The prevention and treatment of missing data in clinical trials

Evaluation of non-invasive biomarkers of kidney allograft rejection in a prospective multicenter unselected cohort study (EU-TRAIN)

Non-invasive biomarkers are promising tools for improving kidney allograft rejection monitoring, but their clinical adoption requires more evidence in specifically designed studies. To address this unmet need, we designed the EU-TRAIN study, a large prospective multicentric unselected cohort funded by the European Commission. Here, we included consecutive adult patients who received a kidney allograft in nine European transplant centers between November 2018 and June 2020. We prospectively assessed gene expression levels of 19 blood messenger RNAs, four antibodies targeting non-human leukocyte antigen (HLA) endothelial antigens, together with circulating anti-HLA donor-specific antibodies (DSA). The primary outcome was allograft rejection (antibody-mediated, T cell-mediated, or mixed) in the first year post-transplantation. Overall, 412 patients were included, with 812 biopsies paired with a blood sample. CD4 gene expression was significantly associated with rejection, while circulating anti-HLA DSA had a significant association with allograft rejection and a strong association with antibody-mediated rejection. All other tested biomarkers, including AKR1C3, CD3E, CD40, CD8A, CD9, CTLA4, ENTPD1, FOXP3, GZMB, ID3, IL7R, MS4A1, MZB1, POU2AF1, POU2F1, TCL1A, TLR4, and TRIB1, as well as antibodies against angiotensin II type 1 receptor, endothelin 1 type A receptor, C3a and C5a receptors, did not show significant associations with allograft rejection. The blood messenger RNAs and non-HLA antibodies did not show an additional value beyond standard of care monitoring parameters and circulating anti-HLA DSA to predict allograft rejection in the first year post-transplantation. Thus, our results open avenues for specifically designed studies to demonstrate the clinical relevance and implementation of other candidate non-invasive biomarkers in kidney transplantation practice.

Effects of Sedentary Behavior Reduction on Blood Pressure in Desk Workers: Results From the RESET-BP Randomized Clinical Trial

BACKGROUND

Sedentary behavior (SB) is observationally associated with cardiovascular disease risk. However, randomized clinical trials testing causation are limited. We hypothesized that reducing SB would decrease blood pressure (BP) and pulse wave velocity (PWV) in sedentary adults.

METHODS

This parallel-arm, 3-month randomized clinical trial recruited desk workers, age 18 to 65 years, with systolic BP 120 to 159 or diastolic BP (DBP) 80 to 99 mm Hg, off antihypertensive medications, and reporting <150 min/wk of moderate to vigorous intensity physical activity. Participants were randomized to a SB reduction intervention or a no-contact control group. The intervention sought to replace 2 to 4 h/d of SB with standing and stepping through coaching, a wrist-worn activity prompter, and a sit-stand desk. SB and physical activity were measured with a thigh-worn accelerometer and quantified during all waking hours and separately during work and nonwork times. Clinic-based resting systolic BP (primary outcome) and DBP, 24-hour ambulatory BP, and PWV were assessed by blinded technicians at baseline and 3 months.

RESULTS

Participants (n=271) had a mean age of 45 years and systolic BP/DBP 129/83 mm Hg. Compared with controls, intervention participants reduced SB (-1.15±0.17 h/d), increased standing (0.94±0.14 h/d), and increased stepping (5.4±2.4 min/d; all P<0.05). SB and activity changes mainly occurred during work time and were below the goal. The intervention did not reduce BP or PWV in the intervention group compared with controls. Between-group differences in resting systolic BP and DBP changes were -0.22±0.90 (P=0.808) and 0.13±0.61 mm Hg (P=0.827), respectively. The findings were similarly null for ambulatory BP and PWV. Decreases in work-time SB were associated with favorable reductions in resting DBP (r=0.15, P=0.017). Contrary to our hypotheses, reductions in work-time SB (r=-0.19, P=0.006) and increases in work-time standing (r=0.17, P=0.011) were associated with unfavorable increases in carotid-femoral PWV. As expected, increases in nonwork-time standing were favorably associated with carotid-femoral PWV (r=-0.14, P=0.038).

CONCLUSIONS

A 3-month intervention that decreased SB and increased standing by ≈1 hour during the work day was not effective for reducing BP. Future directions include examining effects of interventions reducing SB through activity other than work-time standing and clarifying association between standing and PWV in opposite directions for work and nonwork time.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03307343.

Real-world predictors of severe psychological distress during the COVID-19 pandemic in Japan: Insights from a large-scale internet-based cohort study

AIM

The COVID-19 pandemic has had negative physical and psychological impacts worldwide. However, there has been a lack of real-world evidence concerning the predictors of severe psychological distress (SPD) among the general population in Japan during the COVID-19 pandemic. The aim of this study was to examine predictors of SPD during the COVID-19 pandemic.

METHODS

We investigated the predictors of new-onset SPD in the general Japanese population using data from a large-scale internet-based cohort study.

RESULTS

We included 16 489 study participants (age range = 16-81, mean age = 52.7, percentage of male = 50%) in the analysis. Over the course of 1 year from baseline, the estimated proportion of participants who experienced SPD was 5.2% with inverse probability weighting. The predictors of SPD included younger age, being never married, being unemployed, having a higher education background, scoring higher on the Fear of Coronavirus-19 Scale, experiencing more adverse childhood experiences, reporting poorer subjective health status, and COVID-19 with oxygen therapy. Our internet-based survey of the Japanese population may have selection bias, limiting the generalizability to other countries and cultures.

CONCLUSION

This study revealed that being afflicted with COVID-19 requiring oxygen therapy is the most significant predictor of SPD. In addition, we found that vulnerability to social isolation, such as never being unmarried, anxiety toward COVID-19, and susceptibility to stress, are predictors of the emergence of SPD. Therefore, the implementation of online support systems and ensuring access to accurate information may protect against SPD during the COVID-19 pandemic in Japan.

Big data research is everyone's research-Making epilepsy data science accessible to the global community: Report of the ILAE big data commission

Epilepsy care generates multiple sources of high-dimensional data, including clinical, imaging, electroencephalographic, genomic, and neuropsychological information, that are collected routinely to establish the diagnosis and guide management. Thanks to high-performance computing, sophisticated graphics processing units, and advanced analytics, we are now on the cusp of being able to use these data to significantly improve individualized care for people with epilepsy. Despite this, many clinicians, health care providers, and people with epilepsy are apprehensive about implementing Big Data and accompanying technologies such as artificial intelligence (AI). Practical, ethical, privacy, and climate issues represent real and enduring concerns that have yet to be completely resolved. Similarly, Big Data and AI-related biases have the potential to exacerbate local and global disparities. These are highly germane concerns to the field of epilepsy, given its high burden in developing nations and areas of socioeconomic deprivation. This educational paper from the International League Against Epilepsy's (ILAE) Big Data Commission aims to help clinicians caring for people with epilepsy become familiar with how Big Data is collected and processed, how they are applied to studies using AI, and outline the immense potential positive impact Big Data can have on diagnosis and management.

Investigating discrepancies in findings between rigorous randomized trials and meta-analyses evaluating pregnancy interventions to limit gestational weight gain

INTRODUCTION

Robust randomized trials consistently demonstrate little impact from diet and physical activity interventions on gestational weight gain (GWG) and clinical outcomes, although meta-analyses report some benefit. Our aim was to evaluate the effect of trial quality on treatment effect estimates and review conclusions.

METHODS

We conducted a systematic review of dietary and/or physical activity interventions for pregnant women with a body mass index ≥18.5 kg/m2. We assessed studies for risk of bias and methodological features impacting reliability. Outcomes included GWG; gestational diabetes mellitus (GDM); pre-eclampsia; caesarean birth; and birth weight measures. For each outcome, a sequence of meta-analyses was performed based on intervention group and level of potential bias in the effect estimate.

RESULTS

We identified 128 eligible studies. The most robust estimate from a combined diet and physical activity behavioral intervention, with only studies at negligible risk of bias, was a difference in GWG of 1.10 kg (95% CI -1.62 to -0.58; 17,755 women). There was no evidence of an effect on any clinical outcomes.

CONCLUSIONS

Our findings highlight discrepancies produced by the indiscriminate inclusion of studies with methodological flaws in previous systematic reviews. Regular weighing of pregnant women is futile in the absence of clinical benefit.

On the Move in the community: Protocol for a hybrid 1 trial examining effectiveness and fidelity of a community-based group exercise program for older adults

BACKGROUND

On the Move (OTM), a group exercise program to improve mobility in older adults, is efficacious when delivered by research staff. The next step in the development of OTM as a fully implementable intervention is to conduct an effectiveness study in which the intervention is delivered in community settings by community providers.

METHODS

We describe the methods of a hybrid 1 cluster randomized, single-blind, intervention trial to compare the effectiveness of OTM to a delayed intervention control in 502 community-dwelling older adults across 44 sites. OTM classes are taught by certified instructors in the community twice a week for 12 weeks. Control centers receive no intervention for the first 12 weeks followed by 12-weeks of OTM classes. Participants are assessed at baseline, 12 and 24 weeks. The primary outcome is gait speed. Intervention fidelity, measured by adherence and competence in intervention delivery, is assessed by review of instructor intervention diaries and observation. Organizational, instructor, and participant-level factors which may impact fidelity are assessed using questionnaires, focus groups, and structured interviews.

CONCLUSION

The findings of this trial will 1) establish the effectiveness of OTM on improvements in walking and post-intervention persistence of benefits, 2) assess intervention fidelity and identify the impact of organizational, instructor, and participant level factors on fidelity, and 3) determine the extent to which fidelity moderates the effectiveness of OTM. The information derived from this project will provide valuable insight into the real-world effectiveness of OTM as a health promotion program for improving mobility in older adults.

