An introduction to instrumental variable assumptions, validation and estimation

Characteristics, consent patterns, and challenges of randomized trials using the Trials within Cohorts (TwiCs) design - A scoping review

OBJECTIVES

Trials within Cohorts (TwiCs) is a pragmatic design approach that may overcome frequent challenges of traditional randomized trials such as slow recruitment, burdensome consent procedures, or limited external validity. This scoping review aims to identify all randomized controlled trials using the TwiCs design and to summarize their design characteristics, ways to obtain informed consent, output, reported challenges and mitigation strategies.

STUDY DESIGN AND SETTING

Systematic search of Medline, Embase, Cochrane, trial registries and citation tracking up to December 2022. TwiCs were defined as randomized trials embedded in a cohort with postrandomization consent for the intervention group and no specific postrandomization consent for the usual care control group. Information from identified TwiCs was extracted in duplicate from protocols, publications, and registry entries. We analyzed the information descriptively and qualitatively to highlight methodological challenges and solutions related to nonuptake of interventions and informed consent procedure.

RESULTS

We identified a total of 46 TwiCs conducted between 2005 and 2022 in 14 different countries by a handful of research groups. The most common medical fields were oncology (11/46; 24%), infectious diseases (8/46; 17%), and mental health (7/46; 15%). A typical TwiCs was investigator-initiated (46/46; 100%), publicly funded (36/46; 78%), and recruited outpatients (27/46; 59%). Excluding eight pilot trials, only 16/38 (42%) TwiCs adjusted their calculated sample size for nonuptake of the intervention, anticipating a median nonuptake of 25% (interquartile range 10%-32%) in the experimental arm. Seventeen TwiCs (45%) planned analyses to adjust effect estimates for nonuptake. Regarding informed consent, we observed three patterns: 1) three separate consents for cohort participation, randomization, and intervention (17/46; 37%); 2) combined consent for cohort participation and randomization and a separate intervention consent (10/46; 22%); and 3) consent only for cohort participation and intervention (randomization consent not mentioned; 19/46; 41%).

CONCLUSION

Existing TwiCs are globally scattered across a few research groups covering a wide range of medical fields and interventions. Despite the potential advantages, the number of TwiCs remains small. The variability in consent procedures and the possibility of substantial nonuptake of the intervention warrants further research to guide the planning, implementation, and analysis of TwiCs.

The Cost of Opioid Use in High-Risk Hospitalized Infants

INTRODUCTION

Hospitalizations of high-risk infants are among the most expensive in the United States, with many requiring surgery and months of intensive care. Healthcare costs and resource use associated with hospitalized infant opioid exposure are less well known.

METHODS

A retrospective cohort of high-risk infants aged <1 y admitted from 47 children's hospitals from 2010 to 2020 was identified from Pediatric Healthcare Information System. High-risk infants were identified by International Classification of Diseases 9/10 codes for congenital heart disease procedures, medical and surgical necrotizing enterocolitis, extremely low birth weight, very low birth weight, hypoxemic ischemic encephalopathy, extracorporeal membrane oxygenation, and gastrointestinal tract malformations. Healthcare resource utilization was estimated using standardized unit costs (SUCs). The impact of opioid use on SUC was examined using general linear models and an instrumental variable.

RESULTS

Overall, 126,897 high-risk infants were identified. The cohort was majority White (57.1%), non-Hispanic (72.0%), and male (55.4%). Prematurity occurred in 26.4% and a majority underwent surgery (77.9%). Median SUC was $120,585 (interquartile range: $57,602-$276,562) per infant. On instrumental variable analysis, each day of opioid use was associated with an increase of $4406 in SUC. When adjusting for biologic sex, race, ethnicity, insurance type, diagnosis category, number of comorbidities, mechanical ventilation, and total parental nutrition use, each day of opioid use was associated with an increase of $2177 per infant.

CONCLUSIONS

Prolonged opioid use is significantly associated with healthcare utilization and costs for high-risk infants, even when accounting for comorbidities, intensive care, ventilation, and total parental nutrition use. Future studies are needed to estimate the long-term complications and additional costs resulting from prolonged opioid exposures in high-risk infants.

Transcriptome-Wide Root Causal Inference

Root causal genes correspond to the first gene expression levels perturbed during pathogenesis by genetic or non-genetic factors. Targeting root causal genes has the potential to alleviate disease entirely by eliminating pathology near its onset. No existing algorithm discovers root causal genes from observational data alone. We therefore propose the Transcriptome-Wide Root Causal Inference (TWRCI) algorithm that identifies root causal genes and their causal graph using a combination of genetic variant and unperturbed bulk RNA sequencing data. TWRCI uses a novel competitive regression procedure to annotate cis and trans-genetic variants to the gene expression levels they directly cause. The algorithm simultaneously recovers a causal ordering of the expression levels to pinpoint the underlying causal graph and estimate root causal effects. TWRCI outperforms alternative approaches across a diverse group of metrics by directly targeting root causal genes while accounting for distal relations, linkage disequilibrium, patient heterogeneity and widespread pleiotropy. We demonstrate the algorithm by uncovering the root causal mechanisms of two complex diseases, which we confirm by replication using independent genome-wide summary statistics.

Using the global randomization test as a Mendelian randomization falsification test for the exclusion restriction assumption

Mendelian randomization may give biased causal estimates if the instrument affects the outcome not solely via the exposure of interest (violating the exclusion restriction assumption). We demonstrate use of a global randomization test as a falsification test for the exclusion restriction assumption. Using simulations, we explored the statistical power of the randomization test to detect an association between a genetic instrument and a covariate set due to (a) selection bias or (b) horizontal pleiotropy, compared to three approaches examining associations with individual covariates: (i) Bonferroni correction for the number of covariates, (ii) correction for the effective number of independent covariates, and (iii) an r2 permutation-based approach. We conducted proof-of-principle analyses in UK Biobank, using CRP as the exposure and coronary heart disease (CHD) as the outcome. In simulations, power of the randomization test was higher than the other approaches for detecting selection bias when the correlation between the covariates was low (r2 < 0.1), and at least as powerful as the other approaches across all simulated horizontal pleiotropy scenarios. In our applied example, we found strong evidence of selection bias using all approaches (e.g., global randomization test p < 0.002). We identified 51 of the 58 CRP genetic variants as horizontally pleiotropic, and estimated effects of CRP on CHD attenuated somewhat to the null when excluding these from the genetic risk score (OR = 0.96 [95% CI: 0.92, 1.00] versus 0.97 [95% CI: 0.90, 1.05] per 1-unit higher log CRP levels). The global randomization test can be a useful addition to the MR researcher's toolkit.

Mendelian randomization studies of periodontitis: Understanding benefits and natural limitations in an applied context

Mendelian randomization (MR) is a flexible analytical tool that has been widely applied to strengthen causal inference in observational epidemiology and is now gaining attention in many areas including periodontal research. The interpretation of results drawn from MR is based on a series of assumptions, which can be unrealistic or difficult to meet faithfully in some settings. However, we argue that with care, this does not necessarily prevent valuable deployment of the approach. We argue that clarity of presentation as well as careful assessment of specific analytical conditions is a fundamental part of all MR analyses. To that end, awareness of its limitations should also guide the design of MR investigations and the presentation of results rather than rule out its use altogether. Notably, considerations similar to those known to be important in conventional epidemiological settings apply to MR. While MR studies are valuable in their contrast to other study limitations, the application of this technique must be carefully cross-examined. Specific considerations include possible confounders, recruitment strategy and phenotypic measurement and differential analysis properties across studies. In the case of periodontal research, current MR applications are limited by the available evidence base for genetic contributions to periodontitis; however, this sets a specific scene for the strategic use of MR and shines light on a need for greater research emphasis on the genetics of the condition and intermediaries. This article provides a perspective on the uses and inherent limitations of MR studies and the importance of adhering to basic epidemiological principles when designing them.

Pathway-Based Mendelian Randomization for Pre-Infection IL-6 Levels Highlights Its Role in Coronavirus Disease

OBJECTIVES

Interleukin 6 (IL-6) levels at hospital admission have been suggested for disease prognosis, and IL-6 antagonists have been suggested for the treatment of patients with severe COVID-19. However, less is known about the relationship between pre-COVID-19 IL-6 levels and the risk of severe COVID-19. To fill in this gap, here we extensively investigated the association of genetically instrumented IL-6 pathway components with the risk of severe COVID-19.

METHODS

We used a two-sample Mendelian randomization study design and retrieved genetic instruments for blood biomarkers of IL-6 activation, including IL-6, soluble IL-6 receptor, IL-6 signal transducer, and CRP, from respective large available GWASs. To establish associations of these instruments with COVID-19 outcomes, we used data from the Host Genetics Initiative and GenOMICC studies.

