Electronic medical records can be used to emulate target trials of sustained treatment strategies

Physical activity initiated from midlife on risk of dementia and cognitive impairment: The Health and Retirement Study

BACKGROUND

Physical activity is associated with lower risk of dementia and cognitive impairment, but existing randomized controlled trials have shown conflicting results. As cognitive decline occurs decades before the onset of dementia, physical activity interventions initiated in late life may have missed the potential window for prevention. An ideal trial of physical activity initiated from midlife and lasts till incident dementia and cognitive impairment in late life is not feasible. We aimed to estimate the effectiveness of a hypothetical physical activity intervention initiated from midlife on reducing dementia and cognitive impairment by emulating target trials using observational data.

METHODS

The Health and Retirement Study was used to emulate target trials among noninstitutionalized participants aged 45 to 65 years with normal cognition who were physically inactive in the previous 2 years. Cognitive status was determined based on Langa-Weir classification of cognitive function (including immediate and delayed word recall tests, serial sevens subtraction, counting backward). Individuals were categorized as initiating physical activity or not, based on the self-reported physical activity. Intention-to-treat and per-protocol analysis were conducted with pooled logistic regression models with inverse-probability of treatment and censoring weights to estimate risk ratios (RRs), and 95% confidence intervals (95% CIs) were calculated with 200 sets of bootstrapping.

RESULTS

Among 1505 participants (average age 57.6 ± 4.8 years, 67% women, 76.5% White), 72 cases of dementia and 409 cases of cognitive impairment occurred. After 12 years of follow-up, physical activity reduced dementia (RR = 0.70, 95% CI: 0.43, 0.99) for intention-to-treat analysis, and reduced dementia (RR = 0.51, 95% CI: 0.19, 0.99) and cognitive impairment (RR = 0.77, 95% CI: 0.61, 0.92) for per-protocol analysis. No significant reduction was found among older adults.

CONCLUSIONS

Physical activity initiated during midlife may reduce dementia and cognitive impairment in late life, which highlights the importance of preventing cognitive outcomes at an earlier stage of life.

Target trial framework for determining the effect of changes in training load on injury risk using observational data: a methodological commentary

In recent years, a large focus has been placed on managing training load for injury prevention. To minimise injuries, training recommendations should be based on research that examines causal relationships between load and injury risk. While observational studies can be used to estimate causal effects, conventional methods to study the relationship between load and injury are prone to bias. The target trial framework is a valuable tool that requires researchers to emulate a hypothetical randomised trial using observational data. This framework helps to explicitly define research questions and design studies in a way that estimates causal effects. This article provides an overview of the components of the target trial framework as applied to studies on load and injury and describes various considerations that should be made in study design and analyses to minimise bias.

Partial Hepatectomy and Ablation for Survival of Early-Stage Hepatocellular Carcinoma Patients: A Bayesian Emulation Analysis

Partial hepatectomy and ablation therapy are two widely used surgical procedures for localized early-stage hepatocellular carcinoma (HCC) patients. This article aimed to evaluate their relative effectiveness in terms of overall survival. An emulation analysis approach was first developed based on the Bayesian technique. We estimated propensity scores via Bayesian logistic regression and adopted a weighted Bayesian Weibull accelerated failure time (AFT) model incorporating prior information contained in the published literature. With the Surveillance, Epidemiology, and End Results (SEER)-Medicare data, an emulated target trial with rigorously defined inclusion/exclusion criteria and treatment regimens for early-stage HCC patients over 66 years old was developed. For the main cohort with tumor size less than or equal to 5 cm, a total of 1146 patients were enrolled in the emulated trial, with 301 and 845 in the partial hepatectomy and ablation arms, respectively. The analysis suggested ablation to be significantly associated with inferior overall survival (hazard ratio [HR] = 1.35; 95% credible interval [CrI]: 1.14, 1.60). For the subgroup with tumor size less than or equal to 3 cm, there was no significant difference in overall survival between the two arms (HR = 1.15; 95% CrI: 0.88, 1.52). Overall, the comparative treatment effect of ablation and partial hepatectomy on survival remains inconclusive. This finding may provide further insight into HCC clinical treatment.

Making causal inferences from transactional data: A narrative review of opportunities and challenges when implementing the target trial framework

The target trial framework has emerged as a powerful tool for addressing causal questions in clinical practice and in public health. In the healthcare sector, where decision-making is increasingly data-driven, transactional databases, such as electronic health records (EHR) and insurance claims, present an untapped potential for answering complex causal questions. This narrative review explores the potential of the integration of the target trial framework with real-world data to enhance healthcare decision-making processes. We outline essential elements of the target trial framework, and identify pertinent challenges in data quality, privacy concerns, and methodological limitations, proposing solutions to overcome these obstacles and optimize the framework's application.

Benzodiazepine Discontinuation and Mortality Among Patients Receiving Long-Term Benzodiazepine Therapy

Importance

There is interest in reducing long-term benzodiazepine prescribing given harms associated with use, but the cumulative risks or benefits of discontinuation are unknown.

Objective

To identify the association of benzodiazepine discontinuation with mortality and other adverse events among patients prescribed stable long-term benzodiazepine therapy, stratified by baseline opioid exposure.

Design, Setting, and Participants

This comparative effectiveness study with a trial emulation approach included data from a US commercial insurance database between January 1, 2013, and December 31, 2017. Eligible participants were adults with stable long-term benzodiazepine prescription treatment. Data were analyzed between December 2022 and November 2023.

Exposure

Benzodiazepine discontinuation, defined as no benzodiazepine prescription coverage for 31 consecutive days identified during a 6-month grace period after baseline.

Main Outcome and Measures

Mortality during 12 months of follow-up; secondary outcomes included nonfatal overdose, suicide attempt or self-inflicted injury, suicidal ideation, and emergency department use, identified in medical claims. Inverse probability weighting was used to adjust for baseline confounders that potentially affected treatment assignment and censoring due to death or disenrollment. Primary analysis used an intention-to-treat approach; a secondary per-protocol analysis estimated associations after accounting for nonadherence. Analyses were stratified by opioid use.

Results

The study included 213 011 (136 609 female [64.1%]; mean [SD] age, 62.2 [14.9] years; 2953 Asian [1.4%], 18 926 Black [8.9%], 22 734 Hispanic [10.7%], and 168 398 White [60.2%]) and 140 565 (91 811 female [65.3%]; mean [SD] age, 61.1 [13.2] years; 1319 Asian [0.9%], 15 945 Black [11.3%], 11 989 Hispanic [8.5%], and 111 312 White [79.2%]) patients with stable long-term benzodiazepine use without and with opioid exposure, respectively. Among the nonopioid exposed, the adjusted cumulative incidence of death after 1 year was 5.5% (95% CI, 5.4%-5.8%) for discontinuers, an absolute risk difference of 2.1 percentage points (95% CI, 1.9-2.3 percentage points) higher than for nondiscontinuers. The mortality risk was 1.6 (95% CI, 1.6-1.7) times that of nondiscontinuers. Among those with opioid exposure, the adjusted cumulative incidence of death was 6.3% (95% CI, 6.0%-6.6%) for discontinuers, an absolute risk difference of 2.4 percentage points (95% CI, 2.2-2.7 percentage points) higher than for nondiscontinuers and a mortality risk 1.6 (95% CI, 1.5-1.7) times that of nondiscontinuers. Cumulative incidence of secondary outcomes was also higher among discontinuers.

Conclusions and Relevance

This study identifies small absolute increases in risk of harms among patients with stable long-term prescription benzodiazepine treatment who appear to discontinue relative to continuing treatment, including those with and without recent prescription opioid exposure. Policy broadly promoting benzodiazepine discontinuation may have unintended risks.

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.

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.

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.

Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis

Objectives: To evaluate the comparative effectiveness of treatments, a randomized clinical trial remains the gold standard but can be challenged by a high cost, a limited sample size, an inability to fully reflect the real world, and feasibility concerns. The objective is to showcase a big data approach that takes advantage of large electronic medical record (EMR) data to emulate clinical trials. To overcome the limitations of regression analysis, a deep learning-based analysis pipeline was developed. Study Design and Setting: Lumpectomy (breast-conserving surgery) and mastectomy are the two most commonly used surgical procedures for early-stage female breast cancer patients. An emulation trial was designed using the Surveillance, Epidemiology, and End Results (SEER)-Medicare data to evaluate their relative effectiveness in overall survival. The analysis pipeline consisted of a propensity score step, a weighted survival analysis step, and a bootstrap inference step. Results: A total of 65,997 subjects were enrolled in the emulated trial, with 50,704 and 15,293 in the lumpectomy and mastectomy arms, respectively. The two surgery procedures had comparable effects in terms of overall survival (survival year change = 0.08, 95% confidence interval (CI): -0.08, 0.25) for the elderly SEER-Medicare early-stage female breast cancer patients. Conclusion: This study demonstrated the power of "mining large EMR data + deep learning-based analysis," and the proposed analysis strategy and technique can be potentially broadly applicable. It provided convincing evidence of the comparative effectiveness of lumpectomy and mastectomy.

