Avoidable flaws in observational analyses: an application to statins and cancer

Patients on vitamin K treatment: is switching to direct-acting oral anticoagulation cost-effective? A target trial on a prospective cohort

AIMS

Direct-acting oral anticoagulants (DOACs) have, to a substantial degree, replaced vitamin K antagonists (VKA) as treatments for stroke prevention in atrial fibrillation (AF) patients. However, evidence on the real-world causal effects of switching patients from VKA to DOAC is lacking. We aimed to assess the empirical incremental cost-effectiveness of switching patients to DOAC compared with maintaining VKA treatment.

METHODS

The target trial approach was applied to the prospective observational Swiss-AF cohort, which enrolled 2415 AF patients from 2014 to 2017. Clinical data, healthcare resource utilisation and EQ-5D-based utilities representing quality of life were collected in yearly follow-ups. Health insurance claims were available for 1024 patients (42.4%). Overall survival, quality-of-life, costs from the Swiss statutory health insurance perspective and cost-effectiveness were estimated by emulating a target trial in which patients were randomly assigned to switch to DOAC or maintain VKA treatment.

RESULTS

228 patients switching from VKA to DOAC compared with 563 patients maintaining VKA treatment had no overall survival advantage over a 5-year observation period (HR 0.99, 95% CI 0.45, 1.55). The estimated gain in quality-adjusted life years (QALYs) was 0.003 over the 5-year period at an incremental costs of CHF 23 033 (€ 20 940). The estimated incremental cost-effectiveness ratio was CHF 425 852 (€ 387 138) per QALY gained.

CONCLUSIONS

Applying a causal inference method to real-world data, we could not demonstrate switching to DOACs to be cost-effective for AF patients with at least 1 year of VKA treatment. Our estimates align with results from a previous randomised trial.

Is the price right? Paying for value today to get more value tomorrow

BACKGROUND

Contemporary debates about drug pricing feature several widely held misconceptions, including the relationship between incentives and innovation, the proportion of total healthcare spending on pharmaceuticals, and whether the economic evaluation of a medicine can be influenced by things other than clinical efficacy.

MAIN BODY

All citizens should have access to timely, equitable, and cost-effective care covered by public funds, private insurance, or a combination of both. Better managing the collective burden of diseases borne by today's and future generations depends in part on developing better technologies, including better medicines. As in any innovative industry, the expectation of adequate financial returns incentivizes innovators and their investors to develop new medicines. Estimating expected returns requires that they forecast revenues, based on the future price trajectory and volume of use over time. How market participants decide what price to set or accept can be complicated, and some observers and stakeholders want to confirm whether the net prices society pays for novel medicines, whether as a reward for past innovation or an incentive for future innovation, are commensurate with those medicines' incremental value. But we must also ask "value to whom?"; medicines not only bring immediate clinical benefits to patients treated today, but also can provide a broad spectrum of short- and long-term benefits to patients, their families, and society. Spending across all facets of healthcare has grown over the last 25 years, but both inpatient and outpatient spending has outpaced drug spending growth even as our drug armamentarium is constantly improving with safer and more effective medicines. In large part, this is because, unlike hospitals, drugs typically go generic, thus making room in our budgets for new and better ones, even as they often keep patients out of hospitals, driving further savings.

CONCLUSION

A thorough evaluation of drug spending and value can help to promote a better allocation of healthcare resources for both the healthy and the sick, both of whom must pay for healthcare. Taking a holistic approach to assessing drug value makes it clear that a branded drug's value to a patient is often only a small fraction of the drug's total value to society. Societal value merits consideration when determining whether and how to make a medicine affordable and accessible to patients: a drug that is worth its price to society should not be rendered inaccessible to ill patients by imposing high out-of-pocket costs or restricting coverage based on narrow health technology assessments (HTAs). Furthermore, recognizing the total societal cost of un- or undertreated conditions is crucial to gaining a thorough understanding of what guides the biomedical innovation ecosystem to create value for society. It would be unwise to discourage the development of new solutions without first appreciating the cost of leaving the problems unsolved.

Prostate cancer screening in African American men: a review of the evidence

BACKGROUND

Prostate cancer is the most diagnosed cancer in African American men, yet prostate cancer screening regimens in this group are poorly guided by existing evidence, given underrepresentation of African American men in prostate cancer screening trials. It is critical to optimize prostate cancer screening and early detection in this high-risk group because underdiagnosis may lead to later-stage cancers at diagnosis and higher mortality while overdiagnosis may lead to unnecessary treatment.

METHODS

We performed a review of the literature related to prostate cancer screening and early detection specific to African American men to summarize the existing evidence available to guide health-care practice.

RESULTS

Limited evidence from observational and modeling studies suggests that African American men should be screened for prostate cancer. Consideration should be given to initiating screening of African American men at younger ages (eg, 45-50 years) and at more frequent intervals relative to other racial groups in the United States. Screening intervals can be optimized by using a baseline prostate-specific antigen measurement in midlife. Finally, no evidence has indicated that African American men would benefit from screening beyond 75 years of age; in fact, this group may experience higher rates of overdiagnosis at older ages.

CONCLUSIONS

The evidence base for prostate cancer screening in African American men is limited by the lack of large, randomized studies. Our literature search supported the need for African American men to be screened for prostate cancer, for initiating screening at younger ages (45-50 years), and perhaps screening at more frequent intervals relative to men of other racial groups in the United States.

Comparative Effectiveness of Alternative Treatment Approaches to Secondary Hyperparathyroidism in Patients Receiving Maintenance Hemodialysis: An Observational Trial Emulation

RATIONALE & OBJECTIVE

Optimal approaches to treat secondary hyperparathyroidism (SHPT) in patients on maintenance hemodialysis (HD) have yet to be established in randomized controlled trials (RCTs).

STUDY DESIGN

Two observational clinical trial emulations.

SETTING & PARTICIPANTS

Both emulations included adults receiving in-center HD from a national dialysis organization. The patients who had SHPT in the period between 2009 and 2014, were insured for≥180 days by Medicare as primary payer, and did not have contraindications or poor health status limiting theoretical trial participation.

EXPOSURE

The parathyroid hormone (PTH) Target Trial emulation included patients with new-onset SHPT (first PTH 300-600pg/mL), with 2 arms defined as up-titration of either vitamin D sterols or cinacalcet within 30 days (lower target) or no up-titration (higher target). The Agent Trial emulation included patients with a PTH≥300 pg/mL while on≥6μg weekly of vitamin D sterol (paricalcitol equivalent dose) and no prior history of cinacalcet. The 2 arms were defined by the first dose or agent change within 30 days (vitamin D-favoring [vitamin-D was up-titrated] vs cinacalcet-favoring [cinacalcet was added] vs nondefined [neither applies]). Multiple trials per patient were allowed in trial 2.

OUTCOME

The primary outcome was all-cause death over 24 months; secondary outcomes included cardiovascular (CV) hospitalization or the composite of CV hospitalization or death.

ANALYTICAL APPROACH

Pooled logistic regression.

RESULTS

There were 1,152 patients in the PTH Target Trial (635 lower target and 517 higher target). There were 2,726 unique patients with 6,727 patient trials in the Agent Trial (6,268 vitamin D-favoring trials and 459 cinacalcet-favoring trials). The lower PTH target approach was associated with reduced adjusted hazard of death (HR, 0.71 [95% CI, 0.52-0.93]), CV hospitalization (HR, 0.78 [95% CI, 0.63-0.98]), and their composite (HR, 0.74 [95% CI, 0.61-0.89]). The cinacalcet-favoring approach demonstrated lower adjusted hazard of death compared to the vitamin D-favoring approach (HR, 0.79 [95% CI, 0.62-0.99]), but not of CV hospitalization or the composite outcome.

LIMITATIONS

Potential for residual confounding; low use of cinacalcet with low power.

CONCLUSIONS

SHPT management that is focused on lower PTH targets may lower mortality and CV disease in patients receiving HD. These findings should be confirmed in a pragmatic randomized trial.

PLAIN-LANGUAGE SUMMARY

Optimal approaches to treat secondary hyperparathyroidism (SHPT) have not been established in randomized controlled trials. Data from a national dialysis organization was used to identify patients with SHPT in whom escalated treatment may be indicated. The approach to treatment was defined based on observed upward titration of SHPT-controlling medications: earlier titration (lower target) versus delayed titration (higher target); and the choice of medication (cinacalcet vs vitamin D sterols). In the first trial emulation, we estimated a 29% lower rate of death and 26% lower rate of cardiovascular disease or death for patients managed with a lower versus higher target approach. Cinacalcet versus vitamin D-favoring approaches were not consistently associated with outcomes in the second trial emulation. This observational study suggests the need for additional clinical trials of SHPT treatment intensity.