RESULTS

Our analyses revealed inverse associations of genetically instrumented levels of IL-6 and its soluble receptor with the risk of developing severe disease (OR = 0.60 and 0.94, respectively). They also demonstrated a positive association of severe disease with the soluble signal transducer level (OR = 1.13). Only IL-6 associations with severe COVID-19 outcomes reached the significance threshold corrected for multiple testing (p < 0.003; with COVID-19 hospitalization and critical illness).

CONCLUSIONS

These potential causal relationships for pre-COVID-19 IL-6 levels with the risk of developing severe symptoms provide opportunities for further evaluation of these factors as prognostic/preventive markers of severe COVID-19. Further studies will need to clarify whether the higher risk for a severe disease course with lower baseline IL-6 levels may also extend to other infectious diseases.

The causal effect of mental health on labor market outcomes: The case of stress-related mental disorders following a human-made disaster

As disasters increase due to climate change, population density, epidemics, and technology, information is needed about postdisaster consequences for people's mental health and how stress-related mental disorders affect multiple spheres of life, including labor-market attachment. We tested the causal hypothesis that individuals who developed stress-related mental disorders as a consequence of their disaster exposure experienced subsequent weak labor-market attachment and poor work-related outcomes. We leveraged a natural experiment in an instrumental variables model, studying a 2004 fireworks factory explosion disaster that precipitated the onset of stress-related disorders (posttraumatic stress disorder, anxiety, and depression) among individuals in the local community (N = 86,726). We measured labor-market outcomes using longitudinal population-level administrative data: sick leave, unemployment benefits, early retirement pension, and income from wages from 2007 to 2010. We found that individuals who developed a stress-related disorder after the disaster were likely to go on sickness benefit, both in the short- and long-term, were likely to use unemployment benefits and to lose wage income in the long term. Stress-related disorders did not increase the likelihood of early retirement. The natural experiment design minimized the possibility that omitted confounders biased these effects of mental health on work outcomes. Addressing the mental health and employment needs of survivors after a traumatic experience may improve their labor-market outcomes and their nations' economic outputs.

Individual and regional differences in the effects of school racial segregation on Black students' health

Background

School racial segregation in the US has risen steadily since the 1990s, propelled by Supreme Court decisions rolling back the legacy of Brown v. Board. Quasi-experimental research has shown this resegregation harms Black students' health. However, whether individual or family characteristics (e.g., higher family incomes) are protective against segregation's health harms-or whether segregation is more damaging in regions of the US with fewer public sector investments-remains unclear. We leverage the quasi-random timing of school districts being released from Brown-era integration plans to examine heterogeneity in the association between resegregation and Black students' health.

Methods & findings

We took an instrumental variables approach, using the timing of integration order releases as an instrument for school segregation and analyzing a pre-specified list of theoretically-motivated modifiers in the Panel Study of Income Dynamics. In sensitivity analyses, we fit OLS models that directly adjusted for relevant covariates. Results suggest resegregation may have been particularly harmful in the South, where districts resegregated more quickly after order releases. We find little evidence that the effects of school segregation differed across family income, gender, or age.

Conclusion

The end of court-ordered integration threatens the health of Black communities-especially in the US South. Modestly higher incomes do not appear protective against school segregation's harms. Research using larger samples and alternative measures of school segregation-e.g., between districts, instead of within districts-may further our understanding of segregation's health effects, especially in Northern states.

Patient outcomes, efficiency, and adverse events for elective hip and knee replacement in private and NHS hospitals: a population-based cohort study in England

Background

Since the early 2000s, the National Health Service (NHS) in England has expanded provision of publicly funded care in private hospitals as a strategy to meet growing demand for elective care. This study aims to compare patient outcomes, efficiency and adverse events in private and NHS hospitals when providing elective hip and knee replacement.

Methods

We conducted a population-based cohort study including patients ≥18 years, undergoing a publicly funded elective hip or knee replacement in private and NHS hospitals in England between January 1st 2016 and March 31st 2019. Comparative probability was estimated for three patient outcome measures (in-hospital mortality, emergency readmissions with 28 days, hospital transfers), two efficiency measures (pre-operative length of stay (LOS) >0 day and post-operative LOS >2 days), and four adverse events (hospital-associated infection, adverse drug reactions, pressure ulcers, venous thromboembolism). Probit regression was used to adjust for observable confounding followed by instrumental variable (IV) analyses to also account for unobserved confounding at the patient-level. Propensity score matching was then used as a robustness check.

Findings

Our study sample included 169,232 patients in private hospitals, and 262,659 patients in NHS hospitals. Estimates from probit regression indicated that treatment in private hospital was associated with reduced probability of in-hospital mortality (-0.0009, 95% CI -0.0010, -0.0007), emergency readmissions (-0.0181, 95% CI -0.0191, -0.0172), hospital transfers (-0.0076, 95% CI -0.0084, -0.0068), prolonged post-operative LOS (-0.1174, 95% CI -0.1547, -0.0801), hospital-associated infection (-0.0115, 95% CI -0.0123, -0.0107), adverse drug reactions (-0.0051, 95% CI -0.0056, -0.0046), pressure ulcers (-0.0017, 95% CI -0.0019, -0.0014), and venous thromboembolism (-0.0027, 95% CI -0.0031, -0.0022). IV analyses produced no significant differences between private and NHS hospitals, except for lower probability in private hospitals of hospital-associated infection (-0.0057, 95% CI -0.0081, -0.0032), and greater probability in private hospitals of prolonged post-operative LOS (0.2653, 95% CI 0.1833, 0.3472). Propensity score matching produced similar results to probit regression.

Interpretation

Our findings indicate there is potentially important unobservable confounding at the patient-level between private and NHS hospitals not adjusted for when using probit regression or propensity score matching.

Funding

This research did not receive any dedicated funding.

Progression-free survival as a surrogate endpoint for overall survival in patients with relapsed or refractory multiple myeloma

OBJECTIVES

The goal of the research was to assess the quantitative relationship between median progression-free survival (PFS) and median overall survival (OS) specifically among patients with relapsed/refractory multiple myeloma (RRMM) based on published randomized controlled trials (RCTs).

METHODS

Two bibliographic databases (PubMed and Embase, 1970-2017) were systematically searched for RCTs in RRMM that reported OS and PFS, followed by an updated search of studies published between 2010 and 2022 in 3 databases (Embase, MEDLINE, and EBM Reviews, 2010-2022). The association between median PFS and median OS was assessed using the nonparametric Spearman rank and parametric Pearson correlation coefficients. Subsequently, the quantitative relationship between PFS and OS was assessed using weighted least-squares regression adjusted for covariates including age, sex, and publication year. Study arms were weighted by the number of patients in each arm.

RESULTS

A total of 31 RCTs (56 treatment arms, 10,450 patients with RRMM) were included in the analysis. The average median PFS and median OS were 7.1 months (SD 5.5) and 28.1 months (SD 11.8), respectively. The Spearman and Pearson correlation coefficients between median PFS and median OS were 0.80 (P < 0.0001) and 0.79 (P < 0.0001), respectively. In individual treatment arms of RRMM trials, each 1-month increase in median PFS was associated with a 1.72-month (95% CI 1.26-2.17) increase in median OS.

CONCLUSION

Analysis of the relationship between PFS and OS incorporating more recent studies in RRMM further substantiates the use of PFS to predict OS in RRMM.

Application of causal inference methods in individual-participant data meta-analyses in medicine: addressing data handling and reporting gaps with new proposed reporting guidelines

Observational data provide invaluable real-world information in medicine, but certain methodological considerations are required to derive causal estimates. In this systematic review, we evaluated the methodology and reporting quality of individual-level patient data meta-analyses (IPD-MAs) conducted with non-randomized exposures, published in 2009, 2014, and 2019 that sought to estimate a causal relationship in medicine. We screened over 16,000 titles and abstracts, reviewed 45 full-text articles out of the 167 deemed potentially eligible, and included 29 into the analysis. Unfortunately, we found that causal methodologies were rarely implemented, and reporting was generally poor across studies. Specifically, only three of the 29 articles used quasi-experimental methods, and no study used G-methods to adjust for time-varying confounding. To address these issues, we propose stronger collaborations between physicians and methodologists to ensure that causal methodologies are properly implemented in IPD-MAs. In addition, we put forward a suggested checklist of reporting guidelines for IPD-MAs that utilize causal methods. This checklist could improve reporting thereby potentially enhancing the quality and trustworthiness of IPD-MAs, which can be considered one of the most valuable sources of evidence for health policy.

The relationship between preventive dental care and overall medical expenditures

OBJECTIVES

To examine the relationship between preventive dental visits (PDVs) and medical expenditures while mitigating bias from unobserved confounding factors.

STUDY DESIGN

Retrospective data analysis of Indiana Medicaid enrollment and claims data (2015-2018) and the Area Health Resources Files.