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.

Comparative effectiveness of second line glucose lowering drug treatments using real world data: emulation of a target trial

Objective

To build on the recently completed GRADE (Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study) randomised trial examining the comparative effectiveness of second line glucose lowering drugs in achieving and maintaining glycaemic control in adults with type 2 diabetes.

Design

Emulation of a target trial.

Setting

Medical and pharmacy claims data from the OptumLabs Data Warehouse, a de-identified US national dataset of beneficiaries of commercially insured and Medicare Advantage plans, 29 March 2013 to 30 June 2021.

Participants

Adults (≥18 years) with type 2 diabetes who first started taking glimepiride, sitagliptin, liraglutide, insulin glargine, or canagliflozin between 29 March 2013 and 30 June 2021. Participants were treatment naive or were receiving metformin monotherapy at the time of starting the study drug.

Main outcome measures

The main outcomes were time to primary and secondary metabolic failure of the assigned treatment, calculated as days to haemoglobin A1c levels of ≥7.0% and >7.5%, respectively. Secondary metabolic, cardiovascular, and microvascular outcomes were analysed as specified in the GRADE statistical analysis plan. Propensity scores were estimated with the gradient boosting method, and inverse propensity score weighting was used to emulate randomisation to the treatment groups, which were then compared with Cox proportional hazards regression.

Results

The study cohort included participants starting treatment with glimepiride (n=20 511), liraglutide (n=5569), sitagliptin (n=13 039), insulin glargine (n=7262), and canagliflozin (n=5290). The insulin glargine arm was excluded because of insufficient control of confounding. Median times to primary metabolic failure were 439 (95% confidence interval 400 to 489) days in the canagliflozin arm, 439 (426 to 453) days in the glimepiride arm, 624 (567 to 731) days in the liraglutide arm, and 461 (442 to 482) days in the sitagliptin arm. Median time to secondary metabolic failure was also longest in the liraglutide arm. Adults receiving liraglutide had the lowest one year cumulative incidence rate of primary metabolic failure (0.37, 95% confidence interval 0.35 to 0.40) followed by sitagliptin (0.44, 0.43 to 0.45), glimepiride (0.45, 0.44 to 0.45), and canagliflozin (0.46, 0.44 to 0.48). Similarly, the one year cumulative incidence rate of secondary metabolic failure was 0.27 (0.25 to 0.29) in the canagliflozin arm, 0.28 (0.27 to 0.29) in the glimepiride arm, 0.23 (0.21 to 0.26) in the liraglutide arm, and 0.28 (0.27 to 0.29) in the sitagliptin arm. No differences were observed between the study arms in the rates of microvascular and macrovascular complications.

Conclusions

In this target trial emulation of an expanded GRADE study framework, liraglutide was more effective in achieving and maintaining glycaemic control as a second line glucose lowering drug than canagliflozin, sitagliptin, or glimepiride.

Tell me what you want, what you really really want: Estimands in observational pharmacoepidemiologic comparative effectiveness and safety studies

PURPOSE

Ideally, the objectives of a pharmacoepidemiologic comparative effectiveness or safety study should dictate its design and data analysis. This paper discusses how defining an estimand is instrumental to this process.

METHODS

We applied the ICH-E9 (Statistical Principles for Clinical Trials) R1 addendum on estimands - which originally focused on randomized trials - to three examples of observational pharmacoepidemiologic comparative effectiveness and safety studies. Five key elements specify the estimand: the population, contrasted treatments, endpoint, intercurrent events, and population-level summary measure.

RESULTS

Different estimands were defined for case studies representing three types of pharmacological treatments: (1) single-dose treatments using a case study about the effect of influenza vaccination versus no vaccination on mortality risk in an adult population of ≥60 years of age; (2) sustained-treatments using a case study about the effect of dipeptidyl peptidase 4 inhibitor versus glucagon-like peptide-1 agonist on hypoglycemia risk in treatment of uncontrolled diabetes; and (3) as needed treatments using a case study on the effect of nitroglycerin spray as-needed versus no nitroglycerin on syncope risk in treatment of stabile angina pectoris.

CONCLUSIONS

The case studies illustrated that a seemingly clear research question can still be open to multiple interpretations. Defining an estimand ensures that the study targets a treatment effect that aligns with the treatment decision the study aims to inform. Estimand definitions further help to inform choices regarding study design and data-analysis and clarify how to interpret study findings.

Hybrid immunity against reinfection with SARS-CoV-2 following a previous SARS-CoV-2 infection and single dose of the BNT162b2 vaccine in children and adolescents: a target trial emulation

BACKGROUND

Although most children and adolescents have had a previous SARS-CoV-2 infection and many continue to receive COVID-19 vaccinations, studies of the effectiveness of hybrid immunity against reinfection with the omicron (B.1.1.529) variant are scarce. We aimed to examine the effectiveness of vaccination in convalescent children and adolescents against reinfection with the delta (B.1.617.2) variant and the BA.1 and BA.2 and BA.4 and BA.5 omicron subvariants.

METHODS

This retrospective cohort study was devised to emulate a target randomised control trial using a retrospective dataset of anonymised health records of children (5-11 years old) and adolescents (12-16 years old) who were members of the Maccabi Healthcare Services, Israel. The design emulated 91 randomised trials by devising a series of multiple nested trials, compiling the results into a single dataset, and fitting Cox proportional hazards models to estimate adjusted hazard ratios (HRs) with 95% CIs of each measured outcome. The primary aim was to assess the protection from reinfection with the delta variant and the BA.1 and BA.2 and BA.4 and BA.5 omicron subvariants associated with hybrid immunity as a result of a previous SARS-CoV-2 infection followed by vaccination with the BNT162b2 (Pfizer-BioNTech) vaccine.

FINDINGS

Data from between from March 1, 2020, to July 31, 2022, for 163 812 individuals (120 721 children [59 404 girls and 61 317 boys], median age 8·0 years [IQR 6·7 to 10·2]; and 43 091 adolescents [21 239 girls and 21 852 boys], median age 13·5 years [12·6 to 14·8]) were included in at least one trial. A single dose of the BNT162b2 vaccine in convalescent children and adolescents confers statistically significant protection against the delta variant (78% [95% CI 72 to 83] in adolescents and 64% [3 to 87] in children) and the omicron BA.1 and BA.2 subvariants (54% [50 to 57] in adolescents and 71% [67 to 73] in children) compared with children who had a previous infection but were unvaccinated. However, the vaccine was not found to confer statistically significant protection against the BA.4 and BA.5 omicron subvariants in adolescents (8% [-18 to 29]) and children (12% [-6 to 27]).

INTERPRETATION

Decision makers in BA.4 and BA.5 dominant regions should re-examine whether convalescent individuals aged 5-16 years should receive the BNT162b2 vaccine to prevent future reinfection, especially in light of reports that show that most children and adolescents have already been infected with SARS-CoV-2.

FUNDING

None.

Use of Real-World Data in Population Science to Improve the Prevention and Care of Diabetes-Related Outcomes

The past decade of population research for diabetes has seen a dramatic proliferation of the use of real-world data (RWD) and real-world evidence (RWE) generation from non-research settings, including both health and non-health sources, to influence decisions related to optimal diabetes care. A common attribute of these new data is that they were not collected for research purposes yet have the potential to enrich the information around the characteristics of individuals, risk factors, interventions, and health effects. This has expanded the role of subdisciplines like comparative effectiveness research and precision medicine, new quasi-experimental study designs, new research platforms like distributed data networks, and new analytic approaches for clinical prediction of prognosis or treatment response. The result of these developments is a greater potential to progress diabetes treatment and prevention through the increasing range of populations, interventions, outcomes, and settings that can be efficiently examined. However, this proliferation also carries an increased threat of bias and misleading findings. The level of evidence that may be derived from RWD is ultimately a function of the data quality and the rigorous application of study design and analysis. This report reviews the current landscape and applications of RWD in clinical effectiveness and population health research for diabetes and summarizes opportunities and best practices in the conduct, reporting, and dissemination of RWD to optimize its value and limit its drawbacks.

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.

