missed. Conversely, when completion rates are high, the HRQoL data are thought to be more reliable, and informative censoring is less likely. We describe why this reasoning can be inadequate. In trials where high and imbalanced rates of early censoring affect progression-free survival or OS endpoints, the completion rates only apply to the fraction of patients remaining in the trial. In those, HRQoL results should be considered with caution, and reasons for censoring in the primary time-to-event analyses should be explored before making definite conclusions about HRQoL. This is even more relevant in trials with non-inferiority design, where a benefit in HRQoL could be used as a justification to modify practice.

First-line immunotherapy efficacy in advanced squamous non-small cell lung cancer with PD-L1 expression ≥50%: a network meta-analysis of randomized controlled trials.

Objective: The optimal first-line immunotherapy regimen for patients with PD-L1 expression ≥50% in squamous non-small cell lung cancer (Sq-NSCLC) remains uncertain. This study utilized net-work meta-analysis (NMA) to indirectly compare the efficacy of various first-line immuno-therapy regimens in this patient subset. Methods: Systematic searches were conducted across PubMed, the Cochrane Library, Web of Science, and Embase databases for randomized controlled trials reporting overall survival (OS) and progression-free survival (PFS) outcomes. The search spanned from database inception to November 3, 2023. Bayesian network meta-analysis was employed for a comprehen-sive analysis. To ensure scientific rigor and transparency, this study is registered in the Interna-tional Prospective Register of Systematic Reviews (PROSPERO) under the registration number CRD42022349712. Results: The NMA encompassed 9 randomized controlled trials (RCTs), involving 2170 patients and investigating 9 distinct immunotherapy regimens. For OS, the combination of camrelizumab and chemotherapy demonstrated the highest probability (36.68%) of efficacy, fol-lowed by cemiplimab (33.86%) and atezolizumab plus chemotherapy (23.87%). Regarding PFS, the camrelizumab and chemotherapy combination had the highest probability (39.70%) of efficacy, followed by pembrolizumab (22.88%) and pembrolizumab plus chemotherapy (17.69%). Compared to chemotherapy, first-line treatment with immune checkpoint inhibitors (ICIs) in Sq-NSCLC pa-tients exhibited significant improvements in OS (HR 0.59, 95% CI 0.47-0.75) and PFS (HR 0.44, 95% CI 0.37-0.52). Conclusion: This study suggests that, for Sq-NSCLC patients with PD-L1 expression ≥50%, the first-line immunotherapy regimen of camrelizumab plus chemotherapy provides superior OS and PFS outcomes. Furthermore, ICIs demonstrate enhanced efficacy compared to chemotherapy in this patient population. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier: CRD 42022349712.

The use and abuse of survival analysis and Kaplan-Meier curves in surgical trials.

BACKGROUND: Survival analysis based on Cox regression and Kaplan-Meier curves, initially devised for oncology trials, have frequently been used in other contexts where fundamental statistical assumptions (such as a constant hazard ratio) are not satisfied. This is almost always the case in trials that compare surgery with medical management. METHODS: We review a trial that compared extracranial-intracranial bypass surgery (EC-IC bypass) with medical management (MM) of patients with symptomatic occlusion of the carotid or middle cerebral artery, where it was claimed that surgery was of no benefit. We discuss a hypothetical study and review other neurovascular trials which have also used survival analysis to compare results. RESULTS: The trial comparing EC-IC bypass and MM did not satisfy the fundamental proportional hazard assumption necessary for valid analyses. This was also the case for two prior EC-IC bypass trials, as well as for other landmark neurovascular studies, such as the trials comparing endarterectomy with MM for carotid stenoses, or for the trial that compared intervention and MM for unruptured brain arteriovenous malformations. While minor deviations may have little effect on large trials, it may be impossible to show the benefits of surgery when trial size is small and deviations large. CONCLUSION: Survival analyses are inappropriate in RCTs comparing surgery with conservative management, unless survival is calculated after the postoperative period. Alternative ways to compare final clinical outcomes, using for example a fixed follow-up period, should be planned for preventive surgical trials that compare intervention with conservative management.