High-throughput target trial emulation for Alzheimer's disease drug repurposing with real-world data

Target trial emulation is the process of mimicking target randomized trials using real-world data, where effective confounding control for unbiased treatment effect estimation remains a main challenge. Although various approaches have been proposed for this challenge, a systematic evaluation is still lacking. Here we emulated trials for thousands of medications from two large-scale real-world data warehouses, covering over 10 years of clinical records for over 170 million patients, aiming to identify new indications of approved drugs for Alzheimer's disease. We assessed different propensity score models under the inverse probability of treatment weighting framework and suggested a model selection strategy for improved baseline covariate balancing. We also found that the deep learning-based propensity score model did not necessarily outperform logistic regression-based methods in covariate balancing. Finally, we highlighted five top-ranked drugs (pantoprazole, gabapentin, atorvastatin, fluticasone, and omeprazole) originally intended for other indications with potential benefits for Alzheimer's patients.

Neglected Populations Not to Be Forgotten: Tackling Antimicrobial Resistance in Neonatal Infections

Making further progress in reducing child mortality hinges on lowering the annual count of neonatal deaths; currently, this stands at 2 [...].

On the estimation of the effect of weight change on a health outcome using observational data, by utilising the target trial emulation framework

BACKGROUND/OBJECTIVES

When studying the effect of weight change between two time points on a health outcome using observational data, two main problems arise initially (i) 'when is time zero?' and (ii) 'which confounders should we account for?' From the baseline date or the 1st follow-up (when the weight change can be measured)? Different methods have been previously used in the literature that carry different sources of bias and hence produce different results.

METHODS

We utilised the target trial emulation framework and considered weight change as a hypothetical intervention. First, we used a simplified example from a hypothetical randomised trial where no modelling is required. Then we simulated data from an observational study where modelling is needed. We demonstrate the problems of each of these methods and suggest a strategy.

INTERVENTIONS

weight loss/gain vs maintenance.

RESULTS

The recommended method defines time-zero at enrolment, but adjustment for confounders (or exclusion of individuals based on levels of confounders) should be performed both at enrolment and the 1st follow-up.

CONCLUSIONS

The implementation of our suggested method [adjusting for (or excluding based on) confounders measured both at baseline and the 1st follow-up] can help researchers attenuate bias by avoiding some common pitfalls. Other methods that have been widely used in the past to estimate the effect of weight change on a health outcome are more biased. However, two issues remain (i) the exposure is not well-defined as there are different ways of changing weight (however we tried to reduce this problem by excluding individuals who develop a chronic disease); and (ii) immortal time bias, which may be small if the time to first follow up is short.

Real-World Cost-Effectiveness of Pulmonary Vein Isolation for Atrial Fibrillation: A Target Trial Approach

OBJECTIVES

Randomized controlled trials of pulmonary vein isolation (PVI) for treating atrial fibrillation (AF) have proven the procedure's efficacy. Studies assessing its empirical cost-effectiveness outside randomized trial settings are lacking. We aimed to evaluate the effectiveness and cost-effectiveness of PVI versus medical therapy for AF.

METHODS

We followed a target trial approach using the Swiss-AF cohort, a prospective observational cohort study that enrolled patients with AF between 2014 and 2017. Resource utilization and cost information were collected through claims data. Quality of life was measured with EQ-5D-3L utilities. We estimated incremental cost-effectiveness ratios (ICERs) from the perspective of the Swiss statutory health insurance system.

RESULTS

Patients undergoing PVI compared with medical therapy had a 5-year overall survival advantage with a hazard ratio of 0.75 (95% CI 0.46-1.21; P = .69) and a 19.8% SD improvement in quality of life (95% CI 15.5-22.9; P < .001), at an incremental cost of 29 604 Swiss francs (CHF) (95% CI 16 354-42 855; P < .001). The estimated ICER was CHF 158 612 per quality-adjusted life-year (QALY) gained within a 5-year time horizon. Assuming similar health effects and costs over 5 additional years changed the ICER to CHF 82 195 per QALY gained. Results were robust to the sensitivity analyses performed.

CONCLUSIONS

Our results show that PVI might be a cost-effective intervention within the Swiss healthcare context in a 10-year time horizon, but unlikely to be so at 5 years, if a willingness-to-pay threshold of CHF 100 000 per QALY gained is assumed. Given data availability, we find target trial designs are a valuable tool for assessing the cost-effectiveness of healthcare interventions outside of randomized controlled trial settings.

Causal inference using observational intensive care unit data: a scoping review and recommendations for future practice

This scoping review focuses on the essential role of models for causal inference in shaping actionable artificial intelligence (AI) designed to aid clinicians in decision-making. The objective was to identify and evaluate the reporting quality of studies introducing models for causal inference in intensive care units (ICUs), and to provide recommendations to improve the future landscape of research practices in this domain. To achieve this, we searched various databases including Embase, MEDLINE ALL, Web of Science Core Collection, Google Scholar, medRxiv, bioRxiv, arXiv, and the ACM Digital Library. Studies involving models for causal inference addressing time-varying treatments in the adult ICU were reviewed. Data extraction encompassed the study settings and methodologies applied. Furthermore, we assessed reporting quality of target trial components (i.e., eligibility criteria, treatment strategies, follow-up period, outcome, and analysis plan) and main causal assumptions (i.e., conditional exchangeability, positivity, and consistency). Among the 2184 titles screened, 79 studies met the inclusion criteria. The methodologies used were G methods (61%) and reinforcement learning methods (39%). Studies considered both static (51%) and dynamic treatment regimes (49%). Only 30 (38%) of the studies reported all five target trial components, and only seven (9%) studies mentioned all three causal assumptions. To achieve actionable AI in the ICU, we advocate careful consideration of the causal question of interest, describing this research question as a target trial emulation, usage of appropriate causal inference methods, and acknowledgement (and examination of potential violations of) the causal assumptions.

Impact of deintensifying hypoglycaemic drugs in older adults with type 2 diabetes: protocol for an emulation of a target trial

INTRODUCTION

In older adults with type 2 diabetes (T2D), overtreatment with hypoglycaemic drugs (HDs: sulfonylureas, glinides and/or insulins) is frequent and associated with increased 1-year mortality. Deintensification of HD is thus a key issue, for which evidence is though limited. The primary objective of this study will be to estimate the effect of deintensifying HD on clinical outcomes (hospital admission or death) within 3 months in older adults (≥75 years) with T2D.

METHODS

We will emulate with real-world data a target trial, within The Health Improvement Network cohort, a large-scale database of data collected from electronic medical records of 2000 general practitioners in France. From 1 January 2010 to 28 February 2019, we will include eligible patients ≥75 years who will have T2D, a stable dose of HDs, glycated haemoglobin A1c (HbA1c) value <75 mmol/mol (9.0%) and no deintensification in the past year. The target trial will be sequentially emulated (ie, eligibility assessed) every month in the database. Patients will be classified at baseline of each sequential trial in the intervention arm (deintensification of HDs: decrease of ≥50% in the total dose of HDs, including complete cessation) or control arm (no deintensification of HDs). The pooled dataset for all sequential emulated trials will be analysed. The primary outcome will be time to first occurrence of hospital admission or death, within 3 months. Secondary outcomes will be hospitalisation, death, appropriateness of glycaemic control and occurrence of HbA1c >75 mmol/mol within 1 year. Participants will be followed from baseline to 12 months after randomisation, administrative censoring, or death, whichever occurs first. A pooled logistic regression will be used to estimate the treatment effect on the incidence of the outcomes.

DISSEMINATION AND ETHICS

No ethical approval is needed for using retrospectively this fully anonymised database. The results will be disseminated during conferences and through publications in scientific journals.

Effect of selective serotonin reuptake inhibitor treatment following diagnosis of depression on suicidal behaviour risk: a target trial emulation

There is concern regarding the impact of selective serotonin reuptake inhibitors (SSRIs) on suicidal behaviour. Using the target trial framework, we investigated the effect on suicidal behaviour of SSRI treatment following a depression diagnosis. We identified 162,267 individuals receiving a depression diagnosis aged 6-59 years during 2006-2018 in Stockholm County, Sweden, after at least 1 year without antidepressant dispensation. Individuals who initiated an SSRI within 28 days of the diagnosis were assigned as SSRI initiators, others as non-initiators. Intention-to-treat and per-protocol effects were estimated; for the latter, individuals were censored when they ceased adhering to their assigned treatment strategy. We applied inverse probability weighting (IPW) to account for baseline confounding in the intention-to-treat analysis, and additionally for treatment non-adherence and time-varying confounding in the per-protocol analysis. The suicidal behaviour risk difference (RD), and risk ratio (RR) between SSRI initiators and non-initiators were estimated at 12 weeks. In the overall cohort, we found an increased risk of suicidal behaviour among SSRI initiators (intention-to-treat RR = 1.50, 95% CI = 1.25, 1.80; per-protocol RR = 1.69, 95% CI = 1.20, 2.36). In age strata, we only found evidence of an increased risk among individuals under age 25, with the greatest risk among 6-17-year-olds (intention-to-treat RR = 2.90, 95% CI = 1.72, 4.91; per-protocol RR = 3.34, 95% CI = 1.59, 7.00). Our finding of an increased suicidal behaviour risk among individuals under age 25 reflects evidence from RCTs. We found no evidence of an effect in the high-risk group of individuals with past suicidal behaviour. Further studies with information on a wider array of confounders are called for.