METHODS

An instrumental variable (IV) approach was used to estimate the relationship between PDVs and medical and pharmacy expenditures among Medicaid enrollees. The instrument was defined as the number of adult enrollees with at least 1 nonpreventive dental claim per total Medicaid enrollees within a Census tract per year.

RESULTS

In naive analyses, enrollees had on average greater medical expenditures if they had a prior-year PDV (β = $397.21; 95% CI, $184.23-$610.18) and a PDV in the same year as expenditures were measured (β = $344.81; 95% CI, $193.06-$496.56). No significant differences in pharmacy expenditures were observed in naive analyses. Using the IV approach, point estimates of overall medical expenditures for the marginal enrollee who had a prior-year PDV (β = $325.17; 95% CI, -$708.03 to $1358.37) or same-year PDV (β = $170.31; 95% CI, -$598.89 to $939.52) were similar to naive results, although not significant. Our IV approach indicated that PDV was not endogenous in some specifications.

CONCLUSIONS

This is the first study to present estimates with causal inference from a quasi-experimental study of the effect of PDVs on overall medical expenditures. We observed that prior- or same-year PDVs were not related to overall medical or pharmacy expenditures.

Does cycle commuting reduce the risk of mental ill-health? An instrumental variable analysis using distance to nearest cycle path

BACKGROUND

Previous studies have linked cycling with improved mental wellbeing but these studies tend to use cross-sectional survey data that have small sample sizes and self-reported health measures, and are potentially susceptible to omitted-variable bias and reverse causation. We use an instrumental variable approach and an objective measure of mental ill-health taken from linked administrative data to ask: 'Does cycle commuting reduce the risk of mental ill-health?'

METHODS

Our study links data on commuting in Edinburgh and Glasgow from the Scottish population census with mental health prescriptions from the National Health Service Prescribing Information System records. We use road distance from home to nearest cycle path as an instrumental variable for cycle commuting.

RESULTS

In total, 378 253 people aged 16-74 years living and working in the City of Edinburgh and Glasgow City council areas at the 2011 census were included in our study; 1.85% of commuters in Glasgow and 4.8% of commuters in Edinburgh cycled to work. Amongst cyclists, 9% had a prescription for mental health compared with 14% amongst non-cyclists. Using a bivariate probit model, we estimate a mean average reduction in prescriptions for antidepressants and/or anxiolytics in the 5 years following the census of -15.1% (95% CI: -15.3% to -15.0%) amongst cycle commuters compared with those who use any other mode to commute.

CONCLUSIONS

This work suggests that cycle commuting is causally related to reduced mental ill-health and provides further evidence in support of the promotion of active travel to encourage commuters travelling shorter distances to shift to cycle commutes.

Causal relationship between gut microbiota and hidradenitis suppurativa: a two-sample Mendelian randomization study

Background

Accumulating evidence suggests that alterations in gut microbiota composition are associated with the hidradenitis suppurativa (HS). However, the causal association between gut microbiota and HS remain undetermined.

Methods

We performed a bidirectional two-sample Mendelian randomization (MR) analysis using genome-wide association study summary data of gut microbiota and hidradenitis suppurativa from the MiBioGen consortium which concluded 18,340 individuals analyzed by the MiBioGen Consortium, comprising 211 gut microbiota. HS data were acquired from strictly defined HS data collected by FinnGenbiobank analysis, which included 211,548 European ancestors (409 HS patients, 211,139 controls). The inverse variance weighted method (IVW), weighted median (WME), simple model, weighted model, weighted median, and MR-Egger were used to determine the changes of HS pathogenic bacterial taxa, followed by sensitivity analysis including horizontal pleiotropy analysis. The MR Steiger test evaluated the strength of a causal association and the leave-one-out method assessed the reliability of the results. Additionally, a reverse MR analysis was carried out to seek for possible reverse causality.

Results

By combining the findings of all the MR steps, we identified four causal bacterial taxa, namely, Family XI, Porphyromonadaceae, Clostridium innocuum group and Lachnospira. The risk of HS might be positively associated with a high relative abundance of Clostridium innocuum group (Odds ratio, OR 2.17, p = 0.00038) and Lachnospira (OR 2.45, p = 0.017) but negatively associated with Family XI (OR 0.67, p = 0.049) and Porphyromonadaceae (OR 0.29, p = 0.014). There were no noticeable outliers, horizontal pleiotropy, or heterogeneity. Furthermore, there was no proof of reverse causation found in the reverse MR study.

Conclusion

This study indicates that Clostridium innocuum group and Lachnospira might have anti-protective effect on HS, whereas Family XI and Porphyromonadaceae might have a protective effect on HS. Our study reveals that there exists a beneficial or detrimental causal effect of gut microbiota composition on HS and offers potentially beneficial methods for therapy and avoidance of HS.

Instrumental variables for implementation science: exploring context-dependent causal pathways between implementation strategies and evidence-based interventions

BACKGROUND

The impact of both implementation strategies (IS) and evidence-based interventions (EBI) can vary across contexts, and a better understanding of how and why this occurs presents fundamental but challenging questions that implementation science as a field will need to grapple with. We use causal epidemiologic methods to explore the mechanisms of why sharp distinctions between implementation strategies (IS) and efficacy of an evidence-based intervention (EBI) may fail to recognize that the effect of an EBI can be deeply intertwined and dependent on the context of the IS leading to its uptake.

METHODS

We explore the use of instrumental variable (IV) analyses as a critical tool for implementation science methods to isolate three relevant quantities within the same intervention context when exposure to an implementation strategy is random: (1) the effect of an IS on implementation outcomes (e.g., uptake), (2) effect of EBI uptake on patient outcomes, and (3) overall effectiveness of the IS (i.e., ~ implementation*efficacy). We discuss the mechanisms by which an implementation strategy can alter the context, and therefore effect, of an EBI using the underlying IV assumptions. We illustrate these concepts using examples of the implementation of new ART initiation guidelines in Zambia and community-based masking programs in Bangladesh.

RESULTS

Causal questions relevant to implementation science are answered at each stage of an IV analysis. The first stage assesses the effect of the IS (e.g., new guidelines) on EBI uptake (e.g., same-day treatment initiation). The second stage leverages the IS as an IV to estimate the complier average causal effect (CACE) of the EBI on patient outcomes (e.g., effect of same-day treatment initiation on viral suppression). The underlying assumptions of CACE formalize that the causal effect of EBI may differ in the context of a different IS because (1) the mechanisms by which individuals uptake an intervention may differ and (2) the subgroup of individuals who take up an EBI may differ. IV methods thus provide a conceptual framework for how IS and EBIs are linked and that the IS itself needs to be considered a critical contextual determinant. Moreover, it also provides rigorous methodologic tools to isolate the effect of an IS, EBI, and combined effect of the IS and EBI.

DISCUSSION

Leveraging IV methods when exposure to an implementation strategy is random helps to conceptualize the context-dependent nature of implementation strategies, EBIs, and patient outcomes. IV methods formalize that the causal effect of an EBI may be specific to the context of the implementation strategy used to promote uptake. This integration of implementation science concepts and theory with rigorous causal epidemiologic methods yields novel insights and provides important tools for exploring the next generation of questions related to mechanisms and context in implementation science.

Microbiome and its implications in oncogenesis: a Mendelian randomization perspective

The human microbiome, an intricate ecological network, has garnered significant attention due to its potential implications in oncogenesis. This paper delves into the multifaceted relationships between the microbiome, its metabolites, and cancer development, emphasizing the human intestinal tract as the primary microbial habitat. Highlighting the potential causative associations between microbial disturbances and cancer progression, we underscore the role of specific bacterial strains in various cancers, such as stomach and colorectal cancer. Traditional causality assessment methods, like randomized controlled trials (RCTs), have limitations. Therefore, we advocate using Mendelian Randomization (MR) as a powerful alternative to study causal relationships, leveraging genetic variants as instrumental variables. With the proliferation of genome-wide association studies, MR harnesses genetic variations to infer causality, which is especially beneficial when addressing confounders like diet and lifestyle that can skew microbial research. We systematically review MR's application in understanding the microbiome-cancer nexus, emphasizing its strengths and challenges. While MR offers a unique perspective on causality, it faces hurdles like horizontal pleiotropy and weak instrumental variable bias. Integrating MR with multi-omics data, encompassing genomics, transcriptomics, proteomics, and metabolomics, holds promise for future research, potentially heralding groundbreaking discoveries in microbiology and genetics. This comprehensive review underscores the critical role of the human microbiome in oncogenesis and champions MR as an indispensable tool for advancing our understanding in this domain.

