Towards a Clearer Causal Question Underlying the Association Between Cancer and Dementia

BACKGROUND

Several observational studies have described an inverse association between cancer diagnosis and subsequent dementia risk. Multiple biologic mechanisms and potential biases have been proposed in attempts to explain this association. One proposed explanation is the opposite expression of Pin1 in cancer and dementia, and we use this explanation and potential drug target to illustrate the required assumptions and potential sources of bias for inferring an effect of Pin1 on dementia risk from analyses measuring cancer diagnosis as a proxy for Pin1 expression.

METHODS

We used data from the Rotterdam Study, a population-based cohort. We estimate the association between cancer diagnosis (as a proxy for Pin1) and subsequent dementia diagnosis using two different proxy methods and with confounding and censoring for death addressed with inverse probability weights. We estimate and compare the complements of a weighted Kaplan-Meier survival estimator at 20 years of follow-up.

RESULTS

Out of 3634 participants, 899 (25%) were diagnosed with cancer, of whom 53 (6%) had dementia, and 567 (63%) died. Among those without cancer, 15% (411) were diagnosed with dementia, and 667 (24%) died over follow-up. Depending on the confounding and selection bias control, and the way in which cancer was used as a time-varying proxy exposure, the risk ratio for dementia diagnosis ranged from 0.71 (95% confidence interval [CI] = 0.49, 0.95) to 1.1 (95% CI = 0.79, 1.3).

CONCLUSION

Being explicit about the underlying mechanism of interest is key to maximizing what we can learn from this cancer-dementia association given available or readily collected data, and to defining, detecting, and preventing potential biases.

Partial Identification of the Effects of Sustained Treatment Strategies

Although many epidemiologic studies focus on point identification, it is also possible to partially identify causal effects under consistency and the data alone. However, the literature on the so-called "assumption-free" bounds has focused on settings with time-fixed exposures. We describe assumption-free bounds for the effects of both static and dynamic sustained interventions. To provide intuition for the width of the bounds, we also discuss a mathematical connection between assumption-free bounds and clone-censor-weight approaches to causal effect estimation. The bounds, which are often wide in practice, can provide important information about the degree to which causal analyses depend on unverifiable assumptions made by investigators.

Reporting and Description of Research Methodology in Studies Estimating Effects of Firearm Policies

BACKGROUND

Evidence about which firearm policies work, to what extent, and for whom is hotly debated, perhaps partly because variation in research methodology has produced mixed and inconclusive effect estimates. We conducted a scoping review of firearm policy research in the health sciences in the United States, focusing on methodological considerations for causal inference.

METHODS

We identified original, empirical articles indexed in PubMed from 1/1/2000-9/1/2021 that examined any of 18 pre-specified firearm policies. We extracted key study components, including policy type(s) examined, policy operationalization, outcomes, study setting and population, study approach and design, causal language, and whether and how authors acknowledged potential sources of bias.

RESULTS

We screened 7733 articles and included 124. A plurality of studies used a legislative score as their primary exposure (n=39; 32%) and did not examine change in policies over time (n=47; 38%). Most examined firearm homicide (n=51; 41%) or firearm suicide (n=40; 32%) as outcomes. One-third adjusted for other firearm policies (n=41; 33%). Three studies (2%) explicitly mentioned that their goal was to estimate causal effects, but over half used language implying causality (n=72; 58%). Most acknowledged causal identification assumptions of temporality (n=91; 73%) and exchangeability (n=111; 90%); other assumptions were less often acknowledged. One-third of studies included bias analyses (n=42; 34%).

CONCLUSIONS

We identified a range of methodologic approaches in firearm policy research in the health sciences. Acknowledging limitations of data availability and quality, we identify opportunities to improve causal inferences about and reporting on the effects of firearm policies on population health.

Toward a clearer understanding of what works to reduce gun violence: the role of falsification strategies

Strong epidemiologic evidence from ecologic and individual-level studies in the United States supports the claim that access to firearms substantially increases the risk of dying by suicide, homicide, and firearm accidents. Less certain is how well particular interventions work to prevent these deaths and other firearm-related harms. Given the limits of existing data to study firearm violence, and the infeasibility of conducting randomized trials of firearm access, it is important to do the best we can with the data we already have. We argue that falsification strategies are a critical - yet underutilized - component of any such analytic approach. The falsification strategies we focus on are versions of "negative controls" analyses in which we expect an analysis should yield a null causal effect, and thus where not obtaining a null effect estimate raises questions about the assumptions underlying causal interpretation of a study's findings. We illustrate the saliency of this issue today with examples drawn from studies published within the last five years in leading peer-reviewed journals. Collecting rich, high-quality data always takes time, urgent as the need may be. On the other hand, doing better with the data we already have can start right now.

Development of the TrAnsparent ReportinG of observational studies Emulating a Target trial (TARGET) guideline

BACKGROUND

Observational studies are increasingly used to inform health decision-making when randomised trials are not feasible, ethical or timely. The target trial approach provides a framework to help minimise common biases in observational studies that aim to estimate the causal effect of interventions. Incomplete reporting of studies using the target trial framework limits the ability for clinicians, researchers, patients and other decision-makers to appraise, synthesise and interpret findings to inform clinical and public health practice and policy. This paper describes the methods that we will use to develop the TrAnsparent ReportinG of observational studies Emulating a Target trial (TARGET) reporting guideline.

METHODS/DESIGN

The TARGET reporting guideline will be developed in five stages following recommended guidance. The first stage will identify target trial reporting practices by systematically reviewing published studies that explicitly emulated a target trial. The second stage will identify and refine items to be considered for inclusion in the TARGET guideline by consulting content experts using sequential online surveys. The third stage will prioritise and consolidate key items to be included in the TARGET guideline at an in-person consensus meeting of TARGET investigators. The fourth stage will produce and pilot-test both the TARGET guideline and explanation and elaboration document with relevant stakeholders. The fifth stage will disseminate the TARGET guideline and resources via journals, conferences and courses.

ETHICS AND DISSEMINATION

Ethical approval for the survey has been attained (HC220536). The TARGET guideline will be disseminated widely in partnership with stakeholders to maximise adoption and improve reporting of these studies.

Reporting of Observational Studies Explicitly Aiming to Emulate Randomized Trials: A Systematic Review

Importance

Observational (nonexperimental) studies that aim to emulate a randomized trial (ie, the target trial) are increasingly informing medical and policy decision-making, but it is unclear how these studies are reported in the literature. Consistent reporting is essential for quality appraisal, evidence synthesis, and translation of evidence to policy and practice.

Objective

To assess the reporting of observational studies that explicitly aimed to emulate a target trial.

Evidence Review

We searched Medline, Embase, PsycINFO, and Web of Science for observational studies published between March 2012 and October 2022 that explicitly aimed to emulate a target trial of a health or medical intervention. Two reviewers double-screened and -extracted data on study characteristics, key predefined components of the target trial protocol and its emulation (eligibility criteria, treatment strategies, treatment assignment, outcome[s], follow-up, causal contrast[s], and analysis plan), and other items related to the target trial emulation.