Mirtazapine to alleviate severe breathlessness in patients with COPD or interstitial lung diseases (BETTER-B): an international, multicentre, double-blind, randomised, placebo-controlled, phase 3 mixed-method trial

BACKGROUND

Breathlessness frequently becomes severe among people with respiratory disease. Mirtazapine, a widely used antidepressant, has shown promise in the modulation of respiratory sensation and the response to it, as well as reducing feelings of panic, which often accompanies breathlessness. We aimed to determine the effectiveness of mirtazapine to alleviate severe persisting breathlessness.

METHODS

This international, multicentre, phase 3, parallel-group, double-blind, randomised, placebo-controlled trial across 16 centres in seven countries (Australia, Germany, Ireland, Italy, New Zealand, Poland, and the UK), recruited adults with chronic obstructive pulmonary disease (COPD), interstitial lung diseases, or both, and grade 3 or 4 of the modified Medical Research Council breathlessness scale. Consenting participants were randomly assigned (1:1) to receive oral mirtazapine or matching placebo for 56 days. Randomisation was by minimisation. The initial mirtazapine dose was 15 mg, escalating to a maximum of 45 mg per day, tapered at treatment end. Participants, caregivers, assessors, and investigators were masked to group assignment. The primary outcome was worst breathlessness in the preceding 24 h measured on a 0-10 numerical rating scale (NRS), at 56 days post-treatment start, with follow-up to 180 days. The primary analysis was performed in the modified intention-to-treat population using multivariable multi-level repeated measures model. This trial was registered with ISRCTN (ISRCTN10487976 and ISRCTN15751764 [Australia and New Zealand]) and EudraCT (2019-002001-21) and is complete.

FINDINGS

Between Feb 4, 2021 and March 28, 2023, we enrolled 225 eligible participants (148 men and 77 women, 113 to the mirtazapine group and 112 to the placebo group). The median age was 74 years (IQR 67-78). No evidence of a difference was found in worst breathlessness at day 56 between mirtazapine and placebo (difference in adjusted mean NRS score was 0·105 [95% CI -0·407 to 0·618]; p=0·69). Although the study was underpowered, the primary endpoint effect did not reach the pre-specified treatment effect of 0·55 for worst breathlessness score reduction that the study was powered to detect for the primary analysis. There were 215 adverse reactions in 72 (64%) of 113 participants in the mirtazapine group versus 116 in 44 (40%) of 110 participants in the placebo group; 11 serious adverse events in six (5%) participants in the mirtazapine group versus eight in seven (6%) participants in the placebo group; and one (1%) suspected unexpected serious adverse reaction in the mirtazapine group. At day 56, there were three deaths in the mirtazapine group and two deaths in the placebo group. At day 180, there were seven deaths in the mirtazapine group and 11 deaths in the placebo group.

INTERPRETATION

Our findings suggested that mirtazapine of doses 15 to 45 mg daily over 56 days does not improve severe breathlessness among patients with COPD or interstitial lung diseases and might cause adverse reactions. Based on these findings, we do not recommend mirtazapine as a treatment to alleviate severe breathlessness.

FUNDING

EU Horizon 2020 (grant agreement No. 825319); Cicely Saunders International Breathlessness Programme; National Institute for Health and Care Research Applied Research Collaboration South London; Australian National Health and Medical Research Council-EU (application ID: APP1170731).

Changes in illness perception, pain catastrophizing, and psychological distress following hand surgeon consultation: A prospective study

BACKGROUND

Baseline mindset factors are important factors that influence treatment decisions and outcomes. Theoretically, improving the mindset prior to treatment may improve treatment decisions and outcomes. This prospective cohort study evaluated changes in patients' mindset following hand surgeon consultation. Additionally, we assessed if the change in illness perception differed between surgical and nonsurgical patients.

METHODS

The primary outcome was illness perception, measured using the total score of the Brief Illness Perception Questionnaire (B-IPQ, range 0-80). Secondary outcomes were the B-IPQ subscales, pain catastrophizing (measured using the Pain Catastrophizing Scale (PCS)), and psychological distress (measured using the Patient Health Questionnaire-4).

RESULTS

A total of 276 patients with various hand and wrist conditions completed the mindset questionnaires before and after hand surgeon consultation (median time interval: 15 days). The B-IPQ total score improved from 39.7 (±10.6) before to 35.8 (±11.3) after consultation (p < 0.0001, Cohen's d = 0.36); scores also improved for the B-IPQ subscales Coherence, Concern, Emotional Response, Timeline, Treatment Control, and Identity and the PCS. There were no changes in the other outcomes. Surgical patients improved on the B-IPQ subscales Treatment Control and Timeline, while nonsurgical patients did not.

CONCLUSIONS

Illness perception and pain catastrophizing improved following hand surgeon consultation, suggesting that clinicians may actively influence the patients' mindset during consultations, and that they may try to enhance this effect to improve outcomes. Furthermore, surgical patients improved more in illness perceptions, indicating that nonsurgical patients may benefit from a more targeted strategy for changing mindset.

Establishing the minimal clinically important difference of the Brief Fatigue Inventory for brain or CNS cancer patients undergoing radiotherapy

Background

Minimal clinically important differences (MCIDs) quantify the clinical relevance of quality of life results at the individual patient and group level. The aim of this study was to estimate the MCID for the Brief Fatigue Inventory (BFI) and the Worst and Usual Fatigue items in patients with brain or CNS cancer undergoing curative radiotherapy.

Methods

Data from a multi-site prospective registry was used. The MCID was calculated using distribution-based and anchor-based approaches. For the anchor-based approach, the fatigue item from the PROMIS-10 served as the anchor to determine if a patient improved, deteriorated, or had no change from baseline to end of treatment (EOT). We compared the unadjusted means on the BFI for the 3 groups to calculate the MCID. For the distribution-based approaches, we calculated the MCID as 0.5 SD of the scores and as 1.96 times the standard error of measurement.

Results

Three-hundred and fifty nine patients with brain or CNS tumors undergoing curative radiotherapy filled out the 9-item BFI at baseline and EOT. The MCID for the BFI was 1.33 (ranging from 0.99 to 1.70 across the approaches), 1.51 (ranging from 1.16 to 2.02) and 1.76 (ranging from 1.38 to 2.14) for the usual and worst fatigue items, respectively.

Conclusions

This study provides the MCID ranges for the BFI and Worst and Usual fatigue items, which will allow clinically meaningful conclusions to be drawn from BFI scores. These results can be used to select optimal treatments for patients with brain or CNS cancer or to interpret BFI scores from clinical trials.

Predicting Completion of Ecological Momentary Assessments Among Substance-Using Women Experiencing Intimate Partner Violence

Noncompletion of ecological momentary assessment (EMA) surveys is a common issue and may yield bias in results if not properly handled. Using data observed at scheduled times as well as data retrieved later to fill missing responses, this study aims to investigate predictors of EMA completion, including demographic characteristics, time-related factors, and momentary experiences/behaviors. Data were from a 30-day EMA study including 145 women currently experiencing intimate partner violence (IPV) and using substances. The average rate of EMA completion was initially 51.4% at the scheduled times and increased to 72.6% after incorporating data from later-retrieved surveys. Participants who were younger, had more children, or had lower mean levels of negative affect dysregulation showed lower completion rates. At the momentary survey level, more days into the study and afternoon/evening reports (vs. morning reports) were associated with lower completion; lower levels of negative affect dysregulation, less smoking or alcohol use, and experiencing IPV were linked to lower momentary completion. Implications of the results for handling missing data in EMA are discussed and have important ramifications for future research, practice, and theory.

A multisector community-engaged collaborative for mental health integration in primary care and housing developments: Protocol for a stepped-wedge randomized controlled trial (the Harlem Strong Program)

BACKGROUND

Addressing mental health disparities following COVID-19 requires adaptive, multi-sectoral, equity-focused, and community-based approaches. Mental health task-sharing in gateway settings has been found to address mental health care gaps in low- and middle-income countries, but is not a common practice in the U.S., especially in non-medical settings, such as low-income housing developments (LIH). This research study will evaluate the effectiveness of a multisectoral community-engaged collaborative for task-sharing mental health care on consumer, provider, and implementation outcomes, as well as identify barriers and facilitators for implementation.

METHODS

In this stepped-wedge randomized controlled trial with technology supplementation, LIH and primary care sites will be randomly assigned to one of five sequences of three implementation strategies: (1) Education and Resources (E&R), which involves online training and resources on basic mental health task-sharing skills, (2) Multisectoral Community Collaborative Care (MCC), which consists of all E&R resources plus additional community responsive implementation supports and participation in a multisectoral coalition and (3) MCC + Technology, which combines the MCC condition resources with a community crowdsourced technology solution to support implementation. The primary outcome is the effectiveness in meeting consumers' needs through direct service (e.g., adequately addressing depression and anxiety symptoms), and through implementation to increase access to mental health care (reach). The secondary outcome examines additional consumer outcomes including health functioning and social risks, as well as implementation outcomes including provider skills, program adoption, and factors related to barriers and facilitators of quality implementation. A total of 700 consumers receiving mental health care at 20 sites will be surveyed at baseline, 6-, and 12-month follow-ups. Additionally, 100 providers will be evaluated at baseline, 6-, 12-, and 24-month follow-ups before training and after randomization.

DISCUSSION

We hypothesize that MCC and MCC + Technology conditions will demonstrate significantly higher efficacy in changing primary outcomes compared to E&R, and the MCC + Technology supplement will show significantly higher levels of reach of mental health tasks compared to the MCC condition alone. These findings will demonstrate the feasibility of mental health integration into accessible, non-medical community settings such as LIH. Moreover, it will help establish a multilevel system solution based on community engagement and planning with a multisectoral collaboration that can be sustained community-wide.

TRIAL REGISTRATION

NCT05833555 on Clinicaltrials.gov. Registered April 26, 2023.