Estimating bidirectional effects between social connectedness and mental health in adolescent students: Addressing biases due to endogeneity

Research on the bidirectional relationship between social connectedness and health/mental health in adolescents is scarce, with most studies on adults. Some of the existing studies exploited the availability of longitudinal data to provide evidence of the existence of a causal relationship, either from social connectedness to health or establish a bidirectional relationship. There are at least two weaknesses associated with earlier research to assess the size of the effects. As acknowledged in the literature, one relates to attributing causality to empirical findings, due to well-known but inadequately addressed endogeneity biases. The other relates to failure to account for potentially important covariates, sometimes due to data limitations, or because such variables are not frequently used in sociological research. Existing research predominantly finds that the strongest path is from social connectedness to health/mental health, with effect estimates modest in size. I followed a quasi-experimental strategy by modelling adolescent students' perceptions of social connectedness and mental health perceptions as potentially endogenous variables when estimating bidirectional effects. An instrumental variables (IV) modelling approach was followed, supplemented with a recently developed alternative approach to testing the exclusion restrictions of individual instruments. I exploited the rich information available in the PISA 2018 multi-country dataset, which allows for conditioning for a wide array of information on adolescent students' personal circumstances, self-reported personality-related attributes, relationships with parents; and school characteristics. I found that (1) accounting for endogeneity biases is important; and (2) as opposed to findings reported in the literature, the dominant effect is from mental health perceptions to social connectedness for both male and female participants. The policy relevance of the findings is that adolescent mental health should be the primary focus of interventions, i.e., identifying and treating mental health symptoms as a primary intervention and as a precursor to improving the social connectedness of adolescents.

Application of Causal Inference Methods to Pooled Longitudinal Non- Randomized Studies: A Methodological Systematic Review

Observational data provide invaluable real-world information in medicine, but certain methodological considerations are required to derive causal estimates. In this systematic review, we evaluated the methodology and reporting quality of individual-level patient data meta-analyses (IPD-MAs) published in 2009, 2014, and 2019 that sought to estimate a causal relationship in medicine. We screened over 16,000 titles and abstracts, reviewed 45 full-text articles out of the 167 deemed potentially eligible, and included 29 into the analysis. Unfortunately, we found that causal methodologies were rarely implemented, and reporting was generally poor across studies. Specifically, only three of the 29 articles used quasi-experimental methods, and no study used G-methods to adjust for time-varying confounding. To address these issues, we propose stronger collaborations between physicians and methodologists to ensure that causal methodologies are properly implemented in IPD-MAs. In addition, we put forward a suggested checklist of reporting guidelines for IPD-MAs that utilize causal methods. This checklist could improve reporting thereby potentially enhancing the quality and trustworthiness of IPD-MAs, which can be considered one of the most valuable sources of evidence for health policy.

Vitamin D and suicidality: a Chinese early adolescent cohort and Mendelian randomization study

AIMS

Previous cross-sectional and case-control studies have proposed that decreased vitamin D levels are positively correlated with the risk of suicidality in adults. However, limited studies have examined the association between vitamin D and suicidality in adolescents. This study aimed to investigate the relationship between serum vitamin D and suicidality risk among early adolescents.

METHODS

Data were obtained from a Chinese early adolescent cohort. In this cohort, seventh-grade students from a middle school in Anhui Province were invited to voluntarily participate in the baseline assessments and provide peripheral blood samples (in September 2019). The participants were followed up annually (in September 2020 and September 2021). Serum 25-hydroxyvitamin D [25(OH)D] and vitamin D-related single-nucleotide polymorphisms at baseline were measured in November 2021. Traditional observational and Mendelian randomization (MR) analyses were performed to examine the relationship between serum 25(OH)D at baseline and the risk of baseline and incident suicidality (i.e., suicidal ideation [SI], plans and attempts).

RESULTS

Traditional observational analysis did not reveal a significant linear or non-linear association of serum 25(OH)D concentration with the risks of baseline and 2-year incident suicidality in the total sample (P > .05 for all). Sex-stratified analysis revealed a non-linear association between the 25(OH)D concentration and the risk of baseline SI in women (Poverall = .002; Pnon-linear = .001). Moreover, the risk of baseline SI in the 25(OH) insufficiency group was lower than that in the 25(OH) deficiency group in the total sample (odds ratio [OR] = 0.69, 95% confidence interval [CI] = 0.51-0.92, P = .012). This difference remained significant in women (OR = 0.59, 95% CI = 0.40-0.87, P = .008) but not in men (OR = 0.78, 95% CI = 0.53-1.15, P = .205). Additionally, both linear and non-linear MR analyses did not support the causal effect of serum 25(OH)D concentration on the risk of baseline, 1-year and 2-year incident suicidality (P > .05 for all).

CONCLUSIONS

This study could not confirm the causal effect of vitamin D on suicidality risk among Chinese early adolescents. Future studies must confirm these findings with a large sample size.

The challenge of dementia prevention trials and the role of quasi-experimental studies

Observational studies have shown consistently that modifiable risk factors during life are associated with increased dementia risk in old age but randomized controlled trials (RCTs) on dementia prevention evaluating the treatment of these risk factors did not find consistent effects on cognitive outcomes. The discrepancy in findings is potentially attributable to inherent differences between the two study designs. Although RCTs are the gold standard for establishing causality, designing and conducting an RCT for dementia prevention is complex. Quasi-experimental studies (QESs) may contribute to investigating causality without randomization. QESs use variation in exposure to a risk factor or intervention in an observational setting to deduct causal effects. Design-specific approaches are used to control for confounding, the main caveat of QESs. In this article we address the challenges, opportunities, and limitations of QESs for research into dementia prevention. HIGHLIGHTS: Despite consistent associations between modifiable risk factors and dementia, the mostly neutral effects of randomized controlled trials (RCTs) challenge the causality of these associations. RCTs in the field of dementia prevention are often problematic due to ethical, practical, or financial constraints, and their results may have limited generalizability. Four quasi-experimental study (QES) designs may be suitable to study causality between risk factors and dementia; we critically appraise these study designs for dementia-prevention studies. We describe how specific QES designs can be used to study the effects of risk-factor modification for 12 known risk factors for dementia.

The impact of sleep quality on mental health in working Australians: A quasi-experimental approach

Work conditions such as job demand can impact individual sleep quality, and subsequently impact mental health. This study aims to investigate pathway effects of exogenous factors on mental health via sleep, and the direct effect of sleep quality on mental health in working Australians. We employ a novel method in public health studies, a quasi-experimental (instrumental variable) approach, which can address reciprocal relationships between sleep and mental health in order to estimate causal effect of sleep quality on mental health in a sample of 19,789 working Australians aged 25-64 from waves 2013, 2017, and 2021 of the Household, Income and Labour Dynamics in Australia (HILDA) survey data. We find that high job demand, as a valid instrument, adversely affects sleep quality, and the changes in sleep quality ultimately affect mental health of working Australians. These findings highlight the need for policies that address employment conditions by reducing high work demand or work pressure to mitigate poor sleep quality in the Australian workforce, ultimately improving workers' sleep quality and promoting better mental health, overall health outcomes and productivity.

Intraoperative hydromorphone decreases postoperative pain: an instrumental variable analysis

BACKGROUND

Intraoperative administration of short-acting opioids might lead to increased postoperative pain and opioid requirements. There are few data describing the effects of intermediate-duration opioids such as hydromorphone on these outcomes. We have previously shown that a switch from a 2 mg to a 1 mg vial of hydromorphone was associated with decreased intraoperative dose administration. As presentation dose affected intraoperative hydromorphone administration and was unrelated to other policy changes, it could serve as an instrumental variable, assuming significant secular trends were not present during the study period.

METHODS

In this observational cohort study of patients who received intraoperative hydromorphone (n=6750), an instrumental variable analysis was used to evaluate whether intraoperative hydromorphone administration affected postoperative pain scores and opioid administration. Before July 2017, hydromorphone was available as a 2-mg unit dose. From July 1, 2017 to November 20, 2017, hydromorphone was only available in a 1-mg unit dose. A two-stage least squares regression analysis was used to estimate causal effects.

RESULTS

A 0.2-mg increase in intraoperative hydromorphone administration caused a decrease in admission PACU pain scores (mean difference, -0.8; 95% confidence interval, -1.2 to -0.4; P<0.001) and decreased maximum and time-weighted mean pain scores over 2 days postoperatively, without increased opioid administration.

CONCLUSIONS

This study suggests that intraoperative administration of intermediate-duration opioids does not cause the same effects as short-acting opioids with respect to postoperative pain. Instrumental variables can be used to estimate causal effects using observation data when unmeasured confounding is present.

Associations between health behaviours, fertility and reproductive outcomes: triangulation of evidence in the Norwegian Mother, Father and Child Cohort Study (MoBa)

BACKGROUND

Guidance to improve fertility includes reducing alcohol and caffeine consumption, achieving healthy weight-range and stopping smoking. Advice is informed by observational evidence, which is often biased by confounding.

