Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values

Quality of life in older adults with mood states associated with bipolar disorder: A secondary analysis of the English longitudinal study of ageing data

OBJECTIVES

To investigate: (i) whether mood states associated with bipolar disorder are associated with poorer quality of life in older adults, and (ii) what are some of the predictors of quality of life in older adults with mood states associated with bipolar disorder.

METHODS

The authors completed a cross-sectional multilevel analysis of panel data from seven waves of The English Longitudinal Study of Ageing dataset. The main analysis included 567 participants who reported experiencing mood states associated with bipolar disorder. Some participants reported this in more than one wave, resulting in 835 observations of mood states associated with bipolar disorder across the seven waves. Quality of life was assessed using the Control, Autonomy, Self-realization, and Pleasure-19 (CASP-19) measure.

RESULTS

The presence of mood states associated with bipolar disorder was significantly associated with poorer quality of life, even after controlling for multiple covariates (age, sex, social isolation, loneliness, alcohol use, education level, and economic status). Loneliness significantly predicted poorer quality of life in older adults with mood states associated with bipolar disorder. In contrast, higher educational attainment and being female predicted better quality of life in this group.

CONCLUSIONS

Older adults with mood states associated with bipolar disorder have potentially worse quality of life compared to the general population, which may be partly driven by loneliness. This has ramifications for the support offered to this population and suggests that treatments should focus on reducing loneliness to improve outcomes.

Limited early IVIG for the treatment of pediatric myelin oligodendrocyte glycoprotein antibody-associated disease

BACKGROUND AND OBJECTIVES

This study aimed to evaluate whether a 6-month (limited) course of early IVIG is an effective strategy for relapse prevention in children with myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) versus only acute therapies or other early immunotherapies.

METHODS

This was a retrospective multicenter observational study of pediatric MOGAD patients from the US Network of Pediatric Multiple Sclerosis Centers with disease onset between October 1996 and December 2022. Controls were matched to limited early IVIG subjects using a 3:1 ratio. Hazard ratios of time to relapse and rate ratios of annualized relapse rate were calculated. The cumulative probability of remaining relapse-free was evaluated with the Kaplan-Meier method.

RESULTS

We identified 130 unique control subjects treated before second attack with acute treatments only used in matching, 18 subjects treated with limited early IVIG, and 23 subjects treated with other early immunotherapy. The time to relapse was not different between either the limited early IVIG group and control group (HR 0.60 [0.22, 1.66], p = 0.32) or other early immunotherapy group (HR 0.98 [0.27, 3.6], p = 0.98). The limited early IVIG group showed a lower annualized relapse rate, although not statistically significant (RR 0.44 [0.17, 1.14], p = 0.09) compared with controls and a similar annualized relapse rate compared with the other early immunotherapy group (RR 0.56 [0.19, 1.69], p = 0.30).

DISCUSSION

Although underpowered, our results suggest that the use of a limited, 6-month course of early IVIG may reduce the risk of multiphasic disease in pediatric MOGAD.

Baseline habitual dietary nitrate intake and Alzheimer's Disease related neuroimaging biomarkers in the Australian Imaging, Biomarkers and Lifestyle study of ageing

BACKGROUND

Dietary nitrate, as a nitric oxide (NO) precursor, may support brain health and protect against dementia.

OBJECTIVE

Our primary aim was to investigate whether dietary nitrate is associated with neuroimaging markers of brain health linked with Alzheimer's disease (AD).

PARTICIPANTS

Study participants were cognitively unimpaired individuals from the Australian Imaging, Biomarkers and Lifestyle Study of Ageing (AIBL) who had β-amyloid positron emission tomography (PET) scans (n = 554) and magnetic resonance imaging (MRI) scans (n = 335) and had completed a Food Frequency Questionnaire at baseline.

METHODS

Source-specific nitrate intakes were estimated using comprehensive nitrate food composition databases. Rates of cerebral β-amyloid (Aβ) deposition, measured using PET, and rates of brain atrophy, measured using MRI, were assessed between baseline and 126-months follow-up, at intervals of 18 months. Multivariable-adjusted linear mixed effect models were used to examine associations between baseline source-specific nitrate intake and rates of (i) cerebral Aβ deposition and (ii) brain atrophy, over the 126 months of follow-up. Analyses were carried out following stratification of the sample by established dementia Alzheimer's disease (AD) risk factors including sex and presence or absence of the apolipoprotein E (APOE) ε4 allele.

RESULTS

In women carriers of the APOE ε4 allele, higher plant sourced nitrate intake (median intake 121 mg/day), was associated with a slower rate of cerebral Aβ deposition [β: 4.47 versus 8.99 Centiloid (CL) /18 months, p < 0.05] and right hippocampal atrophy [-0.01 versus -0.03 mm3 /18 months, p < 0.01], after multivariable adjustments. Moderate intake showed protective associations in men carriers and in both men and women non-carriers of APOE ε4.

CONCLUSIONS

Associations were observed between plant-derived nitrate intake and cerebral Aβ deposition, particularly in high-risk populations (women and APOE ε4 carriers). Associations were also observed for brain volume atrophy, however these exhibited subgroup variability without clear patterns relative to sex and APOE ε4 allele carriage. These findings suggest a potential link between plant-sourced nitrate and AD related neuroimaging markers of brain health improved brain health, but further validation in larger studies is required.

Marital Status-Specific Associations Between Multidomain Leisure Activities and Cognitive Reserve in Clinically Unimpaired Older Adults: Based on a National Chinese Cohort

Background: It is unclear how marital status moderates the association between multidomain leisure activities and the progression of cognitive decline in community-dwelling older adults. Methods: Data from the Chinese Longitudinal Healthy Longevity Survey with up to 10 years of follow-up were used. The study included participants aged ≥65 years without cognitive impairment at baseline. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Linear mixed-effect models were used to evaluate the modifying effect of marriage on leisure activities (multiple types, frequency, and single type) and cognitive decline. Results: A total of 5286 participants (aged 79.01 ± 9.54 years, 50.0% women, and 61.4% rural residents) were enrolled. The results indicated that marital status moderates the relationship between leisure activities and cognitive decline. In the unmarried group, multi-type and high-frequency leisure activities were more strongly associated with slower cognitive decline. Specific activities such as gardening, reading, performing household chores, and playing cards were found to significantly contribute to cognitive protection exclusively within the unmarried group, with no such effect observed in the married group. Conclusions: Marital status affects the relationship between participation in multiple leisure activities and cognitive decline in cognitively intact elderly people. For unmarried older adults, regular participation in leisure activities may be an effective intervention.

G-formula with multiple imputation for causal inference with incomplete data

G-formula is a popular approach for estimating the effects of time-varying treatments or exposures from longitudinal data. G-formula is typically implemented using Monte-Carlo simulation, with non-parametric bootstrapping used for inference. In longitudinal data settings missing data are a common issue, which are often handled using multiple imputation, but it is unclear how G-formula and multiple imputation should be combined. We show how G-formula can be implemented using Bayesian multiple imputation methods for synthetic data, and that by doing so, we can impute missing data and simulate the counterfactuals of interest within a single coherent approach. We describe how this can be achieved using standard multiple imputation software and explore its performance using a simulation study and an application from cystic fibrosis.

Instability in the environment and children's in-school self-regulatory behaviors

Introduction

Experiences of chronic and/or extreme stress early in childhood are associated with altered self-regulatory behaviors. However, there is a range of variability in children's behavioral outcomes after experiences of stress. Understanding what contributes to this variability in children's responses to stress can aid in the development of more effective programs aimed at supporting children's self-regulatory processes. The current study examined relationships between indices of environmental stability and changes in children's self-regulatory behaviors.

Methods

Ratings of children's self-regulatory behavior were collected in collaboration with a school program once a month over the course of the academic year. Measures of environmental stability were collected for each child.

Results

Children demonstrated increases in self-regulatory behaviors over the course of the study. Additionally, children in home environments characterized by high levels of environmental instability demonstrated greater positive behavior change during the program.

Discussion

This study suggests that there are important individual differences in children's patterns of self-regulatory behavior changes, and points to complex interactions between children's home environment, implementation of a more positive and stable environment, and changes in behavior.

Relationship between collider bias and interactions on the log-additive scale

Collider bias occurs when conditioning on a common effect (collider) of two variables X , Y . In this article, we quantify the collider bias in the estimated association between exposure X and outcome Y induced by selecting on one value of a binary collider S of the exposure and the outcome. In the case of logistic regression, it is known that the magnitude of the collider bias in the exposure-outcome regression coefficient is proportional to the strength of interaction δ 3 between X and Y in a log-additive model for the collider: P ( S = 1 | X , Y ) = exp { δ 0 + δ 1 X + δ 2 Y + δ 3 X Y } . We show that this result also holds under a linear or Poisson regression model for the exposure-outcome association. We then illustrate numerically that even if a log-additive model with interactions is not the true model for the collider, the interaction term in such a model is still informative about the magnitude of collider bias. Finally, we discuss the implications of these findings for methods that attempt to adjust for collider bias, such as inverse probability weighting which is often implemented without including interactions between variables in the weighting model.

The differential impact of early graft dysfunction in kidney donation after brain death and after circulatory death: Insights from the Dutch National Transplant Registry

Kidneys donated after circulatory death (DCD) perform similarly to kidneys donated after brain death (DBD). However, the respective incidences of delayed graft function (DGF) differ. This questions the donor type-specific impact of early graft function on long-term outcomes. Using competing risk and Cox-regression analysis, we compared death-censored graft loss between types of early graft function: DGF (temporary dialysis dependency started within 7 days after transplantation), slow graft function (3-day plasma creatinine decline less than 10% per day), and immediate graft function. In 1061 DBD and 1605 DCD graft recipients (January 2014 until January 2023), graft survival was similar. DGF was associated with death-censored graft loss in DBD and DCD (adjusted hazard ratios: DGF in DBD: 1.79 [1.04-2.91], P = .027, DGF in DCD: 1.84 [1.18-2.87], P = .008; Reference: no DGF). Slow graft function was associated with death-censored graft loss in DBD, but not significantly in DCD (adjusted hazard ratios DBD: 2.82 (1.34-5.93), P = .007, and DCD: 1.54 (0.72-3.35), P = .262; Reference: immediate graft function). Early graft dysfunction has a differential impact on graft outcome in DBD and DCD. The differences between DBD and DCD should be accounted for in research and the clinic.