Diagnosis and management of bipolar disorders

Bipolar disorders (BDs) are recurrent and sometimes chronic disorders of mood that affect around 2% of the world's population and encompass a spectrum between severe elevated and excitable mood states (mania) to the dysphoria, low energy, and despondency of depressive episodes. The illness commonly starts in young adults and is a leading cause of disability and premature mortality. The clinical manifestations of bipolar disorder can be markedly varied between and within individuals across their lifespan. Early diagnosis is challenging and misdiagnoses are frequent, potentially resulting in missed early intervention and increasing the risk of iatrogenic harm. Over 15 approved treatments exist for the various phases of bipolar disorder, but outcomes are often suboptimal owing to insufficient efficacy, side effects, or lack of availability. Lithium, the first approved treatment for bipolar disorder, continues to be the most effective drug overall, although full remission is only seen in a subset of patients. Newer atypical antipsychotics are increasingly being found to be effective in the treatment of bipolar depression; however, their long term tolerability and safety are uncertain. For many with bipolar disorder, combination therapy and adjunctive psychotherapy might be necessary to treat symptoms across different phases of illness. Several classes of medications exist for treating bipolar disorder but predicting which medication is likely to be most effective or tolerable is not yet possible. As pathophysiological insights into the causes of bipolar disorders are revealed, a new era of targeted treatments aimed at causal mechanisms, be they pharmacological or psychosocial, will hopefully be developed. For the time being, however, clinical judgment, shared decision making, and empirical follow-up remain essential elements of clinical care. This review provides an overview of the clinical features, diagnostic subtypes, and major treatment modalities available to treat people with bipolar disorder, highlighting recent advances and ongoing therapeutic challenges.

Recording type 2 diabetes mellitus in a standardised central Saudi database: a retrospective validation study

OBJECTIVES

This study was conducted to assess the validity of recording (and the original diagnostic practice) of type 2 diabetes mellitus at a hospital whose records were integrated to a centralised database (the standardised common data model (CDM) of the Saudi National Pharmacoepidemiologic Database (NPED)).

DESIGN

A retrospective single-centre validation study.

SETTINGS

Data of the study participants were extracted from the CDM of the NPED (only records of one tertiary care hospital were integrated at the time of the study) between 1 January 2013 and 1 July 2018.

PARTICIPANTS

A random sample of patients with type 2 diabetes mellitus (≥18 years old and with a code of type 2 diabetes mellitus) matched with a control group (patients without diabetes) based on age and sex.

OUTCOME MEASURES

The standardised coding of type 2 diabetes in the CDM was validated by comparing the presence of diabetes in the CDM versus the original electronic records at the hospital, the recording in paper-based medical records, and the physician re-assessment of diabetes in the included cases and controls, respectively. Sensitivity, specificity, positive predictive value and negative predictive value were estimated for each pairwise comparison using RStudio V.1.4.1103.

RESULTS

A total of 437 random sample of patients with type 2 diabetes mellitus was identified and matched with 437 controls. Only 190 of 437 (43.0%) had paper-based medical records. All estimates were above 90% except for sensitivity and specificity of CDM versus paper-based records (54%; 95% CI 47% to 61% and 68%; 95% CI 62% to 73%, respectively).

CONCLUSIONS

This study provided an assessment to the extent of which only type 2 diabetes mellitus code can be used to identify patients with this disease at a Saudi centralised database. A future multi-centre study would help adding more emphasis to the study findings.

Effectiveness and comparative effectiveness of evidence-based psychotherapies for posttraumatic stress disorder in clinical practice

BACKGROUND

While evidence-based psychotherapy (EBP) for posttraumatic stress disorder (PTSD) is a first-line treatment, its real-world effectiveness is unknown. We compared cognitive processing therapy (CPT) and prolonged exposure (PE) each to an individual psychotherapy comparator group, and CPT to PE in a large national healthcare system.

METHODS

We utilized effectiveness and comparative effectiveness emulated trials using retrospective cohort data from electronic medical records. Participants were veterans with PTSD initiating mental healthcare (N = 265 566). The primary outcome was PTSD symptoms measured by the PTSD Checklist (PCL) at baseline and 24-week follow-up. Emulated trials were comprised of 'person-trials,' representing 112 discrete 24-week periods of care (10/07-6/17) for each patient. Treatment group comparisons were made with generalized linear models, utilizing propensity score matching and inverse probability weights to account for confounding, selection, and non-adherence bias.

RESULTS

There were 636 CPT person-trials matched to 636 non-EBP person-trials. Completing ⩾8 CPT sessions was associated with a 6.4-point greater improvement on the PCL (95% CI 3.1-10.0). There were 272 PE person-trials matched to 272 non-EBP person-trials. Completing ⩾8 PE sessions was associated with a 9.7-point greater improvement on the PCL (95% CI 5.4-13.8). There were 232 PE person-trials matched to 232 CPT person-trials. Those completing ⩾8 PE sessions had slightly greater, but not statistically significant, improvement on the PCL (8.3-points; 95% CI 5.9-10.6) than those completing ⩾8 CPT sessions (7.0-points; 95% CI 5.5-8.5).

CONCLUSIONS

PTSD symptom improvement was similar and modest for both EBPs. Although EBPs are helpful, research to further improve PTSD care is critical.

Systematic pan-cancer analysis of mutation-treatment interactions using large real-world clinicogenomics data

Quantifying the effectiveness of different cancer therapies in patients with specific tumor mutations is critical for improving patient outcomes and advancing precision medicine. Here we perform a large-scale computational analysis of 40,903 US patients with cancer who have detailed mutation profiles, treatment sequences and outcomes derived from electronic health records. We systematically identify 458 mutations that predict the survival of patients on specific immunotherapies, chemotherapy agents or targeted therapies across eight common cancer types. We further characterize mutation-mutation interactions that impact the outcomes of targeted therapies. This work demonstrates how computational analysis of large real-world data generates insights, hypotheses and resources to enable precision oncology.

Target Trial Emulation for Transparent and Robust Estimation of Treatment Effects for Health Technology Assessment Using Real-World Data: Opportunities and Challenges

Evidence about the relative effects of new treatments is typically collected in randomised controlled trials (RCTs). In many instances, evidence from RCTs falls short of the needs of health technology assessment (HTA). For example, RCTs may not be able to capture longer-term treatment effects, or include all relevant comparators and outcomes required for HTA purposes. Information routinely collected about patients and the care they receive have been increasingly used to complement RCT evidence on treatment effects. However, such routine (or real-world) data are not collected for research purposes, so investigators have little control over the way patients are selected into the study or allocated to the different treatment groups, introducing biases for example due to selection or confounding. A promising approach to minimise common biases in non-randomised studies that use real-world data (RWD) is to apply design principles from RCTs. This approach, known as 'target trial emulation' (TTE), involves (1) developing the protocol with respect to core study design and analysis components of the hypothetical RCT that would answer the question of interest, and (2) applying this protocol to the RWD so that it mimics the data that would have been gathered for the RCT. By making the 'target trial' explicit, TTE helps avoid common design flaws and methodological pitfalls in the analysis of non-randomised studies, keeping each step transparent and accessible. It provides a coherent framework that embeds existing analytical methods to minimise confounding and helps identify potential limitations of RWD and the extent to which these affect the HTA decision. This paper provides a broad overview of TTE and discusses the opportunities and challenges of using this approach in HTA. We describe the basic principles of trial emulation, outline some areas where TTE using RWD can help complement RCT evidence in HTA, identify potential barriers to its adoption in the HTA setting and highlight some priorities for future work.

Alcohol brief intervention, specialty treatment and drinking outcomes at 12 months: Results from a systematic alcohol screening and brief intervention initiative in adult primary care

BACKGROUND

Alcohol screening, brief intervention and referral to treatment (SBIRT) in adult primary care is an evidence-based, public health strategy to address unhealthy alcohol use, but evidence of effectiveness of alcohol brief intervention (ABI) in real-world implementation is lacking.

METHODS

We fit marginal structural models with inverse probability weighting to estimate the causal effects of ABI on 12-month drinking outcomes using longitudinal electronic health records data for 312,056 adults with a positive screening result for unhealthy drinking between 2014 and 2017 in a large healthcare system that implemented systematic primary care-based SBIRT. We examined effects of ABI with and without adjusting for receipt of specialty alcohol use disorder (AUD) treatment, and whether effects varied by patient demographic characteristics and alcohol use patterns.

RESULTS

Receiving ABI resulted in significantly greater reductions in heavy drinking days (mean difference [95% CI] = -0.26 [-0.45, -0.08]), drinking days per week (-0.04 [-0.07, -0.01]), drinks per drinking day (-0.05 [-0.08, -0.02]) and drinks per week (-0.16 [-0.27, -0.04]). Effects of ABI on 12-month drinking outcomes varied by baseline consumption level, age group and whether patients already had an AUD, with better improvement in those who were drinking at levels exceeding only daily limits, younger, and without an AUD.

CONCLUSIONS

Systematic ABI in adult primary care has the potential to reduce drinking among people with unhealthy drinking considerably on both an individual and population level. More research is needed to help optimize ABI, in particular tailoring it to diverse sub-populations, and studying its long-term public health impact.

The effects of dual antiplatelet therapy (DAPT) adherence on survival in patients undergoing revascularization and the determinants of DAPT adherence

BACKGROUND

The prevalence and burden of coronary heart disease (CHD) has increased substantially in India, accompanied with increasing need for percutaneous coronary interventions (PCI). Although a large government-funded insurance scheme in Maharashtra, India covered the cost of PCI for low-income patients, the high cost of post-PCI treatment, especially Dual Antiplatelet Therapy (DAPT), still caused many patients to prematurely discontinue the secondary prevention. Our study aimed to investigate the effectiveness of DAPT adherence on all-cause mortality among post-PCI patients and explore the potential determinants of DAPT adherence in India.