Findings

A total of 200 studies that explicitly aimed to emulate a target trial were included. These studies included 26 subfields of medicine, and 168 (84%) were published from January 2020 to October 2022. The aim to emulate a target trial was explicit in 70 study titles (35%). Forty-three studies (22%) reported use of a published reporting guideline (eg, Strengthening the Reporting of Observational Studies in Epidemiology). Eighty-five studies (43%) did not describe all key items of how the target trial was emulated and 113 (57%) did not describe the protocol of the target trial and its emulation.

Conclusion and Relevance

In this systematic review of 200 studies that explicitly aimed to emulate a target trial, reporting of how the target trial was emulated was inconsistent. A reporting guideline for studies explicitly aiming to emulate a target trial may improve the reporting of the target trial protocols and other aspects of these emulation attempts.

Falsification of the instrumental variable conditions in Mendelian randomization studies in the UK Biobank

Mendelian randomization (MR) is an increasingly popular approach to estimating causal effects. Although the assumptions underlying MR cannot be verified, they imply certain constraints, the instrumental inequalities, which can be used to falsify the MR conditions. However, the instrumental inequalities are rarely applied in MR. We aimed to explore whether the instrumental inequalities could detect violations of the MR conditions in case studies analyzing the effect of commonly studied exposures on coronary artery disease risk.Using 1077 single nucleotide polymorphisms (SNPs), we applied the instrumental inequalities to MR models for the effects of vitamin D concentration, alcohol consumption, C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol on coronary artery disease in the UK Biobank. For their relevant exposure, we applied the instrumental inequalities to MR models proposing each SNP as an instrument individually, and to MR models proposing unweighted allele scores as an instrument. We did not identify any violations of the MR assumptions when proposing each SNP as an instrument individually. When proposing allele scores as instruments, we detected violations of the MR assumptions for 5 of 6 exposures.Within our setting, this suggests the instrumental inequalities can be useful for identifying violations of the MR conditions when proposing multiple SNPs as instruments, but may be less useful in determining which SNPs are not instruments. This work demonstrates how incorporating the instrumental inequalities into MR analyses can help researchers to identify and mitigate potential bias.

Considering Questions Before Methods in Dementia Research With Competing Events and Causal Goals

Studying causal exposure effects on dementia is challenging when death is a competing event. Researchers often interpret death as a potential source of bias, although bias cannot be defined or assessed if the causal question is not explicitly specified. Here we discuss 2 possible notions of a causal effect on dementia risk: the "controlled direct effect" and the "total effect." We provide definitions and discuss the "censoring" assumptions needed for identification in either case and their link to familiar statistical methods. We illustrate concepts in a hypothetical randomized trial on smoking cessation in late midlife, and emulate such a trial using observational data from the Rotterdam Study, the Netherlands, 1990-2015. We estimated a total effect of smoking cessation (compared with continued smoking) on 20-year dementia risk of 2.1 (95% confidence interval: -0.1, 4.2) percentage points and a controlled direct effect of smoking cessation on 20-year dementia risk had death been prevented of -2.7 (95% confidence interval: -6.1, 0.8) percentage points. Our study highlights how analyses corresponding to different causal questions can have different results, here with point estimates on opposite sides of the null. Having a clear causal question in view of the competing event and transparent and explicit assumptions are essential to interpreting results and potential bias.

Bounding the average causal effect in Mendelian randomisation studies with multiple proposed instruments: An application to prenatal alcohol exposure and attention deficit hyperactivity disorder

BACKGROUND

As large-scale observational data become more available, caution regarding causal assumptions remains critically important. This may be especially true for Mendelian randomisation (MR), an increasingly popular approach. Point estimation in MR usually requires strong, often implausible homogeneity assumptions beyond the core instrumental conditions. Bounding, which does not require homogeneity assumptions, is infrequently applied in MR.

OBJECTIVES

We aimed to demonstrate computing nonparametric bounds for the causal risk difference derived from multiple proposed instruments in an MR study where effect heterogeneity is expected.

METHODS

Using data from the Norwegian Mother, Father and Child Cohort Study (n = 2056) and Avon Longitudinal Study of Parents and Children (n = 6216) to study the average causal effect of maternal pregnancy alcohol use on offspring attention deficit hyperactivity disorder symptoms, we proposed 11 maternal SNPs as instruments. We computed bounds assuming subsets of SNPs were jointly valid instruments, for all combinations of SNPs where the MR model was not falsified.

RESULTS

The MR assumptions were violated for all sets with more than 4 SNPs in one cohort and for all sets with more than 2 SNPs in the other. Bounds assuming one SNP was an individually valid instrument barely improved on assumption-free bounds. Bounds tightened as more SNPs were assumed to be jointly valid instruments, and occasionally identified directions of effect, though bounds from different sets varied.

CONCLUSIONS

Our results suggest that, when proposing multiple instruments, bounds can contextualise plausible magnitudes and directions of effects. Computing bounds over multiple assumption sets, particularly in large, high-dimensional data, offers a means of triangulating results across different potential sources of bias within a study and may help researchers to better evaluate and emphasise which estimates are compatible with the most plausible assumptions for their specific setting.

Partial Identification of the Average Causal Effect in Multiple Study Populations: The Challenge of Combining Mendelian Randomization Studies

BACKGROUND

Researchers often use random-effects or fixed-effects meta-analysis to combine findings from multiple study populations. However, the causal interpretation of these models is not always clear, and they do not easily translate to settings where bounds, rather than point estimates, are computed.

METHODS

If bounds on an average causal effect of interest in a well-defined population are computed in multiple study populations under specified identifiability assumptions, then under those assumptions the average causal effect would lie within all study-specific bounds and thus the intersection of the study-specific bounds. We demonstrate this by pooling bounds on the average causal effect of prenatal alcohol exposure on attention deficit-hyperactivity disorder symptoms, computed in two European cohorts and under multiple sets of assumptions in Mendelian randomization (MR) analyses.

RESULTS

For all assumption sets considered, pooled bounds were wide and did not identify the direction of effect. The narrowest pooled bound computed implied the risk difference was between -4 and 34 percentage points.

CONCLUSIONS

All pooled bounds computed in our application covered the null, illustrating how strongly point estimates from prior MR studies of this effect rely on within-study homogeneity assumptions. We discuss how the interpretation of both pooled bounds and point estimation in MR is complicated by possible heterogeneity of effects across populations.

DEcrease STress through RESilience training for Students (DESTRESS) Study: Protocol for a randomized controlled trial nested in a longitudinal observational cohort study

INTRODUCTION

Chronic stress and burnout are highly prevalent among academically trained healthcare professionals, negatively affecting their well-being and capacity to engage in their work. Resilience to stress develops early in one's career path, hence offering resilience training to university students in these professions is one approach to fostering well-being and mental health. The aim of this study is to assess whether offering mindfulness-based resilience training to university students in healthcare professions reduces their perceived chronic stress.