Vertebroplacental ratio for prediction of perinatal outcome and operative delivery for suspected fetal compromise: prospective observational cohort study

OBJECTIVE

To investigate differences in fetal vertebroplacental ratio (VPR) depending on the occurrence of operative delivery for suspected fetal compromise (ODFC) and composite perinatal outcome (CPO) at delivery.

METHODS

This was a prospective observational cohort study conducted in the Department of Obstetrics and Gynecology at the University Hospitals of Leuven, Leuven, Belgium, between December 2022 and April 2024. Women with a term (37-42 gestational weeks) singleton pregnancy with an appropriate-for-gestational-age (AGA) fetus were recruited, before cervical dilatation reached 5 cm, for sonographic fetal weight estimation (EFW) and Doppler sonography of the umbilical artery (UA), umbilical vein (UV), middle cerebral artery (MCA) and vertebral artery (VA). The primary outcomes were differences in VPR multiples of the median (MoM) depending on the occurrence of ODFC and CPO at delivery (based on UA cord blood pH and base excess, 1-min and 5-min Apgar score, and neonatal intensive care unit admission). We explored the technical feasibility of fetal Doppler sonography in this setting and differences in Doppler findings from individual fetal vessels (UA, UV blood flow (UVF), MCA, VA) and related parameters (UVF/EFW and cerebroplacental ratio (CPR)). We also investigated whether adding individual sonographic variables to baseline clinical prediction models could improve discriminatory power (using the area under the receiver-operating-characteristics curve (AUC)) and predictive accuracy (using the Brier score) for both outcomes.

RESULTS

A total of 161 women were recruited. The mean ± SD maternal age was 32.2 ± 3.8 years and approximately half (53.4%) of the women were nulliparous. Most (88.2%) women had labor induced. The mean ± SD gestational age at delivery was 39.3 ± 1.0 weeks and the mean ± SD ultrasound-to-delivery interval was 10.4 ± 2.75 h. An adverse CPO occurred in 13.3% of cases and ODFC occurred in 17.4%. No difference in mean VPR MoM was observed between cases with normal vs adverse CPO (1.04 ± 0.26 vs 1.17 ± 0.25; P = 0.09), or between cases which underwent ODFC vs those which did not (1.06 ± 0.29 vs 1.06 ± 0.26; P = 0.97). Likewise, no differences in other Doppler variables (UA pulsatility index (PI) MoM, MCA-PI MoM, VA-PI MoM, CPR MoM) were observed for both outcomes, except for significantly higher UVF rates in the adverse CPO group (both absolute (P = 0.02) and corrected for EFW (P = 0.048)). For both outcomes, adding VPR MoM or any other sonographic variable to baseline prediction models, which consisted solely of clinical variables, did not improve predictive accuracy or discriminatory power. The baseline model AUC and Brier score values were 0.68 (95% CI, 0.57-0.79) and 0.14 for adverse CPO, and 0.72 (95% CI, 0.61-0.83) and 0.13 for ODFC, respectively.

CONCLUSIONS

Although technically feasible to measure in most women with an AGA fetus admitted for spontaneous or induced labor at term, no difference in VPR MoM was observed depending on the occurrence of ODFC or CPO at delivery. Moreover, adding VPR MoM or any other sonographic variable to a baseline clinical prediction model did not improve predictive accuracy or discriminatory power for either outcome. Hence, peripartum ultrasound for the assessment of fetal weight and placental function has limited added value for predicting adverse labor outcomes in a low-risk obstetric population. © 2025 International Society of Ultrasound in Obstetrics and Gynecology.

Multiple Imputation for Longitudinal Data: A Tutorial

Longitudinal studies are frequently used in medical research and involve collecting repeated measures on individuals over time. Observations from the same individual are invariably correlated and thus an analytic approach that accounts for this clustering by individual is required. While almost all research suffers from missing data, this can be particularly problematic in longitudinal studies as participation often becomes harder to maintain over time. Multiple imputation (MI) is widely used to handle missing data in such studies. When using MI, it is important that the imputation model is compatible with the proposed analysis model. In a longitudinal analysis, this implies that the clustering considered in the analysis model should be reflected in the imputation process. Several MI approaches have been proposed to impute incomplete longitudinal data, such as treating repeated measurements of the same variable as distinct variables or using generalized linear mixed imputation models. However, the uptake of these methods has been limited, as they require additional data manipulation and use of advanced imputation procedures. In this tutorial, we review the available MI approaches that can be used for handling incomplete longitudinal data, including where individuals are clustered within higher-level clusters. We illustrate implementation with replicable R and Stata code using a case study from the Childhood to Adolescence Transition Study.

The Impact of Stressful Childhood Life Events on Atopic Dermatitis Disease Activity and Severity

Atopic dermatitis (AD) is a prevalent condition associated with stress. However, epidemiological data on the impact of both common and severe childhood stressors are limited. This study aimed to evaluate the impact of stressful life events throughout early childhood on AD activity and severity. We conducted a longitudinal cohort study of 13,972 children aged 1-8.5 years from the Avon Longitudinal Study of Parents and Children. Responses to a standardized stressful life event scale were linked to repeated measures of annual AD period prevalence and severity. After adjusting for potential confounders, we found that for each SD increase in stressful life events, there was a small increased risk of concurrent AD activity (OR = 1.04, 95% confidence interval = 1.01-1.07), which was higher for moderate-to-severe AD (OR = 1.13, 95% confidence interval = 1.03-1.23) and for a cumulative measure of stressful events across childhood (OR = 1.11, 95% confidence interval = 1.07-1.16). The association was driven by common stressful life events which were perceived as more impactful to individual children such as starting a new school or having a new baby sibling, than severe adverse childhood events such as being separated from a parent or abused. These results may help provide anticipatory guidance to families.

Estimating hypothetical estimands with causal inference and missing data estimators in a diabetes trial case study

The ICH E9 addendum on estimands in clinical trials provides a framework for precisely defining the treatment effect that is to be estimated, but says little about estimation methods. Here, we report analyses of a clinical trial in type 2 diabetes, targeting the effects of randomized treatment, handling rescue treatment and discontinuation of randomized treatment using the so-called hypothetical strategy. We show how this can be estimated using mixed models for repeated measures, multiple imputation, inverse probability of treatment weighting, G-formula, and G-estimation. We describe their assumptions and practical details of their implementation using packages in R. We report the results of these analyses, broadly finding similar estimates and standard errors across the estimators. We discuss various considerations relevant when choosing an estimation approach, including computational time, how to handle missing data, whether to include post intercurrent event data in the analysis, whether and how to adjust for additional time-varying confounders, and whether and how to model different types of intercurrent event data separately.

Dietary Composition, Meal Timing, and Cancer-Related Fatigue: Insights From the Women's Healthy Eating and Living Study

BACKGROUND

Cancer-related fatigue is difficult to treat, and dietary interventions are promising yet underused.

OBJECTIVE

We explored associations between dietary patterns and fatigue, and the effect of a dietary intervention versus control on fatigue using Women's Healthy Eating and Living study data, plus mediators and moderators of the intervention effect.

METHODS

The Women's Healthy Eating and Living study was a randomized controlled trial among early-stage breast cancer survivors. The 4-year intervention encouraged fruits, vegetables, fiber, and 15% to 20% calories from fat. Fatigue outcomes included a 9-item energy scale and a single-item tiredness question. Dietary quality was estimated using a modified Healthy Eating Index (24-hour dietary recall) and serum carotenoid concentrations. Nutrient timing was obtained from 4-day food logs.

RESULTS

Among 2914 total participants, lower body mass index was associated with less tiredness and more energy at baseline ( P < .001 for both). Earlier start and end times for daily eating windows were associated with less tiredness ( P = .014 and P = .027, respectively) and greater energy ( P = .006 and P = .102, respectively). The intervention did not lead to improvements in fatigue on average ( P > .125). However, the intervention was more effective for participants who were younger, had fewer comorbidities, and did not have radiation treatment. Mediators included increases in serum carotenoids, increases in the modified Healthy Eating Index, and weight loss/maintenance.

CONCLUSION

Diet quality and earlier eating windows were associated with less fatigue.

IMPLICATIONS FOR PRACTICE

Programs that encourage high diet quality and a morning meal and discourage nighttime eating should be tested for efficacy in reducing cancer-related fatigue in survivorship.

The T4-L1-Hip Axis: Sagittal Spinal Realignment Targets in Long-Construct Adult Spinal Deformity Surgery: Early Impact

BACKGROUND

Our understanding of the relationship between sagittal alignment and mechanical complications is evolving. In normal spines, the L1-pelvic angle (L1PA) accounts for the magnitude and distribution of lordosis and is strongly associated with pelvic incidence (PI), and the T4-pelvic angle (T4PA) is within 4° of the L1PA. We aimed to examine the clinical implications of realignment to a normal L1PA and T4-L1PA mismatch.

METHODS

A prospective multicenter adult spinal deformity registry was queried for patients who underwent fixation from the T1-T5 region to the sacrum and had 2-year radiographic follow-up. Normal sagittal alignment was defined as previously described for normal spines: L1PA = PI × 0.5 - 21°, and T4-L1PA mismatch = 0°. Mechanical failure was defined as severe proximal junctional kyphosis (PJK), displaced rod fracture, or reoperation for junctional failure, pseudarthrosis, or rod fracture within 2 years. Multivariable nonlinear logistic regression was used to define target ranges for L1PA and T4-L1PA mismatch that minimized the risk of mechanical failure. The relationship between changes in T4PA and changes in global sagittal alignment according to the C2-pelvic angle (C2PA) was determined using linear regression. Lastly, multivariable regression was used to assess associations between initial postoperative C2PA and patient-reported outcomes at 1 year, adjusting for preoperative scores and age.