Asociación de las características del ensayo con la publicación simultánea y su impacto en citas y menciones: un estudio transversal / Association of trial characteristics with simultaneous publication and its impact on citations and mentions: a cross-sectional study

Introducción y objetivos: Los ensayos clínicos aleatorizados a menudo se presentan en conferencias médicas y se publican al mismo tiempo o después. Los predictores de publicación simultánea y sus consecuencias no están determinados. Nuestro objetivo es caracterizar la práctica de la publicación simultánea, identificar sus predictores y evaluar su impacto. Métodos: En este estudio transversal se incluyeron ensayos clínicos aleatorizados presentados en sesiones de ciencia de última hora de importantes conferencias cardiovasculares desde 2015 hasta 2021. Se analizó la asociación entre las características del ensayo y el momento de la publicación. Se investigó el impacto de la publicación simultánea frente a la no simultánea en el número de citas a 1 año y menciones a 1 mes, así como en el total de citas y menciones en el seguimiento más largo observado. Resultados: De los 478 ensayos incluidos en el análisis, el 48,7% se publicó simultáneamente. Las publicaciones simultáneas tenían mayor probabilidad de presentarse en la sala principal de la conferencia (OR=6,09; IC95%, 1,34-36,92; p=0,029) y se caracterizaban por un tiempo de revisión más corto (OR=0,95; IC95%, 0,91-0,96; p<0,001). Las publicaciones simultáneas se asociaron con un mayor número de citas a 1 año (R2=43,81; IC95%, 23,89-63,73; p<0,001), menciones a 1 mes (R2=132,32; IC95%, 85,42-179,22; p<0,001) y total de citas (R2=222,89; IC95%, 127,98-317,80; p<0,001) en el seguimiento. Conclusiones: Los ensayos clínicos aleatorizados presentados en la sala principal de la conferencia y con un tiempo de revisión más corto tienen mayor probabilidad de publicarse simultáneamente. Las publicaciones simultáneas se asocian con más citas y menciones que las publicaciones no simultáneas. (AU)

Introduction and objectives: Randomized trials are often presented at medical conferences and published simultaneously or later. Predictors of simultaneous publication and its consequences are undetermined. Our aim was to characterize the practice of simultaneous publication, identify its predictors, and evaluate its impact. Methods: In this cross-sectional study, we included randomized trials presented at late-breaking science sessions of major cardiovascular conferences from 2015 to 2021. The association of trial characteristics with the timing of publication was analyzed. The impact of simultaneous vs nonsimultaneous publication was investigated on the number of 1-year citations and 1-month mentions, and the total citations and mentions at the longest observation follow-up. Results: Of 478 trials included in the analysis, 48.7% were published simultaneously. Simultaneous publications were more likely to be presented in the main conference room (OR, 6.09; 95%CI, 1.34-36.92; P=.029) and were characterized by a shorter review time (OR, 0.95; 95%CI, 0.91-0.96; P<.001). Simultaneous publications were associated with higher 1-year citations (R2, 43.81; 95%CI, 23.89-63.73; P<.001), 1-month mentions (R2, 132.32; 95%CI, 85.42-179.22; P<.001) and total citations (R2, 222.89; 95%CI, 127.98-317.80; P<.001). Conclusions: Randomized trials presented in the main conference room and with shorter review time were more likely to be published simultaneously. Simultaneous publications were associated with more citations and mentions than nonsimultaneous publications. (AU)

Randomized trials of estrogen-alone and breast cancer incidence: a meta-analysis.

PURPOSE: In the Women's Health initiative (WHI) randomized clinical trial, conjugated equine estrogen (CEE)-alone significantly reduced breast cancer incidence (P = 0.005). As cohort studies had opposite findings, other randomized clinical trials were identified to conduct a meta-analysis of estrogen-alone influence on breast cancer incidence. METHODS: We conducted literature searches on randomized trials and: estrogen, hormone therapy, and breast cancer, and searches from a prior meta-analysis and reviews. In the meta-analysis, for trials with published relative risks (RR) and 95% confidence intervals (CI), each log-RR was multiplied by weight = 1/V, where V = variance of the log-RR, and V was derived from the corresponding 95% CI. For smaller trials with only breast cancer numbers, the corresponding log-RR = (O - E)/weight, where O is the observed case number in the oestrogen-alone group and E the corresponding expected case number, E = nP. RESULTS: Findings from 10 randomized trials included 14,282 participants and 591 incident breast cancers. In 9 smaller trials, with 1.2% (24 of 2029) vs 2.2% (33 of 1514) randomized to estrogen-alone vs placebo (open label, one trial) (RR 0.65 95% CI 0.38-1.11, P = 0.12). For 5 trials evaluating estradiol formulations, RR = 0.63 95% CI 0.34-1.16, P = 0.15. Combining the 10 trials, 3.6% (262 of 7339) vs 4.7% (329 of 6943) randomized to estrogen-alone vs placebo (overall RR 0.77 95% CI 0.65-0.91, P = 0.002). CONCLUSION: The totality of randomized clinical trial evidence supports a conclusion that estrogen-alone use significantly reduces breast cancer incidence.