Causal effect of shifting from precarious to standard employment on all-cause mortality in Sweden: an emulation of a target trial

BACKGROUND

We aimed at estimating the causal effect of switching from precarious to standard employment on the 6-year and 12-year risk of all-cause mortality among workers aged 20-55 years in Sweden.

METHODS

We emulated a series of 12 target trials starting every year between 2005 and 2016 using Swedish register data (n=251 273). We classified precariously employed individuals using a multidimensional approach at baseline as (1) remaining in precarious employment (PE) (73.8%) and (2) shifting to standard employment (26.2%). All-cause mortality was measured from 2006 to 2017. We pooled data for all 12 emulated trials and used covariate-adjusted pooled logistic regression to estimate intention-to-treat and per-protocol effects via risk ratios (RRs) and standardised risk curves (the parametric g-formula).

RESULTS

Shifting from precarious to standard employment decreases the 12-year risk of death by 20% on the relative scale (RR: 0.82, 95% CI: 0.73; 0.93), regardless of what happens after the initial shift. However, we estimated a 12-year risk reduction of 30% on the relative scale for workers shifting from precarious to standard employment and staying within this employment category for the full 12 years (RR: 0.71, 95% CI: 0.54; 0.95).

CONCLUSIONS

This study finds that shifting from low to higher-quality employment conditions (ie, stable employment, sufficient income levels and high coverage by collective agreements) decreases the risk of death. Remaining in PE increases the risk of premature mortality. Our results emphasise the necessity of ensuring decent work for the entire working population to accomplish the 2030 Agenda for Sustainable Development.

Online multiple hypothesis testing

Modern data analysis frequently involves large-scale hypothesis testing, which naturally gives rise to the problem of maintaining control of a suitable type I error rate, such as the false discovery rate (FDR). In many biomedical and technological applications, an additional complexity is that hypotheses are tested in an online manner, one-by-one over time. However, traditional procedures that control the FDR, such as the Benjamini-Hochberg procedure, assume that all p-values are available to be tested at a single time point. To address these challenges, a new field of methodology has developed over the past 15 years showing how to control error rates for online multiple hypothesis testing. In this framework, hypotheses arrive in a stream, and at each time point the analyst decides whether to reject the current hypothesis based both on the evidence against it, and on the previous rejection decisions. In this paper, we present a comprehensive exposition of the literature on online error rate control, with a review of key theory as well as a focus on applied examples. We also provide simulation results comparing different online testing algorithms and an up-to-date overview of the many methodological extensions that have been proposed.

Comparative Effectiveness of Dynamic Treatment Strategies for Medication Use and Dosage: Emulating a Target Trial Using Observational Data

BACKGROUND

Availability of detailed data from electronic health records (EHRs) has increased the potential to examine the comparative effectiveness of dynamic treatment strategies using observational data. Inverse probability (IP) weighting of dynamic marginal structural models can control for time-varying confounders. However, IP weights for continuous treatments may be sensitive to model choice.

METHODS

We describe a target trial comparing strategies for treating anemia with darbepoetin in hemodialysis patients using EHR data from the UK Renal Registry 2004 to 2016. Patients received a specified dose (microgram/week) or did not receive darbepoetin. We compared 4 methods for modeling time-varying treatment: (A) logistic regression for zero dose, standard linear regression for log dose; (B) logistic regression for zero dose, heteroscedastic linear regression for log dose; (C) logistic regression for zero dose, heteroscedastic linear regression for log dose, multinomial regression for patients who recently received very low or high doses; and (D) ordinal logistic regression.

RESULTS

For this dataset, method (C) was the only approach that provided a robust estimate of the mortality hazard ratio (HR), with less-extreme weights in a fully weighted analysis and no substantial change of the HR point estimate after weight truncation. After truncating IP weights at the 95th percentile, estimates were similar across the methods.

CONCLUSIONS

EHR data can be used to emulate target trials estimating the comparative effectiveness of dynamic strategies adjusting treatment to evolving patient characteristics. However, model checking, monitoring of large weights, and adaptation of model strategies to account for these is essential if an aspect of treatment is continuous.

Immortal Time Bias With Time-Varying Exposures in Environmental Epidemiology: A Case Study in Lung Cancer Survival

Immortal time bias is a well-recognized bias in clinical epidemiology but is rarely discussed in environmental epidemiology. Under the target trial framework, this bias is formally conceptualized as a misalignment between the start of study follow-up (time 0) and treatment assignment. This misalignment can occur when attained duration of follow-up is encoded into treatment assignment using minimums, maximums, or averages. The bias can be exacerbated in the presence of time trends commonly found in environmental exposures. Using lung cancer cases from the California Cancer Registry (2000-2010) linked with estimated concentrations of particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PM2.5), we replicated previous studies that averaged PM2.5 exposure over follow-up in a time-to-event model. We compared this approach with one that ensures alignment between time 0 and treatment assignment, a discrete-time approach. In the former approach, the estimated overall hazard ratio for a 5-μg/m3 increase in PM2.5 was 1.38 (95% confidence interval: 1.36, 1.40). Under the discrete-time approach, the estimated pooled odds ratio was 0.99 (95% confidence interval: 0.98, 1.00). We conclude that the strong estimated effect in the former approach was likely driven by immortal time bias, due to misalignment at time 0. Our findings highlight the importance of appropriately conceptualizing a time-varying environmental exposure under the target trial framework to avoid introducing preventable systematic errors.

Target trial emulation: Do antimicrobials or gastrointestinal nutraceuticals prescribed at first presentation for acute diarrhoea cause a better clinical outcome in dogs under primary veterinary care in the UK?

Target trial emulation applies design principles from randomised controlled trials to the analysis of observational data for causal inference and is increasingly used within human epidemiology. Veterinary electronic clinical records represent a potentially valuable source of information to estimate real-world causal effects for companion animal species. This study employed the target trial framework to evaluate the usefulness on veterinary observational data. Acute diarrhoea in dogs was used as a clinical exemplar. Inclusion required dogs aged ≥ 3 months and < 10 years, presenting for veterinary primary care with acute diarrhoea during 2019. Treatment strategies were: 1. antimicrobial prescription compared to no antimicrobial prescription and 2. gastrointestinal nutraceutical prescription compared to no gastrointestinal nutraceutical prescription. The primary outcome was clinical resolution (defined as no revisit with ongoing diarrhoea within 30 days from the date of first presentation). Informed from a directed acyclic graph, data on the following covariates were collected: age, breed, bodyweight, insurance status, comorbidities, vomiting, reduced appetite, haematochezia, pyrexia, duration, additional treatment prescription and veterinary group. Inverse probability of treatment weighting was used to balance covariates between the treatment groups for each of the two target trials. The risk difference (RD) of 0.4% (95% CI -4.5% to 5.3%) was non-significant for clinical resolution in dogs treated with antimicrobials compared with dogs not treated with antimicrobials. The risk difference (RD) of 0.3% (95% CI -4.5% to 5.0%) was non-significant for clinical resolution in dogs treated with gastrointestinal nutraceuticals compared with dogs not treated with gastrointestinal nutraceuticals. This study successfully applied the target trial framework to veterinary observational data. The findings show that antimicrobial or gastrointestinal prescription at first presentation of acute diarrhoea in dogs causes no difference in clinical resolution. The findings support the recommendation for veterinary professionals to limit antimicrobial use for acute diarrhoea in dogs.

Antiplatelet Therapy in Patients With Abdominal Aortic Aneurysm Without Symptomatic Atherosclerotic Disease

Importance

Patients with abdominal aortic aneurysm have a high risk of ischemic events associated with concomitant atherosclerotic cardiovascular disease, and current clinical practice guidelines recommend antiplatelet therapy to mitigate this risk. However, in patients with aneurysms without symptomatic atherosclerosis, the benefit of antiplatelet therapy has been sparsely investigated.

Objective

To estimate the effect of antiplatelets on the risk of ischemic events and bleeding in individuals with abdominal aneurysms with no symptomatic atherosclerotic vascular disease.

Design, Setting, and Participants

A comparative effectiveness research study using a target trial emulation framework was performed. Population-based, cross-linked observational data from Danish national health registries containing comprehensive, individual-level information on all Danish citizens were used to evaluate patients who were antiplatelet-naive and diagnosed with abdominal aortic aneurysms, with no record of symptomatic atherosclerotic vascular disease, from January 1, 2010, through August 21, 2021.