RESULTS

The median age of the 247 included patients was 64 years (interquartile range, 57 to 69 years), and 202 (82%) were female. Deviation from a normal L1PA or T4-L1PA mismatch in either direction was associated with a significantly higher risk of mechanical failure, independent of age. Risk was minimized with an L1PA of PI × 0.5 - (19° ± 2°) and T4-L1PA mismatch between -3° and +1°. Changes in T4PA and in C2PA at the time of final follow-up were strongly associated (r 2 = 0.96). Higher postoperative C2PA was independently associated with more disability, more pain, and worse self-image at 1 year.

CONCLUSIONS

We defined sagittal alignment targets using L1PA (relative to PI) and the T4-L1PA mismatch, which are both directly modifiable during surgery. In patients undergoing long fusion to the sacrum, realignment based on these targets may lead to fewer mechanical failures.

LEVEL OF EVIDENCE

Therapeutic Level III . See Instructions for Authors for a complete description of levels of evidence.

Moving Beyond Medical Statistics: A Systematic Review on Missing Data Handling in Electronic Health Records

Background: Missing data in electronic health records (EHRs) presents significant challenges in medical studies. Many methods have been proposed, but uncertainty exists regarding the current state of missing data addressing methods applied for EHR and which strategy performs better within specific contexts. Methods: All studies referencing EHR and missing data methods published from their inception until 2024 March 30 were searched via the MEDLINE, EMBASE, and Digital Bibliography and Library Project databases. The characteristics of the included studies were extracted. We also compared the performance of various methods under different missingness scenarios. Results: After screening, 46 studies published between 2010 and 2024 were included. Three missingness mechanisms were simulated when evaluating the missing data methods: missing completely at random (29/46), missing at random (20/46), and missing not at random (21/46). Multiple imputation by chained equations (MICE) was the most popular statistical method, whereas generative adversarial network-based methods and the k nearest neighbor (KNN) classification were the common deep-learning-based or traditional machine-learning-based methods, respectively. Among the 26 articles comparing the performance among medical statistical and machine learning approaches, traditional machine learning or deep learning methods generally outperformed statistical methods. Med.KNN and context-aware time-series imputation performed better for longitudinal datasets, whereas probabilistic principal component analysis and MICE-based methods were optimal for cross-sectional datasets. Conclusions: Machine learning methods show significant promise for addressing missing data in EHRs. However, no single approach provides a universally generalizable solution. Standardized benchmarking analyses are essential to evaluate these methods across different missingness scenarios.

Pathologic Characteristics and Surgical Outcomes of Pediatric Versus Adult Well-Differentiated Thyroid Cancer

OBJECTIVE

Despite the rising incidence of pediatric differentiated thyroid cancer (DTC), postoperative outcomes for such tumors have not been well-characterized. The objective of this study was to compare pathologic tumor characteristics and treatment outcomes for pediatric and adult patients with DTC.

STUDY DESIGN

Retrospective case-control study.

SETTING

National database.

METHODS

Pediatric (<18 years old) and adult (≥18 years old) patients who underwent surgery for DTC in the National Cancer Database (2004-2020) were included. Multivariable logistic, negative binomial, and linear regressions were used to compare pathologic tumor characteristics, treatment characteristics, and short-term surgical outcomes.

RESULTS

337,864 patients with DTC met the study eligibility criteria; 3584 (1.1%) were pediatric patients and 334,280 (98.9%) were adults. After adjustment, pediatric patients were found to have higher rates of pathologic T upstaging (adjusted odds ratio [ORadj]: 1.40, 95% confidence interval [CI]: 1.23-1.59), N upstaging (ORadj: 2.53, 95% CI: 2.23-2.88), and extrathyroidal extension (ORadj: 1.58, 95% CI: 1.29-1.94), compared to adult patients. Pediatric patients were also more likely to receive neck dissection (ORadj: 2.80, 95% CI: 2.55-3.07) and radioactive iodine (ORadj: 1.42, 95% CI: 1.30-1.55). Pediatric patients had higher rates of positive surgical margins (ORadj: 1.25, 95% CI: 1.11-1.41) and 30-day readmissions (ORadj: 1.26, 95% CI: 1.00-1.58) than adult patients.

CONCLUSION

These findings demonstrate that pediatric DTC is associated with more aggressive disease presentations, more radical treatment, and worse short-term surgical outcomes compared to DTC in adults. Pediatric DTC should be considered a unique clinical entity that requires personalized evaluation and multidisciplinary treatment by specialized providers.

Handling missing data in longitudinal clinical trials: three examples from the pediatric psychology literature

Researchers by default tend to choose complex models when analyzing nonindependent response variable data, this may be particularly applicable in the analysis of longitudinal trial data, possibly due to the ability of such models to easily address missing data by default. Both maximum-likelihood (ML) estimation and multiple imputation (MI) are well-known to be acceptable methods for handling missing data, but much of the recently published quantitative literature has addressed questions regarding the research designs and circumstances under which one should be chosen over the other. The purpose of this article is threefold. First, to clearly define the assumptions underlying three common longitudinal trial data analysis models for continuous dependent variable data: repeated measures analysis of covariance (RM-ANCOVA), generalized estimating equation (GEE), and a longitudinal linear mixed model (LLMM). Second, to clarify when ML or MI should be chosen, and to introduce researchers to an easy-to-use, empirically well-validated, and freely available missing data multiple imputation program: BLIMP. Third, to show how missing longitudinal trial data can be handled in the three data analysis models using three popular statistical analysis software packages (SPSS, Stata, and R) while keeping the published quantitative research in mind.

Weight trends among adults with diabetes or hypertension during the COVID-19 pandemic: an observational study using OpenSAFELY

BACKGROUND

COVID-19 pandemic restrictions may have influenced behaviours related to weight.

AIM

To describe patterns of weight change among adults living in England with type 2 diabetes (T2D) and/or hypertension during the pandemic.

DESIGN AND SETTING

An observational cohort study using the routinely collected health data of approximately 40% of adults living in England, accessed through the OpenSAFELY service inside TPP.

METHOD

Clinical and sociodemographic characteristics associated with rapid weight gain (>0.5 kg/m2/year) were investigated using multivariable logistic regression.

RESULTS

Data were extracted on adults with T2D (n = 1 231 455, 43.9% female, and 76.0% White British) or hypertension (n = 3 558 405, 49.7% female, and 84.3% White British). Adults with T2D lost weight overall (median δ = -0.1 kg/m2/year [interquartile range {IQR} -0.7-0.4]). However, rapid weight gain was common (20.7%) and associated with the following: sex (male versus female: adjusted odds ratio [aOR] 0.78 [95% confidence interval {CI} = 0.77 to 0.79]); age (older age reduced odds, for example, aged 60-69 years versus 18-29 years: aOR 0.66 [95% CI = 0.61 to 0.71]); deprivation (least deprived Index of Multiple Deprivation [IMD] quintile versus most deprived IMD quintile: aOR 0.87 [95% CI = 0.85 to 0.89]); White ethnicity (Black versus White: aOR 0.95 [95% CI = 0.92 to 0.98]); mental health conditions (for example, depression: aOR 1.13 [95% CI = 1.12 to 1.15]); and diabetes treatment (non-insulin treatment versus no pharmacological treatment: aOR 0.68 [95% CI = 0.67 to 0.69]). Adults with hypertension maintained stable weight overall (median δ = 0.0 kg/m2/year [IQR -0.6-0.5]); however, rapid weight gain was common (24.7%) and associated with similar characteristics as in T2D.

CONCLUSION

Among adults living in England with T2D and/or hypertension, rapid pandemic weight gain was more common among females, younger adults, those living in more deprived areas, and those with mental health conditions.

An Awareness, Courage, and Love Online Group Intervention for Chinese Older Adults in the Post-Pandemic Era: Study Protocol for a Randomised Controlled Trial

Background. Social connections not only contribute to psychological and emotional well-being but also positively impact physical health, with social isolation and loneliness linked to early mortality and detrimental health outcomes. Objectives. This study aims to evaluate an online Awareness, Courage, and Love (ACL) group intervention designed to enhance social connectedness and subjective well-being while reducing loneliness, depression, and anxiety among older adults. Methods. This randomised controlled trial (RCT) will involve an intervention group receiving a 2 h ACL session via videoconferencing. Eligible participants selected after screening will be assigned randomly to either a treatment or waitlist-control group. Participants in both conditions will complete the assessments at three time points, including baseline, post-intervention, and one-month follow-up. Tools for assessing the concerned variables include the Inclusion of Other in the Self Scale, de Jong Gierveld Loneliness Scale, Patient Health Questionnaire-9 (PHQ-9), Generalised Anxiety Disorder 2-item (GAD-2) Scale, and World Health Organisation-Five Well-Being Index (WHO-5). Conclusions. This study will offer a robust framework for investigating the impact of the online ACL intervention on loneliness and social connectedness among Chinese older adults. The result of this study will reach theoretical, empirical, practical, and teaching significance on mental health care strategies for Chinese older adults.

Comparison of Researcher-Led versus Teacher-Led effectiveness and fidelity: A Hybrid Type 1 study of Kids SIPsmartER in Appalachia middle schools

The implementation of school-based obesity-prevention programs is understudied. Kids SIPsmartER is a 6-month, school-based, behavioral intervention for Appalachian middle school students and includes a teacher implementation strategy. Kids SIPsmartER effectively reduced students' sugar-sweetened beverages (SSB) when Researcher-Led. However, Teacher-Led effectiveness and fidelity are unknown. To explore the relative SSB effects when Kids SIPsmartER was Researcher-Led versus Teacher-Led and to examine teacher fidelity. This study of secondary outcomes used a quasi-experimental analytic approach of a Hybrid Type 1 effectiveness-implementation and cluster randomized controlled tria (RCT) of Kids SIPsmartER. Student SSB behaviors and teacher self-rated fidelity were assessed, respectively, with the validated Beverage Intake Questionnaire (BEVQ-15) and lesson-specific checklists. Analyses included descriptive statistics and modified two-part models with time-fixed effects and school-year cohort cluster controls. The analytic sample included students from six control schools (n = 220), six Researcher-Led intervention schools (n = 306), and five Teacher-Led intervention schools (n = 218), as well as eight teachers. Teacher-Led intervention students decreased SSB by -14.3 ounces/day (95% confidence interval = -15.4, -13.2; P < .001). Relative to control and to Researcher-Led intervention, the Teacher-Led treatment effect among students was -11.6 ounces SSB/day (P < .001, effect size = 0.75) and -4.3 (P = .004, effect size = 0.25), respectively. Teachers returned fidelity checklists for 90% of planned lessons. Fidelity averaged 94% (SD = 4.0%) among returned forms and 85% (SD = 18.9%) when missing forms were counted as zeros. Teachers can implement Kids SIPsmartER with high fidelity and produce statistically and clinically meaningful improvements in students' SSB behaviors. Findings have implications for the sustained implementation of Kids SIPsmartER and other school-based obesity-prevention programs. Clinical Trial information: NCT03740113.