METHODS

This study primarily used data from a pregnancy cohort, the Norwegian Mother, Father and Child Cohort Study. First, we conducted multivariable regression of health behaviours (alcohol and caffeine consumption, body-mass index (BMI), and smoking) on fertility outcomes (e.g. time to conception) and reproductive outcomes (e.g. age at first birth) (n = 84,075 females, 68,002 males), adjusting for birth year, education and attention-deficit and hyperactive-impulsive (ADHD) traits. Second, we used individual-level Mendelian randomisation (MR) to explore possible causal effects of health behaviours on fertility/reproductive outcomes (n = 63,376 females, 45,460 males). Finally, we performed summary-level MR for available outcomes in UK Biobank (n = 91,462-1,232,091) and controlled for education and ADHD liability using multivariable MR.

RESULTS

In multivariable regression analyses, higher BMI associated with fertility (longer time to conception, increased odds of infertility treatment and miscarriage), and smoking was associated with longer time to conception. In individual-level MR analyses, there was strong evidence for effects of smoking initiation and higher BMI on younger age at first birth, of higher BMI on increased time to conception, and weak evidence for effects of smoking initiation on increased time to conception. Age at first birth associations were replicated in summary-level MR analysis; however, effects attenuated using multivariable MR.

CONCLUSIONS

Smoking behaviour and BMI showed the most consistent associations for increased time to conception and a younger age at first birth. Given that age at first birth and time to conception are positively correlated, this suggests that the mechanisms for reproductive outcomes are distinct to the mechanisms acting on fertility outcomes. Multivariable MR suggested that effects on age at first birth might be explained by underlying liability to ADHD and education.

The effect of maternal BMI, smoking and alcohol on congenital heart diseases: a Mendelian randomisation study

BACKGROUND

Congenital heart diseases (CHDs) remain a significant cause of infant morbidity and mortality. Epidemiological studies have explored maternal risk factors for offspring CHDs, but few have used genetic epidemiology methods to improve causal inference.

METHODS

Three birth cohorts, including 65,510 mother/offspring pairs (N = 562 CHD cases) were included. We used Mendelian randomisation (MR) analyses to explore the effects of genetically predicted maternal body mass index (BMI), smoking and alcohol on offspring CHDs. We generated genetic risk scores (GRS) using summary data from large-scale genome-wide association studies (GWAS) and validated the strength and relevance of the genetic instrument for exposure levels during pregnancy. Logistic regression was used to estimate the odds ratio (OR) of CHD per 1 standard deviation (SD) higher GRS. Results for the three cohorts were combined using random-effects meta-analyses. We performed several sensitivity analyses including multivariable MR to check the robustness of our findings.

RESULTS

The GRSs associated with the exposures during pregnancy in all three cohorts. The associations of the GRS for maternal BMI with offspring CHD (pooled OR (95% confidence interval) per 1SD higher GRS: 0.95 (0.88, 1.03)), lifetime smoking (pooled OR: 1.01 (0.93, 1.09)) and alcoholic drinks per week (pooled OR: 1.06 (0.98, 1.15)) were close to the null. Sensitivity analyses yielded similar results.

CONCLUSIONS

Our results do not provide robust evidence of an effect of maternal BMI, smoking or alcohol on offspring CHDs. However, results were imprecise. Our findings need to be replicated, and highlight the need for more and larger studies with maternal and offspring genotype and offspring CHD data.

Anti-Epileptic Drug Target Perturbation and Intracranial Aneurysm Risk: Mendelian Randomization and Colocalization Study

BACKGROUND

In a genome-wide association study of intracranial aneurysms (IA), enrichment was found between genes associated with IA and genes encoding targets of effective anti-epileptic drugs. Our aim was to assess if this pleiotropy is driven by shared disease mechanisms that could potentially highlight a treatment strategy for IA.

METHODS

Using 2-sample inverse-variance weighted Mendelian randomization and genetic colocalization analyses we assessed: (1) if epilepsy liability in general affects IA risk, and (2) whether changes in gene- and protein-expression levels of anti-epileptic drug targets in blood and arterial tissue may causally affect IA risk.

RESULTS

We found no overall effect of epilepsy liability on IA. Expression of 21 genes and 13 proteins corresponding to anti-epileptic drug targets supported a causal effect (P<0.05) on IA risk. Of those genes and proteins, genetic variants affecting CNNM2 levels showed strong evidence for colocalization with IA risk (posterior probability>70%). Higher CNNM2 levels in arterial tissue were associated with increased IA risk (odds ratio, 3.02; [95% CI, 2.32-3.94]; P=3.39×10^-16). CNNM2 expression was best proxied by rs11191580. The magnitude of the effect of this variant was greater than would be expected if systemic blood pressure was the sole IA-causing mechanism in this locus.

CONCLUSIONS

CNNM2 is a driver of the pleiotropy between IA and anti-epileptic drug targets. Administration of the anti-epileptic drugs phenytoin, valproic acid, or carbamazepine may be expected to decrease CNNM2 levels and therefore subsequently decrease IA risk. CNNM2 is therefore an important target to investigate further for its role in the pathogenesis of IA.

Key considerations for choosing a statistical method to deal with incomplete treatment adherence in pragmatic trials

Pragmatic trials offer practical means of obtaining real-world evidence to help improve decision-making in comparative effectiveness settings. Unfortunately, incomplete adherence is a common problem in pragmatic trials. The commonly used methods in randomized control trials often cannot handle the added complexity imposed by incomplete adherence, resulting in biased estimates. Several naive methods and advanced causal inference methods (e.g., inverse probability weighting and instrumental variable-based approaches) have been used in the literature to deal with incomplete adherence. Practitioners and applied researchers are often confused about which method to consider under a given setting. This current work is aimed to review commonly used statistical methods to deal with non-adherence along with their key assumptions, advantages, and limitations, with a particular focus on pragmatic trials. We have listed the applicable settings for these methods and provided a summary of available software. All methods were applied to two hypothetical datasets to demonstrate how these methods perform in a given scenario, along with the R codes. The key considerations include the type of intervention strategy (point treatment settings, where treatment is administered only once versus sustained treatment settings, where treatment has to be continued over time) and availability of data (e.g., the extent of measured or unmeasured covariates that are associated with adherence, dependent confounding impacted by past treatment, and potential violation of assumptions). This study will guide practitioners and applied researchers to use the appropriate statistical method to address incomplete adherence in pragmatic trial settings for both the point and sustained treatment strategies.

Pre-processing data to reduce biases: full matching incorporating an instrumental variable in population-based studies

BACKGROUND

Epidemiologists are often concerned with unobserved biases that produce confounding in population-based studies. We introduce a new design approach-'full matching incorporating an instrumental variable (IV)' or 'Full-IV Matching'-and illustrate its utility in reducing observed and unobserved biases to increase inference accuracy. Our motivating example is tailored to a central question in humanitarian emergencies-the difference in sexual violence risk by displacement setting.

METHODS

We conducted a series of 1000 Monte Carlo simulations generated from a population-based survey after the 2010 Haitian earthquake and included earthquake damage severity as an IV and the unmeasured variable of 'social capital'. We compared standardized mean differences (SMDs) for covariates after different designs to understand potential biases. Mean risk differences (RDs) were used to assess each design's accuracy in estimating the oracle of the simulated data set.

RESULTS

Naive analysis and pair matching equivalently performed. Full matching reduced imbalances between exposed and comparison groups across covariates, except for the unobserved covariate of 'social capital'. Pair and full matching overstated differences in sexual violence risk when displaced to a camp vs a community [pair: RD = 0.13, 95% simulation interval (SI) 0.09-0.16; full: RD = 0.11, 95% SI 0.08-0.14). Full-IV Matching reduced imbalances across observed covariates and importantly 'social capital'. The estimated risk difference (RD = 0.07, 95% SI 0.03-0.11) was closest to the oracle (RD = 0.06, 95% SI 0.4-0.8).

CONCLUSION

Full-IV Matching is a novel approach that is promising for increasing inference accuracy when unmeasured sources of bias likely exist.

Use of Instrumental Variable Analyses for Evaluating Comparative Effectiveness in Empirical Applications of Oncology: A Systematic Review

PURPOSE

This systematic review aims to characterize the use and trends of instrumental variables (IVs) in oncology research, assess the quality and completeness of IV reporting, and evaluate the agreement and interpretation of IV results in comparison with other techniques used for determining comparative effectiveness in observational research.

METHODS

We performed a systematic search of observational empirical oncology papers evaluating the comparative effectiveness of cancer treatments using IV methods. EMBASE and MEDLINE (through June 2021) were used for a keyword search; Scopus and Web of Science were used for a citation search. Publication details and characteristics of IV analysis and reporting were extracted from each study to examine the uptake and quality of IV applications.