Exposure

Prescription filled for aspirin or clopidogrel.

Main Outcomes and Measures

Risk of ischemic events (myocardial infarction and/or ischemic stroke) and risk of major bleeding. For target trial emulation, trials were emulated as sequential, contingent on patient eligibility at the time of inclusion, and were evaluated by means of pooled logistic regression models to estimate the intention-to-treat and as-treated effects, expressed as hazard ratio (HR) and event-free survival.

Results

A total of 6344 patients (65.2% men; age, 72 [IQR, 64-78] years) provided 131 047 trial cases; 3363 of these cases involved initiation of antiplatelet therapy and 127 684 did not. A total of 182 ischemic events occurred among initiators and 5602 ischemic events occurred among noninitiators, corresponding to an intention-to-treat HR of 0.91 (95% CI, 0.73-1.17) and an estimated absolute event-free survival difference of -0.6% (95% CI, -1.7% to 0.5%). After censoring nonadherent person-time, the treatment HR was 0.90 (95% CI, 0.68-1.20), with similar risk difference. For bleeding, the intention-to-treat HR was 1.26 (95% CI, 0.97-1.58) and the event-free survival difference was 1.0%. The treatment HR was 1.21 (95% CI, 0.82-1.72); the risk difference was similar.

Conclusions and Relevance

In this study, no evidence of effectiveness of antiplatelet therapy to lower the risk of ischemic events and a trend toward higher bleeding risk was noted. The observed differences between the treatment groups were minimal, suggesting limited clinical relevance of antiplatelet treatment.

On optimal timing of antenatal corticosteroids: time to reformulate the question

Administration of antenatal corticosteroids (ACS) for accelerating foetal lung maturation in threatened preterm birth is one of the cornerstones of prevention of neonatal mortality and morbidity. To identify the optimal timing of ACS administration, most studies have compared subgroups based on treatment-to-delivery intervals. Such subgroup analysis of the first placebo-controlled randomised controlled trial indicated that a one to seven day interval between ACS administration and birth resulted in the lowest rates of neonatal respiratory distress syndrome. This efficacy window was largely confirmed by a series of subgroup analyses of subsequent trials and observational studies and strongly influenced obstetric management. However, these subgroup analyses suffer from a methodological flaw that often seems to be overlooked and potentially has important consequences for drawing valid conclusions. In this commentary, we point out that studies comparing treatment outcomes between subgroups that are retrospectively identified at birth (i.e. after randomisation) may not only be plagued by post-randomisation confounding bias but, more importantly, may not adequately inform decision making before birth, when the projected duration of the interval is still unknown. We suggest two more formal interpretations of these subgroup analyses, using a counterfactual framework for causal inference, and demonstrate that each of these interpretations can be linked to a different hypothetical trial. However, given the infeasibility of these trials, we argue that none of these rescue interpretations are helpful for clinical decision making. As a result, guidelines based on these subgroup analyses may have led to suboptimal clinical practice. As an alternative to these flawed subgroup analyses, we suggest a more principled approach that clearly formulates the question about optimal timing of ACS treatment in terms of the protocol of a future randomised study. Even if this 'target trial' would never be conducted, its protocol may still provide important guidance to avoid repeating common design flaws when conducting observational 'real world' studies using statistical methods for causal inference.

Emulated trial investigating effects of multiple treatments: estimating combined effects of mucoactive nebulisers in cystic fibrosis using registry data

INTRODUCTION

People with cystic fibrosis (CF) are often on multiple long-term treatments, including mucoactive nebulisers. In the UK, the most common mucoactive nebuliser is dornase alfa (DNase). A common therapeutic approach for people already on DNase is to add hypertonic saline (HS). The effects of DNase and HS used alone have been studied in randomised trials, but their effects in combination have not. This study investigates whether, for people already prescribed DNase, adding HS has additional benefit for lung function or use of intravenous antibiotics.

METHODS

Using UK CF Registry data from 2007 to 2018, we emulated a target trial. We included people aged 6 years and over who were prescribed DNase without HS for 2 years. We investigated the effects of combinations of DNase and HS over 5 years of follow-up. Inverse-probability-of-treatment weighting was used to control confounding. The period predated triple combination CF transmembrane conductance regulator modulators in routine care.

RESULTS

4498 individuals were included. At baseline, average age and forced expiratory volume in 1 s (FEV1%) predicted were 21.1 years and 69.7 respectively. During first year of follow-up, 3799 individuals were prescribed DNase alone; 426 added HS; 57 switched to HS alone and 216 were prescribed neither. We found no evidence that adding HS improved FEV1% at 1-5 years, or use of intravenous antibiotics at 1-4 years, compared with DNase alone.

CONCLUSION

For individuals with CF prescribed DNase, we found no evidence that adding HS had an effect on FEV1% or prescription of intravenous antibiotics. Our study illustrates the emulated target trial approach using CF Registry data.

Emulating Target Trials Comparing Early and Delayed Intubation Strategies

BACKGROUND

Whether intubation should be initiated early in the clinical course of critically ill patients remains a matter of debate. Results from prior observational studies are difficult to interpret because of avoidable flaws including immortal time bias, inappropriate eligibility criteria, and unrealistic treatment strategies.

RESEARCH QUESTION

Do treatment strategies that intubate patients early in the critical care admission improve 30-day survival compared with strategies that delay intubation?

STUDY DESIGN AND METHODS

We estimated the effect of strategies that require early intubation of critically ill patients compared with those that delay intubation. With data extracted from the Medical Information Mart for Intensive Care-IV database, we emulated three target trials, varying the flexibility of the treatment strategies and the baseline eligibility criteria.

RESULTS

Under unrealistically strict treatment strategies with broad eligibility criteria, the 30-day mortality risk was 7.1 percentage points higher for intubating early compared with delaying intubation (95% CI, 6.2-7.9). Risk differences were 0.4 (95% CI, -0.1 to 0.9) and -0.9 (95% CI, -2.5 to 0.7) percentage points in subsequent target trial emulations that included more realistic treatment strategies and eligibility criteria.

INTERPRETATION

When realistic treatment strategies and eligibility criteria are used, strategies that delay intubation result in similar 30-day mortality risks compared with those that intubate early. Delaying intubation ultimately avoids intubation in most patients.

The implementation of target trial emulation for causal inference: a scoping review

OBJECTIVES

We aim to investigate the implementation of Target Trial Emulation (TTE) for causal inference, involving research topics, frequently used strategies, and issues indicating the need for future improvements.

STUDY DESIGN AND SETTING

We performed a scoping review by following the Joanna Briggs Institute (JBI) guidance and Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. A health research-focused librarian searched multiple medical databases, and two independent reviewers completed screening and extraction within covidence review management software.

RESULTS

Our search resulted in 1,240 papers, of which 96 papers were eligible for data extraction. Results show a significant increase in the use of TTE in 2018 and 2021. The study topics varied and focused primarily on cancer, cardiovascular and cerebrovascular diseases, and infectious diseases. However, not all papers specified well all three critical components for generating robust causal evidence: time-zero, random assignment simulation, and comparison strategy. Some common issues were observed from retrieved papers, and key limitations include residual confounding, limited generalizability, and a lack of reporting guidance that need to be improved.

CONCLUSION

Uneven adherence to the TTE framework exists, and future improvements are needed to progress applications using causal inference with observational data.

Unraveling the Anticancer Potential of Statins: Mechanisms and Clinical Significance

Statins are an essential medication class in the treatment of lipid diseases because they inhibit 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase. They reduce cholesterol levels and reduce the risk of cardiovascular disease in both primary and secondary prevention. In addition to their powerful pharmacologic suppression of cholesterol production, statins appear to have pleitropic effects in a wide variety of other diseases by modulating signaling pathways. In recent years, statins have seen a large increase in interest due to their putative anticancer effects. Statins appear to cause upregulation or inhibition in key pathways involved in cancer such as inhibition of proliferation, angiogenesis, and metastasis as well as reducing cancer stemness. Further, statins have been found to induce oxidative stress, cell cycle arrest, autophagy, and apoptosis of cancer cells. Interestingly, clinical studies have shown that statin use is associated with a decreased risk of cancer formation, lower cancer grade at diagnosis, reduction in the risk of local reoccurrence, and increasing survival in patients. Therefore, our objective in the present review is to summarize the findings of the publications on the underlying mechanisms of statins' anticancer effects and their clinical implications.

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.

Target trial emulation with multi-state model analysis to assess treatment effectiveness using clinical COVID-19 data

BACKGROUND

Real-world observational data are an important source of evidence on the treatment effectiveness for patients hospitalized with coronavirus disease 2019 (COVID-19). However, observational studies evaluating treatment effectiveness based on longitudinal data are often prone to methodological biases such as immortal time bias, confounding bias, and competing risks.