Gaps in the usage and reporting of multiple imputation for incomplete data: findings from a scoping review of observational studies addressing causal questions

BACKGROUND

Missing data are common in observational studies and often occur in several of the variables required when estimating a causal effect, i.e. the exposure, outcome and/or variables used to control for confounding. Analyses involving multiple incomplete variables are not as straightforward as analyses with a single incomplete variable. For example, in the context of multivariable missingness, the standard missing data assumptions ("missing completely at random", "missing at random" [MAR], "missing not at random") are difficult to interpret and assess. It is not clear how the complexities that arise due to multivariable missingness are being addressed in practice. The aim of this study was to review how missing data are managed and reported in observational studies that use multiple imputation (MI) for causal effect estimation, with a particular focus on missing data summaries, missing data assumptions, primary and sensitivity analyses, and MI implementation.

METHODS

We searched five top general epidemiology journals for observational studies that aimed to answer a causal research question and used MI, published between January 2019 and December 2021. Article screening and data extraction were performed systematically.

RESULTS

Of the 130 studies included in this review, 108 (83%) derived an analysis sample by excluding individuals with missing data in specific variables (e.g., outcome) and 114 (88%) had multivariable missingness within the analysis sample. Forty-four (34%) studies provided a statement about missing data assumptions, 35 of which stated the MAR assumption, but only 11/44 (25%) studies provided a justification for these assumptions. The number of imputations, MI method and MI software were generally well-reported (71%, 75% and 88% of studies, respectively), while aspects of the imputation model specification were not clear for more than half of the studies. A secondary analysis that used a different approach to handle the missing data was conducted in 69/130 (53%) studies. Of these 69 studies, 68 (99%) lacked a clear justification for the secondary analysis.

CONCLUSION

Effort is needed to clarify the rationale for and improve the reporting of MI for estimation of causal effects from observational data. We encourage greater transparency in making and reporting analytical decisions related to missing data.

Relationship between reasons for intermittent missing patient-reported outcomes data and missing data mechanisms

PURPOSE

Non-response (NR) to patient-reported outcome (PRO) questionnaires may cause bias if not handled appropriately. Collecting reasons for NR is recommended, but how reasons for NR are related to missing data mechanisms remains unexplored. We aimed to explore this relationship for intermittent NRs.

METHODS

Patients with multiple myeloma completed validated PRO questionnaires at enrolment and 12 follow-up time-points. NR was defined as non-completion of a follow-up assessment within seven days, which triggered contact with the patient, recording the reason for missingness and an invitation to complete the questionnaire (denoted "salvage response"). Mean differences between salvage and previous on-time scores were estimated for groups defined by reasons for NR using linear regression with clustered standard errors. Statistically significant mean differences larger than minimal important difference thresholds were interpreted as "missing not at random" (MNAR) mechanism (i.e. assumed to be related to declining health), and the remainder interpreted as aligned with "missing completely at random" (MCAR) mechanism (i.e. assumed unrelated to changes in health).

RESULTS

Most (7228/7534 (96%)) follow-up questionnaires were completed; 11% (802/7534) were salvage responses. Mean salvage scores were compared to previous on-time scores by reason: those due to hospital admission, mental or physical reasons were worse in 10/22 PRO domains; those due to technical difficulties/procedural errors were no different in 21/22 PRO domains; and those due to overlooked/forgotten or other/unspecified reasons were no different in any domains.

CONCLUSION

Intermittent NRs due to hospital admission, mental or physical reasons were aligned with MNAR mechanism for nearly half of PRO domains, while intermittent NRs due to technical difficulties/procedural errors or other/unspecified reasons generally were aligned with MCAR mechanism.

Addressing missing outcome data in randomised controlled trials: A methodological scoping review

BACKGROUND

Missing outcome data is common in trials, and robust methods to address this are needed. Most trial reports currently use methods applicable under a missing completely at random assumption (MCAR), although this strong assumption can often be inappropriate.

OBJECTIVE

To identify and summarise current literature on the analytical methods for handling missing outcome data in randomised controlled trials (RCTs), emphasising methods appropriate for data missing at random (MAR) or missing not at random (MNAR).

STUDY DESIGN AND SETTING

We conducted a methodological scoping review and identified papers through searching four databases (MEDLINE, Embase, CENTRAL, and CINAHL) from January 2015 to March 2023. We also performed forward and backward citation searching. Eligible papers discussed methods or frameworks for handling missing outcome data in RCTs or simulation studies with an RCT design.

RESULTS

From 1878 records screened, our search identified 101 eligible papers. 90 (89%) papers described specific methods for addressing missing outcome data and 11 (11%) described frameworks for overall methodological approach. Of the 90 methods papers, 30 (33%) described methods under the MAR assumption, 48 (53%) explored methods under the MNAR assumption and 11 (12%) discussed methods under a hybrid of MAR and MNAR assumptions. Control-based methods under the MNAR assumption were the most common method explored, followed by multiple imputation under the MAR assumption.

CONCLUSION

This review provides guidance on available analytic approaches for handling missing outcome data, particularly under the MNAR assumption. These findings may support trialists in using appropriate methods to address missing outcome data.

Predictors of urine toxicology and other biologic specimen missingness in randomized trials of substance use disorders

BACKGROUND

High levels of missing outcome data for biologically confirmed substance use (BCSU) threaten the validity of substance use disorder (SUD) clinical trials. Underlying attributes of clinical trials could explain BCSU missingness and identify targets for improved trial design.

METHODS

We reviewed 21 clinical trials funded by the NIDA National Drug Abuse Treatment Clinical Trials Network (CTN) and published from 2005 to 2018 that examined pharmacologic and psychosocial interventions for SUD. We used configurational analysis-a Boolean algebra approach that identifies an attribute or combination of attributes predictive of an outcome-to identify trial design features and participant characteristics associated with high levels of BCSU missingness. Associations were identified by configuration complexity, consistency, coverage, and robustness. We limited results using a consistency threshold of 0.75 and summarized model fit using the product of consistency and coverage.

RESULTS

For trial design features, the final solution consisted of two pathways: psychosocial treatment as a trial intervention OR larger trial arm size (complexity=2, consistency=0.79, coverage=0.93, robustness score=0.71). For participant characteristics, the final solution consisted of two pathways: interventions targeting individuals with poly- or nonspecific substance use OR younger age (complexity=2, consistency=0.75, coverage=0.86, robustness score=1.00).

CONCLUSIONS

Psychosocial treatments, larger trial arm size, interventions targeting individuals with poly- or nonspecific substance use, and younger age among trial participants were predictive of missing BCSU data in SUD clinical trials. Interventions to mitigate missing data that focus on these attributes may reduce threats to validity and improve utility of SUD clinical trials.

Factors influencing nursing student satisfaction in aged care placements: An Australian cross-sectional study

AIM

This study aimed to investigate factors influencing nursing students' satisfaction with aged care placements.

BACKGROUND

Providing positive clinical experiences in aged care is crucial for students to learn safe, quality care and to foster a sustainable workforce.

DESIGN

Cross-sectional study METHODS: Nursing students in nursing degrees participated in the national placement evaluation survey. A total of 2378 responses were extracted from the national clinical placement evaluation survey in 2023. Using multinomial logistic regression, demographics, academic, placement characteristics and placement education quality (clinical environment and learning support) were investigated in relation to three different levels of students' overall satisfaction (low, moderate, high).

RESULTS

Students reported overall satisfaction with their clinical placement, with a mean score of 7.9 (SD=2.1) on a 10-point scale. While most students agreed that they had achieved their learning objectives (90.0 %), they reported limited opportunities to interact with the multidisciplinary team (80.0 %). Further, students reported a relatively negative experience with staff, such as willingness to work with students (78.9 %) and being positive role models (78.9 %). Comparing the low satisfaction group to the moderate satisfaction group, male gender, identifying as an indigenous student and higher academic years increased the odds of being 'least satisfied', whereas international students, whose first language was not English and those with higher perceived placement education quality scores had lower odds of low satisfaction group membership. Conversely, compared with the moderate satisfaction group, those with the highest satisfaction with their clinical placement had a greater odds of being older, an international student and having higher scores in placement quality for the clinical environment and learning support. This model predicted 58.7 % of students' overall satisfaction.

CONCLUSIONS

Positive learning experiences in aged care may promote the importance of practice in this area to new graduates. Despite students' overall positive satisfaction with aged care placements, it is clear there are areas to address: a need to develop a structured approach to enhance aged care clinical experiences, progressive development of learning objectives, enhancing student career preparation and increasing participation in interprofessional collaboration may be useful approaches.

Predicting Tracheostomy Need on Admission to the Intensive Care Unit-A Multicenter Machine Learning Analysis

OBJECTIVE

It is difficult to predict which mechanically ventilated patients will ultimately require a tracheostomy which further predisposes them to unnecessary spontaneous breathing trials, additional time on the ventilator, increased costs, and further ventilation-related complications such as subglottic stenosis. In this study, we aimed to develop a machine learning tool to predict which patients need a tracheostomy at the onset of admission to the intensive care unit (ICU).

STUDY DESIGN

Retrospective Cohort Study.

SETTING

Multicenter Study of 335 Intensive Care Units between 2014 and 2015.

METHODS

The eICU Collaborative Research Database (eICU-CRD) was utilized to obtain the patient cohort. Inclusion criteria included: (1) Age >18 years and (2) ICU admission requiring mechanical ventilation. The primary outcome of interest included tracheostomy assessed via a binary classification model. Models included logistic regression (LR), random forest (RF), and Extreme Gradient Boosting (XGBoost).

RESULTS

Of 38,508 invasively mechanically ventilated patients, 1605 patients underwent a tracheostomy. The XGBoost, RF, and LR models had fair performances at an AUROC 0.794, 0.780, and 0.775 respectively. Limiting the XGBoost model to 20 features out of 331, a minimal reduction in performance was observed with an AUROC of 0.778. Using Shapley Additive Explanations, the top features were an admission diagnosis of pneumonia or sepsis and comorbidity of chronic respiratory failure.