Externally Controlled Studies Using Real-World Data in Patients With Hematological Cancers: A Systematic Review

Importance

The use of real-world data (RWD) external control arms in prospective studies is increasing. The advantages, including the immediate availability of a control population, must be balanced with the requirements of meeting evidentiary standards.

Objective

To address the question of whether and to what extent the methods of RWD studies compare to standard methods used in randomized clinical trials.

Evidence Review

A systematic search across 4 electronic databases and Google Scholar was conducted from January 1, 2000, to October 23, 2023. Studies were included in the systematic review if they compared an intervention arm in a clinical trial to an RWD control arm in patients with hematological cancers and if they were published between 2000 and 2023.

Findings

Thirty-two prospective intervention studies incorporating external control data from RWD sources of patients with hematological cancers were identified. A total of 4306 patients from intervention arms and 10 594 from RWD control arms were included across all studies. Only 2 studies (6%) included prospectively collected RWD. The complete trial inclusion criteria were applied to the RWD cohort in 7 studies (22%). Four studies (13%) published the statistical analysis plan and prespecified use of RWD. A total of 23 studies (72%) applied matching algorithms for trial and RWD cohorts, including matching for demographic, disease, and/or therapy-related characteristics. The end point criteria were the same as the trial in 8 studies (25%). In contrast, 12 studies (38%) used different end points, and 12 (38%) did not provide an end point definition for the RWD. Twelve studies (38%) had a median follow-up difference of less than a year between arms. Eight studies (25%) reported toxic effect data for the trial arm, of which 5 studies reported toxic effect data for the RWD arm.

Conclusions and Relevance

In this systematic review, limitations were observed in the application of clinical trial eligibility criteria to RWD, statistical rigor and application of matching methods, the definition of end points, follow-up, and reporting of adverse events, which may challenge the conclusions reported in studies using RWD.

Early, medium and long-term mental health in cancer survivors compared with cancer-free comparators: matched cohort study using linked UK electronic health records

Background

We aimed to compare the risk of incident depression, anxiety, non-fatal self-harm and completed suicide in survivors from a wide range of cancers versus cancer-free individuals.

Methods

We used electronic health records from the United Kingdom Clinical Practice Research Datalink linked to cancer registry data, hospital admissions data and death records between 1998 and 2021. Adult survivors of the 20 most common cancers were matched (age, sex, general practice) 1:10 to cancer-free individuals. Cox regression models, adjusted for shared risk factors, were used to estimate associations between cancer survivorship and mental health outcomes.

Findings

853,177 adults with cancer diagnosed in 1998-2018 were matched to 8,106,643 cancer-free individuals. Survivors of all 20 cancer types under study had a higher risk of experiencing a new episode of anxiety and depression during follow-up compared with cancer-free individuals; there was also evidence of raised risks of non-fatal self-harm in 17/20 cancers and completed suicide in 8/20 cancers. Effect sizes were greatest in cancers with poorer 5-year survival: hazard ratios (HRs) for anxiety and depression of 1.1-1.2 were seen for malignant melanoma survivors, while HRs for both outcomes were >2.5 for lung and oesophageal cancer survivors. HRs were highest in the first year from cancer diagnosis, reducing over time since diagnosis. However, 5-year cancer survivors still experienced elevated risks of a subsequent new episode of anxiety or depression, in 18/20 cancers.

Interpretation

Survivors of the 20 most common cancers were at increased risk of experiencing depression and anxiety, and these increased risks persisted in medium-to long-term cancer survivors. Substantially raised risks of non-fatal self-harm and completed suicide were also seen for several types of cancer. The risks of all mental health outcomes were generally higher in survivors of cancers with poorer prognosis. Our findings suggest a need for improved psychological support for all patients with cancer.

Funding

Wellcome Trust.

The association between religious beliefs and values with inflammation among Middle-age and older adults

Objectives: Dimensions of religion and spirituality are associated with better emotional, physical, and cognitive health. However, the underlying physiological mechanisms are not well known. We investigated the relationship between dimensions of religion and spirituality with levels of C-reactive protein (CRP), a biomarker of systematic inflammation, in middle-aged and older adults in the United States.Methods: In this descriptive longitudinal study using secondary data, we used proportional odds models of the generalized estimating equation (GEE) to assess the association between religious beliefs and values and religious service attendance with CRP levels from respondents (n = 2,385) aged 50 years and older in the Health and Retirement Study from 2006 to 2014.Results: Middle-aged to older adults who reported higher religious beliefs and values had lower levels of CRP, controlling for age, sex, education, marital status, race, household income, and health, such as hypertension, diabetes, cancer, and body mass index (BMI).Conclusion: Religious beliefs and values are associated with lower CRP levels among middle-aged and older adults in the U.S. This study adds to the understanding of biological processes underlying the relationship between dimensions of religion and spirituality with better cognitive and physical health, potentially through inflammation.

Structural brain differences in patients with schizophrenia spectrum disorders with and without auditory verbal hallucinations

Schizophrenia spectrum disorders (SSD) are debilitating, with auditory verbal hallucinations (AVHs) being a core characteristic. While gray matter volume (GMV) reductions are commonly replicated in SSD populations, the neural basis of AVHs remains unclear. Using previously published data, this study comprises two main analyses, one of GMV dissimilarities between SSD and healthy controls (HC), and one of GMV differences specifically associated with AVHs. Structural brain images from 71 adults with (n = 46) and without (n = 25) SSD were employed. Group differences in GMVs of the cortex, anterior cingulate (ACC), superior temporal gyrus (STG), hippocampi, and thalami were assessed. Additionally, volumes of left Heschl's gyrus (HG) in a subgroup experiencing AVHs (AVH+, n = 23) were compared with those of patients who did not (AVH-, n = 23). SSD patients displayed reduced GMVs of the cortex, ACC, STG, hippocampi, and thalami compared to HC. AVH+ had significantly reduced left HG volume when compared to AVH-. Finally, a right-lateralized ventral prefrontal cluster was found to be uniquely associated with AVH severity. This study corroborates previous findings of GMV reductions in SSD cohorts. Chiefly, our secondary analysis suggests that AVHs are associated with language areas and their contralateral homologues.

Association between surgeon training grade and the risk of revision following unicompartmental knee replacement: An analysis of National Joint Registry data

BACKGROUND

Unicompartmental knee replacements (UKRs) are performed by surgeons at various stages in training with varying levels of supervision, but we do not know if this is a safe practice with comparable outcomes to consultant-performed UKR. The aim of this study was to use registry data for England and Wales to investigate the association between surgeon grade (consultant, or trainee), the senior supervision of trainees (supervised by a scrubbed consultant, or not), and the risk of revision surgery following UKR.

METHODS AND FINDINGS

We conducted an observational study using prospectively collected data from the National Joint Registry for England and Wales (NJR). We included adult patients who underwent primary UKR for osteoarthritis (n = 106,206), recorded in the NJR between 2003 and 2019. Exposures were the grade of the operating surgeon (consultant, or trainee) and whether or not trainees were directly supervised by a consultant during the procedure (referred to as "supervised by a scrubbed consultant"). The primary outcome was all-cause revision surgery. The secondary outcome was the number of procedures revised for the following specific indications: aseptic loosening/lysis, infection, progression of osteoarthritis, unexplained pain, and instability. Flexible parametric survival models were adjusted for patient, operation, and healthcare setting factors. We included 106,206 UKRs in 91,626 patients, of which 4,382 (4.1%) procedures were performed by a trainee. The unadjusted cumulative probability of failure at 15 years was 17.13% (95% CI [16.44, 17.85]) for consultants, 16.42% (95% CI [14.09, 19.08]) for trainees overall, 15.98% (95% CI [13.36, 19.07]) for trainees supervised by a scrubbed consultant, and 17.32% (95% CI [13.24, 22.50]) for trainees not supervised by a scrubbed consultant. There was no association between surgeon grade and all-cause revision in either crude or adjusted models (adjusted HR = 1.01, 95% CI [0.90, 1.13]; p = 0.88). Trainees achieved comparable all-cause survival to consultants, regardless of the level of scrubbed consultant supervision (supervised: adjusted HR = 0.99, 95% CI [0.87, 1.14]; p = 0.94; unsupervised: adjusted HR = 1.03, 95% CI [0.87, 1.22]; p = 0.74). Limitations of this study relate to its observational design and include: the potential for nonrandom allocation of cases by consultants to trainees; residual confounding; and the use of the binary variable "surgeon grade," which does not capture variations in the level of experience between trainees.

CONCLUSIONS

This nationwide study of UKRs with over 16 years' follow up demonstrates that trainees within the current training system in England and Wales achieve comparable all-cause implant survival to consultants. These findings support the current methods by which surgeons in England and Wales are trained to perform UKR.