METHODS

For exemplary target trial emulation, we used a cohort of patients hospitalized with COVID-19 (n = 501) in a single centre. We described the methodology for evaluating the effectiveness of a single-dose treatment, emulated a trial using real-world data, and drafted a hypothetical study protocol describing the main components. To avoid immortal time and time-fixed confounding biases, we applied the clone-censor-weight technique. We set a 5-day grace period as a period of time when treatment could be initiated. We used the inverse probability of censoring weights to account for the selection bias introduced by artificial censoring. To estimate the treatment effects, we took the multi-state model approach. We considered a multi-state model with five states. The primary endpoint was defined as clinical severity status, assessed by a 5-point ordinal scale on day 30. Differences between the treatment group and standard of care treatment group were calculated using a proportional odds model and shown as odds ratios. Additionally, the weighted cause-specific hazards and transition probabilities for each treatment arm were presented.

RESULTS

Our study demonstrates that trial emulation with a multi-state model analysis is a suitable approach to address observational data limitations, evaluate treatment effects on clinically heterogeneous in-hospital death and discharge alive endpoints, and consider the intermediate state of admission to ICU. The multi-state model analysis allows us to summarize results using stacked probability plots that make it easier to interpret results.

CONCLUSIONS

Extending the emulated target trial approach to multi-state model analysis complements treatment effectiveness analysis by gaining information on competing events. Combining two methodologies offers an option to address immortal time bias, confounding bias, and competing risk events. This methodological approach can provide additional insight for decision-making, particularly when data from randomized controlled trials (RCTs) are unavailable.

Evaluating Metformin Strategies for Cancer Prevention: A Target Trial Emulation Using Electronic Health Records

BACKGROUND

Metformin users appear to have a substantially lower risk of cancer than nonusers in many observational studies. These inverse associations may be explained by common flaws in observational analyses that can be avoided by explicitly emulating a target trial.

METHODS

We emulated target trials of metformin therapy and cancer risk using population-based linked electronic health records from the UK (2009-2016). We included individuals with diabetes, no history of cancer, no recent prescription for metformin or other glucose-lowering medication, and hemoglobin A1c (HbA1c) <64 mmol/mol (<8.0%). Outcomes included total cancer and 4 site-specific cancers (breast, colorectal, lung, and prostate). We estimated risks using pooled logistic regression with adjustment for risk factors via inverse-probability weighting. We emulated a second target trial among individuals regardless of diabetes status. We compared our estimates with those obtained using previously applied analytic approaches.

RESULTS

Among individuals with diabetes, the estimated 6-year risk differences (metformin - no metformin) were -0.2% (95% CI = -1.6%, 1.3%) in the intention-to-treat analysis and 0.0% (95% CI = -2.1%, 2.3%) in the per-protocol analysis. The corresponding estimates for all site-specific cancers were close to zero. Among individuals regardless of diabetes status, these estimates were also close to zero and more precise. By contrast, previous analytic approaches yielded estimates that appeared strongly protective.

CONCLUSIONS

Our findings are consistent with the hypothesis that metformin therapy does not meaningfully influence cancer incidence. The findings highlight the importance of explicitly emulating a target trial to reduce bias in the effect estimates derived from observational analyses.

Statin use and risk of colorectal cancer in patients with inflammatory bowel disease

Background

Statin use has been linked to a reduced risk of advanced colorectal adenomas, but its association with colorectal cancer (CRC) in patients with inflammatory bowel disease (IBD) - a high risk population for CRC - remains inconclusive.

Methods

From a nationwide IBD cohort in Sweden, we identified 5273 statin users and 5273 non-statin users (1:1 propensity score matching) from July 2006 to December 2018. Statin use was defined as the first filled prescription for ≥30 cumulative defined daily doses and followed until December 2019. Primary outcome was incident CRC. Secondary outcomes were CRC-related mortality and all-cause mortality. Cox regression estimated adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs).

Findings

During a median follow-up of 5.6 years, 70 statin users (incidence rate (IR): 21.2 per 10,000 person-years) versus 90 non-statin users (IR: 29.2) were diagnosed with incident CRC (rate difference (RD), -8.0 (95% CIs: -15.8 to -0.2 per 10,000 person-years); aHR = 0.76 (95% CIs: 0.61 to 0.96)). The benefit for incident CRC was duration-dependent in a nested case-control design: as compared to short-term use (30 days to <1 year), the adjusted odd ratios were 0.59 (0.25 to 1.43) for 1 to <2 years of use, 0.46 (0.21 to 0.98) for 2 to <5 years of use, and 0.38 (0.16 to 0.86) for ≥5 years of use (Pfor tread = 0.016). Compared with non-statin users, statin users also had a decreased risk for CRC-related mortality (IR: 6.0 vs. 11.9; RD, -5.9 (-10.5 to -1.2); aHR, 0.56 (0.37 to 0.83)) and all-cause mortality (IR: 156.4 vs. 231.4; RD, -75.0 (-96.6 to -53.4); aHR, 0.63 (0.57 to 0.69)).

Interpretation

Statin use was associated with a lower risk of incident CRC, CRC-related mortality, and all-cause mortality. The benefit for incident CRC was duration-dependent, with a significantly lower risk after ≥2 years of statin use.

Funding

This research was supported by Forte (i.e., the Swedish Research Council for Health, Working Life and Welfare).

Implementation of the trial emulation approach in medical research: a scoping review

BACKGROUND

When conducting randomised controlled trials is impractical, an alternative is to carry out an observational study. However, making valid causal inferences from observational data is challenging because of the risk of several statistical biases. In 2016 Hernán and Robins put forward the 'target trial framework' as a guide to best design and analyse observational studies whilst preventing the most common biases. This framework consists of (1) clearly defining a causal question about an intervention, (2) specifying the protocol of the hypothetical trial, and (3) explaining how the observational data will be used to emulate it.

METHODS

The aim of this scoping review was to identify and review all explicit attempts of trial emulation studies across all medical fields. Embase, Medline and Web of Science were searched for trial emulation studies published in English from database inception to February 25, 2021. The following information was extracted from studies that were deemed eligible for review: the subject area, the type of observational data that they leveraged, and the statistical methods they used to address the following biases: (A) confounding bias, (B) immortal time bias, and (C) selection bias.

RESULTS

The search resulted in 617 studies, 38 of which we deemed eligible for review. Of those 38 studies, most focused on cardiology, infectious diseases or oncology and the majority used electronic health records/electronic medical records data and cohort studies data. Different statistical methods were used to address confounding at baseline and selection bias, predominantly conditioning on the confounders (N = 18/49, 37%) and inverse probability of censoring weighting (N = 7/20, 35%) respectively. Different approaches were used to address immortal time bias, assigning individuals to treatment strategies at start of follow-up based on their data available at that specific time (N = 21, 55%), using the sequential trial emulations approach (N = 11, 29%) or the cloning approach (N = 6, 16%).

CONCLUSION

Different methods can be leveraged to address (A) confounding bias, (B) immortal time bias, and (C) selection bias. When working with observational data, and if possible, the 'target trial' framework should be used as it provides a structured conceptual approach to observational research.

Emulating Target Trials With Real-World Data to Inform Health Technology Assessment: Findings and Lessons From an Application to Emergency Surgery

OBJECTIVES

International health technology assessment (HTA) agencies recommend that real-world data (RWD) are used in some circumstances to add to the evidence base about the effectiveness and cost-effectiveness of health interventions. The target trial framework applies the design principles of randomized-controlled trials to RWD and can help alleviate inevitable concerns about bias and design flaws with nonrandomized studies. This article aimed to tackle the lack of guidance and exemplar applications on how this methodology can be applied to RWD to inform HTA decision making.

METHODS

We use Hospital Episode Statistics data from England on emergency hospital admissions from 2010 to 2019 to evaluate the cost-effectiveness of emergency surgery for 2 acute gastrointestinal conditions. We draw on the case study to describe the main challenges in applying the target trial framework alongside RWD and provide recommendations for how these can be addressed in practice.

RESULTS

The 4 main challenges when applying the target trial framework to RWD are (1) defining the study population, (2) defining the treatment strategies, (3) establishing time zero (baseline), and (4) adjusting for unmeasured confounding. The recommendations for how to address these challenges, mainly around the incorporation of expert judgment and use of appropriate methods for handling unmeasured confounding, are illustrated within the case study.

CONCLUSIONS

The recommendations outlined in this study could help future studies seeking to inform HTA decision processes. These recommendations can complement checklists for economic evaluations and design tools for estimating treatment effectiveness in nonrandomized studies.

Target Trial Emulation to Improve Causal Inference from Observational Data: What, Why, and How?