METHODS AND ANALYSIS

The study has a hybrid design combining a longitudinal observational cohort with a nested randomized controlled trial (RCT) with sequential multiple assignment and multistage adaptive interventions while taking participants' preferences into account. All students in healthcare related programmes at the Erasmus University Rotterdam are invited to participate. Within the observational cohort, students with a score of 14 or higher on the Perceived Stress Scale (PSS) are invited to take part in the RCT (n = 706). Eligible participants are randomized to control or active intervention in a ratio of 1:6. Those randomized to the control group and non-randomized participants in the cohort receive passive web-based psychoeducation about chronic stress and burnout through referral to specific websites. Participants randomized to the intervention group receive one of 8 active mindfulness-based interventions. They select a rank order of 4 preferred interventions and are randomized across these with equal probability. Non-response to the intervention is followed by sequential randomized assignment to another intervention, for a total maximum of 3 sequential interventions. All participants receive questionnaires at baseline, before and after each 8-week intervention period, and at 1- and 2-year follow-up. The primary outcome is perceived chronic stress measured with the PSS. Secondary outcomes include mental well-being, burnout, quality of life, healthcare utilization, drug use, bodyweight, mental and physical stress-related symptoms, resilience, and study progress.

ETHICS AND REGISTRATION

Approval from the Medical Ethics Review Committee was obtained under protocol number MEC-2018-1645. The trial is registered in the Netherlands National Trial Register by registration number NL7623, 22/03/2019, https://www.trialregister.nl/.

Suicide Deaths Among Women in California Living With Handgun Owners vs Those Living With Other Adults in Handgun-Free Homes, 2004-2016

IMPORTANCE

Little is known about the extent to which secondhand exposure to household firearms is associated with risk of suicide in adults who do not own guns, most of whom are women.

OBJECTIVE

To evaluate changes in risk of suicide among women living in gun-free households after one of their cohabitants became a handgun owner.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study observed participants for up to 12 years and 2 months from October 18, 2004, to December 31, 2016. Data were analyzed from April to November 2021. The study population included 9.5 million adult women in California who did not own guns and who entered the study while living with 1 or more adults in a handgun-free home.

EXPOSURES

Secondhand exposure to household handguns.

MAIN OUTCOMES AND MEASURES

Suicide, firearm suicide, nonfirearm suicide.

RESULTS

Of 9.5 million women living in handgun-free homes, 331 968 women (3.5% of the study population; mean [SD] age, 41.6 [18.0] years) became exposed to household handguns during the study period. In the entire study population, 294 959 women died: 2197 (1%) of these were by suicide, 337 (15%) of which were suicides by firearm. Rates of suicide by any method during follow-up were higher among cohort members residing with handgun owners compared with those residing in handgun-free homes (hazard ratio, 1.43; 95% CI, 1.11-1.84). The excess suicide rate was accounted for by higher rates of suicide by firearm (hazard ratio, 4.32; 95% CI, 2.89-6.46). Women in households with and without handguns had similar rates of suicide by nonfirearm methods (hazard ratio, 0.90; 95% CI, 0.63-1.27).

CONCLUSIONS AND RELEVANCE

In this study, the rate of suicide among women was significantly higher after a cohabitant of theirs became a handgun owner compared with the rate observed while they lived in handgun-free homes.

Iron, folic acid, and multiple micronutrient supplementation strategies during pregnancy and adverse birth outcomes in Botswana

Background

Methods

Findings

Interpretation

Funding

Invited Commentary: Conducting and Emulating Trials to Study Effects of Social Interventions

All else being equal, if we had 1 causal effect we wished to estimate, we would conduct a randomized trial with a protocol that mapped onto that causal question, or we would attempt to emulate that target trial with observational data. However, studying the social determinants of health often means there are not just 1 but several causal contrasts of simultaneous interest and importance, and each of these related but distinct causal questions may have varying degrees of feasibility in conducting trials. With this in mind, we discuss challenges and opportunities that arise when conducting and emulating such trials. We describe designing trials with the simultaneous goals of estimating the intention-to-treat effect, the per-protocol effect, effects of alternative protocols or joint interventions, effects within subgroups, and effects under interference, and we describe ways to make the most of all feasible randomized trials and emulated trials using observational data. Our comments are grounded in the study results of Courtin et al. (Am J Epidemiol. 2022;191(8):1444-1452).

Patterns of handgun divestment among handgun owners in California

Background

Little is known about voluntary divestment of firearms among US firearm owners. Here, we aim to estimate the proportion of handgun owners who divest their handguns in the years following their initial acquisition; examine the timing, duration, and dynamics of those divestments; and describe characteristics of those who divest.

Methods

We use data from the Longitudinal Study of Handgun Ownership and Transfer, a cohort of registered voters in California with detailed information on 626,756 adults who became handgun owners during the 12-year study period, 2004–2016. For the current study, persons were followed from the time of their initial handgun acquisition until divestment, loss to follow-up, death, or the end of the study period. We describe the cumulative proportion who divest overall and by personal and area-level characteristics. We also estimate the proportion who reacquired handguns among persons who divested.

Results

Overall, 4.5% (95% CI 4.5–4.6) of handgun owners divested within 5 years of their first acquisition, with divestment relatively more common among women and among younger adults. Among those who divested, 36.6% (95% CI 35.8–37.5) reacquired a handgun within 5 years.

Conclusions

Handgun divestment is rare, with the vast majority of new handgun owners retaining them for years.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40621-021-00362-6.

Mendelian Randomization With Repeated Measures of a Time-varying Exposure: An Application of Structural Mean Models

Mendelian randomization (MR) is often used to estimate effects of time-varying exposures on health outcomes using observational data. However, MR studies typically use a single measurement of exposure and apply conventional instrumental variable (IV) methods designed to handle time-fixed exposures. As such, MR effect estimates for time-varying exposures are often biased, and interpretations are unclear. We describe the instrumental conditions required for IV estimation with a time-varying exposure, and the additional conditions required to causally interpret MR estimates as a point effect, a period effect or a lifetime effect depending on whether researchers have measurements at a single or multiple time points. We propose methods to incorporate time-varying exposures in MR analyses based on g-estimation of structural mean models, and demonstrate its application by estimating the period effect of alcohol intake, high-density lipoprotein cholesterol and low-density lipoprotein cholesterol on intermediate coronary heart disease outcomes using data from the Framingham Heart Study. We use this data example to highlight the challenges of interpreting MR estimates as causal effects, and describe other extensions of structural mean models for more complex data scenarios.