The impact of soccer-specific psychophysiological stress on inhibition and cognitive flexibility in elite youth players

While researchers and practitioners attribute an essential role to executive functions (EFs) for soccer performance, the usefulness of respective diagnostics and the predictive value remain unclear. One limitation restricting the translation and relevance of study results to improve actual game performance is the insufficient consideration of competitive conditions. Thus, this study aimed to conduct soccer-specific cognitive diagnostics under a soccer-specific psychophysiological stress condition, mimicing the demands of a competitive game. A total of 92 (Mage = 15.17, SDage = 1.45) youth elite players performed tests for inhibition (flanker task) or cognitive flexibility (number-letter task) with a soccer-specific motor response (i.e., pass into goals). After a pre-test in a neutral condition, players were randomly assigned to a neutral (moderate soccer-specific exercise) or a stress condition (physical stress and competitive instructions and filming for psychological stress). Objective (i.e., cortisol, heart rate variability) and subjective stress-related measures (i.e., SAM, VAS) were assessed six times throughout experimental procedure. Analyses revealed significant interaction effects between time and condition for all objective and subjective variables indicating a successful experimental stress induction. For cognitive performance, results revealed significant main effects of time, but no significant interaction effects between time and condition. However, descriptive statistics suggested improved performance under stress, with decreased flanker effect and switch costs. Additionally, response time variability in the flanker task significantly decreased in the stress condition. These findings offer insights into individual stress perception and processing under game-related psychophysiological demands, expanding previous research on situational EF alterations that also hold relevance for applied practitioners.

Multi-metric comparison of machine learning imputation methods with application to breast cancer survival

Handling missing data in clinical prognostic studies is an essential yet challenging task. This study aimed to provide a comprehensive assessment of the effectiveness and reliability of different machine learning (ML) imputation methods across various analytical perspectives. Specifically, it focused on three distinct classes of performance metrics used to evaluate ML imputation methods: post-imputation bias of regression estimates, post-imputation predictive accuracy, and substantive model-free metrics. As an illustration, we applied data from a real-world breast cancer survival study. This comprehensive approach aimed to provide a thorough assessment of the effectiveness and reliability of ML imputation methods across various analytical perspectives. A simulated dataset with 30% Missing At Random (MAR) values was used. A number of single imputation (SI) methods - specifically KNN, missMDA, CART, missForest, missRanger, missCforest - and multiple imputation (MI) methods - specifically miceCART and miceRF - were evaluated. The performance metrics used were Gower's distance, estimation bias, empirical standard error, coverage rate, length of confidence interval, predictive accuracy, proportion of falsely classified (PFC), normalized root mean squared error (NRMSE), AUC, and C-index scores. The analysis revealed that in terms of Gower's distance, CART and missForest were the most accurate, while missMDA and CART excelled for binary covariates; missForest and miceCART were superior for continuous covariates. When assessing bias and accuracy in regression estimates, miceCART and miceRF exhibited the least bias. Overall, the various imputation methods demonstrated greater efficiency than complete-case analysis (CCA), with MICE methods providing optimal confidence interval coverage. In terms of predictive accuracy for Cox models, missMDA and missForest had superior AUC and C-index scores. Despite offering better predictive accuracy, the study found that SI methods introduced more bias into the regression coefficients compared to MI methods. This study underlines the importance of selecting appropriate imputation methods based on study goals and data types in time-to-event research. The varying effectiveness of methods across the different performance metrics studied highlights the value of using advanced machine learning algorithms within a multiple imputation framework to enhance research integrity and the robustness of findings.

Physical activity based on daily steps in patients with chronic musculoskeletal pain: evolution and associated factors

BACKGROUND

People with chronic musculoskeletal pain (CMSP) often have low physical activity. Various factors can influence the activity level. The aim of this study was to monitor physical activity, assessed by the number of steps per day, over time in people with CMSP and identify factors that could be associated with this activity feature.

METHODS

This prospective study involved people undergoing rehabilitation following an orthopedic trauma that had led to CMSP. At entry, participants completed self-reported questionnaires assessing pain, anxiety, depression, catastrophyzing, kinesiophobia, and behavioural activity patterns (avoidance, pacing and overdoing). They also underwent functional tests, assessing walking endurance and physical fitness. To determine daily step counts, participants wore an accelerometer for 1 week during rehabilitation and 3 months post-rehabilitation. The number of steps per day was compared among three time points: weekend of rehabilitation (an estimate of pre-rehabilitation activity; T1), weekdays of rehabilitation (T2), and post-rehabilitation (T3). Linear regression models were used to analyze the association between daily steps at T2 and at T3 and self-reported and performance-based parameters.

RESULTS

Data from 145 participants were analyzed. The mean number of steps was significantly higher during T2 than T1 and T3 (7323 [3047] vs. 4782 [2689], p < 0.001, Cohen's d = 0.769, and 4757 [2680], p < 0.001, Cohen's d = 0.693), whereas T1 and T3 results were similar (p = 0.92, Cohen's d = 0.008). Correlations of number of steps per day among time points were low (r ≤ 0.4). Multivariable regression models revealed an association between daily steps at T2 and pain interfering with walking, anxiety and overdoing behaviour. Daily steps at T3 were associated with overdoing behaviour and physical fitness.

CONCLUSIONS

Despite chronic pain, people in rehabilitation after an orthopedic trauma increased their physical activity if they were given incentives to do so. When these incentives disappeared, most people returned to their previous activity levels. A multimodal follow-up approach could include both therapeutic and environmental incentives to help maintain physical activity in this population.

Correcting mortality estimates among children and youth on antiretroviral therapy in southern Africa: A comparative analysis between a multi-country tracing study and linkage to a health information exchange

OBJECTIVES

The objective of this study is to assess the outcomes of children, adolescents and young adults with HIV reported as lost to follow-up, correct mortality estimates for children, adolescents and young adults with HIV for unascertained outcomes in those loss to follow-up (LTFU) based on tracing and linkage data separately using data from the International epidemiology Databases to Evaluate AIDS in Southern Africa.

METHODS

We included data from two different populations of children, adolescents and young adults with HIV; (1) clinical data from children, adolescents and young adults with HIV aged ≤24 years from Lesotho, Malawi, Mozambique, Zambia and Zimbabwe; (2) clinical data from children, adolescents and young adults with HIV aged ≤14 years from the Western Cape (WC) in South Africa. Outcomes of patients lost to follow-up were available from (1) a tracing study and (2) linkage to a health information exchange. For both populations, we compared six methods for correcting mortality estimates for all children, adolescents and young adults with HIV.

RESULTS

We found substantial variations of mortality estimates among children, adolescents and young adults with HIV reported as lost to follow-up versus those retained in care. Ascertained mortality was higher among lost and traceable children, adolescents and young adults with HIV and lower among lost and linkable than those retained in care (mortality: 13.4% [traced] vs. 12.6% [retained-other Southern Africa countries]; 3.4% [linked] vs. 9.4% [retained-WC]). A high proportion of lost to follow-up children, adolescents and young adults with HIV had self-transferred (21.0% and 47.0%) in the traced and linked samples, respectively. The uncorrected method of non-informative censoring yielded the lowest mortality estimates among all methods for both tracing (6.0%) and linkage (4.0%) approaches at 2 years from ART start. Among corrected methods using ascertained data, multiple imputation, incorporating ascertained data (MI(asc.)) and inverse probability weighting with logistic weights were most robust for the tracing approach. In contrast, for the linkage approach, MI(asc.) was the most robust.

CONCLUSIONS

Our findings emphasise that lost to follow-up is non-ignorable and both tracing and linkage improved outcome ascertainment: tracing identified substantial mortality in those reported as lost to follow-up, whereas linkage did not identify out-of-facility deaths, but showed that a large proportion of those reported as lost to follow-up were self-transfers.

predicTTE: An accessible and optimal tool for time-to-event prediction in neurological diseases

Time-to-event prediction is a key task for biological discovery, experimental medicine, and clinical care. This is particularly true for neurological diseases where development of reliable biomarkers is often limited by difficulty visualising and sampling relevant cell and molecular pathobiology. To date, much work has relied on Cox regression because of ease-of-use, despite evidence that this model includes incorrect assumptions. We have implemented a set of deep learning and spline models for time-to-event modelling within a fully customizable 'app' and accompanying online portal, both of which can be used for any time-to-event analysis in any disease by a non-expert user. Our online portal includes capacity for end-users including patients, Neurology clinicians, and researchers, to access and perform predictions using a trained model, and to contribute new data for model improvement, all within a data-secure environment. We demonstrate a pipeline for use of our app with three use-cases including imputation of missing data, hyperparameter tuning, model training and independent validation. We show that predictions are optimal for use in downstream applications such as genetic discovery, biomarker interpretation, and personalised choice of medication. We demonstrate the efficiency of an ensemble configuration, including focused training of a deep learning model. We have optimised a pipeline for imputation of missing data in combination with time-to-event prediction models. Overall, we provide a powerful and accessible tool to develop, access and share time-to-event prediction models; all software and tutorials are available at www.predictte.org.

Handling missing data when estimating causal effects with targeted maximum likelihood estimation

Targeted maximum likelihood estimation (TMLE) is increasingly used for doubly robust causal inference, but how missing data should be handled when using TMLE with data-adaptive approaches is unclear. Based on data (1992-1998) from the Victorian Adolescent Health Cohort Study, we conducted a simulation study to evaluate 8 missing-data methods in this context: complete-case analysis, extended TMLE incorporating an outcome-missingness model, the missing covariate missing indicator method, and 5 multiple imputation (MI) approaches using parametric or machine-learning models. We considered 6 scenarios that varied in terms of exposure/outcome generation models (presence of confounder-confounder interactions) and missingness mechanisms (whether outcome influenced missingness in other variables and presence of interaction/nonlinear terms in missingness models). Complete-case analysis and extended TMLE had small biases when outcome did not influence missingness in other variables. Parametric MI without interactions had large bias when exposure/outcome generation models included interactions. Parametric MI including interactions performed best in bias and variance reduction across all settings, except when missingness models included a nonlinear term. When choosing a method for handling missing data in the context of TMLE, researchers must consider the missingness mechanism and, for MI, compatibility with the analysis method. In many settings, a parametric MI approach that incorporates interactions and nonlinearities is expected to perform well.