ABSTRACT

Target trial emulation has drastically improved the quality of observational studies investigating the effects of interventions. Its ability to prevent avoidable biases that have plagued many observational analyses has contributed to its recent popularity. This review explains what target trial emulation is, why it should be the standard approach for causal observational studies that investigate interventions, and how to do a target trial emulation analysis. We discuss the merits of target trial emulation compared with often used, but biased analyses, as well as potential caveats, and provide clinicians and researchers with the tools to better interpret results from observational studies investigating the effects of interventions.

Current practices in studies applying the target trial emulation framework: a protocol for a systematic review

INTRODUCTION

Observational studies represent an alternative to estimate real-world causal effects in the absence of available randomised controlled trials (RCTs). Target trial emulation is a framework for the application of RCT design principles to emulate a hypothetical open-label RCT (the hypothetical target trial) using existing observational data as the primary data source as opposed to the prospective recruitment and measurement of randomised units. The aim of this systematic review is to investigate the practices of studies applying the target trial emulation framework to evaluate the effectiveness of interventions.

METHODS AND ANALYSIS

We will systematically search in Medline (via Ovid), Embase (via Ovid, entries from medRxiv are included), PsycINFO (via Ovid), SCOPUS, Web of Science, Cochrane Library, the ISRCTN registry and ClinicalTrials.gov for all study reports and protocols which used the trial emulation framework (without time restriction). We will extract information concerning study design, data source, analysis, results, interpretation and dissemination. Two reviewers will perform study selection, data extraction and quality assessment. Disagreements between reviewers will be resolved by a third reviewer. A narrative approach will be used to synthesise and report qualitative and quantitative data. Reporting of the review will be informed by Preferred Reporting Items for Systematic Review and Meta-Analysis guidance (PRISMA).

ETHICS AND DISSEMINATION

Ethical approval is not required as it is a protocol for a systematic review. Findings will be disseminated through peer-reviewed publications and conference presentations.

Association of Statin Use With Risk of Liver Disease, Hepatocellular Carcinoma, and Liver-Related Mortality

IMPORTANCE

Given the burden of chronic liver disease on the health care system, more information on the hepatoprotective association of statins in the general population is needed.

OBJECTIVE

To examine whether regular statin use is associated with a reduction in liver disease, particularly hepatocellular carcinoma (HCC) and liver-related deaths, in the general population.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used data from the UK Biobank (UKB) (individuals aged 37-73 years) collected from baseline (2006-2010) to the end of follow-up in May 2021, from the TriNetX cohort (individuals aged 18-90 years) enrolled from baseline (2011-2020) until end of follow-up in September 2022, and from the Penn Medicine Biobank (PMBB) (individuals aged 18-102 years) with ongoing enrollment starting in 2013 to the end of follow-up in December 2020. Individuals were matched using propensity score matching according to the following criteria: age, sex, body mass index, ethnicity, diabetes with or without insulin or biguanide use, hypertension, ischemic heart disease, dyslipidemia, aspirin use, and number of medications taken (UKB only). Data analysis was performed from April 2021 to April 2023.

EXPOSURE

Regular statin use.

MAIN OUTCOMES AND MEASURES

Primary outcomes were liver disease and HCC development as well as liver-associated death.

RESULTS

A total of 1 785 491 individuals were evaluated after matching (aged 55 to 61 years on average, up to 56% men, and up to 49% women). A total of 581 cases of liver-associated death, 472 cases of incident HCC, and 98 497 new liver diseases were registered during the follow-up period. Individuals were aged 55-61 years on average, with a slightly higher proportion of men (up to 56%). In UKB individuals (n = 205 057) without previously diagnosed liver disease, statin users (n = 56 109) had a 15% lower hazard ratio (HR) for the association of developing a new liver disease (HR, 0.85; 95% CI, 0.78-0.92; P < .001). In addition, statin users demonstrated a 28% lower HR for the association with liver-related death (HR, 0.72; 95% CI, 0.59-0.88; P = .001) and a 42% lower HR for the development of HCC (HR, 0.58; 95% CI, 0.35-0.96; P = .04). In TriNetX individuals (n = 1 568 794), the HR for the association of HCC was reduced even further for statin users (HR, 0.26; 95% CI, 0.22-0.31; P = .003). The hepatoprotective association of statins was time and dose dependent, with a significant association in PMBB individuals (n = 11 640) for incident liver diseases after 1 year of statin use (HR, 0.76; 95% CI, 0.59-0.98; P = .03). Taking statins was particularly beneficial in men, individuals with diabetes, and individuals with a high Fibrosis-4 index at baseline. Carriers of the heterozygous minor allele of PNPLA3 rs738409 benefited from statin use and had a 69% lower HR for the association with HCC (UKB HR, 0.31; 95% CI, 0.11-0.85; P = .02).

CONCLUSIONS AND RELEVANCE

This cohort study indicates substantial preventive associations of statins against liver disease, with an association with duration and dose of intake.

Effect of Nirmatrelvir/Ritonavir (Paxlovid) on Hospitalization among Adults with COVID-19: an EHR-based Target Trial Emulation from N3C

This study leverages electronic health record data in the National COVID Cohort Collaborative's (N3C) repository to investigate disparities in Paxlovid treatment and to emulate a target trial assessing its effectiveness in reducing COVID-19 hospitalization rates. From an eligible population of 632,822 COVID-19 patients seen at 33 clinical sites across the United States between December 23, 2021 and December 31, 2022, patients were matched across observed treatment groups, yielding an analytical sample of 410,642 patients. We estimate a 65% reduced odds of hospitalization among Paxlovid-treated patients within a 28-day follow-up period, and this effect did not vary by patient vaccination status. Notably, we observe disparities in Paxlovid treatment, with lower rates among Black and Hispanic or Latino patients, and within socially vulnerable communities. Ours is the largest study of Paxlovid's real-world effectiveness to date, and our primary findings are consistent with previous randomized control trials and real-world studies.

Emulating Target Trials to Avoid Immortal Time Bias - An Application to Antibiotic Initiation and Preterm Delivery

BACKGROUND

Randomized trials in pregnancy are extremely challenging, and observational studies are often the only option to evaluate medication safety during pregnancy. However, such studies are often susceptible to immortal time bias if treatment initiation occurs after time zero of follow-up. We describe how emulating a sequence of target trials avoids immortal time bias and apply the approach to estimate the safety of antibiotic initiation between 24 and 37 weeks gestation on preterm delivery.

METHODS

The Tsepamo Study captured birth outcomes at hospitals throughout Botswana from 2014 to 2021. We emulated 13 sequential target trials of antibiotic initiation versus no initiation among individuals presenting to care <24 weeks, one for each week from 24 to 37 weeks. For each trial, eligible individuals had not previously initiated antibiotics. We also conducted an analysis susceptible to immortal time bias by defining time zero as 24 weeks and exposure as antibiotic initiation between 24 and 37 weeks. We calculated adjusted risk ratios (RR) and 95% confidence intervals (CI) for preterm delivery.

RESULTS

Of 111,403 eligible individuals, 17,009 (15.3%) initiated antibiotics between 24 and 37 weeks. In the sequence of target trials, RRs (95% CIs) ranged from 1.04 (0.90, 1.19) to 1.24 (1.11, 1.39) (pooled RR: 1.11 [1.06, 1.15]). In the analysis susceptible to immortal time bias, the RR was 0.90 (0.86, 0.94).

CONCLUSIONS

Defining exposure as antibiotic initiation at any time during follow-up after time zero resulted in substantial immortal time bias, making antibiotics appear protective against preterm delivery. Conducting a sequence of target trials can avoid immortal time bias in pregnancy studies.

Long-Term Health Consequences After Ovarian Removal at Benign Hysterectomy : A Nationwide Cohort Study

BACKGROUND

More evidence is needed to substantiate current recommendations about removing ovaries during hysterectomy for benign conditions.

OBJECTIVE

To compare long-term outcomes in women with and without bilateral salpingo-oophorectomy (BSO) during hysterectomy for benign conditions.

DESIGN

Emulated target trial using data from a population-based cohort.

SETTING

Women in Denmark aged 20 years or older during 1977 to 2017.

PARTICIPANTS

142 985 women with hysterectomy for a benign condition, 22 974 with BSO and 120 011 without.

INTERVENTION

Benign hysterectomy with or without BSO.

MEASUREMENTS

The primary outcomes were overall hospitalization for cardiovascular disease (CVD), overall cancer incidence, and all-cause mortality through December 2018.

RESULTS

Compared with women without BSO, women with BSO who were younger than 45 years at surgery had a higher 10-year cumulative risk for hospitalization for CVD (risk difference [RD], 1.19 percentage points [95% CI, 0.09 to 2.43 percentage points]). Women with BSO had a higher 10-year cumulative risk for cancer for ages 45 to 54 years (RD, 0.73 percentage point [CI, 0.05 to 1.38 percentage points]), 55 to 64 years (RD, 1.92 percentage points [CI, 0.69 to 3.25 percentage points]), and 65 years or older (RD, 2.54 percentage points [CI, 0.91 to 4.25 percentage points]). Women with BSO had higher 10-year mortality in all age groups, although the differences were statistically significant only for ages 45 to 54 years (RD, 0.79 percentage point [CI, 0.27 to 1.30 percentage points]). The mortality at 20 years was inconsistent with that at 10 years in women aged 65 years or older.