METHOD

We collected clinical data of 4,595 patients undergoing PCI in 110 participating medical centers in Maharashtra, India from 2012 to 2015 by electronic medical records. We surveyed 2527 adult patients who were under the insurance scheme by telephone interview, usually between 6 to 12 months after their revascularization. Patients reporting DAPT continuation in the telephone survey were categorized as DAPT adherence. The outcome of the interest was all-cause mortality within 1 year after the index procedure. Multivariate Cox proportional hazard (PH) model with adjustment of potential confounders and standardization were used to explore the effects of DAPT adherence on all-cause mortality. We further used a multivariate logistic model to investigate the potential determinants of DAPT adherence.

RESULTS

Out of the 2527 patients interviewed, 2064 patients were included in the analysis, of whom 470 (22.8%) discontinued DAPT prematurely within a year. After adjustment for baseline confounders, DAPT adherence was associated with lower one-year all-cause mortality compared to premature discontinuation (less than 6-month), with an adjusted hazard ratio (HR) of 0.52 (95% Confidence Interval (CI) = (0.36, 0.67)). We also found younger patients (OR per year was 0.99 (0.97, 1.00)) and male (vs. female, OR of 1.30 (0.99, 1.70)) had higher adherence to DAPT at one year as did patients taking antihypertensive medications (vs. non medication, OR of 1.57 (1.25, 1.95)).

CONCLUSION

These findings suggest the protective effects of DAPT adherence on 1-year mortality among post-PCI patients in a low-income setting and indicate younger age, male sex and use of other preventive treatments were predictors of higher DAPT adherence.

The Incidence of SARS-CoV-2 Reinfection in Persons With Naturally Acquired Immunity With and Without Subsequent Receipt of a Single Dose of BNT162b2 Vaccine : A Retrospective Cohort Study

BACKGROUND

There is insufficient evidence regarding the magnitude and durability of protection conferred by a combined effect of naturally acquired immunity after SARS-CoV-2 infection and vaccine-induced immunity.

OBJECTIVE

To compare the incidence rate of SARS-CoV-2 reinfection in previously infected persons to that of previously infected persons who subsequently received a single dose of BNT162b2 messenger RNA vaccine.

DESIGN

A retrospective cohort study emulating a randomized controlled target trial through a series of nested trials.

SETTING

Nationally centralized database of Maccabi Healthcare Services, Israel.

PARTICIPANTS

Persons with documented SARS-CoV-2 infection who did not receive subsequent SARS-CoV-2 vaccination were compared with persons with documented SARS-CoV-2 infection who received a single dose of the BNT162b2 vaccine at least 3 months after infection.

INTERVENTION

Forty-one randomized controlled trials were emulated, in which 107 413 Maccabi Healthcare Services' members aged 16 years and older were eligible for at least 1 trial.

MEASUREMENTS

SARS-CoV-2-related outcomes of infection, symptomatic disease, hospitalization, and death, between 2 March and 13 December 2021.

RESULTS

A statistically significant decreased risk (hazard ratio, 0.18 [95% CI, 0.15 to 0.20]) for reinfection was found among persons who were previously infected and then vaccinated versus those who were previously infected but remained unvaccinated. In addition, there was a decreased risk for symptomatic disease (hazard ratio, 0.24 [CI, 0.20 to 0.29]) among previously infected and vaccinated persons compared with those who were not vaccinated after infection. No COVID-19-related mortality cases were found.

LIMITATION

Hybrid protection against non-Delta variants could not be inferred.

CONCLUSION

Persons previously infected with SARS-CoV-2 gained additional protection against reinfection and COVID-19 from a subsequent single dose of the BNT162b2 vaccine. Nonetheless, even without a subsequent vaccination, reinfection appeared relatively rare.

PRIMARY FUNDING SOURCE

None.

Cohort design and natural language processing to reduce bias in electronic health records research

Electronic health record (EHR) datasets are statistically powerful but are subject to ascertainment bias and missingness. Using the Mass General Brigham multi-institutional EHR, we approximated a community-based cohort by sampling patients receiving longitudinal primary care between 2001-2018 (Community Care Cohort Project [C3PO], n = 520,868). We utilized natural language processing (NLP) to recover vital signs from unstructured notes. We assessed the validity of C3PO by deploying established risk models for myocardial infarction/stroke and atrial fibrillation. We then compared C3PO to Convenience Samples including all individuals from the same EHR with complete data, but without a longitudinal primary care requirement. NLP reduced the missingness of vital signs by 31%. NLP-recovered vital signs were highly correlated with values derived from structured fields (Pearson r range 0.95-0.99). Atrial fibrillation and myocardial infarction/stroke incidence were lower and risk models were better calibrated in C3PO as opposed to the Convenience Samples (calibration error range for myocardial infarction/stroke: 0.012-0.030 in C3PO vs. 0.028-0.046 in Convenience Samples; calibration error for atrial fibrillation 0.028 in C3PO vs. 0.036 in Convenience Samples). Sampling patients receiving regular primary care and using NLP to recover missing data may reduce bias and maximize generalizability of EHR research.

Allopurinol Initiation and All-Cause Mortality Among Patients With Gout and Concurrent Chronic Kidney Disease : A Population-Based Cohort Study

BACKGROUND

Two recent randomized clinical trials of escalating doses of allopurinol for the progression of chronic kidney disease (CKD) reported no benefits but potentially increased risk for death. Whether the risk could occur in patients with gout and concurrent CKD remains unknown.

OBJECTIVE

To examine the relation of allopurinol initiation, allopurinol dose escalation, and achieving target serum urate (SU) level after allopurinol initiation to all-cause mortality in patients with both gout and CKD.

DESIGN

Cohort study.

SETTING

The Health Improvement Network U.K. primary care database (2000 to 2019).

PARTICIPANTS

Patients aged 40 years or older who had gout and concurrent moderate-to-severe CKD.

MEASUREMENTS

The association between allopurinol initiation and all-cause mortality over 5-year follow-up in propensity score (PS)-matched cohorts was examined. Analysis of hypothetical trials were emulated: achieving target SU level (<0.36 mmol/L) versus not achieving target SU level and dose escalation versus no dose escalation for mortality over 5-year follow-up in allopurinol initiators.

RESULTS

Mortality was 4.9 and 5.8 per 100 person-years in 5277 allopurinol initiators and 5277 PS-matched noninitiators, respectively (hazard ratio [HR], 0.85 [95% CI, 0.77 to 0.93]). In the target trial emulation analysis, the HR of mortality for the achieving target SU level group compared with the not achieving target SU level group was 0.87 (CI, 0.75 to 1.01); the HR of mortality for allopurinol in the dose escalation group versus the no dose escalation group was 0.88 (CI, 0.73 to 1.07).

LIMITATION

Residual confounding cannot be ruled out.

CONCLUSION

In this population-based data, neither allopurinol initiation, nor achieving target SU level with allopurinol, nor allopurinol dose escalation was associated with increased mortality in patients with gout and concurrent CKD.

PRIMARY FUNDING SOURCE

Project Program of National Clinical Research Center for Geriatric Disorders.

Effectiveness of Localized Lockdowns in the COVID-19 Pandemic

Nonpharmaceutical interventions, such as social distancing and lockdowns, have been essential to control of the coronavirus disease 2019 (COVID-19) pandemic. In particular, localized lockdowns in small geographic areas have become an important policy intervention for preventing viral spread in cases of resurgence. These localized lockdowns can result in lower social and economic costs compared with larger-scale suppression strategies. Using an integrated data set from Chile (March 3-June 15, 2020) and a novel synthetic control approach, we estimated the effect of localized lockdowns, disentangling its direct and indirect causal effects on transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our results showed that the effects of localized lockdowns are strongly modulated by their duration and are influenced by indirect effects from neighboring geographic areas. Our estimates suggest that extending localized lockdowns can slow down SARS-CoV-2 transmission; however, localized lockdowns on their own are insufficient to control pandemic growth in the presence of indirect effects from contiguous neighboring areas that do not have lockdowns. These results provide critical empirical evidence about the effectiveness of localized lockdowns in interconnected geographic areas.