Risk of fibromyalgia following antibiotic prescriptions: A population-based case-control study

BACKGROUND

The health of the gut microbiome is now recognized to be an important component of the gut-brain axis which itself appears to be implicated in pain perception. Antibiotics are known to create dysbiosis in the microbiome, so whether fibromyalgia is more commonly diagnosed after antibiotic prescriptions provides a means of exploring the role of the microbiome in the experience of chronic pain.

METHODS

A case-control study was carried out using electronic health records collected in the UK's Clinical Practice Research Datalink (CPRD), a comprehensive database of primary care consultations. For each case of diagnosed fibromyalgia, three controls were identified and matched by age, gender and GP practice. The exposure variable was the number and timing of antibiotic prescriptions over previous years. The analysis involved adjusting for a wide range of co-variates that might be possible confounders.

RESULTS

A total of 44,674 cases of fibromyalgia were identified together with 133,513 controls. After adjusting for co-variates, it was found that both the total number of prescriptions and their timing was associated with an FM diagnosis. For example, the quartile with the highest number of prescriptions and that with the longest exposure had a greater than three-fold increase in FM diagnoses (number of prescriptions: odds ratio 3.92; 95% CIs: 3.71-4.13; exposure odds ratio 3.28; CIs: 3.13-3.43). Some antibiotics (such as tetracyclines and metronidazole) seemed to confer greater risk than others.

CONCLUSIONS

The results lend support for prior antibiotics being an important risk factor for a diagnosis of FM.

SIGNIFICANCE

This study shows an association between the volume as well as timing of prior antibiotic prescriptions and of a subsequent diagnosis of fibromyalgia in primary care.

Association of Hospital Market Competition with Outcomes of Complex Cancer Surgery

BACKGROUND

The association of hospital market competition, financial costs, and quality of oncologic care has not been well-defined. This study sought to evaluate variations in patient outcomes and financial expenditures after complex cancer surgery across high- and low-competition markets.

METHODS

Medicare 100% Standard Analytic Files were used to identify patients with lung, esophageal, gastric, hepatopancreaticobiliary, or colorectal cancer who underwent surgical resection between 2018 and 2021. Data were merged with the annual hospital survey database, and the hospital market Herfindahl-Hirschman index was used to categorize hospitals into low- and high-concentration markets. Multi-level, multivariable regression models adjusting for patient characteristics (i.e., age, sex, comorbidities, and social vulnerability), year of procedure, and hospital factors (i.e., case volume, nurse-bed ratio, and teaching status) were used to assess the association between hospital market competition and outcomes.

RESULTS

Among 117,641 beneficiaries who underwent complex oncologic surgery, the mean age was 73.8 ± 6.1 years, and approximately one-half of the cohort was male (n = 56,243, 47.8%). Overall, 63.8% (n = 75,041) of the patients underwent care within a high-competition market. Notably, there was marked geographic variation relative to market competition. High versus low market-competition hospitals were more likely to be in high social vulnerability areas (35.1 vs 27.5%; p < 0.001), as well as care for racial/ethnic minority individuals (13.8 vs 7.7%; p < 0.001), and patients with more comorbidities (≥ 2 Elixhauser comorbidities: 63.1 vs 61.1%; p < 0.001). In the multivariable analysis, treatment at hospitals in high- versus low-competition markets was associated with lower odds of achieving a textbook outcome (odds ratio, 0.95; 95% confidence interval, 0.91-0.99; p = 0.009). Patients at high-competition hospitals had greater mean index hospitalization costs ($19,462.2 [16211.9] vs $18,844.7 [14994.7]) and 90-day post-discharge costs ($7807.8 [15431.3] vs $7332.8 [14038.2]) (both p < 0.001) than individuals at low-competition hospitals.

CONCLUSIONS

Hospital market competition was associated with poor achievement of an optimal postoperative outcome and greater hospitalization costs.

Circulating miRNA Signature Predicts Cancer Incidence in Lynch Syndrome-A Pilot Study

Lynch syndrome (LS) is the most common autosomal dominant cancer syndrome and is characterized by high genetic cancer risk modified by lifestyle factors. This study explored whether a circulating miRNA (c-miR) signature predicts LS cancer incidence within a 4-year prospective surveillance period. To gain insight how lifestyle behavior could affect LS cancer risk, we investigated whether the cancer-predicting c-miR signature correlates with known risk-reducing factors such as physical activity, body mass index (BMI), dietary fiber, or NSAID usage. The study included 110 c-miR samples from LS carriers, 18 of whom were diagnosed with cancer during a 4-year prospective surveillance period. Lasso regression was utilized to find c-miRs associated with cancer risk. Individual risk sum derived from the chosen c-miRs was used to develop a model to predict LS cancer incidence. This model was validated using 5-fold cross-validation. Correlation and pathway analyses were applied to inspect biological functions of c-miRs. Pearson correlation was used to examine the associations of c-miR risk sum and lifestyle factors. hsa-miR-10b-5p, hsa-miR-125b-5p, hsa-miR-200a-3p, hsa-miR-3613-5p, and hsa-miR-3615 were identified as cancer predictors by Lasso, and their risk sum score associated with higher likelihood of cancer incidence (HR 2.72, 95% confidence interval: 1.64-4.52, C-index = 0.72). In cross-validation, the model indicated good concordance with the average C-index of 0.75 (0.6-1.0). Coregulated hsa-miR-10b-5p, hsa-miR-125b-5p, and hsa-miR-200a-3p targeted genes involved in cancer-associated biological pathways. The c-miR risk sum score correlated with BMI (r = 0.23, P < 0.01). In summary, BMI-associated c-miRs predict LS cancer incidence within 4 years, although further validation is required.

PREVENTION RELEVANCE

The development of cancer risk prediction models is key to improving the survival of patients with LS. This pilot study describes a serum miRNA signature-based risk prediction model that predicts LS cancer incidence within 4 years, although further validation is required.

Ultra-processed food consumption and risk of chronic respiratory diseases mortality among adults: evidence from a prospective cohort study

PURPOSE

The purpose of the study was to determine the relationships between ultra-processed food (UPF) consumption and risk of mortality due to chronic respiratory diseases (CRDs) overall, chronic obstructive pulmonary disease (COPD), and lung cancer.

METHODS

A total of 96,607 participants aged 55 years and over were included from the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer trial. Dietary intake was measured using food frequency questionnaire. Cox regression was fitted to estimate the risk of all-cause mortality and mortality due to CRDs overall, COPD and lung cancer associated with UPF intake. Competing risk regression was used to account for deaths from other causes and censoring.

RESULTS

During the follow-up of 1,379,655.5 person-years (median 16.8 years), 28,700 all-cause, 4092 CRDs, 2015 lung cancer and 1,536 COPD mortality occurred. A higher intake of UPF increased the risk of mortality from CRDs overall by 10% (HR 1.10; 95% CI 1.01, 1.22) and COPD by 26% (HR 1.26; 95% CI 1.06, 1.49) but not associated with lung cancer mortality risk (HR 0.97; 95% CI 0.84, 1.12). However, the risk of lung cancer increased by 16% (HR 1.16; 95% CI 1.01, 1.34) in the highest UPF intake after multiple imputation. Dose-response relationships existed for CRDs and COPD mortality but not lung cancer.

CONCLUSION

UPF consumption was associated with an increased risk of CRD mortality. The association between UPF consumption and lung cancer mortality is inconclusive and only significant when multiple imputation was applied.

Health-related quality of life in the year following road trauma: Longitudinal analysis using piecewise latent curve modeling

BACKGROUND

Road trauma (RT) survivors have reduced health-related quality of life (HRQoL). We identified phases and predictors of HRQoL change following RT injury.

METHODS

In a prospective cohort study of 1480 Canadian RT survivors aged 16 to 103 years (July 2018 - March 2020), physical component (PCS) and mental component (MCS) summary scores from the SF-12v2 were measured pre-injury and 2, 4, 6, and 12 months post-injury and their trajectories were analyzed with piecewise latent growth curve modeling. Potential predictors of HRQoL changes included sociodemographic, psychological, medical, and trauma-related factors.

RESULTS

PCS and MCS scores worsened from pre-injury to 2-months (phase 1) and then improved (phase 2), but never regained baseline values. Older age, somatic symptoms and pain catastrophizing were associated with lower preinjury PCS and MCS scores. Psychological distress was associated with lower preinjury MCS scores and higher preinjury PCS scores. Phase 1 PCS scores decreased most in females, participants with fewer pre-injury somatic symptoms and those without expectations for fast recovery. Phase 1 MCS decreases were associated with younger age, female sex, living alone, lower psychological distress, lack of expectation for fast recovery and higher injury pain. In phase 2, MCS improved most in participants not using recreational drugs; PCS improved most in participants with higher education and longer recovery expectations.

LIMITATIONS

There may be recall bias with reporting pre-injury HRQoL. Selection bias is possible.

CONCLUSIONS

Many factors influence HRQoL following RT. These findings may inform measures to minimize HRQoL reduction following RT and speed up subsequent recovery.

Enhancing psychiatric rehabilitation outcomes through a multimodal multitask learning model based on BERT and TabNet: An approach for personalized treatment and improved decision-making

Evaluating the rehabilitation status of individuals with serious mental illnesses (SMI) necessitates a comprehensive analysis of multimodal data, including unstructured text records and structured diagnostic data. However, progress in the effective assessment of rehabilitation status remains limited. Our study develops a deep learning model integrating Bidirectional Encoder Representations from Transformers (BERT) and TabNet through a late fusion strategy to enhance rehabilitation prediction, including referral risk, dangerous behaviors, self-awareness, and medication adherence, in patients with SMI. BERT processes unstructured textual data, such as doctor's notes, whereas TabNet manages structured diagnostic information. The model's interpretability function serves to assist healthcare professionals in understanding the model's predictive decisions, improving patient care. Our model exhibited excellent predictive performance for all four tasks, with an accuracy exceeding 0.78 and an area under the curve of 0.70. In addition, a series of tests proved the model's robustness, fairness, and interpretability. This study combines multimodal and multitask learning strategies into a model and applies it to rehabilitation assessment tasks, offering a promising new tool that can be seamlessly integrated with the clinical workflow to support the provision of optimized patient care.