LIMITATION

Age was a proxy for menopausal status.

CONCLUSION

The authors find that these results support current recommendations for conserving ovaries in premenopausal women without a high risk for ovarian cancer and suggest a cautious approach in postmenopausal women.

PRIMARY FUNDING SOURCE

The Danish Cancer Society's Scientific Committee and the Mermaid Project.

Hypothetical interventions on risk factors for depression among middle-aged and older community-dwellers in China: An application of the parametric g-formula in a longitudinal study

BACKGROUND

Sleep disturbances, frailty, and body pain are widespread in middle-aged and older adults with depression, and have been identified as depression risk factors. However, there is a scarcity of research on the benefits of sleep improvement, frailty amelioration, and pain management on incident depression.

METHODS

A total of 8895 respondents aged above 45 years were derived from the China Health and Retirement Longitudinal Study (CHARLS) between 2011 and 2018. The parametric g-formula was used to estimate the 7-year risks of depression under independent hypothetical interventions on nighttime sleep duration (NSD), daytime napping duration (DND), perceived sleep quality (PSQ), frailty, and pain, as well as their various combinations.

RESULTS

The observed depression risk was 41.77 %. The independent intervention on frailty was the most effective in lowering incident depression, with a risk ratio (RR) of 0.61 (95 % CI: 0.57-0.64), followed by PSQ (RR: 0.75, 95 % CI: 0.73-0.78), pain (RR: 0.90, 95 % CI: 0.87-0.91), and NSD (RR: 0.96, 95 % CI: 0.93-0.98). In subgroup analysis, intervention on NSD was more effective in men, PSQ was more effective in middle-aged individuals, and frailty and pain were more effective in older persons. The combined intervention of NSD, PSQ, frailty, and pain lowered the risk the greatest (RR: 0.35, 95 % CI: 0.32-0.37).

LIMITATIONS

Generalizing our results to other populations should be possible if they have the same distribution of effect modifiers and interference patterns because of the calculation principle of the parametric g-formula.

CONCLUSIONS

Interventions for sleep disturbances, frailty, and body pain can minimize the risk of depression.

Nirmatrelvir and risk of hospital admission or death in adults with covid-19: emulation of a randomized target trial using electronic health records

OBJECTIVE

To estimate the effectiveness of nirmatrelvir, compared with no treatment, in reducing admission to hospital or death at 30 days in people infected with the SARS-CoV-2 virus and at risk of developing severe disease, according to vaccination status and history of previous SARS-CoV-2 infection.

DESIGN

Emulation of a randomized target trial with electronic health records.

SETTING

Healthcare databases of the US Department of Veterans Affairs PARTICIPANTS: 256 288 participants with a SARS-CoV-2 positive test result and at least one risk factor for developing severe covid-19 disease, between 3 January and 30 November 2022. 31 524 were treated with nirmatrelvir within five days of testing positive for SARS-CoV-2 and 224 764 received no treatment.

MAIN OUTCOME MEASURES

The effectiveness of starting nirmatrelvir within five days of a positive SARS-CoV-2 test result versus no treatment in reducing the risk of admission to hospital or death at 30 days was estimated in those who were not vaccinated, in those who received one or two doses of vaccine, and those who received a vaccine booster and, separately, in participants with a primary SARS-CoV-2 infection or reinfection. The inverse probability weighting method was used to balance personal and health characteristics between the groups. Relative risk and absolute risk reduction were computed from cumulative incidence at 30 days, estimated by weighted Kaplan-Meier estimator.

RESULTS

Among people who were not vaccinated (n=76 763; 5338 nirmatrelvir and 71 425 no treatment), compared with no treatment, the relative risk of nirmatrelvir in reducing admission to hospital or death at 30 days was 0.60 (95% confidence interval 0.50 to 0.71); the absolute risk reduction was 1.83% (95% confidence interval 1.29% to 2.49%). The relative risk and absolute risk reduction, compared with no treatment, were 0.65 (0.57 to 0.74) and 1.27% (0.90% to 1.61%), respectively, in people who received one or two doses of vaccine (n=84 620; 7989 nirmatrelvir and 76 631 no treatment); 0.64 (0.58 to 0.71) and 1.05% (0.85% to 1.27%) in individuals who received a booster dose of vaccine (n=94 905; 18 197 nirmatrelvir and 76 708 no treatment); 0.61 (0.57 to 0.65) and 1.36% (1.19% to 1.53%) in participants with a primary SARS-CoV-2 infection (n=228 081; 26 350 nirmatrelvir and 201 731 no treatment); and 0.74 (0.63 to 0.87) and 0.79% (0.36% to 1.18%) in participants who were reinfected with the SARS-CoV-2 virus (n=28 207; 5174 nirmatrelvir and 23 033 no treatment). Nirmatrelvir was associated with a reduced risk of admission to hospital or death in those aged ≤65 years and > 65 years; in men and women; in black and white participants; in those with 1-2, 3-4, and ≥5 risk factors for progression to severe covid-19 illness; and in those infected during the omicron BA.1 or BA.2 predominant era, and the BA.5 predominant era.

CONCLUSIONS

In people with SARS-CoV-2 infection who were at risk of developing severe disease, compared with no treatment, nirmatrelvir was associated with a reduced risk of admission to hospital or death at 30 days in people who were not vaccinated, vaccinated, and had received a booster vaccine, and in those with a primary SARS-CoV-2 infection and reinfection.

The Role of Statins in the Prevention of Ovarian and Endometrial Cancers

Ovarian and endometrial cancers are the most common gynecologic malignancies and emerging evidence suggests that lipid metabolism and subsequent inflammation are important etiologic factors for both tumors. Statins (HMG-CoA reductase inhibitors) are the most widely prescribed lipid-lowering drugs in the United States and are used by 25% of adults aged 40+ years. In addition to their cardio-protective actions, statins have anti-inflammatory effects and have demonstrated antiproliferative and apoptotic properties in cancer cell lines, supporting a potential role in cancer prevention. To appropriately quantify potential public health impact of statin use for cancer prevention, there is a great need to understand the potential risk reduction among individuals at a higher risk of gynecologic cancers, the group that will likely need to be targeted to effectively balance risk/benefit of medications repurposed for cancer prevention. In this commentary, we focus on summarizing emerging evidence suggesting that the anti-inflammatory and lipid-lowering mechanisms of statins may provide important cancer-preventive benefits for gynecologic cancers as well as outline important unanswered questions and future research directions.

Molnupiravir and risk of hospital admission or death in adults with covid-19: emulation of a randomized target trial using electronic health records

OBJECTIVE

To emulate a randomized target trial to estimate the association between the antiviral drug molnupiravir and hospital admission or death in adults with SARS-CoV-2 infection in the community during the omicron predominant era who were at high risk of progression to severe covid-19.

DESIGN

Emulation of a randomized target trial using electronic health records.

SETTING

US Department of Veterans Affairs.

PARTICIPANTS

85 998 adults with SARS-CoV-2 infection between 5 January and 30 September 2022 and at least one risk factor for progression to severe covid-19: 7818 participants were eligible for and treated with molnupiravir and 78 180 received no treatment.

MAIN OUTCOMES MEASURE

The primary outcome was a composite of hospital admission or death at 30 days. The clone method with inverse probability of censoring weighting was used to adjust for informative censoring and balance baseline characteristics between the groups. The cumulative incidence function was used to estimate the relative risk and the absolute risk reduction at 30 days.

RESULTS

Molnupiravir was associated with a reduction in hospital admissions or death at 30 days (relative risk 0.72 (95% confidence interval 0.64 to 0.79)) compared with no treatment; the event rates for hospital admission or death at 30 days were 2.7% (95% confidence interval 2.5% to 3.0%) for molnupiravir and 3.8% (3.7% to 3.9%) for no treatment; the absolute risk reduction was 1.1% (95% confidence interval 0.8% to 1.4%). Molnupiravir appeared to be effective in those who had not been vaccinated against covid-19 (relative risk 0.83 (0.70 to 0.97) and absolute risk reduction 0.9% (0.2% to 1.9%)), had received one or two vaccine doses (0.69 (0.56 to 0.83) and 1.3% (0.7% to 1.9%)), and had received a booster dose (0.71 (0.58 to 0.83) and 1.0% (0.5% to 1.4%)); in those infected during the era when the omicron subvariant BA.1 or BA.2 was predominant (0.72 (0.62 to 0.83) and 1.2% (0.7% to 1.6%)) and when BA.5 was predominant (0.75 (0.66 to 0.86) and 0.9% (0.5% to 1.3%)); and in those with no history of SARS-CoV-2 infection (0.72 (0.64 to 0.81) and 1.1% (0.8% to 1.4%)) and with a history of SARS-CoV-2 infection (0.75 (0.58 to 0.97) and 1.1% (0.1% to 1.8%)).