Musculoskeletal care - at the confluence of data science, sensors, engineering, and computation

Data has always been integral to modern medicine in almost all aspects of patient care and the recent proliferation of data has opened up innumerable opportunities for all the stakeholders in trying to improve the quality of care and health outcomes including quality of life and rehabilitation. Greater usage and adoption of digital technologies have led to the convergence of health data in different forms – clinical, self-reported, electronic health records social media, etc. The application and utilization of patient data set continue to get broadened each day with greater availability and access. These are empowering newer cutting-edge solutions such as connected care and artificial intelligence, 3D printing and real-life mimicking prosthetics. The availability of data at micro and macro levels has the potential to act as a catalyst for personalized care based on behavioral, cultural, genetic, and psychological needs for patients with musculoskeletal disorders. Realistic algorithms coupled with biomarkers which can identify relevant interventions and alert the care providers regarding any deterioration. Although in the nascent stage currently, 3D printing, exoskeletons, and virtual rehabilitation hold tremendous potential of cost-effective, precise interventions for the patients.

The importance of the design of observational studies in comparative effectiveness research: Lessons from the GARFIELD-AF and ORBIT-AF registries

Randomized controlled trials (RCTs) are considered the gold standard for estimating the effectiveness of a treatment. However, in many instances they are impractical to conduct because of time limitations, cost restrictions, or ethical reasons. As a consequence, non-randomized observational studies have an important role in comparative effectiveness and safety research since they can address issues that would not be possible using conventional RCT methodology. Observational studies can be strategically designed to reduce the risk of potential sources of bias by emulating the design principles of an equivalent but ideal randomized trial - the target trial - that would answer the research question of interest. In this article, we review some of the necessary components of observational studies required for valid causal inference within the framework of target trial emulation, so as to avoid common methodological pitfalls of study design. We discuss the assumptions of consistency, time-zero specification, exchangeability and positivity. To illustrate these concepts in a context where existing knowledge is well-established through clinical trials, we evaluate and compare the treatment effects of vitamin K antagonists (VKA) against no VKA (No VKA) on the treatment of atrial fibrillation from two real-world observational studies, namely the GARFIELD-AF and ORBIT-AF registries. Results are compared with those of published RCTs.

OUP accepted manuscript

Aims

Previous studies have found high sodium intake to be associated with increased risks of cardiovascular disease (CVD) and all-cause mortality among individuals with hypertension; findings on the effect of intake among individuals without hypertension have been equivocal. We aimed to compare the risks of incident CVD and all-cause mortality among initiators of sodium-containing acetaminophen with the risk of initiators of non-sodium-containing formulations of the same drug according to the history of hypertension.

Methods and results

Using The Health Improvement Network, we conducted two cohort studies among individuals with and without hypertension. We examined the relation of sodium-containing acetaminophen to the risk of each outcome during 1-year follow-up using marginal structural models with an inverse probability weighting to adjust for time-varying confounders. The outcomes were incident CVD (myocardial infarction, stroke, and heart failure) and all-cause mortality. Among individuals with hypertension (mean age: 73.4 years), 122 CVDs occurred among 4532 initiators of sodium-containing acetaminophen (1-year risk: 5.6%) and 3051 among 146 866 non-sodium-containing acetaminophen initiators (1-year risk: 4.6%). The average weighted hazard ratio (HR) was 1.59 [95% confidence interval (CI) 1.32–1.92]. Among individuals without hypertension (mean age: 71.0 years), 105 CVDs occurred among 5351 initiators of sodium-containing acetaminophen (1-year risk: 4.4%) and 2079 among 141 948 non-sodium-containing acetaminophen initiators (1-year risk: 3.7%), with an average weighted HR of 1.45 (95% CI 1.18–1.79). Results of specific CVD outcomes and all-cause mortality were similar.

Conclusion

The initiation of sodium-containing acetaminophen was associated with increased risks of CVD and all-cause mortality among individuals with or without hypertension. Our findings suggest that individuals should avoid unnecessary excessive sodium intake through sodium-containing acetaminophen use.

Metformin and primary bone cancer risk in Taiwanese patients with type 2 diabetes mellitus

BACKGROUND

The effect of metformin on primary bone cancer risk has not been researched. This retrospective cohort study investigated the risk of primary bone cancer between metformin initiators and non-metformin initiators in patients with type 2 diabetes mellitus.

METHODS

A total of 673,532 patients with newly diagnosed type 2 diabetes mellitus and had been prescribed antidiabetic drugs for 2 or more times during 1999-2009 were enrolled from Taiwan's National Health Insurance. Metformin initiators and non-metformin initiators were defined according to the prescriptions of antidiabetic drugs within the initial 12 months. The patients were then followed up until December 31, 2011 for the incidence of primary bone cancer. Cox regression incorporated with the inverse probability of treatment-weighting using propensity scores was used to estimate hazard ratios in intention-to-treat and per-protocol analyses.

RESULTS

In the intention-to-treat analysis, the respective incidence rates were 10.56 and 12.90 per 100,000 person-years in 453,532 metformin initiators and 220,000 non-metformin initiators and the hazard ratio for initiators versus non-initiators was 0.830 (95% confidence interval 0.686-1.004, P-value = 0.0551). In the per-protocol analysis, the incidence rates were 7.58 and 11.77 per 100,000 person-years, respectively, and the hazard ratio was 0.615 (95% confidence interval 0.468-0.808, P-value = 0.0005). Subgroup analyses with regards to sex and age (<60 and ≥60 years) showed that the significantly lower risk associated with metformin use was only observed in men aged ≥60 years in the per-protocol analysis.

CONCLUSIONS

A significantly lower risk of primary bone cancer can be observed in patients with type 2 diabetes mellitus who adhere to metformin treatment. This benefit can only be observed in men aged ≥60 years.

Weight Change and the Onset of Cardiovascular Diseases: Emulating Trials Using Electronic Health Records

BACKGROUND

Cross-sectional measures of body mass index (BMI) are associated with cardiovascular disease (CVD) incidence, but less is known about whether weight change affects the risk of CVD.

METHODS

We estimated the effect of 2-y weight change interventions on 7-y risk of CVD (CVD death, myocardial infarction, stroke, hospitalization from coronary heart disease, and heart failure) by emulating hypothetical interventions using electronic health records. We identified 138,567 individuals with 45-69 years of age without chronic disease in England from 1998 to 2016. We performed pooled logistic regression, using inverse-probability weighting to adjust for baseline and time-varying confounders. We categorized each individual into a weight loss, maintenance, or gain group.

RESULTS

Among those of normal weight, both weight loss [risk difference (RD) vs. weight maintenance = 1.5% (0.3% to 3.0%)] and gain [RD = 1.3% (0.5% to 2.2%)] were associated with increased risk for CVD compared with weight maintenance. Among overweight individuals, we observed moderately higher risk of CVD in both the weight loss [RD = 0.7% (-0.2% to 1.7%)] and the weight gain group [RD = 0.7% (-0.1% to 1.7%)], compared with maintenance. In the obese, those losing weight showed lower risk of coronary heart disease [RD = -1.4% (-2.4% to -0.6%)] but not of stroke. When we assumed that chronic disease occurred 1-3 years before the recorded date, estimates for weight loss and gain were attenuated among overweight individuals; estimates for loss were lower among obese individuals.

CONCLUSION

Among individuals with obesity, the weight-loss group had a lower risk of coronary heart disease but not of stroke. Weight gain was associated with increased risk of CVD across BMI groups. See video abstract at, http://links.lww.com/EDE/B838.

Estimating the effect of nutritional interventions using observational data: the American Heart Association's 2020 Dietary Goals and mortality

BACKGROUND

Because randomized trials of sustained dietary changes are sometimes impractical for long-term outcomes, the explicit emulation of a (hypothetical) target trial using observational data may be an important tool for nutritional epidemiology.

OBJECTIVES

We describe a methodological approach that aims to emulate a target trial of dietary interventions sustained over many years using data from observational cohort studies.

METHODS

We estimated the 20-y risk of all-cause mortality under the sustained implementation of the food-based goals of the American Heart Association (AHA) 2020 using data from 3 prospective observational studies of US men [Health Professionals Follow-up Study (HPFS)] and women [Nurses' Health Study (NHS) and Nurses' Health Study II (NHS II)]. We applied the parametric g-formula to estimate the 20-y mortality risk under a dietary intervention and under no dietary intervention.

RESULTS

There were 165,411 participants who met the eligibility criteria. The mean age at baseline was 57.4 y (range, 43-82 y) in the HPFS, 52.4 y (range, 39-66 y) in the NHS, and 40.2 y (range, 30-50 y) in the NHS II. During 20 y of follow-up, 13,241 participants died. The estimated 20-y mortality risks under a dietary intervention versus no intervention were 21.9% compared with 25.8%, respectively, in the HPFS (risk difference, -3.9%; 95% CI: -4.9% to -3.2%); 10.0% compared with 12.6%, respectively, in the NHS (risk difference, -2.6%; 95% CI: -3.1% to -1.8%); and 2.1% compared with 2.5%, respectively, in the NHS II (risk difference, -0.35%; 95% CI: -0.56% to -0.09%). The corresponding risk ratios were 0.85 (95% CI: 0.81-0.88) in the HPFS, 0.79 (95% CI: 0.75-0.85) in the NHS, and 0.86 (95% CI: 0.78-0.96) in the NHS II.