RESULTS

Sixty-five empirical papers were identified from February 2001 through June 2021. Geographic variation (50.8%) was the most common type of IV used, and the majority of IV applications constructed binary instruments (53.8%). Concurrent analyses using another non-IV method to adjust for confounding were conducted in 56 (86.2%) studies, 17 (30.4%) of which produced results divergent from IV approaches. We observed a modest uptake of IV methods between 2011 and 2021 together with its dissemination, which remained fairly limited to the United States (76.9%). The quality and completeness of IV reporting varied greatly. The underlying assumptions required for a valid IV analysis were only accounted for in full by 20 (30.8%) studies.

CONCLUSION

There are limited use and variable quality of IV analyses in oncology. Future research should look to establish standards to better facilitate the quality, transparency, and completeness of IV reporting in this setting.

Learning the Treatment Impact on Time-to-Event Outcomes: The Transcarotid Artery Revascularization Simulated Cohort

Proportional hazard Cox regression models are overwhelmingly used for analyzing time-dependent outcomes. Despite their associated hazard ratio is a valuable index for the difference between populations, its strong dependency on the underlying assumptions makes it a source of misinterpretation. Recently, a number of works have dealt with the subtleties and limitations of this interpretation. Besides, a number of alternative indices and different Cox-type models have been proposed. In this work, we use synthetic data, motivated by a real-world problem, for showing the strengths and weaknesses of some of those methods in the analysis of time-dependent outcomes. We use the power of synthetic data for considering observable results but also utopian designs.

eQTLs as causal instruments for the reconstruction of hormone linked gene networks

Hormones act within in highly dynamic systems and much of the phenotypic response to variation in hormone levels is mediated by changes in gene expression. The increase in the number and power of large genetic association studies has led to the identification of hormone linked genetic variants. However, the biological mechanisms underpinning the majority of these loci are poorly understood. The advent of affordable, high throughput next generation sequencing and readily available transcriptomic databases has shown that many of these genetic variants also associate with variation in gene expression levels as expression Quantitative Trait Loci (eQTLs). In addition to further dissecting complex genetic variation, eQTLs have been applied as tools for causal inference. Many hormone networks are driven by transcription factors, and many of these genes can be linked to eQTLs. In this mini-review, we demonstrate how causal inference and gene networks can be used to describe the impact of hormone linked genetic variation upon the transcriptome within an endocrinology context.

Compliance with telephone-based lifestyle weight loss programs improves low back pain but not knee pain outcomes: complier average causal effects analyses of 2 randomised trials

ABSTRACT

We conducted a complier average causal effect (CACE) analyses for 2 pragmatic randomised controlled trials. We aimed to assess the effectiveness of telephone-based lifestyle weight loss interventions compared with usual care among compliers. Participants from 2 trials with low back pain (n = 160) and knee osteoarthritis (n = 120) with a body mass index ≥27 kg/m2 were included. We defined adherence to the telephone-based lifestyle weight loss program as completing 60% (6 from 10) of telephone health coaching calls. The primary outcomes for CACE analyses were pain intensity (0-10 Numerical Rating Scale) and disability (Roland Morris Disability Questionnaire for low back pain and Western Ontario and McMaster Universities Osteoarthritis Index for knee osteoarthritis). Secondary outcomes were weight, physical activity, and diet. We used an instrumental variable approach to estimate CACE in compliers. From the intervention groups of the trials, 29% of those with low back pain (n = 23/80) and 34% of those with knee osteoarthritis (n = 20/60) complied. Complier average causal effect estimates showed potentially clinically meaningful effects, but with low certainty because of wide confidence intervals, for pain intensity (-1.4; 95% confidence interval, -3.1, 0.4) and small but also uncertain effects for disability (-2.1; 95% confidence interval, -8.6, 4.5) among compliers in the low back pain trial intervention compared with control but not in the knee osteoarthritis trial. Our findings showed that compliers of a telephone-based weight loss intervention in the low back pain trial generally had improved outcomes; however, there were inconsistent effects in compliers from the knee osteoarthritis trial. Complier average causal effect estimates were larger than intention-to-treat results but must be considered with caution.

Comparative effectiveness of intracranial hypertension management guided by ventricular versus intraparenchymal pressure monitoring: a CENTER-TBI study

OBJECTIVE

To compare outcomes between patients with primary external ventricular device (EVD)-driven treatment of intracranial hypertension and those with primary intraparenchymal monitor (IP)-driven treatment.

METHODS

The CENTER-TBI study is a prospective, multicenter, longitudinal observational cohort study that enrolled patients of all TBI severities from 62 participating centers (mainly level I trauma centers) across Europe between 2015 and 2017. Functional outcome was assessed at 6 months and a year. We used multivariable adjusted instrumental variable (IV) analysis with "center" as instrument and logistic regression with covariate adjustment to determine the effect estimate of EVD on 6-month functional outcome.

RESULTS

A total of 878 patients of all TBI severities with an indication for intracranial pressure (ICP) monitoring were included in the present study, of whom 739 (84%) patients had an IP monitor and 139 (16%) an EVD. Patients included were predominantly male (74% in the IP monitor and 76% in the EVD group), with a median age of 46 years in the IP group and 48 in the EVD group. Six-month GOS-E was similar between IP and EVD patients (adjusted odds ratio (aOR) and 95% confidence interval [CI] OR 0.74 and 95% CI [0.36-1.52], adjusted IV analysis). The length of intensive care unit stay was greater in the EVD group than in the IP group (adjusted rate ratio [95% CI] 1.70 [1.34-2.12], IV analysis). One hundred eighty-seven of the 739 patients in the IP group (25%) required an EVD due to refractory ICPs.

CONCLUSION

We found no major differences in outcomes of patients with TBI when comparing EVD-guided and IP monitor-guided ICP management. In our cohort, a quarter of patients that initially received an IP monitor required an EVD later for ICP control. The prevalence of complications was higher in the EVD group.

PROTOCOL

The core study is registered with ClinicalTrials.gov , number NCT02210221, and the Resource Identification Portal (RRID: SCR_015582).

Understanding the assumptions underlying Mendelian randomization

With the rapidly increasing availability of large genetic data sets in recent years, Mendelian Randomization (MR) has quickly gained popularity as a novel secondary analysis method. Leveraging genetic variants as instrumental variables, MR can be used to estimate the causal effects of one phenotype on another even when experimental research is not feasible, and therefore has the potential to be highly informative. It is dependent on strong assumptions however, often producing biased results if these are not met. It is therefore imperative that these assumptions are well-understood by researchers aiming to use MR, in order to evaluate their validity in the context of their analyses and data. The aim of this perspective is therefore to further elucidate these assumptions and the role they play in MR, as well as how different kinds of data can be used to further support them.

Pragmatic Clinical Studies: An Emerging Clinical Research Discipline for Improving Evidence-Based Practice of Cardiovascular Diseases in Asia

Pragmatic clinical studies, an emerging clinical research discipline, include a wide range of studies that are largely embedded with routine clinical practice and aim to evaluate the comparative effectiveness and safety of different clinical intervention strategies. Increased availability and quality of electronic medical/health records drives the development of pragmatic clinical studies. In this review, we describe evolution of the conceptual framework of pragmatic clinical studies and share perspectives on the importance of pragmatic clinical studies in evidence-based practice for cardiovascular diseases, as a complement to conventional randomized controlled trials. We also highlight specific needs of pragmatic clinical studies in improving evidence-based practice for cardiovascular disease in Asian countries. The main challenges of pragmatic clinical studies are discussed briefly in this review.

School racial segregation and long-term cardiovascular health among Black adults in the US: A quasi-experimental study

BACKGROUND

Cardiovascular disease (CVD) disproportionately affects Black adults in the United States. This is increasingly acknowledged to be due to inequitable distribution of health-promoting resources. One potential contributor is inequities in educational opportunities, although it is unclear what aspects of education are most salient. School racial segregation may affect cardiovascular health by increasing stress, constraining socioeconomic opportunities, and altering health behaviors. We investigated the association between school segregation and Black adults' CVD risk.

METHODS AND FINDINGS

We leveraged a natural experiment created by quasi-random (i.e., arbitrary) timing of local court decisions since 1991 that released school districts from court-ordered desegregation. We used the Panel Study of Income Dynamics (PSID) (1991 to 2017), linked with district-level school segregation measures and desegregation court order status. The sample included 1,053 Black participants who ever resided in school districts that were under a court desegregation order in 1991. The exposure was mean school segregation during observed schooling years. Outcomes included several adult CVD risk factors and outcomes. We fitted standard ordinary least squares (OLS) multivariable linear regression models, then conducted instrumental variables (IV) analysis, using the proportion of schooling years spent in districts that had been released from court-ordered desegregation as an instrument. We adjusted for individual- and district-level preexposure confounders, birth year, and state fixed effects. In standard linear models, school segregation was associated with a lower probability of good self-rated health (-0.05 percentage points per SD of the segregation index; 95% CI: -0.08, -0.03; p < 0.001) and a higher probability of binge drinking (0.04 percentage points; 95% CI: 0.002, 0.07; p = 0.04) and heart disease (0.01 percentage points; 95% CI: 0.002, 0.15; p = 0.007). IV analyses also found that school segregation was associated with a lower probability of good self-rated health (-0.09 percentage points; 95% CI: -0.17, -0.02, p = 0.02) and a higher probability of binge drinking (0.17 percentage points; 95% CI: 0.04, 0.30, p = 0.008). For IV estimates, only binge drinking was robust to adjustments for multiple hypothesis testing. Limitations included self-reported outcomes and potential residual confounding and exposure misclassification.