CONCLUSIONS

Our machine learning model accurately predicts the probability that a patient will eventually require a tracheostomy upon ICU admission, and upon prospective validation, we have the potential to institute earlier interventions and reduce the complications of prolonged ventilation.

Effectiveness of vacuum-assisted wound closure and mesh-mediated fascial traction in open abdomen management

PURPOSE

To determine the effectiveness of vacuum-assisted wound closure and mesh-mediated fascial traction (VAWCM) in patients undergoing open abdomen management (OAM).

METHODS

Data from cases with OAM for at least five days who were admitted to our institution between January 2011 and December 2020 were included. We compared the patient's age, sex, medical history, indication for initial surgery, APACHE II scores, indication for OAM, operative time, intraoperative blood loss, intraoperative transfusion, success of primary fascial closure (rectus fascial closure and bilateral anterior rectus abdominis sheath turnover flap method), success of planned ventral hernia, duration of OAM, and in-hospital mortality between patients undergoing VAWCM (VAWCM cases, n = 27) and vacuum-assisted wound closure (VAWC) alone (VAWC cases, n = 25).

RESULTS

VAWCM cases had a significantly higher success rate of primary fascial closure (70% vs. 36%, p = 0.030) and lower in-hospital mortality (26% vs. 72%, p = 0.002) than VAWC cases. A multivariate logistic regression analysis showed that VAWCM was an independent factor influencing in-hospital mortality (odds ratio, 0.14; 95% confidence interval: 0.04-0.53; p = 0.004).

CONCLUSION

VAWCM is associated with an increased rate of successful primary fascial closure and may reduce in-hospital mortality.

Burden of cardiometabolic disorders and lifetime risk of new-onset atrial fibrillation among men and women: the Rotterdam Study

AIMS

To examine the association between the burden of cardiometabolic disorders with new-onset atrial fibrillation (AF) and lifetime risk of AF incidence among men and women.

METHODS AND RESULTS

Four thousand one hundred and one men and 5421 women free of AF at baseline (1996-2008) from the population-based Rotterdam Study were included. Sex-specific Cox proportional-hazards regression models were used to assess the association between the burden of cardiometabolic disorders and risk of new-onset AF. The remaining lifetime risk for AF was estimated at index ages of 55, 65, and 75 years up to age 108. Mean age at baseline was 65.5 ± 9.4 years. Median follow-up time was 12.8 years. In the fully adjusted model, a stronger association was found between a larger burden of cardiometabolic disorders and incident AF among women [hazard ratio (HR): 1.33% and 95% conference interval (CI): 1.22-1.46], compared to men [1.18 (1.08-1.29)] (P for sex-interaction <0.05). The lifetime risk for AF significantly increased with the number of cardiometabolic disorders among both sexes. At an index age of 55 years, the lifetime risks (95% CIs) for AF were 27.1% (20.8-33.4), 26.5% (22.8-30.5), 29.9% (26.7-33.2), 30.8% (25.7-35.8), and 33.3% (23.1-43.6) among men, for 0, 1, 2, 3, and ≥4 comorbid cardiometabolic disorders. Corresponding risks were 15.8% (10.5-21.2), 23.0% (19.8-26.2), 29.7% (26.8-32.6), 26.2% (20.8-31.6), and 34.2% (17.3-51.1) among women.

CONCLUSION

We observed a significant combined impact of cardiometabolic disorders on AF risk, in particular among women. Participants with cardiometabolic multimorbidity had a significantly higher lifetime risk of AF, especially at a young index age.

Censored Least Squares for Imputing Missing Values in PARAFAC Tensor Factorization

Tensor factorization is a dimensionality reduction method applied to multidimensional arrays. These methods are useful for identifying patterns within a variety of biomedical datasets due to their ability to preserve the organizational structure of experiments and therefore aid in generating meaningful insights. However, missing data in the datasets being analyzed can impose challenges. Tensor factorization can be performed with some level of missing data and reconstruct a complete tensor. However, while tensor methods may impute these missing values, the choice of fitting algorithm may influence the fidelity of these imputations. Previous approaches, based on alternating least squares with prefilled values or direct optimization, suffer from introduced bias or slow computational performance. In this study, we propose that censored least squares can better handle missing values with data structured in tensor form. We ran censored least squares on four different biological datasets and compared its performance against alternating least squares with prefilled values and direct optimization. We used the error of imputation and the ability to infer masked values to benchmark their missing data performance. Censored least squares appeared best suited for the analysis of high-dimensional biological data by accuracy and convergence metrics across several studies.

Empirically contrasting urine drug screening-based opioid use disorder treatment outcome definitions

BACKGROUND AND AIMS

A lack of consensus on the optimal outcome measures to assess opioid use disorder (OUD) treatment efficacy and their precise definition and computation has hampered the pooling of research data for evidence synthesis and meta-analyses. This study aimed to empirically contrast multiple clinical trial definitions of treatment success by applying them to the same dataset.

METHODS

Data analysis used a suite of functions, developed as a software package for the R language, to operationalize 61 treatment outcome definitions based on urine drug screening (UDS) results. Outcome definitions were derived from clinical trials that are among the most influential in the OUD treatment field. Outcome functions were applied to a harmonized dataset from three large-scale National Drug Abuse Treatment Clinical Trials Network (CTN) studies, which tested various medication for OUD (MOUD) options (n = 2492). Hierarchical clustering was employed to empirically contrast outcome definitions.

RESULTS

The optimal number of clusters identified was three. Cluster 1, comprising eight definitions focused on detecting opioid-positive UDS, did not include missing UDS in outcome calculations, potentially resulting in inflated rates of treatment success. Cluster 2, with the highest variability, included 10 definitions characterized by strict criteria for treatment success, relying heavily on UDS results from either a brief period or a single study visit. The 43 definitions in Cluster 3 represented a diverse range of outcomes, conceptualized as measuring abstinence, use reduction and relapse. These definitions potentially offer more balanced measures of treatment success or failure, as they avoid the extreme methodologies characteristic of Clusters 1 and 2.

CONCLUSIONS

Clinical trials using urine drug screening (UDS) for objective substance use assessment in outcome definitions should consider (1) incorporating missing UDS data in outcome computation and (2) avoiding over-reliance on UDS data confined to a short time frame or the occurrence of a single positive urine test following a period of abstinence.

Tutorial on Biostatistics: Sample Size and Power Calculation for Ophthalmic Studies With Correlated Binary Eye Outcomes

Purpose

To describe and demonstrate sample size and power calculation for ophthalmic studies with a binary outcome from one or both eyes.

Methods

We describe sample size and power calculation for four commonly used eye designs: (1) one-eye design or person-design: one eye per subject or outcome is at person-level; (2) paired design: two eyes per subject and two eyes are in different treatment groups; (3) two-eye design: two eyes per subject and both eyes are in the same treatment group; and (4) mixture design: mixture of one eye and two eyes per subject. For each design, we demonstrate sample size and power calculations in real ophthalmic studies.

Results

Using formulas and commercial or free statistical packages including SAS, STATA, R, and PS, we calculated sample size and power. We demonstrated that different statistical packages require different parameters and provide similar, yet not identical, results. We emphasize that studies using data from two eyes of a subject need to account for the intereye correlation for appropriate sample size and power calculations. We demonstrate the gain in efficiency in designs that include two eyes of a subject compared to one-eye designs.

Conclusions

Ophthalmic studies use different eye designs that include one or both eyes in the same or different treatment groups. Appropriate sample size and power calculations depend on the eye design and should account for intereye correlation when two eyes from some or all subjects are included in a study. Calculations can be executed using formulas and commercial or free statistical packages.

Application of the Estimand Framework to Anesthesia Trials

SUMMARY

Events occurring after randomization, such as use of rescue medication, treatment discontinuation, or death, are common in randomized trials. These events can change either the existence or interpretation of the outcome of interest. However, appropriate handling of these intercurrent events is often unclear. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) E9(R1) addendum introduced the estimand framework, which aligns trial objectives with the design, conduct, statistical analysis, and interpretation of results. This article describes how the estimand framework can be used in anesthesia trials to precisely define the treatment effect to be estimated, key attributes of an estimand, common intercurrent events in anesthesia trials with strategies for handling them, and use of the estimand framework in a hypothetical anesthesia trial on postoperative delirium. When planning anesthesia trials, clearly defining the estimand is vital to ensure that what is being estimated is clearly understood, is clinically relevant, and helps answer the clinical questions of interest.

Comparative effectiveness of an individualized model of hemodialysis vs conventional hemodialysis: a study protocol for a multicenter randomized controlled trial (the TwoPlus trial)

BACKGROUND

Most patients starting chronic in-center hemodialysis (HD) receive conventional hemodialysis (CHD) with three sessions per week targeting specific biochemical clearance. Observational studies suggest that patients with residual kidney function can safely be treated with incremental prescriptions of HD, starting with less frequent sessions and later adjusting to thrice-weekly HD. This trial aims to show objectively that clinically matched incremental HD (CMIHD) is non-inferior to CHD in eligible patients.

METHODS

An unblinded, parallel-group, randomized controlled trial will be conducted across diverse healthcare systems and dialysis organizations in the USA. Adult patients initiating chronic hemodialysis (HD) at participating centers will be screened. Eligibility criteria include receipt of fewer than 18 treatments of HD and residual kidney function defined as kidney urea clearance ≥3.5 mL/min/1.73 m2 and urine output ≥500 mL/24 h. The 1:1 randomization, stratified by site and dialysis vascular access type, assigns patients to either CMIHD (intervention group) or CHD (control group). The CMIHD group will be treated with twice-weekly HD and adjuvant pharmacologic therapy (i.e., oral loop diuretics, sodium bicarbonate, and potassium binders). The CHD group will receive thrice-weekly HD according to usual care. Throughout the study, patients undergo timed urine collection and fill out questionnaires. CMIHD will progress to thrice-weekly HD based on clinical manifestations or changes in residual kidney function. Caregivers of enrolled patients are invited to complete semi-annual questionnaires. The primary outcome is a composite of patients' all-cause death, hospitalizations, or emergency department visits at 2 years. Secondary outcomes include patient- and caregiver-reported outcomes. We aim to enroll 350 patients, which provides ≥85% power to detect an incidence rate ratio (IRR) of 0.9 between CMIHD and CHD with an IRR non-inferiority of 1.20 (α = 0.025, one-tailed test, 20% dropout rate, average of 2.06 years of HD per patient participant), and 150 caregiver participants (of enrolled patients).