CONCLUSIONS

We estimated that adherence to the food-based AHA 2020 Dietary Goals starting in midlife may reduce the 20-y risk of mortality.

Emulating Target Trials to Improve Causal Inference From Agent-Based Models

Agent-based models are a key tool for investigating the emergent properties of population health settings, such as infectious disease transmission, where the exposure often violates the key "no interference" assumption of traditional causal inference under the potential outcomes framework. Agent-based models and other simulation-based modeling approaches have generally been viewed as a separate knowledge-generating paradigm from the potential outcomes framework, but this can lead to confusion about how to interpret the results of these models in real-world settings. By explicitly incorporating the target trial framework into the development of an agent-based or other simulation model, we can clarify the causal parameters of interest, as well as make explicit the assumptions required for valid causal effect estimation within or between populations. In this paper, we describe the use of the target trial framework for designing agent-based models when the goal is estimation of causal effects in the presence of interference, or spillover.

An emulated target trial analysis based on Medicare data suggested non-inferiority of Dabigatran versus Rivaroxaban

OBJECTIVES

Rivaroxaban and Dabigatran were the first two non-vitamin K antagonist oral anticoagulants (NOACs) for preventing stroke among non-valvular Atrial Fibrillation patients. This article aimed to evaluate the relative efficacy and safety of Rivaroxaban versus Dabigatran.

STUDY DESIGN AND SETTING

An emulated target trial analysis was conducted based on Medicare, in which we constructed three "randomized clinical trials" with well-defined inclusion/exclusion criteria, treatment regimens, and analysis procedures. We analyzed the individual trials, examined temporal variations, and generated unified results via pooled analysis.

RESULTS

With a two-year data collection window (2012-2013), 70,129 subjects were enrolled in the three emulated trials, with 36,269 and 34,089 in the Rivaroxaban and Dabigatran arms, respectively. Dabigatran (the reference group for hazard ratio - HR) was superior regarding time to any primary event (including ischemic stroke, other thromboembolic events, major bleeding, and death; HR 1.232, P-value 0.0025), major bleeding (HR 1.187, P-value <0.0001), and mortality (HR 1.488, P-value <0.0001). Differences regarding stroke and other thromboembolic events were not significant.

CONCLUSION

Dabigatran was found as superior for the Medicare patients with multiple chronic conditions. Temporal variations, which had been largely neglected in the literature, were observed. This study may provide new insight into treating AF with NOACs.

Prone Positioning and Survival in Mechanically Ventilated Patients With Coronavirus Disease 2019-Related Respiratory Failure

OBJECTIVES

Therapies for patients with respiratory failure from coronavirus disease 2019 are urgently needed. Early implementation of prone positioning ventilation improves survival in patients with acute respiratory distress syndrome, but studies examining the effect of proning on survival in patients with coronavirus disease 2019 are lacking. Our objective was to estimate the effect of early proning initiation on survival in patients with coronavirus disease 2019-associated respiratory failure.

DESIGN

Data were derived from the Study of the Treatment and Outcomes in Critically Ill Patients with coronavirus disease 2019, a multicenter cohort study of critically ill adults with coronavirus disease 2019 admitted to 68 U.S. hospitals. Using these data, we emulated a target trial of prone positioning ventilation by categorizing mechanically ventilated hypoxemic (ratio of Pao2 over the corresponding Fio2 ≤ 200 mm Hg) patients as having been initiated on proning or not within 2 days of ICU admission. We fit an inverse probability-weighted Cox model to estimate the mortality hazard ratio for early proning versus no early proning. Patients were followed until death, hospital discharge, or end of follow-up.

SETTING

ICUs at 68 U.S. sites.

PATIENTS

Critically ill adults with laboratory-confirmed coronavirus disease 2019 receiving invasive mechanical ventilation with ratio of Pao2 over the corresponding Fio2 less than or equal to 200 mm Hg.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Among 2,338 eligible patients, 702 (30.0%) were proned within the first 2 days of ICU admission. After inverse probability weighting, baseline and severity of illness characteristics were well-balanced between groups. A total of 1,017 (43.5%) of the 2,338 patients were discharged alive, 1,101 (47.1%) died, and 220 (9.4%) were still hospitalized at last follow-up. Patients proned within the first 2 days of ICU admission had a lower adjusted risk of death compared with nonproned patients (hazard ratio, 0.84; 95% CI, 0.73-0.97).

CONCLUSIONS

In-hospital mortality was lower in mechanically ventilated hypoxemic patients with coronavirus disease 2019 treated with early proning compared with patients whose treatment did not include early proning.

Association of Real-time Continuous Glucose Monitoring With Glycemic Control and Acute Metabolic Events Among Patients With Insulin-Treated Diabetes

IMPORTANCE

Continuous glucose monitoring (CGM) is recommended for patients with type 1 diabetes; observational evidence for CGM in patients with insulin-treated type 2 diabetes is lacking.

OBJECTIVE

To estimate clinical outcomes of real-time CGM initiation.

DESIGN, SETTING, AND PARTICIPANTS

Exploratory retrospective cohort study of changes in outcomes associated with real-time CGM initiation, estimated using a difference-in-differences analysis. A total of 41 753 participants with insulin-treated diabetes (5673 type 1; 36 080 type 2) receiving care from a Northern California integrated health care delivery system (2014-2019), being treated with insulin, self-monitoring their blood glucose levels, and having no prior CGM use were included.

EXPOSURES

Initiation vs noninitiation of real-time CGM (reference group).

MAIN OUTCOMES AND MEASURES

Ten end points measured during the 12 months before and 12 months after baseline: hemoglobin A1c (HbA1c); hypoglycemia (emergency department or hospital utilization); hyperglycemia (emergency department or hospital utilization); HbA1c levels lower than 7%, lower than 8%, and higher than 9%; 1 emergency department encounter or more for any reason; 1 hospitalization or more for any reason; and number of outpatient visits and telephone visits.

RESULTS

The real-time CGM initiators included 3806 patients (mean age, 42.4 years [SD, 19.9 years]; 51% female; 91% type 1, 9% type 2); the noninitiators included 37 947 patients (mean age, 63.4 years [SD, 13.4 years]; 49% female; 6% type 1, 94% type 2). The prebaseline mean HbA1c was lower among real-time CGM initiators than among noninitiators, but real-time CGM initiators had higher prebaseline rates of hypoglycemia and hyperglycemia. Mean HbA1c declined among real-time CGM initiators from 8.17% to 7.76% and from 8.28% to 8.19% among noninitiators (adjusted difference-in-differences estimate, -0.40%; 95% CI, -0.48% to -0.32%; P < .001). Hypoglycemia rates declined among real-time CGM initiators from 5.1% to 3.0% and increased among noninitiators from 1.9% to 2.3% (difference-in-differences estimate, -2.7%; 95% CI, -4.4% to -1.1%; P = .001). There were also statistically significant differences in the adjusted net changes in the proportion of patients with HbA1c lower than 7% (adjusted difference-in-differences estimate, 9.6%; 95% CI, 7.1% to 12.2%; P < .001), lower than 8% (adjusted difference-in-differences estimate, 13.1%; 95% CI, 10.2% to 16.1%; P < .001), and higher than 9% (adjusted difference-in-differences estimate, -7.1%; 95% CI, -9.5% to -4.6%; P < .001) and in the number of outpatient visits (adjusted difference-in-differences estimate, -0.4; 95% CI, -0.6 to -0.2; P < .001) and telephone visits (adjusted difference-in-differences estimate, 1.1; 95% CI, 0.8 to 1.4; P < .001). Initiation of real-time CGM was not associated with statistically significant changes in rates of hyperglycemia, emergency department visits for any reason, or hospitalizations for any reason.

CONCLUSIONS AND RELEVANCE

In this retrospective cohort study, insulin-treated patients with diabetes selected by physicians for real-time continuous glucose monitoring compared with noninitiators had significant improvements in hemoglobin A1c and reductions in emergency department visits and hospitalizations for hypoglycemia, but no significant change in emergency department visits or hospitalizations for hyperglycemia or for any reason. Because of the observational study design, findings may have been susceptible to selection bias.

A Trial Emulation Approach for Policy Evaluations with Group-level Longitudinal Data

To limit the spread of the novel coronavirus, governments across the world implemented extraordinary physical distancing policies, such as stay-at-home orders. Numerous studies aim to estimate the effects of these policies. Many statistical and econometric methods, such as difference-in-differences, leverage repeated measurements, and variation in timing to estimate policy effects, including in the COVID-19 context. Although these methods are less common in epidemiology, epidemiologic researchers are well accustomed to handling similar complexities in studies of individual-level interventions. Target trial emulation emphasizes the need to carefully design a nonexperimental study in terms of inclusion and exclusion criteria, covariates, exposure definition, and outcome measurement-and the timing of those variables. We argue that policy evaluations using group-level longitudinal ("panel") data need to take a similar careful approach to study design that we refer to as policy trial emulation. This approach is especially important when intervention timing varies across jurisdictions; the main idea is to construct target trials separately for each treatment cohort (states that implement the policy at the same time) and then aggregate. We present a stylized analysis of the impact of state-level stay-at-home orders on total coronavirus cases. We argue that estimates from panel methods-with the right data and careful modeling and diagnostics-can help add to our understanding of many policies, though doing so is often challenging.