Instrumental variable estimation for a time-varying treatment and a time-to-event outcome via structural nested cumulative failure time models

BACKGROUND

In many applications of instrumental variable (IV) methods, the treatments of interest are intrinsically time-varying and outcomes of interest are failure time outcomes. A common example is Mendelian randomization (MR), which uses genetic variants as proposed IVs. In this article, we present a novel application of g-estimation of structural nested cumulative failure models (SNCFTMs), which can accommodate multiple measures of a time-varying treatment when modelling a failure time outcome in an IV analysis.

METHODS

A SNCFTM models the ratio of two conditional mean counterfactual outcomes at time k under two treatment strategies which differ only at an earlier time m. These models can be extended to accommodate inverse probability of censoring weights, and can be applied to case-control data. We also describe how the g-estimates of the SNCFTM parameters can be used to calculate marginal cumulative risks under nondynamic treatment strategies. We examine the performance of this method using simulated data, and present an application of these models by conducting an MR study of alcohol intake and endometrial cancer using longitudinal observational data from the Nurses' Health Study.

RESULTS

Our simulations found that estimates from SNCFTMs which used an IV approach were similar to those obtained from SNCFTMs which adjusted for confounders, and similar to those obtained from the g-formula approach when the outcome was rare. In our data application, the cumulative risk of endometrial cancer from age 45 to age 72 under the "never drink" strategy (4.0%) was similar to that under the "always ½ drink per day" strategy (4.3%).

CONCLUSIONS

SNCFTMs can be used to conduct MR and other IV analyses with time-varying treatments and failure time outcomes.

Diemer and Swanson Reply to "Considerations Before Using Pandemic as Instrument"

Dimitris and Platt (Am J Epidemiol. 2021;190(11):2275-2279) take on the challenging topic of using "shocks" such as the severe acute respiratory system coronavirus 2 (SARS-CoV-2) pandemic as instrumental variables to study the effect of some exposure on some outcome. Evoking our recent lived experiences, they conclude that the assumptions necessary for an instrumental variable analysis will often be violated and therefore strongly caution against such analyses. Here, we build upon this warranted caution while acknowledging that such analyses will still be pursued and conducted. We discuss strategies for evaluating or reasoning about when such an analysis is clearly inappropriate for a given research question, as well as strategies for interpreting study findings with special attention to incorporating plausible sources of bias in any conclusions drawn from a given finding.

Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization: The STROBE-MR Statement

Importance

Mendelian randomization (MR) studies use genetic variation associated with modifiable exposures to assess their possible causal relationship with outcomes and aim to reduce potential bias from confounding and reverse causation.

Objective

To develop the STROBE-MR Statement as a stand-alone extension to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guideline for the reporting of MR studies.

Design, Setting, and Participants

The development of the STROBE-MR Statement followed the Enhancing the Quality and Transparency of Health Research (EQUATOR) framework guidance and used the STROBE Statement as a starting point to draft a checklist tailored to MR studies. The project was initiated in 2018 by reviewing the literature on the reporting of instrumental variable and MR studies. A group of 17 experts, including MR methodologists, MR study design users, developers of previous reporting guidelines, and journal editors, participated in a workshop in May 2019 to define the scope of the Statement and draft the checklist. The draft checklist was published as a preprint in July 2019 and discussed on the preprint platform, in social media, and at the 4th Mendelian Randomization Conference. The checklist was then revised based on comments, further refined through 2020, and finalized in July 2021.

Findings

The STROBE-MR checklist is organized into 6 sections (Title and Abstract, Introduction, Methods, Results, Discussion, and Other Information) and includes 20 main items and 30 subitems. It covers both 1-sample and 2-sample MR studies that assess 1 or multiple exposures and outcomes, and addresses MR studies that follow a genome-wide association study and are reported in the same article. The checklist asks authors to justify why MR is a helpful method to address the study question and state prespecified causal hypotheses. The measurement, quality, and selection of genetic variants must be described and attempts to assess validity of MR-specific assumptions should be well reported. An item on data sharing includes reporting when the data and statistical code required to replicate the analyses can be accessed.

Conclusions and Relevance

STROBE-MR provides guidelines for reporting MR studies. Improved reporting of these studies could facilitate their evaluation by editors, peer reviewers, researchers, clinicians, and other readers, and enhance the interpretation of their results.

Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19

Drug repurposing provides a rapid approach to meet the urgent need for therapeutics to address COVID-19. To identify therapeutic targets relevant to COVID-19, we conducted Mendelian randomization analyses, deriving genetic instruments based on transcriptomic and proteomic data for 1,263 actionable proteins that are targeted by approved drugs or in clinical phase of drug development. Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. We found significant Mendelian randomization results for three proteins (ACE2, P = 1.6 × 10-6; IFNAR2, P = 9.8 × 10-11 and IL-10RB, P = 2.3 × 10-14) using cis-expression quantitative trait loci genetic instruments that also had strong evidence for colocalization with COVID-19 hospitalization. To disentangle the shared expression quantitative trait loci signal for IL10RB and IFNAR2, we conducted phenome-wide association scans and pathway enrichment analysis, which suggested that IFNAR2 is more likely to play a role in COVID-19 hospitalization. Our findings prioritize trials of drugs targeting IFNAR2 and ACE2 for early management of COVID-19.

Mendelian randomisation approaches to the study of prenatal exposures: A systematic review

BACKGROUND

Mendelian randomisation (MR) designs apply instrumental variable techniques using genetic variants to study causal effects. MR is increasingly used to evaluate the role of maternal exposures during pregnancy on offspring health.

OBJECTIVES

We review the application of MR to prenatal exposures and describe reporting of methodologic challenges in this area.

DATA SOURCES

We searched PubMed, EMBASE, Medline Ovid, Cochrane Central, Web of Science, and Google Scholar.

STUDY SELECTION AND DATA EXTRACTION

Eligible studies met the following criteria: (a) a maternal pregnancy exposure; (b) an outcome assessed in offspring of the pregnancy; and (c) a genetic variant or score proposed as an instrument or proxy for an exposure.

SYNTHESIS

We quantified the frequency of reporting of MR conditions stated, techniques used to examine assumption plausibility, and reported limitations.

RESULTS

Forty-three eligible studies were identified. When discussing challenges or limitations, the most common issues described were known potential biases in the broader MR literature, including population stratification (n = 29), weak instrument bias (n = 18), and certain types of pleiotropy (n = 30). Of 22 studies presenting point estimates for the effect of exposure, four defined their causal estimand. Twenty-four studies discussed issues unique to prenatal MR, including selection on pregnancy (n = 1) and pleiotropy via postnatal exposure (n = 10) or offspring genotype (n = 20).

CONCLUSIONS

Prenatal MR studies frequently discuss issues that affect all MR studies, but rarely discuss problems specific to the prenatal context, including selection on pregnancy and effects of postnatal exposure. Future prenatal MR studies should report and attempt to falsify their assumptions, with particular attention to issues specific to prenatal MR. Further research is needed to evaluate the impacts of biases unique to prenatal MR in practice.