A review and analysis of outcomes in randomized clinical trials of plasma transfusion in patients with bleeding or for the prevention of bleeding: The BEST collaborative study.

BACKGROUND: Previous systematic reviews have revealed an inconsistency of outcome definitions as a major barrier in providing evidence-based guidance for the use of plasma transfusion to prevent or treat bleeding. We reviewed and analyzed outcomes in randomized controlled trials (RCTs) to provide a methodology for describing and classifying outcomes. STUDY DESIGN AND METHODS: RCTs involving transfusion of plasma published after 2000 were identified from a prior review (Yang 2012) and combined with an updated systematic literature search of multiple databases (July 1, 2011 to January 17, 2023). Inclusion of publications, data extraction, and risk of bias assessments were performed in duplicate. (PROSPERO registration number is: CRD42020158581). RESULTS: In total, 5579 citations were identified in the new systematic search and 22 were included. Six additional trials were identified from the previous review, resulting in a total of 28 trials: 23 therapeutic and five prophylactic studies. An increasing number of studies in the setting of major bleeding such as in cardiovascular surgery and trauma were identified. Eighty-seven outcomes were reported with a mean of 11 (min-max. 4-32) per study. There was substantial variation in outcomes used with a preponderance of surrogate measures for clinical effect such as laboratory parameters and blood usage. CONCLUSION: There is an expanding literature on plasma transfusion to inform guidelines. However, considerable heterogeneity of reported outcomes constrains comparisons. A core outcome set should be developed for plasma transfusion studies. Standardization of outcomes will motivate better study design, facilitate comparison, and improve clinical relevance for future trials of plasma transfusion.

Assessing treatment effect heterogeneity in the presence of missing effect modifier data in cluster-randomized trials.

Understanding whether and how treatment effects vary across subgroups is crucial to inform clinical practice and recommendations. Accordingly, the assessment of heterogeneous treatment effects based on pre-specified potential effect modifiers has become a common goal in modern randomized trials. However, when one or more potential effect modifiers are missing, complete-case analysis may lead to bias and under-coverage. While statistical methods for handling missing data have been proposed and compared for individually randomized trials with missing effect modifier data, few guidelines exist for the cluster-randomized setting, where intracluster correlations in the effect modifiers, outcomes, or even missingness mechanisms may introduce further threats to accurate assessment of heterogeneous treatment effect. In this article, the performance of several missing data methods are compared through a simulation study of cluster-randomized trials with continuous outcome and missing binary effect modifier data, and further illustrated using real data from the Work, Family, and Health Study. Our results suggest that multilevel multiple imputation and Bayesian multilevel multiple imputation have better performance than other available methods, and that Bayesian multilevel multiple imputation has lower bias and closer to nominal coverage than standard multilevel multiple imputation when there are model specification or compatibility issues.

Adaptive selection of the optimal strategy to improve precision and power in randomized trials.

Benkeser et al. demonstrate how adjustment for baseline covariates in randomized trials can meaningfully improve precision for a variety of outcome types. Their findings build on a long history, starting in 1932 with R.A. Fisher and including more recent endorsements by the U.S. Food and Drug Administration and the European Medicines Agency. Here, we address an important practical consideration: how to select the adjustment approach-which variables and in which form-to maximize precision, while maintaining Type-I error control. Balzer et al. previously proposed Adaptive Pre-specification within TMLE to flexibly and automatically select, from a prespecified set, the approach that maximizes empirical efficiency in small trials (N < 40). To avoid overfitting with few randomized units, selection was previously limited to working generalized linear models, adjusting for a single covariate. Now, we tailor Adaptive Pre-specification to trials with many randomized units. Using V-fold cross-validation and the estimated influence curve-squared as the loss function, we select from an expanded set of candidates, including modern machine learning methods adjusting for multiple covariates. As assessed in simulations exploring a variety of data-generating processes, our approach maintains Type-I error control (under the null) and offers substantial gains in precision-equivalent to 20%-43% reductions in sample size for the same statistical power. When applied to real data from ACTG Study 175, we also see meaningful efficiency improvements overall and within subgroups.