Real-world experience of Fuzheng Yiqing granule as chemoprophylaxis against COVID-19 infection among close contacts: A prospective cohort study

BACKGROUND

The objective of the current study was to evaluate whether the use of traditional Chinese medicine, Fuzheng Yiqing granule (FZYQG), was associated with a reduced infection risk of COVID-19 in close contacts.

RESEARCH DESIGN AND METHODS

This was a prospective cohort study across 203 quarantine centres for close contacts and secondary contacts of COVID-19 patients in Yangzhou city. FZYQG group was defined as quarantined individuals who voluntarily took FZYQG; control group did not take FZYQG. The primary outcome was the coronavirus test positive rate during quarantine period. Logistic regression with propensity score inverse probability weighting was used for adjusted analysis to evaluate independent association between FZYQG and test positive rate.

RESULTS

From July 13, 2021 to September 30, 2021, 3438 quarantined individuals took FZYQG and 2248 refused to take the granule. Test positive rate was significantly lower among quarantined individuals who took FZYQG (0.29% vs. 1.73%, risk ratio 0.17, 95% confidence interval (CI): 0.08-0.34, p < 0.001). On logistic regression, odds for test positive were decreased in FZYQG group (odds ratio: 0.16, 95% CI: 0.08-0.32, p < 0.001).

CONCLUSIONS

Close and secondary contacts of COVID-19 patients who received FZYQG had a lower test positive rate than control individuals in real-world experience.

TRIAL REGISTRATION

This study has been registered on Chinese Clinical Trial Registry (ChiCTR2100049590) on August 5, 2021.

Cannabis use disorder and perioperative outcomes following complex cancer surgery

INTRODUCTION

Cannabis usage is increasing in the United States, especially among patients with cancer. We sought to evaluate whether cannabis use disorder (CUD) was associated with higher morbidity and mortality among patients undergoing complex cancer surgery.

METHODS

Patients who underwent complex cancer surgery between January 2016 and December 2019 were identified in the National Inpatient Sample database. CUD was defined according to ICD-10 codes. Propensity score matching was performed to create a 1:1 matched cohort that was well balanced with respect to covariates, which included patient comorbidities, sociodemographic factors, and procedure type. The primary composite outcome was in-hospital mortality and seven major perioperative complications (myocardial ischemia, acute kidney injury, stroke, respiratory failure, venous thromboembolism, hospital-acquired infection, and surgical procedure-related complications).

RESULTS

Among 15 014 patients who underwent a high-risk surgical procedure, a cohort of 7507 patients with CUD (median age; 43 years [IQR: 30-56 years]; n = 3078 [41.0%] female) were matched with 7507 patients who were not cannabis users (median age; 44 years [IQR: 30-58 years); n = 2997 [39.9%] female). CUD was associated with slight increased risk relative to postoperative kidney injury (CUD, 7.8% vs. no CUD, 6.1%); however, in-hospital mortality was slightly lower (CUD, 0.9% vs. no CUD, 1.6%) (both p < 0.001). On multivariable analysis, after controlling for other risk factors, CUD was not associated with higher morbidity and mortality (adjusted odds ratio: 1.06, 95% CI: 0.98-1.15; p = 0.158).

CONCLUSION

CUD was not associated with a higher risk of postoperative morbidity and mortality following complex cancer surgery.

Associations Between Childhood Trauma Characteristics and Theory of Mind in Adults: Results From a Large, Diverse Sample

Theory of mind (ToM) is an essential social cognitive process encompassing abilities to represent and understand others' mental states. Although previous reports linked childhood trauma to social cognitive deficits, how characteristics of trauma exposure, such as subtype or timing, affect ToM remains unaddressed. Using data from a diverse adult sample (n = 2200), we tested whether exposure type and first exposure timing of common childhood trauma associated with ToM. Neither interpersonal loss (β = - 0.25, p = 0.170, [- 0.61, 0.10]) nor child maltreatment (β = - 0.21, p = 0.369, [- 0.66, 0.25]) was associated with lower ToM. There was no effect of timing of age at which trauma was experienced (F = 2.19, p = 0.087). While we did not identify age-dependent effects, future studies should examine links between timing or chronicity of prospectively reported childhood trauma and social cognition. Understanding of how childhood experiences shape ToM could reveal mechanisms underlying social cognition development and inform prevention efforts.

Long COVID and cardiovascular disease: a prospective cohort study

BACKGROUND

Pre-existing cardiovascular disease (CVD) or cardiovascular risk factors have been associated with an increased risk of complications following hospitalisation with COVID-19, but their impact on the rate of recovery following discharge is not known.

OBJECTIVES

To determine whether the rate of patient-perceived recovery following hospitalisation with COVID-19 was affected by the presence of CVD or cardiovascular risk factors.

METHODS

In a multicentre prospective cohort study, patients were recruited following discharge from the hospital with COVID-19 undertaking two comprehensive assessments at 5 months and 12 months. Patients were stratified by the presence of either CVD or cardiovascular risk factors prior to hospitalisation with COVID-19 and compared with controls with neither. Full recovery was determined by the response to a patient-perceived evaluation of full recovery from COVID-19 in the context of physical, physiological and cognitive determinants of health.

RESULTS

From a total population of 2545 patients (38.8% women), 472 (18.5%) and 1355 (53.2%) had CVD or cardiovascular risk factors, respectively. Compared with controls (n=718), patients with CVD and cardiovascular risk factors were older and more likely to have had severe COVID-19. Full recovery was significantly lower at 12 months in patients with CVD (adjusted OR (aOR) 0.62, 95% CI 0.43 to 0.89) and cardiovascular risk factors (aOR 0.66, 95% CI 0.50 to 0.86).

CONCLUSION

Patients with CVD or cardiovascular risk factors had a delayed recovery at 12 months following hospitalisation with COVID-19. Targeted interventions to reduce the impact of COVID-19 in patients with cardiovascular disease remain an unmet need.

TRAIL REGISTRATION NUMBER

ISRCTN10980107.

Enhancing environmental data imputation: A physically-constrained machine learning framework

In water resources management, new computational capabilities have made it possible to develop integrated models to jointly analyze climatic conditions and water quantity/quality of the entire watershed system. Although the value of this integrated approach has been demonstrated so far, the limited availability of field data may hinder its applicability by causing high uncertainty in the model response. In this context, before collecting additional data, it is recommended first to recognize what improvement in model performance would occur if all available records could be well exploited. This work proposes a novel machine learning framework with physical constraints capable of successfully imputing a high percentage of missing data belonging to several environmental domains (meteorology, water quantity, water quality), yielding satisfactory results. In particular, the minimum NSE computed for meteorologic variables is 0.72. For hydrometric variables, NSE is always >0.97. More than 78 % of the physical-water-quality variables is characterized by NSE > 0.45, and >66 % of the chemical-water quality variables reaches NSE > 0.35. This work's results demonstrate the proposed framework's effectiveness as a data augmentation tool to improve the performance of integrated environmental modeling.

Clinical predictors of Alzheimer's disease-like brain atrophy in individuals with memory complaints

OBJECTIVES

The definition and assessment methods for subjective cognitive decline (SCD) vary among studies. We aimed to investigate which features or assessment methods of SCD best predict Alzheimer's disease (AD)-related structural atrophy patterns.

METHODS

We assessed 104 individuals aged 55+ with memory complaints but normal cognitive screening. Our research questions were as follows: To improve the prediction of AD related morphological changes, (1) Would the use of a standardized cognitive screening scale be beneficial? (2) Is conducting a thorough neuropsychological evaluation necessary instead of relying solely on cognitive screening tests? (3) Should we apply SCD-plus research criteria, and if so, which criterion would be the most effective? (4) Is it necessary to consider medical and psychiatric comorbidities, vitamin deficiencies, vascular burden on MRI, and family history? We utilized Freesurfer to analyze cortical thickness and regional brain volume meta-scores linked to AD or predicting its development. We employed multiple linear regression models for each variable, with morphology as the dependent variable.

RESULTS

AD-like morphology was associated with subjective complaints in males, individuals with advanced age, and higher education. Later age of onset for complaints, complaints specifically related to memory, excessive deep white matter vascular lesions, and using medications that have negative implications for cognitive health (according to the Beers criteria) were predictive of AD-related morphology. The subjective cognitive memory questionnaire scores were found to be a better predictor of reduced volumes than a single-question assessment. It is important to note that not all SCD-plus criteria were evaluated in this study, particularly the APOE genotype, amyloid, and tau status, due to resource limitations.

CONCLUSIONS

The detection of AD-related structural changes is impacted by demographics and assessment methods. Standardizing SCD assessment methods can enhance predictive accuracy.

Impact of Insurance Status and Region on Angiotensin Receptor-Neprilysin Inhibitor Prescription During Heart Failure Hospitalizations

BACKGROUND

An angiotensin receptor-neprilysin inhibitor (ARNI) is the preferred renin-angiotensin system (RAS) inhibitor for heart failure with reduced ejection fraction (HFrEF). Among eligible patients, insurance status and prescriber concern regarding out-of-pocket costs may constrain early initiation of ARNI and other new therapies.

OBJECTIVES

In this study, the authors sought to evaluate the association of insurance and other social determinants of health with ARNI initiation at discharge from HFrEF hospitalization.

METHODS

The authors analyzed ARNI initiation from January 2017 to June 2020 among patients with HFrEF eligible to receive RAS inhibitor at discharge from hospitals in the Get With The Guidelines-Heart Failure registry. The primary outcome was the proportion of ARNI prescription at discharge among those prescribed RAS inhibitor who were not on ARNI on admission. A logistic regression model was used to determine the association of insurance status, U.S. region, and their interaction, as well as self-reported race, with ARNI initiation at discharge.