Hypothetical blood-pressure-lowering interventions and risk of stroke and dementia

We aimed to study the effects of hypothetical interventions on systolic blood pressure (SBP) and smoking on risk of stroke and dementia using data from 15 years of follow-up in the Rotterdam Study. We used data from 4930 individuals, aged 55-80 years, with no prior history of stroke, dementia or cognitive impairment, followed for 15 years within the Rotterdam Study, a population-based cohort. We defined the following sustained interventions on SBP: (1) maintaining SBP below 120 mmHg, (2) maintaining SBP below 140 mmHg, (3) reducing SBP by 10% if above 140 mmHg, (4) reducing SBP by 20% if above 140 mmHg, and a combined intervention of quitting smoking with each of these SBP-lowering strategies. We considered incident stroke and incident dementia diagnoses as outcomes. We applied the parametric g-formula to adjust for baseline and time-varying confounding. The observed 15-year risk for stroke was 10.7%. Compared to no specified intervention (i.e., the "natural course"), all interventions that involved reducing SBP were associated with a stroke risk reduction of about 10% (e.g., reducing SBP by 20% if above 140 mmHg risk ratio: 0.89; 95% CI 0.76, 1). Jointly intervening on SBP and smoking status further decreased the risk of stroke (e.g., risk ratio: 0.83; 95% CI 0.71, 0.94). None of the specified interventions were associated with a substantive change in dementia risk. Our study suggests that a joint intervention on SBP and smoking cessation during later life may reduce stroke risk, while the potential for reducing dementia risk were not observed.

Emulating a target trial of statin use and risk of dementia using cohort data

OBJECTIVE

Observational data can be used to attempt to emulate a target trial of statin use and estimate analogues of intention-to-treat and per protocol effects on dementia risk.

METHODS

Using data from a prospective cohort study in the Netherlands, we conceptualized a sequence of "trials" in which eligible individuals ages 55-80 years were classified as statin initiators or noninitiators for every consecutive month between 1993 and 2007 and were followed until diagnosis of dementia, death, loss to follow-up, or the end of follow-up. We estimated 2 types of effects of statin use on dementia and a combined endpoint of dementia or death: the effect of initiation vs no initiation and the effect of sustained use vs no use. We estimated risk by statin treatment strategy over time via pooled logistic regression. We used inverse-probability weighting to account for treatment-confounder feedback in estimation of per-protocol effects.

RESULTS

Of 233,526 eligible person-trials (6,373 individuals), there were 622 initiators and 232,904 noninitiators. Comparing statin initiation with no initiation, the 10-year risk differences (95% confidence interval) were -0.1% (-2.3% to 1.8%) for dementia and 0.3% (-2.7% to 3.3%) for dementia or death. Comparing sustained statin use vs no use, the 10-year risk differences were -2.2% (-5.2% to 1.6%) for dementia and -5.1% (-10.5% to -1.1%) for dementia or death.

CONCLUSIONS

Individuals with sustained statin use, but not statin initiation alone, had reduced 10-year risks of dementia and dementia or death. Our results should be interpreted with caution due to the small number of initiators and events and potential for residual confounding.

Prediction meets causal inference: the role of treatment in clinical prediction models

In this paper we study approaches for dealing with treatment when developing a clinical prediction model. Analogous to the estimand framework recently proposed by the European Medicines Agency for clinical trials, we propose a 'predictimand' framework of different questions that may be of interest when predicting risk in relation to treatment started after baseline. We provide a formal definition of the estimands matching these questions, give examples of settings in which each is useful and discuss appropriate estimators including their assumptions. We illustrate the impact of the predictimand choice in a dataset of patients with end-stage kidney disease. We argue that clearly defining the estimand is equally important in prediction research as in causal inference.

Handgun Ownership and Suicide in California

BACKGROUND

Research has consistently identified firearm availability as a risk factor for suicide. However, existing studies are relatively small in scale, estimates vary widely, and no study appears to have tracked risks from commencement of firearm ownership.

METHODS

We identified handgun acquisitions and deaths in a cohort of 26.3 million male and female residents of California, 21 years old or older, who had not previously acquired handguns. Cohort members were followed for up to 12 years 2 months (from October 18, 2004, to December 31, 2016). We used survival analysis to estimate the relationship between handgun ownership and both all-cause mortality and suicide (by firearm and by other methods) among men and women. The analysis allowed the baseline hazard to vary according to neighborhood and was adjusted for age, race and ethnic group, and ownership of long guns (i.e., rifles or shotguns).

RESULTS

A total of 676,425 cohort members acquired one or more handguns, and 1,457,981 died; 17,894 died by suicide, of which 6691 were suicides by firearm. Rates of suicide by any method were higher among handgun owners, with an adjusted hazard ratio of 3.34 for all male owners as compared with male nonowners (95% confidence interval [CI], 3.13 to 3.56) and 7.16 for female owners as compared with female nonowners (95% CI, 6.22 to 8.24). These rates were driven by much higher rates of suicide by firearm among both male and female handgun owners, with a hazard ratio of 7.82 for men (95% CI, 7.26 to 8.43) and 35.15 for women (95% CI, 29.56 to 41.79). Handgun owners did not have higher rates of suicide by other methods or higher all-cause mortality. The risk of suicide by firearm among handgun owners peaked immediately after the first acquisition, but 52% of all suicides by firearm among handgun owners occurred more than 1 year after acquisition.

CONCLUSIONS

Handgun ownership is associated with a greatly elevated and enduring risk of suicide by firearm. (Funded by the Fund for a Safer Future and others.).

Firearm access and adolescent suicide risk: toward a clearer understanding of effect size

BACKGROUND

Strong and consistent associations between access to firearms and suicide have been found in ecologic and individual-level observational studies. For adolescents, a seminal case-control study estimated that living in a home with (vs without) a firearm was associated with a fourfold increase in the risk of death by suicide.

METHODS

We use data from a nationally representative study of 10 123 US adolescents aged 13-18 years to (1) measure how much adolescents who live in a home with a firearm differ from those who do not in ways related to their risk of suicide, and (2) incorporate these differences into an updated effect estimate of the risk of adolescent suicide attributable to living in a home with firearms.

RESULTS

Almost one-third (30.7%) of adolescents reported living in a home with firearms. Relative to those who did not, adolescents reporting living in a home with a firearm were slightly more likely to be male, older and reside in the South and rural areas, but few differences were identified for mental health characteristics. The effect size found by Brent and colleagues appeared robust to sources of possible residual confounding: updated relative risks remained above 4.0 across most sensitivity analyses and at least 3.1 in even the most conservative estimates.

CONCLUSIONS

Although unmeasured confounding and other biases may nonetheless remain, our updated estimates reinforce the suggestion that adolescents' risk of suicide was increased threefold to fourfold if they had lived in homes with a firearm compared with if they had not.