CONCLUSIONS

The findings of this emulation of a randomized target trial suggest that molnupiravir might have reduced hospital admission or death at 30 days in adults with SARS-CoV-2 infection in the community during the recent omicron predominant era who were at high risk of progression to severe covid-19 and eligible for treatment with molnupiravir.

How strong is the evidence to support statins repurposing for the treatment of cirrhosis?

In this editorial, we briefly mention the studies that support the use of statins to change the natural history of liver cirrhosis, alongside potential biases and flaws that need to be considered when analyzing data. The key message that we want to communicate is that even if current evidence is somehow compelling, it is limited, mostly from observational studies, and in general not enough to formally recommend the prescription of statins in patients with cirrhosis as disease-modifying agents. Finally, we also mention some important facts about the safety of statins in the context of patients with underlying liver disease.

Association of statin use with outcomes of patients admitted with COVID-19: an analysis of electronic health records using superlearner

IMPORTANCE

Statin use prior to hospitalization for Coronavirus Disease 2019 (COVID-19) is hypothesized to improve inpatient outcomes including mortality, but prior findings from large observational studies have been inconsistent, due in part to confounding. Recent advances in statistics, including incorporation of machine learning techniques into augmented inverse probability weighting with targeted maximum likelihood estimation, address baseline covariate imbalance while maximizing statistical efficiency.

OBJECTIVE

To estimate the association of antecedent statin use with progression to severe inpatient outcomes among patients admitted for COVD-19.

DESIGN, SETTING AND PARTICIPANTS

We retrospectively analyzed electronic health records (EHR) from individuals ≥ 40-years-old who were admitted between March 2020 and September 2022 for ≥ 24 h and tested positive for SARS-CoV-2 infection in the 30 days before to 7 days after admission.

EXPOSURE

Antecedent statin use-statin prescription ≥ 30 days prior to COVID-19 admission.

MAIN OUTCOME

Composite end point of in-hospital death, intubation, and intensive care unit (ICU) admission.

RESULTS

Of 15,524 eligible COVID-19 patients, 4412 (20%) were antecedent statin users. Compared with non-users, statin users were older (72.9 (SD: 12.6) versus 65.6 (SD: 14.5) years) and more likely to be male (54% vs. 51%), White (76% vs. 71%), and have ≥ 1 medical comorbidity (99% vs. 86%). Unadjusted analysis demonstrated that a lower proportion of antecedent users experienced the composite outcome (14.8% vs 19.3%), ICU admission (13.9% vs 18.3%), intubation (5.1% vs 8.3%) and inpatient deaths (4.4% vs 5.2%) compared with non-users. Risk differences adjusted for labs and demographics were estimated using augmented inverse probability weighting with targeted maximum likelihood estimation using Super Learner. Statin users still had lower rates of the composite outcome (adjusted risk difference: - 3.4%; 95% CI: - 4.6% to - 2.1%), ICU admissions (- 3.3%; - 4.5% to - 2.1%), and intubation (- 1.9%; - 2.8% to - 1.0%) but comparable inpatient deaths (0.6%; - 1.3% to 0.1%).

CONCLUSIONS AND RELEVANCE

After controlling for confounding using doubly robust methods, antecedent statin use was associated with minimally lower risk of severe COVID-19-related outcomes, ICU admission and intubation, however, we were not able to corroborate a statin-associated mortality benefit.

Oxygenation thresholds for invasive ventilation in hypoxemic respiratory failure: a target trial emulation in two cohorts

BACKGROUND

The optimal thresholds for the initiation of invasive ventilation in patients with hypoxemic respiratory failure are unknown. Using the saturation-to-inspired oxygen ratio (SF), we compared lower versus higher hypoxemia severity thresholds for initiating invasive ventilation.

METHODS

This target trial emulation included patients from the Medical Information Mart for Intensive Care (MIMIC-IV, 2008-2019) and the Amsterdam University Medical Centers (AmsterdamUMCdb, 2003-2016) databases admitted to intensive care and receiving inspired oxygen fraction ≥ 0.4 via non-rebreather mask, noninvasive ventilation, or high-flow nasal cannula. We compared the effect of using invasive ventilation initiation thresholds of SF < 110, < 98, and < 88 on 28-day mortality. MIMIC-IV was used for the primary analysis and AmsterdamUMCdb for the secondary analysis. We obtained posterior means and 95% credible intervals (CrI) with nonparametric Bayesian G-computation.

RESULTS

We studied 3,357 patients in the primary analysis. For invasive ventilation initiation thresholds SF < 110, SF < 98, and SF < 88, the predicted 28-day probabilities of invasive ventilation were 72%, 47%, and 19%. Predicted 28-day mortality was lowest with threshold SF < 110 (22.2%, CrI 19.2 to 25.0), compared to SF < 98 (absolute risk increase 1.6%, CrI 0.6 to 2.6) or SF < 88 (absolute risk increase 3.5%, CrI 1.4 to 5.4). In the secondary analysis (1,279 patients), the predicted 28-day probability of invasive ventilation was 50% for initiation threshold SF < 110, 28% for SF < 98, and 19% for SF < 88. In contrast with the primary analysis, predicted mortality was highest with threshold SF < 110 (14.6%, CrI 7.7 to 22.3), compared to SF < 98 (absolute risk decrease 0.5%, CrI 0.0 to 0.9) or SF < 88 (absolute risk decrease 1.9%, CrI 0.9 to 2.8).

CONCLUSION

Initiating invasive ventilation at lower hypoxemia severity will increase the rate of invasive ventilation, but this can either increase or decrease the expected mortality, with the direction of effect likely depending on baseline mortality risk and clinical context.

Levosimendan in patients undergoing extracorporeal membrane oxygenation after cardiac surgery: an emulated target trial using observational data

BACKGROUND

Retrospective cohorts have suggested that levosimendan may facilitate the weaning of veno-arterial extracorporeal membrane oxygenation (VA-ECMO). We therefore studied this clinical question by emulating a randomized trial with observational data.

METHODS

All patients with refractory postcardiotomy cardiogenic shock and assisted with VA-ECMO, admitted to a surgical intensive care unit at La Pitié-Salpêtrière Hospital between 2016 and 2019, were eligible. To avoid immortal-time bias, we emulated a target trial sequentially comparing levosimendan administration versus no levosimendan administration in patients treated with VA-ECMO. The primary outcome was time to successful ECMO weaning. The secondary outcomes were 30-day and 1-year mortality. We performed a multivariable analysis to adjust for confounding at baseline.

RESULTS

Two hundred and thirty-nine patients were included in the study allowing building a nested trials cohort of 1434 copies of patients. No association of levosimendan treatment and VA-ECMO weaning was found (HR = 0.91, [0.57; 1.45], p = 0.659 in multivariable analysis), or 30-day mortality (OR = 1.03, [0.52; 2.03], p = 0.940) and 1-year mortality (OR = 1.00, [0.53; 1.89], p = 0.999).

CONCLUSIONS

Using the emulated target trial framework, this study did not find any association of levosimendan treatment and ECMO weaning success after postcardiotomy cardiogenic shock. However, the population of interest remains heterogeneous and subgroups might benefit from levosimendan.

Can Observational Analyses of Routinely Collected Data Emulate Randomized Trials? Design and Feasibility of the Observational Patient Evidence for Regulatory Approval Science and Understanding Disease Project

OBJECTIVES

The Observational Patient Evidence for Regulatory Approval Science and Understanding Disease (OPERAND) project examines whether real-world data (RWD) can be used to inform regulatory decision making.

METHODS

OPERAND evaluates whether observational analyses using RWD to emulate index trials can produce effect estimates similar to those of the trials and examines the impact of relaxing the eligibility criteria of the observational analyses to obtain samples that more closely match the real-world populations receiving the treatments. In OPERAND, 2 research teams independently attempt to emulate the ROCKET Atrial Fibrillation and LEAD-2 trials using OptumLabs data. This article describes the design of the project, summarizes the approaches of the 2 research teams, and presents feasibility results for 2 emulations using new-user designs.

RESULTS

There were differences in the teams' conceptualizations of the emulation, design decisions for cohort identification, and resulting RWD cohorts. These differences occurred even though both teams were guided by the same index trials and had access to the same source of RWD.

CONCLUSIONS

Reasonable alternative design and analysis approaches may be taken to answer the same research question, even when attempting to emulate the same index trial. Researcher decision making is an understudied and potentially important source of variability across RWD analyses.