CONCLUSIONS

School segregation exposure in childhood may have longstanding impacts on Black adults' cardiovascular health. Future research should replicate these analyses in larger samples and explore potential mechanisms. Given the recent rise in school segregation, this study has implications for policies and programs to address racial inequities in CVD.

The Impact of Care Intensity and Work on the Mental Health of Family Caregivers: Losses and Gains

OBJECTIVES

We estimate the causal impact of intensive caregiving, defined as providing at least 80 h of care per month, and work on the mental health of caregivers while considering possible sources of endogeneity in these relationships.

METHODS

We use 2 linked data sources from the United States by matching caregivers in the National Study of Caregiving with corresponding care recipients in the National Health and Aging Trends Study for years 2011-2017. We address possible sources of endogeneity in the relationships between caregiving, work, and mental health by using instrumental variables methodology, instrumenting for both caregiving and work behavior. We examine 2 measures used to screen for depression (PHQ-2, psychodiagnostic test) and anxiety (GAD-2, generalized anxiety disorders screening instrument), a composite measure that combines these measures (PHQ-4), and positive well-being variables to ascertain possible gains from caregiving.

RESULTS

Providing at least 80 h of care per month to a parent compared to less intensive caregiving increases the PHQ-4 scale for anxiety and depression disorders. This is driven by the screening score for anxiety and not psychodiagnostic test scores for depression. Relationship quality decreases substantially for intensive caregivers, and intensive caregiving leads to less satisfaction that the care recipient is well-cared for. We do not find offsetting mental health gains for intensive caregivers compared to nonintensive caregivers. Work does not independently affect the mental health of caregivers.

DISCUSSION

Caregiver interventions that reduce objective demands or support intensive caregivers could reduce or prevent well-being losses and improve the caregiver's relationship with the recipient.

Effect of Treatment in a Specialized Pediatric Hemato-Oncology Setting on 5-Year Survival in Acute Lymphoblastic Leukemia: A Quasi-Experimental Study

Simple Summary

Adolescents and young adults (AYAs) with acute lymphoblastic leukemia (ALL) have a worse prognosis than children. In addition to differences in biology—such as higher incidence of unfavorable genetic alterations in the AYA population—this might be related to the fact that ALL patients under a certain age (often 18 years) are generally treated in special pediatric hemato-oncology settings, which is associated with improved survival, while patients above that age are treated in adult hemato-oncology care settings. Based on previous research, adult treatment settings have increasingly adopted pediatric-inspired protocols, which appear to have led to increased survival of adolescent ALL patients. This study aims to assess whether there remains an effect of treatment of ALL patients in a specialized pediatric hemato-oncology setting on 5-year survival. This study provides insight into the effects of such treatment for ALL patients, and may stimulate further research into causal relationships in other oncological conditions.

Abstract

Survival rates of adolescents and young adults (AYAs) with acute lymphoblastic leukemia (ALL) are inferior to those of pediatric ALL patients. In part, this may be caused by differences in treatment setting. Generally, children are treated in specialized pediatric hemato-oncology settings, whereas AYAs are treated in adult hemato-oncology settings. Since 2005, adult treatment protocols have included pediatric-inspired chemotherapy, which has been the standard of care for AYAs from 2008 onwards. This study aims to assess whether, despite protocols in both settings having become more similar, there remains an effect of treatment in specialized pediatric hemato-oncology settings on 5-year survival for ALL patients in the Netherlands. We used nationwide registry data (2004–2013) on 472 ALL patients aged between 10 and 30 years old. A fuzzy regression discontinuity design was applied to estimate the treatment effect using two-stage least squares regression with the treatment threshold at 17 years and 7 months of age, adjusting for sex, age at diagnosis, and immunophenotype. We found a risk difference of 0.419 (p = 0.092; 95% CI = −0.0686; 0.907), meaning a 41.9 percentage point greater probability of surviving five years after diagnosis for ALL patients treated in specialized pediatric hemato-oncology settings. Our results suggest that ALL patients around the threshold could benefit from increased collaboration between pediatric and adult hemato-oncology in terms of survival.

The Effect of Perceived Threats and Response Efficacy on Adaptation to Smog: An Instrumental Variables Design

Threats and response efficacyperceptions are core conceptsof the protection motivationtheory, and recent years have witnessed a considerable growth of research on the effect of thesefactors on adaptation to air pollution. However, few studies use appropriate designs to deal with endogeneity issues, a situation that raises serious questions on the validity of their findings. To overcome this problem, this study uses the instrumental variables method to test the effect of perceived threats and response efficacy on adaptation to smog episodes. The results of this study show that the conjunction of a moderate to high perception of threats with a high perception of response efficacy is positively associated with the adoption of the recommended behavior. The increase of perceived threats does not seem to have an effect on the behavior of individuals with low response efficacy perception. Moreover, change in perceived response efficacy does not lead to any change in the behavior of individuals with low threat perceptions. Concerning policy implications, this study suggests that smog warnings and health communication campaigns could be more effective if they provide accurate information simultaneously on air pollution level, its adverse effects, and advice on how to mitigate these effects.

Association between discontinuing chronic opioid therapy and newly diagnosed substance use disorders, accidents, self-inflicted injuries and drug overdoses within the prescribers' health care system: a retrospective cohort study

BACKGROUND AND AIM

Prescribers are commonly confronted with discontinuing opioid therapy among patients prescribed chronic opioid therapy (COT). This study aimed to measure the association between discontinuing COT and diagnoses of substance use disorders (SUDs) and opioid-related adverse outcomes (AOs).

DESIGN

Retrospective cohort study.

SETTING

United States Veterans Healthcare Administration.

PARTICIPANTS

Veterans with chronic pain on COT who discontinued opioid therapy were compared with those continuing COT using data from fiscal years 2009 to 2015.

MEASUREMENTS

Newly diagnosed substance use disorders (SUD composite; individual types: opioid, non-opioid drug and alcohol use disorders) and opioid-related adverse outcomes (AO composite; individual types: accidents resulting in wounds/injuries, opioid-related accidents/overdoses, alcohol and non-opioid medication-related accidents/overdoses, self-inflicted injuries and violence-related injuries) were evaluated. Primary analyses were conducted using 1:1 matching of discontinuers with those continuing COT based on propensity score and index date (±180-day window). Sensitivity analyses were conducted using logistic regressions with stabilized inverse probability of treatment weighting (SIPTW) and instrumental variable (IV) models.

FINDINGS

A total of 15 695 (75.4%) and 17 337 (76.6%) discontinuers were matched with those continuing COT among the cohorts testing SUD and AO development respectively. In the primary propensity score matched analyses, the composite SUD outcome was not different between discontinuers and those continuing COT (OR = 0.932, 95% CI = 0.850, 1.022). The composite AO outcome was lower among discontinuers (OR = 0.660, 95% CI = 0.623, 0.699) compared with those continuing COT. SIPTW analyses found lower SUD (OR = 0.789, 95% CI = 0.743, 0.837), and AO (OR = 0.660, 95% CI = 0.623, 0.699) rates among discontinuers. IV models found mixed and sometimes contradictory results.

CONCLUSIONS

Discontinuing patients from chronic opioid therapy appears to be associated with decreased diagnoses for opioid-related adverse outcomes. The association with substance use disorders appears to be inconclusive.

A methodological framework for tackling confounding by indication when assessing the treatment effects of Chinese herbal injections in the real world

AIM

In the context of integrative medicine, whether Chinese herbal injections are effective in routine practice has become a question of broad interest. However, confounding by indication (i.e., indication bias) is a prevalent and highly challenging methodological issue when using routinely collected health care data to assess the real-world effectiveness of Chinese herbal injections.