Thrombosis, Bleeding, and the Observational Effect of Early Therapeutic Anticoagulation on Survival in Critically Ill Patients With COVID-19

BACKGROUND

Hypercoagulability may be a key mechanism of death in patients with coronavirus disease 2019 (COVID-19).

OBJECTIVE

To evaluate the incidence of venous thromboembolism (VTE) and major bleeding in critically ill patients with COVID-19 and examine the observational effect of early therapeutic anticoagulation on survival.

DESIGN

In a multicenter cohort study of 3239 critically ill adults with COVID-19, the incidence of VTE and major bleeding within 14 days after intensive care unit (ICU) admission was evaluated. A target trial emulation in which patients were categorized according to receipt or no receipt of therapeutic anticoagulation in the first 2 days of ICU admission was done to examine the observational effect of early therapeutic anticoagulation on survival. A Cox model with inverse probability weighting to adjust for confounding was used.

SETTING

67 hospitals in the United States.

PARTICIPANTS

Adults with COVID-19 admitted to a participating ICU.

MEASUREMENTS

Time to death, censored at hospital discharge, or date of last follow-up.

RESULTS

Among the 3239 patients included, the median age was 61 years (interquartile range, 53 to 71 years), and 2088 (64.5%) were men. A total of 204 patients (6.3%) developed VTE, and 90 patients (2.8%) developed a major bleeding event. Independent predictors of VTE were male sex and higher D-dimer level on ICU admission. Among the 2809 patients included in the target trial emulation, 384 (11.9%) received early therapeutic anticoagulation. In the primary analysis, during a median follow-up of 27 days, patients who received early therapeutic anticoagulation had a similar risk for death as those who did not (hazard ratio, 1.12 [95% CI, 0.92 to 1.35]).

LIMITATION

Observational design.

CONCLUSION

Among critically ill adults with COVID-19, early therapeutic anticoagulation did not affect survival in the target trial emulation.

PRIMARY FUNDING SOURCE

None.

Evaluating eligibility criteria of oncology trials using real-world data and AI

There is a growing focus on making clinical trials more inclusive but the design of trial eligibility criteria remains challenging^1-3. Here we systematically evaluate the effect of different eligibility criteria on cancer trial populations and outcomes with real-world data using the computational framework of Trial Pathfinder. We apply Trial Pathfinder to emulate completed trials of advanced non-small-cell lung cancer using data from a nationwide database of electronic health records comprising 61,094 patients with advanced non-small-cell lung cancer. Our analyses reveal that many common criteria, including exclusions based on several laboratory values, had a minimal effect on the trial hazard ratios. When we used a data-driven approach to broaden restrictive criteria, the pool of eligible patients more than doubled on average and the hazard ratio of the overall survival decreased by an average of 0.05. This suggests that many patients who were not eligible under the original trial criteria could potentially benefit from the treatments. We further support our findings through analyses of other types of cancer and patient-safety data from diverse clinical trials. Our data-driven methodology for evaluating eligibility criteria can facilitate the design of more-inclusive trials while maintaining safeguards for patient safety.

An Emulation of Randomized Trials of Administrating Antipsychotics in PTSD Patients for Outcomes of Suicide-Related Events

Post-traumatic stress disorder (PTSD) is a prevalent mental disorder marked by psychological and behavioral changes. Currently, there is no consensus of preferred antipsychotics to be used for the treatment of PTSD. We aim to discover whether certain antipsychotics have decreased suicide risk in the PTSD population, as these patients may be at higher risk. A total of 38,807 patients were identified with a diagnosis of PTSD through the ICD9 or ICD10 codes from January 2004 to October 2019. An emulation of randomized clinical trials was conducted to compare the outcomes of suicide-related events (SREs) among PTSD patients who ever used one of eight individual antipsychotics after the diagnosis of PTSD. Exclusion criteria included patients with a history of SREs and a previous history of antipsychotic use within one year before enrollment. Eligible individuals were assigned to a treatment group according to the antipsychotic initiated and followed until stopping current treatment, switching to another same class of drugs, death, or loss to follow up. The primary outcome was to identify the frequency of SREs associated with each antipsychotic. SREs were defined as ideation, attempts, and death by suicide. Pooled logistic regression methods with the Firth option were conducted to compare two drugs for their outcomes using SAS version 9.4 (SAS Institute, Cary, NC, USA). The results were adjusted for baseline characteristics and post-baseline, time-varying confounders. A total of 5294 patients were eligible for enrollment with an average follow up of 7.86 months. A total of 157 SREs were recorded throughout this study. Lurasidone showed a statistically significant decrease in SREs when compared head to head to almost all the other antipsychotics: aripiprazole, haloperidol, olanzapine, quetiapine, risperidone, and ziprasidone (p < 0.0001 and false discovery rate-adjusted p value < 0.0004). In addition, olanzapine was associated with higher SREs than quetiapine and risperidone, and ziprasidone was associated with higher SREs than risperidone. The results of this study suggest that certain antipsychotics may put individuals within the PTSD population at an increased risk of SREs, and that careful consideration may need to be taken when prescribed.

Association of a Shortened Duration of Adjuvant Chemotherapy With Overall Survival Among Individuals With Stage III Colon Cancer

IMPORTANCE

Several real-world oncology studies have produced findings that contradict those from randomized clinical trials. Such disparities may be associated with methodological shortcomings.

OBJECTIVE

To examine the association between a shortened duration of adjuvant chemotherapy among individuals with stage III colon cancer using real-world data.

DESIGN, SETTING, AND PARTICIPANTS

This comparative effectiveness study included individuals diagnosed with stage III colon cancer between January 2004 and December 2015 who initiated adjuvant chemotherapy at oncology clinics within the province of Alberta, Canada. Patients were identified through record linkage of various administrative databases and were followed up until September 2017. Eligibility criteria were modeled after those used in the International Duration Evaluation of Adjuvant (IDEA) trial. A target trial emulation and naive observational analysis were conducted. Results from both cohorts were benchmarked against findings from the IDEA trial. Data analysis was conducted from March to December 2020.

EXPOSURE

A shortened duration of adjuvant 5-fluorouracil/leucovorin plus oxaliplatin (FOLFOX) or capecitabine plus oxaliplatin (CAPOX) chemotherapy, defined as 3 to 5 months of treatment vs 6 months.

MAIN OUTCOMES AND MEASURES

Overall survival assessed via vital statistics. The per-protocol hazard ratio (HR) was estimated using a weighted pooled logistic regression model. Subgroup analyses were conducted by treatment regimen (ie, FOLFOX vs CAPOX) and cancer stage (ie, T1-3 and N1 vs T4 or N2).

RESULTS

From an initial cohort of 3086 patients, 485 (16%) were eligible for inclusion in the target trial analysis. The median age was 59 years (range, 19-81 years), and 230 (47%) were women. The maximum follow-up was 11.6 years. Median overall survival was not reached. A total of 90 patients (19%) died. The 5-year Kaplan Meier overall survival estimate was 0.79 (95% CI, 0.75-0.84). Estimates from the trial emulation were similar to those from the IDEA trial. For example, a shortened duration of adjuvant chemotherapy was not associated with overall survival among patients prescribed CAPOX in the IDEA trial (HR, 0.96; 95% CI, 0.85-1.08) or in the trial emulation (HR, 0.96; 95% CI, 0.43-2.14). In contrast, the naive observational analysis suggested that a shortened duration of CAPOX was significantly associated with worse survival (HR, 3.33; 95% CI, 1.04-10.65).

CONCLUSIONS AND RELEVANCE

In this study, the explicit emulation of a target trial better approximated results from an analogous well-conducted randomized clinical trial.

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

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

Comparative Effectiveness of Renin-Angiotensin System Inhibitors and Calcium Channel Blockers in Individuals With Advanced CKD: A Nationwide Observational Cohort Study

RATIONALE & OBJECTIVE

It is unknown whether initiating renin-angiotensin system (RAS) inhibitor therapy in patients with advanced chronic kidney disease (CKD) is superior to alternative antihypertensive agents such as calcium channel blockers (CCBs). We compared the risks for kidney replacement therapy (KRT), mortality, and major adverse cardiovascular events (MACE) in patients with advanced CKD in routine nephrology practice who were initiating either RAS inhibitor or CCB therapy.

STUDY DESIGN

Observational study in the Swedish Renal Registry, 2007 to 2017.