DISCUSSION

Our proposal challenges the status quo of HD care delivery. Our overarching hypothesis posits that CMIHD is non-inferior to CHD. If successful, the results will positively impact one of the highest-burdened patient populations and their caregivers.

TRIAL REGISTRATION

Clinicaltrials.gov NCT05828823. Registered on 25 April 2023.

Real-world predictors of changes in fear of COVID-19 in the Japanese general population: a large-scale internet-based cohort study with 20,712 participants

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a respiratory infection that considerably impacts both physical and mental health. In particular, the prolonged nature of psychological issues associated with COVID-19 has become a concern. However, evidence based on longitudinal studies investigating the changes in fear of COVID-19 has been limited, posing a public health challenge.

METHODS

We investigated the predictors of changes in the Fear of COVID-19 Scale (FCV-19S) scores in the general Japanese population using data from a large-scale internet-based cohort study.

RESULTS

We included 20,712 study participants (mean age = 51.1 years, percentage of males = 49.9%). The baseline FCV-19S score for the research participants was 17.0, and one year later, the FCV-19S score decreased to 15.8. The predictors of increase in FCV-19S scores were older age, male sex, COVID-19 requiring oxygen therapy, higher baseline FCV-19S total score, severe psychological distress, never married, worsening subjective health status, a greater number of COVID-19 vaccinations, a history of alcohol dependency, and living with family members. Conversely, the predictors of decrease in FCV-19S scores included habitual alcohol intake, COVID-19 not requiring oxygen therapy and a higher household income. Our study was an internet-based survey focused on residents of Japan, which raises the possibility of selection bias and makes it unclear whether the findings can be extrapolated to other countries and cultures.

CONCLUSION

During the observation period, the FCV-19S scores significantly decreased. Severe COVID-19 requiring oxygen therapy within one year of baseline was the most impactful predictor of an increase in FCV-19S score. On the other hand, mild COVID-19 not requiring oxygen therapy was a predictor of a decrease in FCV-19S scores. Therefore, we believe that it is necessary to adopt individualized approaches stratified by the severity of the infection when addressing the fear of COVID-19.

Advancing equitable access to digital mental health in the Asia-Pacific region in the context of the COVID-19 pandemic and beyond: A modified Delphi consensus study

The COVID-19 pandemic had an unprecedented impact on global mental health and well-being, including across the Asia-Pacific. Efforts to mitigate virus spread led to far-reaching disruption in the delivery of health and social services. In response, there was a rapid shift to the use of digital mental health (DMH) approaches. Though these technologies helped to improve access to care for many, there was also substantial risk of access barriers leading to increased inequities in access to mental health care, particularly among at-risk and equity-deserving populations. The objective of this study was to conduct a needs assessment and identify priorities related to equitable DMH access among at-risk and equity-deserving populations in the Asia Pacific region during the first year of the COVID-19 pandemic. The study consisted of a modified Delphi consensus methodology including two rounds of online surveys and online consultations with stakeholders from across the region. Study participants included policy makers, clinicians and service providers, and people with lived experience of mental health conditions. Results demonstrate that vulnerabilities to negative mental health impacts and access barriers were compounded during the pandemic. Access barriers included a lack of linguistically and culturally appropriate DMH options, low mental health literacy and poor access to technological infrastructure and devices, low levels of awareness and trust of DMH options, and lack of policies and guidelines to support effective and equitable delivery of DMH. Recommendations to improve equitable access include ensuring that diverse people with lived experience are engaged in research, co-design and policy development, the development and implementation of evidence-based and equity-informed guidelines and frameworks, clear communication about DMH evidence and availability, and the integration of DMH into broader health systems. Study results can inform the development and implementation of equitable DMH as its use becomes more widespread across health systems.

Issues and Solutions in Psychiatric Clinical Trial with Case Studies

The coronavirus disease-2019 pandemic resulted in a major increase in depression and anxiety disorders worldwide, which increased the demand for mental health services. However, clinical interventions for treating mental disorders are currently insufficient to meet this growing demand. There is an urgent need to conduct scientific and standardized clinical research that are consistent with the features of mental disorders in order to deliver more effective and safer therapies in the clinic. Our study aimed to expose the challenges, complexities of study design, ethical issues, sample selection, and efficacy evaluation in clinical research for mental disorders. The reliance on subjective symptom presentation and rating scales for diagnosing mental diseases was discovered, emphasizing the lack of clear biological standards, which hampers the construction of rigorous research criteria. We underlined the possibility of psychotherapy in efficacy evaluation alongside medication treatment, proposing for a multidisciplinary approach comprising psychiatrists, neuroscientists, and statisticians. To comprehend mental disorders progression, we recommend the development of artificial intelligence integrated evaluation tools, the use of precise biomarkers, and the strengthening of longitudinal designs. In addition, we advocate for international collaboration to diversity samples and increase the dependability of findings, with the goal of improving clinical research quality in mental disorders through sample representativeness, accurate medical history gathering, and adherence to ethical principles.

Issues and Solutions in Psychiatric Clinical Trial with Case Studies

The coronavirus disease-2019 pandemic resulted in a major increase in depression and anxiety disorders worldwide, which increased the demand for mental health services. However, clinical interventions for treating mental disorders are currently insufficient to meet this growing demand. There is an urgent need to conduct scientific and standardized clinical research that are consistent with the features of mental disorders in order to deliver more effective and safer therapies in the clinic. Our study aimed to expose the challenges, complexities of study design, ethical issues, sample selection, and efficacy evaluation in clinical research for mental disorders. The reliance on subjective symptom presentation and rating scales for diagnosing mental diseases was discovered, emphasizing the lack of clear biological standards, which hampers the construction of rigorous research criteria. We underlined the possibility of psychotherapy in efficacy evaluation alongside medication treatment, proposing for a multidisciplinary approach comprising psychiatrists, neuroscientists, and statisticians. To comprehend mental disorders progression, we recommend the development of artificial intelligence integrated evaluation tools, the use of precise biomarkers, and the strengthening of longitudinal designs. In addition, we advocate for international collaboration to diversity samples and increase the dependability of findings, with the goal of improving clinical research quality in mental disorders through sample representativeness, accurate medical history gathering, and adherence to ethical principles.

Clarifying Causal Effects of Interest and Underlying Assumptions in Randomized and Nonrandomized Clinical Trials in Oncology Using Directed Acyclic Graphs and Single-World Intervention Graphs

Recent clinical trials in oncology have used increasingly complex methodologies, such as causal inference methods for intercurrent events, external control, and covariate adjustment, posing challenges in clarifying the estimand and underlying assumptions. This article proposes expressing causal structures using graphical tools-directed acyclic graphs (DAGs) and single-world intervention graphs (SWIGs)-in the planning phase of a clinical trial. It presents five rules for selecting a sufficient set of adjustment variables on the basis of a diagram representing the clinical trial, along with three case studies of randomized and single-arm trials and a brief tutorial on DAG and SWIG. Through the case studies, DAGs appear effective in clarifying assumptions for identifying causal effects, although SWIGs should complement DAGs due to their limitations in the presence of intercurrent events in oncology research.

Effectiveness and tolerability of rectal ointment and suppositories containing sucralfate for hemorrhoidal symptoms: a prospective, observational study

BACKGROUND AND AIMS

A high number of topical products are available for the treatment of hemorrhoidal symptoms. Sucralfate-based topical products constitute a new treatment alternative that act as a mechanical barrier to facilitate healing. The aim of this prospective, observational study was to determine patient- and physician-assessed effectiveness and tolerability of rectal ointment and suppositories containing sucralfate for the treatment of hemorrhoidal symptoms in routine clinical practice.

METHODS

Adult patients with diagnosed, mild-to-moderate, symptomatic non-bleeding hemorrhoids treated with rectal ointment or suppositories containing sucralfate were enrolled. Patients were administered treatment twice per day for at least 1 week until symptom resolution and/or for a maximum of 4 weeks. The primary endpoint was patient-assessed effectiveness on a modified Symptom Severity Score (mSSS, range 0 to 14). Physician-assessed effectiveness (9 symptoms, 0 to 5 Likert scale), hemorrhoid grade, and patient satisfaction were also determined.

RESULTS

Five investigators enrolled 60 patients; mean age was 48.4 ± 16.6 years and 72.4% were female. Pain or pressure sensitivity was reported as the most severe symptom by patients, and pressure sensitivity, discharge, soiling, and prolapse by physicians. Mean patient-assessed mSSS at baseline was 6.6 ± 1.9 and was significantly improved overall and in the ointment and suppository groups individually by -4.6 ± 2.0, -4.4 ± 1.8, and -4.8 ± 2.2, respectively (p < 0.0001). Investigator-assessed mean baseline symptom score was 18.1 ± 3.9 and improved by -7.1 ± 4.5, -6.9 ± 5.4, and -7.3 ± 3.5, respectively (p < 0.0001). Investigator-assessed symptoms of pressure sensitivity, swelling, and discharge were improved to the greatest extent. Hemorrhoid grade was improved in 38% of patients at the end of treatment. Compliance with treatment was 97.4% and patient satisfaction with application and onset of action was high (81.3% and 76.2%, respectively). Both the ointment and suppository were well tolerated.