Assembly of the LongSHOT cohort: public record linkage on a grand scale

BACKGROUND

Virtually all existing evidence linking access to firearms to elevated risks of mortality and morbidity comes from ecological and case-control studies. To improve understanding of the health risks and benefits of firearm ownership, we launched a cohort study: the Longitudinal Study of Handgun Ownership and Transfer (LongSHOT).

METHODS

Using probabilistic matching techniques we linked three sources of individual-level, state-wide data in California: official voter registration records, an archive of lawful handgun transactions and all-cause mortality data. There were nearly 28.8 million unique voter registrants, 5.5 million handgun transfers and 3.1 million deaths during the study period (18 October 2004 to 31 December 2016). The linkage relied on several identifying variables (first, middle and last names; date of birth; sex; residential address) that were available in all three data sets, deploying them in a series of bespoke algorithms.

RESULTS

Assembly of the LongSHOT cohort commenced in January 2016 and was completed in March 2019. Approximately three-quarters of matches identified were exact matches on all link variables. The cohort consists of 28.8 million adult residents of California followed for up to 12.2 years. A total of 1.2 million cohort members purchased at least one handgun during the study period, and 1.6 million died.

CONCLUSIONS

Three steps taken early may be particularly useful in enhancing the efficiency of large-scale data linkage: thorough data cleaning; assessment of the suitability of off-the-shelf data linkage packages relative to bespoke coding; and careful consideration of the minimum sample size and matching precision needed to support rigorous investigation of the study questions.

Methodological Challenges When Studying Distance to Care as an Exposure in Health Research

Distance to care is a common exposure and proposed instrumental variable in health research, but it is vulnerable to violations of fundamental identifiability conditions for causal inference. We used data collected from the Botswana Birth Outcomes Surveillance study between 2014 and 2016 to outline 4 challenges and potential biases when using distance to care as an exposure and as a proposed instrument: selection bias, unmeasured confounding, lack of sufficiently well-defined interventions, and measurement error. We describe how these issues can arise, and we propose sensitivity analyses for estimating the degree of bias.

The challenging interpretation of instrumental variable estimates under monotonicity

Background

Instrumental variable (IV) methods are often used to identify 'local' causal effects in a subgroup of the population of interest. Such 'local' effects may not be ideal for informing clinical or policy decision making. When the instrument is non-causal, additional difficulties arise for interpreting 'local' effects. Little attention has been paid to these difficulties, even though commonly proposed instruments in epidemiology are non-causal (e.g. proxies for physician's preference; genetic variants in some Mendelian randomization studies).

Methods

For IV estimates obtained from both causal and non-causal instruments under monotonicity, we present results to help investigators pose four questions about the local effect estimates obtained in their studies. (1) To what subgroup of the population does the effect pertain? Can we (2) estimate the size of or (3) describe the characteristics of this subgroup relative to the study population? (4) Can the sensitivity of the effect estimate to deviations from monotonicity be quantified?

Results

We show that the common interpretations and approaches for answering these four questions are generally only appropriate in the case of causal instruments.

Conclusions

Appropriate interpretation of an IV estimate under monotonicity as a 'local' effect critically depends on whether the proposed instrument is causal or non-causal. The results and formal proofs presented here can help in the transparent reporting of IV results and in enhancing the use of IV estimates in informing decision-making efforts.

The Course of Eating Disorders Involving Bingeing and Purging Among Adolescent Girls: Prevalence, Stability, and Transitions

PURPOSE

To quantify eating disorder (ED) stability and diagnostic transition among a community-based sample of adolescents and young adult females in the United States.

METHODS

Using 11 prospective assessments from 9,031 U.S. females ages 9-15 years at baseline of the Growing Up Today Study, we classified cases of the following EDs involving bingeing and purging: bulimia nervosa (BN), binge ED, purging disorder (PD), and subthreshold variants defined by less frequent (monthly vs. weekly) bingeing and purging behaviors. We measured number of years symptomatic and probability of maintaining symptoms, crossing to another diagnosis, or resolving symptoms across consecutive surveys.

RESULTS

Study lifetime disorder prevalence was 2.1% for BN and roughly 6% each for binge ED and PD. Most cases reported symptoms during only one survey year. Twenty-six percent of cases crossed between diagnoses during follow-up. Among participants meeting full threshold diagnostic criteria, transition from BN was most prevalent, crossing most frequently from BN to PD (12.9% of BN cases). Within each disorder phenotype, 20%-40% of cases moved between subthreshold and full threshold criteria across consecutive surveys.

CONCLUSIONS

Diagnostic crossover is not rare among adolescent and young adult females with an ED. Transition patterns from BN to PD add support for considering these classifications in the same diagnostic category of disorders that involve purging. The prevalence of crossover between monthly and weekly symptom frequency suggests that a continuum or staging approach may increase utility of ED classification for prognostic and therapeutic intervention.

Interpretation and Potential Biases of Mendelian Randomization Estimates With Time-Varying Exposures

Mendelian randomization (MR) is used to answer a variety of epidemiologic questions. One stated advantage of MR is that it estimates a "lifetime effect" of exposure, though this term remains vaguely defined. Instrumental variable analysis, on which MR is based, has focused on estimating the effects of point or time-fixed exposures rather than "lifetime effects." Here we use an empirical example with data from the Rotterdam Study (Rotterdam, the Netherlands, 2009-2013) to demonstrate how confusion can arise when estimating "lifetime effects." We provide one possible definition of a lifetime effect: the average change in outcome measured at time t when the entire exposure trajectory from conception to time t is shifted by 1 unit. We show that MR only estimates this type of lifetime effect under specific conditions-for example, when the effect of the genetic variants used on exposure does not change over time. Lastly, we simulate the magnitude of bias that would result in realistic scenarios that use genetic variants with effects that change over time. We recommend that investigators in future MR studies carefully consider the effect of interest and how genetic variants whose effects change with time may impact the interpretability and validity of their results.

The choice of effect measure for binary outcomes: Introducing counterfactual outcome state transition parameters

Standard measures of effect, including the risk ratio, the odds ratio, and the risk difference, are associated with a number of well-described shortcomings, and no consensus exists about the conditions under which investigators should choose one effect measure over another. In this paper, we introduce a new framework for reasoning about choice of effect measure by linking two separate versions of the risk ratio to a counterfactual causal model. In our approach, effects are defined in terms of "counterfactual outcome state transition parameters", that is, the proportion of those individuals who would not have been a case by the end of follow-up if untreated, who would have responded to treatment by becoming a case; and the proportion of those individuals who would have become a case by the end of follow-up if untreated who would have responded to treatment by not becoming a case. Although counterfactual outcome state transition parameters are generally not identified from the data without strong monotonicity assumptions, we show that when they stay constant between populations, there are important implications for model specification, meta-analysis, and research generalization.