RESULTS

From 42,766 admissions, 24,904 were excluded for absolute or relative contraindications to RAS inhibitors. RAS inhibitors were prescribed for 16,817 (94.2%) of remaining discharges, for which ARNI was prescribed in 1,640 (9.8%). Self-reported Black patients were less likely to be initiated on ARNI compared to self-reported White patients (OR: 0.64; 95% CI: 0.50-0.81). Compared to Medicare beneficiaries, patients with third-party insurance, Medicaid, or no insurance were less likely to be initiated on ARNI (OR: 0.47 [95% CI: 0.31-0.72], OR: 0.41 [95% CI: 0.25-0.67], and OR: 0.20 [95% CI: 0.08-0.47], respectively). ARNI therapy varied by hospital region, with lowest utilization in the Mountain region. An interaction was demonstrated between the impact of insurance disparities and hospital region.

CONCLUSIONS

Among patients hospitalized between 2017 and 2020 for HFrEF who were prescribed RAS inhibitor therapy at discharge, insurance status, geographic region, and self-reported race were associated with ARNI initiation.

Kids SIPsmartER reduces sugar-sweetened beverages among Appalachian middle-school students and their caregivers: a cluster randomized controlled trial

BACKGROUND

High consumption of sugar-sweetened beverages (SSB) is a global health concern. Additionally, sugar-sweetened beverage (SSB) consumption is disproportionately high among adolescents and adults in rural Appalachia. The primary study objective is to determine the intervention effects of Kids SIPsmartER on students' SSB consumption. Secondary objectives focus on caregivers' SSB consumption and secondary student and caregiver outcomes [e.g, body mass index (BMI), quality of life (QOL)].

METHODS

This Type 1 hybrid, cluster randomized controlled trial includes 12 Appalachian middle schools (6 randomized to Kids SIPsmartER and 6 to control). Kids SIPsmartER is a 6-month, 12 lesson, multi-level, school-based, behavior and health literacy program aimed at reducing SSB among 7th grade middle school students. The program also incorporates a two-way text message strategy for caregivers. In this primary prevention intervention, all 7th grade students and their caregivers from participating schools were eligible to participate, regardless of baseline SSB consumption. Validated instruments were used to assess SSB behaviors and QOL. Height and weight were objectively measured in students and self-reported by caregivers. Analyses included modified two-part models with time fixed effects that controlled for relevant demographics and included school cluster robust standard errors.

RESULTS

Of the 526 students and 220 caregivers, mean (SD) ages were 12.7 (0.5) and 40.6 (6.7) years, respectively. Students were 55% female. Caregivers were mostly female (95%) and White (93%); 25% had a high school education or less and 33% had an annual household income less than $50,000. Regardless of SSB intake at baseline and relative to control participants, SSB significantly decreased among students [-7.2 ounces/day (95% CI = -10.7, -3.7); p < 0.001, effect size (ES) = 0.35] and caregivers [-6.3 ounces/day (95% CI = -11.3, -1.3); p = 0.014, ES = 0.33]. Among students (42%) and caregivers (28%) who consumed > 24 SSB ounces/day at baseline (i.e., high consumers), the ES increased to 0.45 and 0.95, respectively. There were no significant effects for student or caregiver QOL indicators or objectively measured student BMI; however, caregiver self-reported BMI significantly decreased in the intervention versus control schools (p = 0.001).

CONCLUSIONS

Kids SIPsmartER was effective at reducing SSB consumption among students and their caregivers in the rural, medically underserved Appalachian region. Importantly, SSB effects were even stronger among students and caregivers who were high consumers at baseline.

TRIAL REGISTRATION

Clincialtrials.gov: NCT03740113. Registered 14 November 2018- Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03740113 .

Risk of fractures in half a million survivors of 20 cancers: a population-based matched cohort study using linked English electronic health records

BACKGROUND

A history of multiple myeloma, prostate cancer, and breast cancer has been associated with adverse bone health, but associations across a broader range of cancers are unclear. We aimed to compare the risk of any bone fracture and major osteoporotic fractures in survivors of a wide range of cancers versus cancer-free individuals.

METHODS

In this population-based matched cohort study, we used electronic health records from the UK Clinical Practice Research Datalink linked to hospital data. We included adults (aged ≥18 years) eligible for linkage, and we restricted the study start to Jan 2, 1998, onwards and applied administrative censoring on Jan 31, 2020. The cancer survivor group included survivors of the 20 most common cancers. Each individual with cancer was matched (age, sex, and general practice) to up to five controls (1:5) who were cancer-free. The primary outcomes were any bone fracture and any major osteoporotic fracture (pelvic, hip, wrist, spine, or proximal humeral fractures) occurring more than 1 year after index date (ie, the diagnosis date of the matched individual with cancer). We used Cox regression models, adjusted for shared risk factors, to estimate associations between cancer survivorship and bone fractures.

FINDINGS

578 160 adults with cancer diagnosed in 1998-2020 were matched to 3 226 404 cancer-free individuals. Crude incidence rates of fractures in cancer survivors ranged between 8·39 cases (95% CI 7·45-9·46) per 1000 person-years for thyroid cancer and 21·62 cases (20·18-23·18) per 1000 person-years for multiple myeloma. Compared with cancer-free individuals, the risk of any bone fracture was increased in 15 of 20 cancers, and of major osteoporotic fractures in 17 of 20 cancers. Effect sizes varied: adjusted hazard ratios (HRs) were largest for multiple myeloma (1·94, 95% CI 1·77-2·13) and prostate cancer (1·43, 1·39-1·47); HRs in the range 1·20-1·50 were seen for stomach, liver, pancreas, lung, breast, kidney, and CNS cancers; smaller associations (HR <1·20) were observed for malignant melanoma, non-Hodgkin lymphoma, leukaemia, and oesophageal, colorectal, and cervical cancers. Increased risks of major osteoporotic fracture were noted most substantially in multiple myeloma (2·25, 1·96-2·58) and CNS (2·12, 1·56-2·87), liver (1·62, 1·01-2·61), prostate (1·60, 1·53-1·67), and lung cancers (1·60, 1·44-1·77). Effect sizes tended to reduce over time since diagnosis but remained elevated for more than 5 years in several cancers, such as multiple myeloma and stomach, lung, breast, prostate, and CNS cancers.

INTERPRETATION

Survivors of most types of cancer were at increased risk of bone fracture for several years after cancer, with variation by cancer type. These findings can help to inform mitigation and prevention strategies.

FUNDING

Wellcome Trust.

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 to check a simulation study

Simulation studies are powerful tools in epidemiology and biostatistics, but they can be hard to conduct successfully. Sometimes unexpected results are obtained. We offer advice on how to check a simulation study when this occurs, and how to design and conduct the study to give results that are easier to check. Simulation studies should be designed to include some settings in which answers are already known. They should be coded in stages, with data-generating mechanisms checked before simulated data are analysed. Results should be explored carefully, with scatterplots of standard error estimates against point estimates surprisingly powerful tools. Failed estimation and outlying estimates should be identified and dealt with by changing data-generating mechanisms or coding realistic hybrid analysis procedures. Finally, we give a series of ideas that have been useful to us in the past for checking unexpected results. Following our advice may help to prevent errors and to improve the quality of published simulation studies.

Cross-informant agreement between caregivers and teachers for prosocial behavior across child welfare settings

Healthy social functioning has been a growing focus for understanding children's positive development and well-being. Despite the flexibility and cost-effectiveness of behavior rating scales, there has been a rising issue of concern in both practice and research applications regarding rating scales and its low cross-informant agreement. The present study aimed to analyze the extent to which caregivers and teachers agree about children's prosocial behaviors, identify whether there were differences in the degree of agreement across child welfare settings, and ultimately offer recommendations for assessing behavior for children involved with child welfare services. To do so, the reports of 1,224 children, caregivers, and teachers from the National Survey of Child and Adolescent Well-Being (NSCAW) I who have been investigated by Child Protective Services (CPS) for abuse and/or neglect have been examined. Intra-class correlation coefficients (ICCs) of caregiver and teacher assessment of children's prosocial functioning were calculated to understand the degree of agreement in their perceptions of children's prosocial behaviors. ICC values presented show that agreement was low but significant across all samples and subscales (ICC range, .11-.22). It is suggested that future researchers pursue examination of the underlying mechanisms or factors that contribute to informant discrepancies.

Incident dementia risk among patients with type 2 diabetes receiving metformin versus alternative oral glucose-lowering therapy: an observational cohort study using UK primary healthcare records

INTRODUCTION

4.2 million individuals in the UK have type 2 diabetes, a known risk factor for dementia and mild cognitive impairment (MCI). Diabetes treatment may modify this association, but existing evidence is conflicting. We therefore aimed to assess the association between metformin therapy and risk of incident all-cause dementia or MCI compared with other oral glucose-lowering therapies (GLTs).

RESEARCH DESIGN AND METHODS

We conducted an observational cohort study using the Clinical Practice Research Datalink among UK adults diagnosed with diabetes at ≥40 years between 1990 and 2019. We used an active comparator new user design to compare risks of dementia and MCI among individuals initially prescribed metformin versus an alternative oral GLT using Cox proportional hazards regression controlling for sociodemographic, lifestyle and clinical confounders. We assessed for interaction by age and sex. Sensitivity analyses included an as-treated analysis to mitigate potential exposure misclassification.

RESULTS

We included 211 396 individuals (median age 63 years; 42.8% female), of whom 179 333 (84.8%) initiated on metformin therapy. Over median follow-up of 5.4 years, metformin use was associated with a lower risk of dementia (adjusted HR (aHR) 0.86 (95% CI 0.79 to 0.94)) and MCI (aHR 0.92 (95% CI 0.86 to 0.99)). Metformin users aged under 80 years had a lower dementia risk (aHR 0.77 (95% CI 0.68 to 0.85)), which was not observed for those aged ≥80 years (aHR 0.95 (95% CI 0.87 to 1.05)). There was no interaction with sex. The as-treated analysis showed a reduced effect size compared with the main analysis (aHR 0.90 (95% CI 0.83 to 0.98)).

CONCLUSIONS

Metformin use was associated with lower risks of incident dementia and MCI compared with alternative GLT among UK adults with diabetes. While our findings are consistent with a neuroprotective effect of metformin against dementia, further research is needed to reduce risks of confounding by indication and assess causality.