CONCLUSIONS

The effectiveness of topical ointment or suppository containing sucralfate on patient- and investigator-assessed hemorrhoidal symptoms in real-life clinical practice was demonstrated. Patient satisfaction was high and treatments were well tolerated. Larger controlled trials are warranted to confirm the results.

Recent advances in the prevention and treatment of decompensated cirrhosis and acute-on-chronic liver failure (ACLF) and the role of biomarkers

The progression of cirrhosis with clinically significant portal hypertension towards decompensated cirrhosis remains clinically challenging and the evolution towards acute-on-chronic liver failure (ACLF), with one or more extrahepatic organ failures, is associated with very high mortality. In the last decade, significant progress has been made in the understanding of the mechanisms leading to decompensation and ACLF. As portal hypertension advances, bacterial translocation across an impaired gut barrier culminates in endotoxaemia, systemic inflammation and cirrhosis-associated immune dysfunction (CAID). Gut-derived systemic inflammation and CAID have become the logical targets for innovative therapies that prevent hepatic decompensation episodes and the progression to ACLF.Furthermore, classification of disease and biomarker discovery to personalise care have advanced in the field. This review discusses progress in biomarker discovery and personalisation of treatment in decompensated cirrhosis and ACLF.

Role of Gut Microbe Composition in Psychosocial Symptom Response to Exercise Training in Breast Cancer Survivors (ROME) study: protocol for a randomised controlled trial

INTRODUCTION

Breast cancer survivors have an increased risk for chronic fatigue and altered gut microbiota composition, both with negative health and quality of life affects. Exercise modestly improves fatigue and is linked to gut microbial diversity and production of beneficial metabolites. Studies suggest that gut microbiota composition is a potential mechanism underlying fatigue response to exercise. Randomised controlled trials testing the effects of exercise on the gut microbiome are limited and there is a scarcity of findings specific to breast cancer survivors. The objective of this study is to determine if fitness-related modifications to gut microbiota occur and, if so, mediate the effects of aerobic exercise on fatigue response.

METHODS AND ANALYSIS

The research is a randomised controlled trial among breast cancer survivors aged 18-74 with fatigue. The primary aim is to determine the effects of aerobic exercise training compared with an attention control on gut microbiota composition. The secondary study aims are to test if exercise training (1) affects the gut microbiota composition directly and/or indirectly through inflammation (serum cytokines), autonomic nervous system (heart rate variability) or hypothalamic-pituitary-adrenal axis mediators (hair cortisol assays), and (2) effects on fatigue are direct and/or indirect through changes in the gut microbiota composition. All participants receive a standardised controlled diet. Assessments occur at baseline, 5 weeks, 10 weeks and 15 weeks (5 weeks post intervention completion). Faecal samples collect the gut microbiome and 16S gene sequencing will identify the microbiome. Fatigue is measured by a 13-item multidimensional fatigue scale.

ETHICS AND DISSEMINATION

The University of Alabama at Birmingham Institutional Review Board (IRB) approved this study on 15 May 2019, UAB IRB#30000320. A Data and Safety Monitoring Board convenes annually or more often if indicated. Findings will be disseminated in peer-reviewed journals and conference presentations.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov, NCT04088708.

Missingness mechanisms and generalizability of patient reported outcome measures in colorectal cancer survivors - assessing the reasonableness of the "missing completely at random" assumption

BACKGROUND

Patient-Reported Outcome Measures (PROM) provide important information, however, missing PROM data threaten the interpretability and generalizability of findings by introducing potential bias. This study aims to provide insight into missingness mechanisms and inform future researchers on generalizability and possible methodological solutions to overcome missing PROM data problems during data collection and statistical analyses.

METHODS

We identified 10,236 colorectal cancer survivors (CRCs) above 18y, diagnosed between 2014 and 2018 through the Danish Clinical Registries. We invited a random 20% (2,097) to participate in a national survey in May 2023. We distributed reminder e-mails at day 10 and day 20, and compared Initial Responders (response day 0-9), Subsequent Responders (response day 10-28) and Non-responders (no response after 28 days) in demographic and cancer-related characteristics and PROM-scores using linear regression.

RESULTS

Of the 2,097 CRCs, 1,188 responded (57%). Of these, 142 (7%) were excluded leaving 1,955 eligible CRCs. 628 (32%) were categorized as initial responders, 418 (21%) as subsequent responders, and 909 (47%) as non-responders. Differences in demographic and cancer-related characteristics between the three groups were minor and PROM-scores only marginally differed between initial and subsequent responders.

CONCLUSION

In this study of long-term colorectal cancer survivors, we showed that initial responders, subsequent responders, and non-responders exhibit comparable demographic and cancer-related characteristics. Among respondents, Patient-Reported Outcome Measures were also similar, indicating generalizability. Assuming Patient-Reported Outcome Measures of subsequent responders represent answers by the non-responders (would they be available), it may be reasonable to judge the missingness mechanism as Missing Completely At Random.

A Description of Missing Data in Single-Case Experimental Designs Studies and an Evaluation of Single Imputation Methods

Missing data is inevitable in single-case experimental designs (SCEDs) studies due to repeated measures over a period of time. Despite this fact, SCEDs implementers such as researchers, teachers, clinicians, and school psychologists usually ignore missing data in their studies. Performing analyses without considering missing data in an intervention study using SCEDs or a meta-analysis study including SCEDs studies in a topic can lead to biased results and affect the validity of individual or overall results. In addition, missingness can undermine the generalizability of SCEDs studies. Considering these drawbacks, this study aims to give descriptive and advisory information to SCEDs practitioners and researchers about missing data in single-case data. To accomplish this task, the study presents information about missing data mechanisms, item level and unit level missing data, planned missing data designs, drawbacks of ignoring missing data in SCEDs, and missing data handling methods. Since single imputation methods among missing data handling methods do not require complicated statistical knowledge, are easy to use, and hence are more likely to be used by practitioners and researchers, the present study evaluates single imputation methods in terms of intervention effect sizes and missing data rates by using a real and hypothetical data sample. This study encourages SCEDs implementers, and also meta-analysts to use some of the single imputation methods to increase the generalizability and validity of the study results in case they encounter missing data in their studies.

Statistical considerations for some issues in clinical bridging studies evaluating companion diagnostic devices

An in vitro diagnostic device (IVD) that is essential for the safe and effective use of a corresponding therapeutic product is commonly referred to as companion diagnostic device. Clinical trials using companion diagnostic devices (tests) together with therapies can yield the information necessary to address whether both products are safe and effective. A clinical trial ideally assesses safety and effectiveness of a therapy, where the clinical trial enrolls subjects based on the final market ready companion diagnostic test (CDx). However, such a requirement may be difficult to accomplish or impractical to achieve at the time of the clinical trial enrollment, due to unavailability of the CDx. Instead, clinical trial assay(s) (CTA), which are not the final marketable product, are often used in enrollment of patients in a clinical trial. When CTA is used for subject enrollment, a clinical bridging study provides a mechanism to bridge the clinical efficacy of the therapeutic product from CTA to CDx. This manuscript reviews some issues and challenges commonly associated with clinical bridging studies, including missing data, use of local tests for enrollment, prescreening before enrollment, and evaluation of CDx for low positive rate biomarkers, with particular focus on clinical trials using a binary endpoint and provide alternative statistical methodologies to assess effectiveness of CDx.

Design, cohort profile and comparison of the KTD-Innov study: a prospective multidimensional biomarker validation study in kidney allograft rejection

There is an unmet need for robust and clinically validated biomarkers of kidney allograft rejection. Here we present the KTD-Innov study (ClinicalTrials.gov, NCT03582436), an unselected deeply phenotyped cohort of kidney transplant recipients with a holistic approach to validate the clinical utility of precision diagnostic biomarkers. In 2018-2019, we prospectively enrolled consecutive adult patients who received a kidney allograft at seven French centers and followed them for a year. We performed multimodal phenotyping at follow-up visits, by collecting clinical, biological, immunological, and histological parameters, and analyzing a panel of 147 blood, urinary and kidney tissue biomarkers. The primary outcome was allograft rejection, assessed at each visit according to the international Banff 2019 classification. We evaluated the representativeness of participants by comparing them with patients from French, European, and American transplant programs transplanted during the same period. A total of 733 kidney transplant recipients (64.1% male and 35.9% female) were included during the study. The median follow-up after transplantation was 12.3 months (interquartile range, 11.9-13.1 months). The cumulative incidence of rejection was 9.7% at one year post-transplant. We developed a distributed and secured data repository in compliance with the general data protection regulation. We established a multimodal biomarker biobank of 16,736 samples, including 9331 blood, 4425 urinary and 2980 kidney tissue samples, managed and secured in a collaborative network involving 7 clinical centers, 4 analytical platforms and 2 industrial partners. Patients' characteristics, immune profiles and treatments closely resembled those of 41,238 French, European and American kidney transplant recipients. The KTD-Innov study is a unique holistic and multidimensional biomarker validation cohort of kidney transplant recipients representative of the real-world transplant population. Future findings from this cohort are likely to be robust and generalizable.

Efficacy and acceptability of cognitive-behavioral therapy and serotonin reuptake inhibitors for pediatric obsessive-compulsive disorder: a network meta-analysis

BACKGROUND

Cognitive-behavioral therapy (CBT) and serotonin reuptake inhibitors (SRIs) are recommended treatments for pediatric obsessive-compulsive disorder (OCD), but their relative efficacy and acceptability have not been comprehensively examined. Further, it remains unclear whether the efficacy of in-person CBT is conserved when delivered in other formats, such as over telephone/webcam or as Internet-delivered CBT (ICBT).