The mediating role of the venules between smoking and ischemic stroke

A potential mechanism by which smoking affects ischemic stroke is through wider venules, but this mediating role of wider venules has never been quantified. Here, we aimed to estimate to what extent the effect of smoking on ischemic stroke is possibly mediated by the venules via the recently developed four-way effect decomposition. This study was part of a population-based study including 9109 stroke-free persons participated in the study in 1990, 2004, or 2006 (mean age: 63.7 years; 58% women). Smoking behavior (smoking versus non-smoking) was identified by interview. Retinal venular calibers were measured semi-automatically on retinal photographs. Incident strokes were assessed until January 2016. A regression-based approach was used with venular calibers as mediator to decompose the total effect of smoking compared to non-smoking into four components: controlled direct effect (neither mediation nor interaction), pure indirect effect (mediation only), reference interaction effect (interaction only) and mediated interaction effect (both mediation and interaction). During a mean follow-up of 12.5 years, 665 persons suffered an ischemic stroke. Smoking increased the risk of developing ischemic stroke compared to non-smoking with an excess risk of 0.41 (95% confidence interval 0.10; 0.67). With retinal venules as a potential mediator, the excess relative risk could be decomposed into 77% controlled direct effect, 4% mediation only, 4% interaction only, and 15% mediated interaction. To conclude, in the pathophysiology of ischemic stroke, the effect of smoking on ischemic stroke may partly explained by changes in the venules, where there is both pure mediation and mediated interaction.

Partial Identification of the Average Treatment Effect Using Instrumental Variables: Review of Methods for Binary Instruments, Treatments, and Outcomes

Several methods have been proposed for partially or point identifying the average treatment effect (ATE) using instrumental variable (IV) type assumptions. The descriptions of these methods are widespread across the statistical, economic, epidemiologic, and computer science literature, and the connections between the methods have not been readily apparent. In the setting of a binary instrument, treatment, and outcome, we review proposed methods for partial and point identification of the ATE under IV assumptions, express the identification results in a common notation and terminology, and propose a taxonomy that is based on sets of identifying assumptions. We further demonstrate and provide software for the application of these methods to estimate bounds. Supplementary materials for this article are available online.

Patients and investigators prefer measures of absolute risk in subgroups for pragmatic randomized trials

OBJECTIVES

Pragmatic randomized trials are important tools for shared decision-making, but no guidance exists on patients' preferences for types of causal information. We aimed to assess preferences of patients and investigators toward causal effects in pragmatic randomized trials.

STUDY DESIGN AND SETTING

We (a) held three focus groups with patients (n = 23) in Boston, MA; (b) surveyed (n = 12) and interviewed (n = 5) investigators with experience conducting pragmatic trials; and (c) conducted a systematic literature review of pragmatic trials (n = 63).

RESULTS

Patients were distrustful of new-to-market medications unless substantially more effective than existing choices, preferred stratified absolute risks, and valued adherence-adjusted analyses when they expected to adhere. Investigators wanted both intention-to-treat and per-protocol effects but felt methods for estimating per-protocol effects were lacking. When estimating per-protocol effects, many pragmatic trials used inappropriate methods to adjust for adherence and loss to follow-up.

CONCLUSION

We made four recommendations for pragmatic trials to improve patient centeredness: (1) focus on superiority in effectiveness or safety, rather than noninferiority; (2) involve patients in specifying a priori subgroups; (3) report absolute measures of risk; and (4) complement intention-to-treat effect estimates with valid per-protocol effect estimates.

Understanding the Assumptions Underlying Instrumental Variable Analyses: a Brief Review of Falsification Strategies and Related Tools

PURPOSE OF REVIEW

Instrumental variable (IV) methods continue to be applied to questions ranging from genetic to social epidemiology. In the epidemiologic literature, discussion of whether the assumptions underlying IV analyses hold is often limited to only certain assumptions and even then, arguments are mostly made using subject matter knowledge. To complement subject matter knowledge, there exist a variety of falsification strategies and other tools for weighing the plausibility of the assumptions underlying IV analyses.

RECENT FINDINGS

There are many tools that can refute the IV assumptions or help estimate the magnitude or direction of possible bias if the conditions do not hold perfectly. Many of these tools, including both recently developed strategies and strategies described decades ago, are underused or only used in specific applications of IV methods in epidemiology.

SUMMARY

Although estimating causal effects with IV analyses relies on unverifiable assumptions, the assumptions can sometimes be refuted. We suggest that the epidemiologists using IV analyses employ all the falsification strategies that apply to their research question in order to avoid settings that demonstrably violate a core condition for valid inference.

Agreement between Weight Status and Perceived Body Size and the Association with Body Size Satisfaction in Children

OBJECTIVE

Extensive evidence suggests that children and adolescents often inaccurately perceive their body size. However, the extent of this misperception is unclear. This paper describes the agreement between children's actual weight and the perception of body size (self-reported and maternally reported) and the association of actual weight with self-reported body satisfaction.

METHODS

In a population-based cohort study of 3,408 children aged 9 to 10 years, we assessed the children's self-perception and ideal perception of their body size with the Children's Body Image Scale. Maternal perception of offspring body size was assessed with the question "How would you describe your child at the moment?" Children's height and weight were measured.

RESULTS

Children tended to rate themselves toward average proportions; e.g., 83.0% of 499 children with overweight/obesity perceived themselves as less heavy then they were. Of those who underestimated their body size, most (79.2%) had a desire to be thinner; all of the children who correctly recognized their overweight/obesity had such a desire.

CONCLUSIONS

Despite the misperception of body size, the majority of children with overweight/obesity indicated dissatisfaction with their body size, suggesting more self-awareness than would be assumed based on the self-perception assessment of body size alone.

Characteristics of seeking treatment among U.S. adolescents with eating disorders

OBJECTIVE

The majority of persons with eating disorders (EDs) do not seek ED treatment, yet little is known about treatment-seeking barriers or facilitators. The aim of the study is to describe the characteristics associated with seeking ED treatment among U.S. adolescents with EDs.

METHOD

Data from a nationally representative cross-sectional study of U.S. adolescents ages 13-18 years were used for these analyses. Specifically, adolescents who met criteria for lifetime EDs (N = 281) were included. Sociodemographic information, characteristics of EDs, psychiatric comorbidities, and other mental health service use were assessed via interview.

RESULTS

Only 20% of adolescents sought ED treatment. Females were 2.2 (95% CI 0.8, 6.4) times more likely to seek treatment than males (19.9% vs. 8.9%). Adolescents who met criteria for anorexia nervosa or bulimia nervosa were 2.4 (95% CI 0.9, 6.3) and 1.9 (95% CI 1.0, 3.8) times more likely to seek treatment than adolescents who met criteria for binge-eating disorder (27.5% and 22.3% vs. 11.6%). Specific ED behaviors (restriction and purging), ED-related impairment, and any mental health service use were also associated with adolescent treatment seeking.