SETTINGS & PARTICIPANTS

2,458 new users of RAS inhibitors and 2,345 CCB users with estimated glomerular filtration rates<30mL/min/1.73m² (CKD G4-G5 without KRT) who were being followed up by a nephrologist. As a positive control cohort, new users of the same drugs with CKD G3 (estimated glomerular filtration rate, 30-60mL/min/1.73m²) were evaluated.

EXPOSURES

RAS inhibitor versus CCB therapy initiation.

OUTCOME

Initiation of KRT (maintenance dialysis or transplantation), all-cause mortality, and MACE (composite of cardiovascular death, myocardial infarction, or stroke).

ANALYTICAL APPROACH

HRs with 95% CIs were estimated using propensity score-weighted Cox proportional hazards regression adjusting for demographic, clinical, and laboratory covariates.

RESULTS

Median age was 74 years, 38% were women, and median follow-up was 4.1 years. After propensity score weighting, there was significantly lower risk for KRT after new use of RAS inhibitors compared with new use of CCBs (adjusted HR, 0.79 [95% CI, 0.69-0.89]) but similar risks for mortality (adjusted HR, 0.97 [95% CI, 0.88-1.07]) and MACE (adjusted HR, 1.00 [95% CI, 0.88-1.15]). Results were consistent across subgroups and in as-treated analyses. The positive control cohort of patients with CKD G3 showed similar KRT risk reduction (adjusted HR, 0.67 [95% CI, 0.56-0.80]) with RAS inhibitor therapy compared with CCBs.

LIMITATIONS

Potential confounding by indication.

CONCLUSIONS

Our findings provide evidence from real-world clinical practice that initiation of RAS inhibitor therapy compared with CCBs may confer kidney benefits among patients with advanced CKD, with similar cardiovascular protection.

Evaluating the impact of the Bolsa Familia conditional cash transfer program on premature cardiovascular and all-cause mortality using the 100 million Brazilian cohort: a natural experiment study protocol

INTRODUCTION

Brazil's Bolsa Familia Program (BFP) is the world's largest conditional cash transfer scheme. We shall use a large cohort of applicants for different social programmes to evaluate the effect of BFP receipt on premature all-cause and cardiovascular mortality.

METHODS AND ANALYSIS

We will identify BFP recipients and non-recipients among new applicants from 2004 to 2015 in the 100 Million Brazilian Cohort, a database of 114 million individuals containing sociodemographic and mortality information of applicants to any Brazilian social programme. For individuals applying from 2011, when we have better recorded income data, we shall compare premature (age 30-69) cardiovascular and all-cause mortality among BFP recipients and non-recipients using regression discontinuity design (RDD) with household monthly per capita income as the forcing variable. Effects will be estimated using survival models accounting for individuals follow-up. To test the sensitivity of our findings, we will estimate models with different bandwidths, include potential confounders as covariates in the survival models, and restrict our data to locations with the most reliable data. In addition, we will estimate the effect of BFP on studied outcomes using propensity score risk-set matching, separately for individuals that applied ≤2010 and >2011, allowing comparability with RDD. Analyses will be stratified by geographical region, gender, race/ethnicity and socioeconomic position. We will investigate differential impacts of BFP and the presence of effect modification for a combination of characteristics, including gender and race/ethnicity.

ETHICS AND DISSEMINATION

The study was approved by the ethics committees of Oswaldo Cruz Foundation and the University of Glasgow College of Medicine and Veterinary Life Sciences. The deidentified dataset will be provided to researchers, and data analysis will be performed in a safe computational environment without internet access. Study findings will be published in high quality peer-reviewed research articles. The published results will be disseminated in the social media and to policy-makers.

A trial emulation approach for policy evaluations with group-level longitudinal data

To limit the spread of the novel coronavirus, governments across the world implemented extraordinary physical distancing policies, such as stay-at-home orders, and numerous studies aim to estimate their effects. Many statistical and econometric methods, such as difference-in-differences, leverage repeated measurements and variation in timing to estimate policy effects, including in the COVID-19 context. While these methods are less common in epidemiology, epidemiologic researchers are well accustomed to handling similar complexities in studies of individual-level interventions. "Target trial emulation" emphasizes the need to carefully design a non-experimental study in terms of inclusion and exclusion criteria, covariates, exposure definition, and outcome measurement -- and the timing of those variables. We argue that policy evaluations using group-level longitudinal ("panel") data need to take a similar careful approach to study design, which we refer to as "policy trial emulation." This is especially important when intervention timing varies across jurisdictions; the main idea is to construct target trials separately for each "treatment cohort" (states that implement the policy at the same time) and then aggregate. We present a stylized analysis of the impact of state-level stay-at-home orders on total coronavirus cases. We argue that estimates from panel methods -- with the right data and careful modeling and diagnostics -- can help add to our understanding of many policies, though doing so is often challenging.

An Emulation of Randomized Trials of Administrating Benzodiazepines in PTSD Patients for Outcomes of Suicide-Related Events

Benzodiazepines is a class of medications frequently prescribed to patients with post-traumatic stress disorder. Patients with PTSD have a notable increased risk of suicide compared to the general population. These medications have been theorized to increase suicidality and pose a risk when used in this patient population. Previous research has found little utility of using benzodiazepines in the PTSD population. However, benzodiazepines are still commonly prescribed by some clinicians for their symptomatic benefit. This study aims to identify the comparative efficacy of commonly prescribed benzodiazepines including midazolam, lorazepam, alprazolam, clonazepam, diazepam and temazepam in relation to suicide-related behaviors (SRBs). A total of 38,807 patients who had an ICD9 or ICD10 diagnosis of PTSD from January 2004 to October 2019 were identified through an electronic medical record database. Inclusion criteria include patients that initiated one of the above benzodiazepines after PTSD diagnosis. Exclusion criteria include previous history of benzodiazepine usage or history of SRBs within the last year prior to enrollment. For patients enrolled in this study, other concomitant drugs were not limited. The primary outcome was onset of SRBs with each respective benzodiazepine. SRBs were identified as ideation, attempt, or death from suicide. We emulated clinical trials of head-to-head comparison between two drugs by pooled logistic regression methods with the Firth option adjusting for baseline characteristics and post-baseline confounders. A total of 5753 patients were eligible for this study, with an average follow up of 5.82 months. The overall incidence for SRB was 1.51% (87/5753). Head-to-head comparisons identified that patients who received alprazolam had fewer SRBs compared to clonazepam (p = 0.0351) and lorazepam (p = 0.0373), and patients taking midazolam experienced fewer relative incidences of SRBs when compared to lorazepam (p = 0.0021) and clonazepam (p = 0.0297). After adjusting for the false discovery rate (FDR), midazolam still had fewer SRBs compared to lorazepam (FDR-adjusted p value = 0.0315). Certain benzodiazepines may provide a reduced risk of development of SRBs, suggesting careful consideration when prescribing benzodiazepines to the PTSD population.

Delayed Denosumab Injections and Fracture Risk Among Patients With Osteoporosis : A Population-Based Cohort Study

BACKGROUND

Denosumab is effective for osteoporosis, but discontinuation leads to rapid reversal of its therapeutic effect.

OBJECTIVE

To estimate the risk for fracture among users of denosumab who delayed subsequent doses compared with users who received doses on time.

DESIGN

Population-based cohort study.

SETTING

The Health Improvement Network U.K. primary care database, 2010 to 2019.

PATIENTS

Persons aged 45 years or older who initiated denosumab therapy for osteoporosis.

MEASUREMENTS

Observational data were used to emulate an analysis of a hypothetical trial with 3 dosing intervals: subsequent denosumab injection given within 4 weeks after the recommended date ("on time"), delay by 4 to 16 weeks ("short delay"), and delay by more than 16 weeks ("long delay"). The primary outcome was a composite of all fracture types at 6 months after the recommended date. Secondary outcomes were major osteoporotic fracture, vertebral fracture, hip fracture, and nonvertebral fracture.

RESULTS

Investigators identified 2594 patients initiating denosumab therapy. The risk for composite fracture over 6 months was 27.3 in 1000 for on-time dosing, 32.2 in 1000 for short delay, and 42.4 in 1000 for long delay. Compared with on-time injections, short delay had a hazard ratio (HR) for composite fracture of 1.03 (95% CI, 0.63 to 1.69) and long delay an HR of 1.44 (CI, 0.96 to 2.17) (P for trend = 0.093). For vertebral fractures, short delay had an HR of 1.48 (CI, 0.58 to 3.79) and long delay an HR of 3.91 (CI, 1.62 to 9.45).

LIMITATION

Dosing schedules were not randomly assigned.

CONCLUSION

Although delayed administration of subsequent denosumab doses by more than 16 weeks is associated with increased risk for vertebral fracture compared with on-time dosing, evidence is insufficient to conclude that fracture risk is increased at other anatomical sites with long delay.

PRIMARY FUNDING SOURCE

National Clinical Research Center for Orthopedics, Sports Medicine & Rehabilitation.