METHODS

PubMed, PsycINFO, trial registries, and previous systematic reviews were searched for randomized controlled trials (RCTs) comparing CBT (in-person, webcam/telephone-delivered, or ICBT) or SRIs with control conditions or each other. Network meta-analyses were conducted to examine efficacy (post-treatment Children's Yale-Brown Obsessive Compulsive Scale) and acceptability (treatment discontinuation). Confidence in effect estimates was evaluated with CINeMA (Confidence in Network Meta-Analysis).

RESULTS

Thirty eligible RCTs and 35 contrasts comprising 2,057 youth with OCD were identified. In-person CBT was significantly more efficacious than ICBT, waitlist, relaxation training, and pill placebo (MD range: 3.95-11.10; CINeMA estimate of confidence: moderate) but did not differ significantly from CBT delivered via webcam/telephone (MD: 0.85 [-2.51, 4.21]; moderate), SRIs (MD: 3.07 [-0.07, 6.20]; low), or the combination of in-person CBT and SRIs (MD: -1.20 [-5.29, 2.91]; low). SRIs were significantly more efficacious than pill placebo (MD: 4.59 [2.70, 6.48]; low) and waitlist (MD: 8.03 [4.24, 11.82]; moderate). No significant differences for acceptability emerged, but confidence in estimates was low.

CONCLUSIONS

In-person CBT and SRIs produce clear benefits compared to waitlist and pill placebo and should be integral parts of the clinical management of pediatric OCD, with in-person CBT overall having a stronger evidence base. The combination of in-person CBT and SRIs may be most efficacious, but few studies hinder firm conclusions. The efficacy of CBT appears conserved when delivered via webcam/telephone, while more trials evaluating ICBT are needed.

Joint modeling of longitudinal CD4 count data and time to first occurrence of composite outcome

In this study, we jointly modeled longitudinal CD4 count data and survival outcome (time-to-first occurrence of composite outcome of death, cardiac tamponade or constriction) in other to investigate the effects of Mycobacterium indicus pranii immunotherapy and the CD4 count measurements on the hazard of the composite outcome among patients with HIV and tuberculous (TB) pericarditis. In this joint modeling framework, the models for longitudinal and the survival data are linked by an association structure. The association structure represents the hazard of the event for 1-unit increase in the longitudinal measurement. Models fitting and parameter estimation were carried out using R version 4.2.3. The association structure that represents the strength of the association between the hazard for an event at time point j and the area under the longitudinal trajectory up to the same time j provides the best fit. We found that 1-unit increase in CD4 count results in 2 % significant reduction in the hazard of the composite outcome. Among HIV and TB pericarditis individuals, the hazard of the composite outcome does not differ between of M.indicus pranii versus placebo. Application of joint models to investigate the effect of M.indicus pranii on the hazard of the composite outcome is limited. Hence, this study provides information on the effect of M.indicus pranii on the hazard of the composite outcome among HIV and TB pericarditis patients.

Use of Sequential Hot-Deck Imputation for Missing Health Care Systems Data for Population Health Research

Electronic medical record (EMR) data present many opportunities for population health research. The use of EMR data for population risk models can be impeded by the high proportion of missingness in key patient variables. Common approaches like complete case analysis and multiple imputation may not be appropriate for some population health initiatives that require a single, complete analytic data set. In this study, we demonstrate a sequential hot-deck imputation (HDI) procedure to address missingness in a set of cardiometabolic measures in an EMR data set. We assessed the performance of sequential HDI within the individual variables and a commonly used composite risk score. A data set of cardiometabolic measures based on EMR data from 2 large urban hospitals was used to create a benchmark data set with simulated missingness. Sequential HDI was applied, and the resulting data were used to calculate atherosclerotic cardiovascular disease risk scores. The performance of the imputation approach was assessed using a set of metrics to evaluate the distribution and validity of the imputed data. Of the 567,841 patients, 65% had at least 1 missing cardiometabolic measure. Sequential HDI resulted in the distribution of variables and risk scores that reflected those in the simulated data while retaining correlation. When stratified by age and sex, risk scores were plausible and captured patterns expected in the general population. The use of sequential HDI was shown to be a suitable approach to multivariate missingness in EMR data. Sequential HDI could benefit population health research by providing a straightforward, computationally nonintensive approach to missing EMR data that results in a single analytic data set.

Drug use and COVID-19 testing, vaccination, and infection among underserved, minority communities in Miami, Florida

The Coronavirus Disease 2019 (COVID-19) pandemic has disproportionately impacted people who use drugs (PWUD). This study explored relationships between drug use, COVID-19 testing, vaccination, and infection. This cross-sectional study was conducted in Miami, Florida between March 2021 and October 2022 as part of the National Institutes of Health (NIH) Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) initiative and the Miami Adult Studies on HIV (MASH) cohort. Users of cannabis, cocaine/crack, heroin/fentanyl, methamphetamines, hallucinogens, and/or prescription drug misuse in the previous 12 months were considered PWUD. Sociodemographic data, COVID-19 testing history, and vaccination-related beliefs were self-reported. Vaccinations were confirmed with medical records and positivity was determined with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. Statistical analyses included chi-square tests and logistic regression. Of 1,780 participants, median age was 57 years, 50.7% were male, 50.2% Non-Hispanic Black, and 66.0% reported an annual income less than $15,000. Nearly 28.0% used drugs. PWUD were less likely than non-users to self-report ever testing positive for SARS-CoV-2 (14.7% vs. 21.0%, p = 0.006). However, 2.6% of participants tested positive for SARS-CoV-2, with no significant differences between PWUD and non-users (3.7% vs. 2.2%, p = 0.076). PWUD were more likely than non-users to experience difficulties accessing testing (10.2% vs. 7.1%, p = 0.033), vaccine hesitancy (58.9% vs. 43.4%, p = 0.002) and had lower odds of receiving any dose of a COVID-19 vaccine compared to non-users (aOR, 0.63; 95% CI, 0.49-0.81; p<0.001). PWUD presented with greater difficulties accessing COVID-19 testing, greater vaccine hesitancy, and lower odds of vaccination. Testing and immunization plans that are tailored to the needs of PWUD and consider access, trust-building campaigns, and education may be needed.

A cluster-randomized trial of water, sanitation, handwashing and nutritional interventions on stress and epigenetic programming

A regulated stress response is essential for healthy child growth and development trajectories. We conducted a cluster-randomized trial in rural Bangladesh (funded by the Bill & Melinda Gates Foundation, ClinicalTrials.gov NCT01590095) to assess the effects of an integrated nutritional, water, sanitation, and handwashing intervention on child health. We previously reported on the primary outcomes of the trial, linear growth and caregiver-reported diarrhea. Here, we assessed additional prespecified outcomes: physiological stress response, oxidative stress, and DNA methylation (N = 759, ages 1-2 years). Eight neighboring pregnant women were grouped into a study cluster. Eight geographically adjacent clusters were block-randomized into the control or the combined nutrition, water, sanitation, and handwashing (N + WSH) intervention group (receiving nutritional counseling and lipid-based nutrient supplements, chlorinated drinking water, upgraded sanitation, and handwashing with soap). Participants and data collectors were not masked, but analyses were masked. There were 358 children (68 clusters) in the control group and 401 children (63 clusters) in the intervention group. We measured four F2-isoprostanes isomers (iPF(2α)-III; 2,3-dinor-iPF(2α)-III; iPF(2α)-VI; 8,12-iso-iPF(2α)-VI), salivary alpha-amylase and cortisol, and methylation of the glucocorticoid receptor (NR3C1) exon 1F promoter including the NGFI-A binding site. Compared with control, the N + WSH group had lower concentrations of F2-isoprostanes isomers (differences ranging from -0.16 to -0.19 log ng/mg of creatinine, P < 0.01), elevated post-stressor cortisol (0.24 log µg/dl; P < 0.01), higher cortisol residualized gain scores (0.06 µg/dl; P = 0.023), and decreased methylation of the NGFI-A binding site (-0.04; P = 0.037). The N + WSH intervention enhanced adaptive responses of the physiological stress system in early childhood.

Disability and COVID-19: Challenges, testing, vaccination, and postponement and avoidance of medical care among minoritized communities

BACKGROUND

People with disabilities face heightened vulnerability to COVID-19.

OBJECTIVE

This study investigated (1) the relationships between disability and COVID-19-related challenges, testing, vaccination, and infection and (2) predictors of loss of healthcare coverage and postponement and avoidance of medical care during the pandemic.

METHODS

This cross-sectional study was conducted in Miami, Florida, between March 2021 and February 2022 as part of the NIH Rapid Acceleration of Diagnostics-Underserved Populations initiative. Disability was defined using a standard measure that assesses six universal functions. Participants reported sociodemographic data, COVID-19 testing, infection history, challenges, and healthcare history. Vaccinations were confirmed with medical records and COVID-19 positivity was assessed using real-time reverse transcription-polymerase chain reaction. Statistical analyses included multivariable logistic regression.

RESULTS

Among 1,689 participants with a median age of 57.0, 50.6% were male, and 48.9% were non-Hispanic Black. Disability was associated with greater odds of all assessed COVID-19 challenges: healthcare (aOR:1.60; 95% CI:1.23-2.07), housing (aOR:2.15; 95% CI:1.62-2.87), insufficient food (aOR:1.97; 95% CI:1.54-2.52), water scarcity (aOR:2.33; 95% CI:1.60-3.37), medications (aOR:2.04; 95% CI:1.51-2.77), and transportation (aOR:2.56; 95% CI:1.95-3.36). Those reporting employment disability were less likely to have received COVID-19 testing (81.1% vs. 85.3%, p = 0.026) or to have history of COVID-19 positivity (aOR:0.63; 95% CI:0.44-0.92). Disability predicted avoidance (aOR:2.76; 95% CI:1.95-3.91) and postponement (aOR: 2.24; 95% CI:1.72-2.91) of medical care.

CONCLUSIONS

Disability is associated with higher odds of COVID-19 challenges and postponement and avoidance of medical care. Those reporting employment disability had a lower likelihood of COVID-19 testing. Public health responses to healthcare crises should prioritize the special challenges of people living with disabilities.