DISCUSSION

Adolescent treatment seeking was infrequent overall, with individuals with counter-stereotypic ED presentations least likely to have sought treatment. Adolescent treatment seeking could be promoted through increasing awareness among the public and healthcare professionals that EDs affect a heterogeneous group of people. More generally, research involving both treatment-seeking and non-treatment-seeking individuals holds great potential to refine the field's knowledge of ED etiology, prevalence, treatment, and prevention.

10-year trajectories of depressive symptoms and risk of dementia: a population-based study

BACKGROUND

Late-life depressive symptoms have been extensively studied for their relationship with incident dementia, but have been typically assessed at a single timepoint. Such an approach neglects the course of depression, which, given its remitting and relapsing nature, might provide further insights into the complex association of depression with dementia. We therefore repeatedly measured depressive symptoms in a population of adults over a decade to study the subsequent risk of dementia.

METHODS

Our study was embedded in the Rotterdam Study, a population-based study of adults aged 55 years or older in Rotterdam (Netherlands), ongoing since 1990. The cohort is monitored continuously for major events by data linkage between the study database and general practitioners. We examined a cohort of participants who were free from dementia, but had data for depressive symptoms from at least one examination round in 1993-95, 1997-99, or 2002-04. We assessed depressive symptoms with the validated Dutch version of the Center for Epidemiology Depression Scale (CES-D) and the Hospital Anxiety and Depression Scale-Depression. We used these data to identify 11-year trajectories of depressive symptoms by latent class trajectory modelling. We screened participants for dementia at each examination round and followed up participants for 10 years for incident dementia by latent trajectory from the third examination round to 2014. We calculated hazard ratios (HR) for dementia by assigned trajectory using two Cox proportional hazards models (model 1 adjusted for age and sex only, and model 2 adjusted additionally for APOEɛ4 carrier status, educational level, body-mass index, smoking, alcohol consumption, cognitive score, use of antidepressants, and prevalent disease status at baseline). We repeated the analyses censoring for incident stroke, restricting to Alzheimer's disease as an outcome, and accounting for mortality as a competing risk for dementia.

FINDINGS

From 1993-2004, we obtained data for depressive symptoms from at least one examination round for 3325 participants (median age: 74·88 years [IQR 70·62-80·06], 1995 [60%] women). We identified five trajectories of depressive symptoms in these 3325 individuals, characterised by maintained low CES-D scores (low; 2441 [73%]); moderately high starting scores but then remitting (decreasing; 369 [11%]); low starting scores, increasing, then remitting (remitting; 170 [5%]); low starting scores that steadily increased (increasing; 255 [8%]); and maintained high scores (high; 90 [3%]). During 26 330 person-years, 434 participants developed incident dementia. Only the trajectory with increasing depressive symptoms was associated with a higher risk of dementia compared with the low depressive symptom trajectory, using model 2 (HR 1·42, 95% CI 1·05-1·94; p=0·024). Additionally, only the increasing trajectory was associated with a higher risk of dementia compared with the low trajectory after censoring for incident stroke (1·58, 1·15-2·16; p=0·0041), restricting to Alzheimer's disease as an outcome (1·44, 1·03-2·02; p=0·034), and accounting for mortality as a competing risk (1·45, 1·06-1·97; p=0·019).

INTERPRETATION

Risk of dementia differed with different courses of depression, which could not be captured by a single assessment of depressive symptoms. The higher risk of dementia only in the increasing trajectory suggests depression might be a prodrome of dementia.

FUNDING

Erasmus Medical Center; ZonMw; the Netherlands Ministry of Education Culture and Science; and the Netherlands Ministry for Health, Welfare and Sports.

Predicting persistence to antidepressant treatment in administrative claims data: Considering the influence of refill delays and prior persistence on other medications

BACKGROUND

Many patients with major depressive disorder (MDD) who begin antidepressant treatment discontinue use before for six months, the recommended minimum treatment length. This study sought to identify predictors of six-month antidepressant persistence including predictors utilizing patients' electronic prescription records.

METHODS

Commercially insured children (3-17 years) and adults (18-64 years) with MDD who initiated antidepressant treatment, 1/1/2003-2/28/2010, were assessed for six-month persistence (based on prescriptions' days supply, allowing a 30-day grace period). Antidepressant persistence prediction models were developed separately for children and adults. Two additional measures, days without medication between the first and second antidepressant fill (children and adults) and prior persistence on other medications (adults only), were added to the models, concordance (c) statistics were compared and risk reclassification evaluated.

RESULTS

Among children (n=8837 children) and adults (n=47,495) with MDD, six-month antidepressant persistence was low and varied by age (37%, 18-24 years to 52%, 3-12 and 50-64 years). Independent baseline predictors of persistence were identified, with model c-statistics: children=0.582, adults=0.584. Patients with more days without medication between fills were less likely to be persistent (10-30 vs. 0 days, children: RR=0.72, adults: RR=0.74), as were adults not previously persistent to other medications (RR=0.73).

LIMITATIONS

The definition of six-month persistence is dependent on correct days supply values and the grace period utilized; potential predictors were limited to measures available in claims data.

CONCLUSIONS

Six-month antidepressant persistence was low and overall prediction of persistence was poor; however, days without medication between fills and prior persistence on other medications marginally improved the ability to predict antidepressant persistence.

Examining the utility of narrowing anorexia nervosa subtypes for adults

OBJECTIVE

The purpose of this investigation was to examine whether narrowing the criteria of anorexia nervosa (AN) subtypes among adults based on further delineations of current binge eating and purging (i.e., binge eating only, purging only, binge eating and purging, and restricting only) improves the potential clinical utility of the current DSM-5 system that specifies two types (i.e., current binge eating and/or purging and restricting, specified as the absence of current binge eating and/or purging).

METHOD

Self-reported eating disorder and psychiatric symptoms based on the Eating Disorder Questionnaire were examined in 347 adults from a multisite clinical sample who met DSM-IV criteria for AN. Classification based on binge eating and purging symptoms yielded the following subtypes: 118 restricting only (AN-R; no current binge eating or purging); 133 binge eating and purging (AN-B & P; current binge eating and purging); 43 binge eating only (AN-B; current binge eating and no current purging); and 53 purging only (AN-P; current purging and no current binge eating).

RESULTS

The AN-R group had lower current body mass index compared to AN-B & P and AN-P with no group differences in highest, lowest, or desired body mass index. The probability of amenorrhea was higher for the AN-R and AN-B & P groups than the AN-P group. The probability of diet pill use was elevated for the AN-B & P and AN-P groups compared to the AN-R group. The AN-P group also had a higher probability of fasting than the AN-R group. The probability of substance use including tobacco was lower in the AN-R group than the other three groups. No group differences were found on measures of hospitalization, body image, physical symptoms, exercise, or dieting behaviors.

CONCLUSIONS

These findings do not support the validity or clinical utility of classifying AN into narrower subtypes based on current binge eating, purging, and binge eating with purging given that few differences were found among groups who reported any combination of current binge eating and purging. Future research is needed to replicate these findings and to further examine the AN subtype classification schemes.