METHODS AND RESULTS

We proposed a methodological approach to tackling confounding by indication in assessing the real-world effectiveness of Chinese herbal injections, incorporating empirical experiences, a literature review and interactive discussions, and a panel of external experts to finally achieve a consensus. This approach consisted of three cohesive steps, including a full understanding of treatment patterns, construction of fair comparisons by identifying appropriate combination treatments and comparators, and using statistical methods to further control for confounding. In the investigation of treatment patterns, we proposed five domains to identify treatment patterns with Chinese herbal injections, and we offered five patterns of combination treatments to characterize how Chinese herbal injections are used in conjunction with other treatments. In constructing fair comparisons, we suggested the use of both nonuse and active comparators; given the diverse combination treatments, we developed six scenarios that may form fair comparisons. In the statistical analysis, we discussed five statistical models for controlling confounding by indication, including their pros and cons. We also included a practical example to illustrate the usefulness of the methodological approach.

CONCLUSION

The proposed approach may serve as an effective tool to guide researchers to reliably assess the effectiveness of Chinese herbal injections in the context of integrative medicine.

Mendelian randomization

Mendelian randomization (MR) is a term that applies to the use of genetic variation to address causal questions about how modifiable exposures influence different outcomes. The principles of MR are based on Mendel's laws of inheritance and instrumental variable estimation methods, which enable the inference of causal effects in the presence of unobserved confounding. In this Primer, we outline the principles of MR, the instrumental variable conditions underlying MR estimation and some of the methods used for estimation. We go on to discuss how the assumptions underlying an MR study can be assessed and give methods of estimation that are robust to certain violations of these assumptions. We give examples of a range of studies in which MR has been applied, the limitations of current methods of analysis and the outlook for MR in the future. The difference between the assumptions required for MR analysis and other forms of non-interventional epidemiological studies means that MR can be used as part of a triangulation across multiple sources of evidence for causal inference.

Early life lead exposure from private well water increases juvenile delinquency risk among US teens

Early life exposure to environmental lead (Pb) has been linked to decreased IQ, behavior problems, lower lifetime earnings, and increased criminal activity. Beginning in the 1970s, limits on Pb in paint, gasoline, food cans, and regulated water utilities sharply curtailed US environmental Pb exposure. Nonetheless, hundreds of thousands of US children remain at risk. This study reports on how unregulated private well water is an underrecognized Pb exposure source that is associated with an increased risk of teenage juvenile delinquency. We build a longitudinal dataset linking blood Pb measurements for 13,580 children under age 6 to their drinking water source, individual- and neighborhood-level demographics, and reported juvenile delinquency records. We estimate how early life Pb exposure from private well water influences reported delinquency. On average, children in homes with unregulated private wells had 11% higher blood Pb than those with community water service. This higher blood Pb was significantly associated with reported delinquency. Compared to children with community water service, those relying on private wells had a 21% (95% CI: 5 to 40%) higher risk of being reported for any delinquency and a 38% (95% CI: 10 to 73%) increased risk of being reported for serious delinquency after age 14. These results suggest that there could be substantial but as-yet-unrecognized social benefits from intervention programs to prevent children's exposure to Pb from private wells, on which 13% of the US population relies.

Impact of transitioning from long-term to intermittent opioid therapy on the development of opioid-related adverse outcomes: A retrospective cohort study

BACKGROUND

Increasing pressures exist to reduce or discontinue opioid use among patients currently on long-term opioid therapy (LTOT). It is essential to understand the potential effects of opioid reduction.

METHODS

This retrospective cohort study was conducted among veterans with chronic pain and on LTOT. Using 1:1 propensity score-matched samples of veterans switching to intermittent opioid therapy and those continuing LTOT, we examined the development of subsequent substance use disorders (SUD composite; individual SUD types: opioid, non-opioid drug, and alcohol use disorders) and opioid-related adverse outcomes (ORAO composite; individual ORAO types: accidents resulting in wounds/injuries, opioid-related and alcohol/non-opioid medication-related accidents and overdoses, self-inflicted and violence-related injuries). Sensitivity analyses were conducted using logistic regression with stabilized inverse probability of treatment weighting (SIPTW) and instrumental variable (IV) models.

RESULTS

A total of 29,293 veterans switching to intermittent therapy were matched to veterans continuing LTOT. With matched samples, no differences were found in composite SUDs and ORAOs between the groups. With SIPTW, veterans switching to intermittent opioid therapy had higher odds of composite SUDs and ORAOs (SUDs aOR=1.12, 95%CI: 1.07,1.17; ORAOs aOR=1.05, 95%CI:1.00,1.09). IV models found lower risks for composite SUDs and ORAOs among veterans switching to intermittent opioid therapy (SUDs: β = -0.38, 95%CI:-0.63,-0.13; ORAOs: β = -0.27, 95%CI:-0.50,-0.04).

CONCLUSIONS

There were no consistent associations between transitioning patients from LTOT to intermittent opioid therapy and the risk of SUDs and ORAOs.

A National Study to Compare Effective Management of Constipation in Children Receiving Concurrent Versus Standard Hospice Care

Constipation is a distressing and uncomfortable symptom children experience at end of life. There is a gap in knowledge about how different approaches to hospice care delivery might improve pediatric symptom management of constipation. The purpose of this study was to evaluate the effectiveness of pediatric concurrent hospice versus standard hospice care to manage constipation. Medicaid data (2011-2013) were analyzed. Children who were younger than 21 years enrolled in hospice care and had a hospice enrollment between January 1, 2011, and December 31, 2013, were included. Instrumental variable analysis was used to test the effectiveness of concurrent versus standard hospice care. Among the 18 152 children, approximately 14% of participants were diagnosed or treated for constipation from a nonhospice provider during hospice enrollment. A higher proportion of children received nonhospice care for constipation in concurrent hospice care, compared with standard hospice (19.5% vs 13.2%), although this was not significant (β = .22, P < .05) after adjusting for covariates. The findings demonstrated that concurrent care was no more effective than standard hospice care in managing pediatric constipation. Hospice and nonhospice providers may be doing a sufficient job ordering bowel regimens before constipation becomes a serious problem for children at end of life.

Online Pilot Grocery Intervention among Rural and Urban Residents Aimed to Improve Purchasing Habits

Online grocery shopping has the potential to improve access to food, particularly among low-income households located in urban food deserts and rural communities. The primary aim of this pilot intervention was to test whether a three-armed online grocery trial improved fruit and vegetable (F&V) purchases. Rural and urban adults across seven counties in Kentucky, Maryland, and North Carolina were recruited to participate in an 8-week intervention in fall 2021. A total of 184 adults were enrolled into the following groups: (1) brick-and-mortar "BM" (control participants only received reminders to submit weekly grocery shopping receipts); (2) online-only with no support "O" (participants received weekly reminders to grocery shop online and to submit itemized receipts); and (3) online shopping with intervention nudges "O+I" (participants received nudges three times per week to grocery shop online, meal ideas, recipes, Facebook group support, and weekly reminders to shop online and to submit itemized receipts). On average, reported food spending on F/V by the O+I participants was USD 6.84 more compared to the BM arm. Online shopping with behavioral nudges and nutrition information shows great promise for helping customers in diverse locations to navigate the increasing presence of online grocery shopping platforms and to improve F&V purchases.

Statistical methods for non-adherence in non-inferiority trials: useful and used? A systematic review

BACKGROUND

In non-inferiority trials with non-adherence to interventions (or non-compliance), intention-to-treat and per-protocol analyses are often performed; however, non-random non-adherence generally biases these estimates of efficacy.

OBJECTIVE

To identify statistical methods that adjust for the impact of non-adherence and thus estimate the causal effects of experimental interventions in non-inferiority trials.

DESIGN

A systematic review was conducted by searching the Ovid MEDLINE database (31 December 2020) to identify (1) randomised trials with a primary analysis for non-inferiority that applied (or planned to apply) statistical methods to account for the impact of non-adherence to interventions, and (2) methodology papers that described such statistical methods and included a non-inferiority trial application.

OUTCOMES

The statistical methods identified, their impacts on non-inferiority conclusions, and their advantages/disadvantages.

RESULTS

A total of 24 papers were included (4 protocols, 13 results papers and 7 methodology papers) reporting relevant methods on 26 occasions. The most common were instrumental variable approaches (n=9), including observed adherence as a covariate within a regression model (n=3), and modelling adherence as a time-varying covariate in a time-to-event analysis (n=3). Other methods included rank preserving structural failure time models and inverse-probability-of-treatment weighting. The methods identified in protocols and results papers were more commonly specified as sensitivity analyses (n=13) than primary analyses (n=3). Twelve results papers included an alternative analysis of the same outcome; conclusions regarding non-inferiority were in agreement on six occasions and could not be compared on six occasions (different measures of effect or results not provided in full).

CONCLUSIONS

Available statistical methods which attempt to account for the impact of non-adherence to interventions were used infrequently. Therefore, firm inferences about their influence on non-inferiority conclusions could not be drawn. Since intention-to-treat and per-protocol analyses do not guarantee unbiased conclusions regarding non-inferiority, the methods identified should be considered for use in sensitivity analyses.

PROSPERO REGISTRATION NUMBER

CRD42020177458.