Enhancing Lifestyles in the Metabolic syndrome (ELM) multisite behavioral efficacy trial. Design and baseline cohort

BACKGROUND

Prevalence of metabolic syndrome (MetS) increased from one-quarter to one-third of the U.S. adult population over 8 years and is spreading to young adults and Asian and Hispanic Americans. Diagnosed when >3 out of 5 cardiometabolic risk factors are present, there is widespread agreement that its fundamental roots are in a lifestyle characterized by poor dietary quality and physical inactivity. Past lifestyle trials for MetS produce benefits that have limited sustainability, suggesting the need for new treatment approaches.

METHODS

This is the design and baseline cohort of the Enhancing Lifestyles in the Metabolic Syndrome (ELM) multi-site trial. The trial tests the hypothesis that a habit-based lifestyle treatment offered over 6 months, followed by 18 monthly maintenance contacts, can produce 4 new diet, physical activity, and mindfulness habits and, if so, sustained MetS remission. The design is an individually randomized, partially clustered group treatment trial of 618 participants with the MetS recruited from 5 sites in the U.S. and randomized to a small group lifestyle treatment or an enhanced standard of care education comparator. The primary outcome is MetS remission at 24 months. Secondary outcomes compare arms at 6, 15, and 24 months on MetS components, lifestyle targets, weight, body mass index, hemoglobin A1c, LDL cholesterol, medications, quality of life, psychosocial factors, and cost-effectiveness.

RESULTS

The cohort of 618 participants was recruited by screening 14,817 over 2.5 years (screening to enrollment ratio 24:1). Recruitment exceeded the target of 600 despite 2 COVID-19 pauses. The mean age was 55.5 years, 24.3% were male, 25.5% were a racial minority, 9.7% identified as Hispanic, and 83.0% were classified as obese (body mass index >30). The most common MetS components were abdominal obesity (97.7%) and elevated blood pressure or antihypertensive medication (86.2%).

CONCLUSIONS

The geographic, sociodemographic, and clinical diversity of the cohort, combined with rigorous behavioral efficacy trial methods, will provide a conclusive answer to the question of whether this habit-based lifestyle program can produce sustained 24-month remission of the MetS and thereby help to curb a significant and growing public health problem.

Reported Hearing Outcome Measures Following Stereotactic Radiosurgery for Vestibular Schwannoma: A Scoping Review

Background  Evidence on hearing outcome measures when assessing hearing preservation following stereotactic radiosurgery (SRS) for adults with vestibular schwannoma (VS) has not previously been collated in a structured review. Objective  The objective of the present study was to perform a scoping review of the evidence regarding the choice of hearing outcomes and other methodological characteristics following SRS for adults with VS. Methods  The protocol was registered in the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) and reported according to the Preferred Reporting Items for Systematic Review and Meta-Analyses extension guidelines for scoping reviews. A systematic search of five online databases revealed 1,591 studies, 247 of which met the inclusion criteria. Results  The majority of studies ( n  = 213, 86%) were retrospective cohort or case series with the remainder ( n  = 34, 14%) prospective cohort. Pure-tone audiometry and speech intelligibility were included in 222 (90%) and 158 (64%) studies, respectively, often summarized within a classification scheme and lacking procedural details. Fifty-nine (24%) studies included self-report measures. The median duration of follow-up, when reported, was 43 months (interquartile range: 29, 4-150). Conclusion  Evidence on hearing disability after SRS for VS is based on low-quality studies which are inherently susceptible to bias. This review has highlighted an urgent need for a randomized controlled trial assessing hearing outcomes in patients with VS managed with radiosurgery or radiological observation. Similarly, consensus and coproduction of a core outcome set to determine relevant hearing and communication outcome domains is required. This will ensure that patient priorities, including communication abilities in the presence of background noise and reduced participation restrictions, are addressed.

Comparison of methods that combine multiple randomized trials to estimate heterogeneous treatment effects

Individualized treatment decisions can improve health outcomes, but using data to make these decisions in a reliable, precise, and generalizable way is challenging with a single dataset. Leveraging multiple randomized controlled trials allows for the combination of datasets with unconfounded treatment assignment to better estimate heterogeneous treatment effects. This article discusses several nonparametric approaches for estimating heterogeneous treatment effects using data from multiple trials. We extend single-study methods to a scenario with multiple trials and explore their performance through a simulation study, with data generation scenarios that have differing levels of cross-trial heterogeneity. The simulations demonstrate that methods that directly allow for heterogeneity of the treatment effect across trials perform better than methods that do not, and that the choice of single-study method matters based on the functional form of the treatment effect. Finally, we discuss which methods perform well in each setting and then apply them to four randomized controlled trials to examine effect heterogeneity of treatments for major depressive disorder.

Efficacy and acceptability of a self-guided internet-delivered cognitive-behavioral educational program for obsessive-compulsive symptoms with international recruitment

Cognitive-behavioural therapy is an effective treatment for obsessive-compulsive disorder (OCD). However, there are many barriers in accessing this treatment, with stigma being a particularly prominent barrier for many patients. Self-guided internet-delivered cognitive-behavioural therapy (ICBT), which does not require any contact with a therapist, has the potential to overcome this barrier. However, there is limited research on the efficacy of self-guided ICBT for OCD. The aim of the current study was to examine the efficacy of self-guided ICBT for OCD in a large international sample. Two hundred and sixteen participants were included in the study (Mage = 34.00; SD = 12.57; 72.7% female). On the primary outcome measure, the Yale-Brown Obsessive-Compulsive Scale (YBOCS), a medium within-group effect size was found from pre-treatment to post-treatment (g = 0.63), and a large within-group effect size was found from pre-treatment to 3-month follow-up (g = 0.98). Approximately one-quarter to one-third of participants met criteria for clinically significant improvement at post-treatment and 3-month follow-up (11% and 17% met criteria for remission at post-treatment and 3-month follow-up, respectively). These results demonstrate that self-guided ICBT may be an efficacious treatment for individuals with OCD who cannot or do not wish to engage with a mental health professional, resulting in medium to large effect sizes.

Testing the missing at random assumption in generalized linear models in the presence of instrumental variables

Practical problems with missing data are common, and many methods have been developed concerning the validity and/or efficiency of statistical procedures. On a central focus, there have been longstanding interests on the mechanism governing data missingness, and correctly deciding the appropriate mechanism is crucially relevant for conducting proper practical investigations. In this paper, we present a new hypothesis testing approach for deciding between the conventional notions of missing at random and missing not at random in generalized linear models in the presence of instrumental variables. The foundational idea is to develop appropriate discrepancy measures between estimators whose properties significantly differ only when missing at random does not hold. We show that our testing approach achieves an objective data-oriented choice between missing at random or not. We demonstrate the feasibility, validity, and efficacy of the new test by theoretical analysis, simulation studies, and a real data analysis.

How do sports injury epidemiological outcomes vary depending on athletes' response rates to a weekly online questionnaire? An analysis of 39-week follow-up from 391 athletics (track and field) athletes

OBJECTIVE

To explore how sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) vary depending on the response rates to a weekly online self-reported questionnaire for athletes.

METHODS

Weekly information on athletics injuries and exposure from 391 athletics (track and field) athletes was prospectively collected over 39 weeks (control group of the PREVATHLE randomized controlled trial) using an online self-reported questionnaire. The data were used to calculate sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) for sub-groups with different minimum individual athletes' response rates (i.e., from at least 100%, at least 97%, at least 95%, … to at least 0% response rate). We then calculated the relative variation between each sub-group and the sub-group with a 100% response rate as a reference. A substantial variation was considered when the relative variation was greater than one SD or 95% CI of the respective epidemiological outcome calculated in the sub-group with a 100% response rate.

RESULTS

Of 15 249 expected weekly questionnaires, 7209 were completed and returned, resulting in an overall response rate of 47.3%. The individual athletes' response rates ranged from 0% (n = 51) to 100% (n = 100). The prevalence, average weekly prevalence, and time to first injury only varied substantially for the sub-groups below a 5%, 10% and 18% minimum individual response rate, respectively. The incidence and injury burden showed substantial variations for all sub-groups with a response rate below 100%.

CONCLUSIONS

Epidemiological outcomes varied depending on the minimum individual athletes' response rate, with injury prevalence, average weekly prevalence, and time to first injury varying less than injury incidence and injury burden. This highlights the need to take into account the individual response rate when calculating epidemiological outcomes, and determining the optimal study-specific cut-offs of the minimum individual response rate needed.

Missing Outcome Data in Recent Perinatal and Neonatal Clinical Trials

Missing outcome data in clinical trials may jeopardize the validity of the trial results and inferences for clinical practice. Although sick and preterm newborns are treated as a captive patient population during their stay in the NICUs, their long-term outcomes are often ascertained after discharge. This greatly increases the risk of attrition. We surveyed recently published perinatal and neonatal randomized trials in 7 high-impact general medical and pediatric journals to review the handling of missing primary outcome data and any choice of imputation methods. Of 87 eligible trials in this survey, 77 (89%) had incomplete primary outcome data. The missing outcome data were not discussed at all in 9 reports (12%). Most study teams restricted their main analysis to participants with complete information for the primary outcome (61 trials; 79%). Only 38 of the 77 teams (49%) performed sensitivity analyses using a variety of imputation methods. We conclude that the handling of missing primary outcome data was frequently inadequate in recent randomized perinatal and neonatal trials. To improve future approaches to missing outcome data, we discuss the strengths and limitations of different imputation methods, the appropriate estimation of sample size, and how to deal with data withdrawal. However, the best strategy to reduce bias from missing outcome data in perinatal and neonatal trials remains prevention. Investigators should anticipate and preempt missing data through careful study design, and closely monitor all incoming primary outcome data for completeness during the conduct of the trial.