Instrumental variable analysis in the presence of unmeasured confounding

Assessing the performance of physician's prescribing preference as an instrumental variable in comparative effectiveness research with moderate and small sample sizes: a simulation study

Aim: This simulation study is to assess the utility of physician's prescribing preference (PPP) as an instrumental variable for moderate and smaller sample sizes. Materials & methods: We designed a simulation study to imitate a comparative effectiveness research under different sample sizes. We compare the performance of instrumental variable (IV) and non-IV approaches using two-stage least squares (2SLS) and ordinary least squares (OLS) methods, respectively. Further, we test the performance of different forms of proxies for PPP as an IV. Results: The percent bias of 2SLS is around approximately 20%, while the percent bias of OLS is close to 60%. The sample size is not associated with the level of bias for the PPP IV approach. Conclusion: Irrespective of sample size, the PPP IV approach leads to less biased estimates of treatment effectiveness than OLS adjusting for known confounding only. Particularly for smaller sample sizes, we recommend constructing PPP from long prescribing histories to improve statistical power.

Instrumental Variable Analysis of Racial Discrimination and Blood Pressure in a Sample of Young Adults

Racial inequities in blood pressure levels have been extensively documented. Experiences of racial discrimination could explain some of this disparity, although findings from previous studies have been inconsistent. To address limitations of prior literature, including measurement error, we implemented instrumental variable analysis to assess the relationship between racial discrimination in institutional settings and blood pressure. Using data from 3,876 Black and White adults with an average age of 32 years from examination 4 (1992-1993) of the Coronary Artery Risk Development in Young Adults Study, our primary analysis examined the relationship between self-reported experiences of racial discrimination in institutional settings and blood pressure using reflectance meter measurement of skin color as an instrument. Findings suggested that an increase in experiences of racial discrimination was associated with higher systolic and diastolic blood pressure (β = 2.23 mm Hg (95% confidence interval: 1.85, 2.61) and β = 1.31 (95% confidence interval: 1.00, 1.62), respectively). Our instrumental variable estimates suggest that experiences of racial discrimination within institutional settings contribute to racial inequities in elevated blood pressure and cardiovascular disease outcomes in a relatively young cohort of adults and may yield clinically relevant differences in cardiovascular health over the life course.

Dealing with confounding in observational studies: A scoping review of methods evaluated in simulation studies with single-point exposure

The aim of this article was to perform a scoping review of methods available for dealing with confounding when analyzing the effect of health care treatments with single-point exposure in observational data. We aim to provide an overview of methods and their performance assessed by simulation studies indexed in PubMed. We searched PubMed for simulation studies published until January 2021. Our search was restricted to studies evaluating binary treatments and binary and/or continuous outcomes. Information was extracted on the methods' assumptions, performance, and technical properties. Of 28,548 identified references, 127 studies were eligible for inclusion. Of them, 84 assessed 14 different methods (ie, groups of estimators that share assumptions and implementation) for dealing with measured confounding, and 43 assessed 10 different methods for dealing with unmeasured confounding. Results suggest that there are large differences in performance between methods and that the performance of a specific method is highly dependent on the estimator. Furthermore, the methods' assumptions regarding the specific data features also substantially influence the methods' performance. Finally, the methods result in different estimands (ie, target of inference), which can even vary within methods. In conclusion, when choosing a method to adjust for measured or unmeasured confounding it is important to choose the most appropriate estimand, while considering the population of interest, data structure, and whether the plausibility of the methods' required assumptions hold.

SNPs in lncRNA KCNQ1OT1 Modulate Its Expression and Confer Susceptibility to Salt Sensitivity of Blood Pressure in a Chinese Han Population

Long noncoding RNA (lncRNA) plays an important role in cardiovascular diseases, but the involvement of lncRNA in salt sensitivity of blood pressure (SSBP) is not well-known. We aimed to explore the association of sixteen single-nucleotide polymorphisms (SNPs) in five lncRNA genes (KCNQOT1, lnc-AGAP1-8:1, lnc-IGSF3-1:1, etc.) with their expression and susceptibility to SSBP. A two-stage association study was conducted among 2057 individuals. Quantified expression of the lncRNA was detected using real-time PCR. Genotyping was accomplished using the MassARRAY System. The expression quantitative tra2it loci test and the generalized linear model were utilized to explore the function of SNPs. One-sample Mendelian randomization was used to study the causal relationship between KCNQOT1 and SSBP. Significant effects were observed in KCNQ1OT1 expressions on the SSBP phenotype (p < 0.05). Rs10832417 and rs3782064 in KCNQ1OT1 may influence the secondary structure, miRNA binding, and expression of KCNQ1OT1. Rs10832417 and rs3782064 in KCNQ1OT1 were identified to be associated with one SSBP phenotype after multiple testing corrections and may be mediated by KCNQ1OT1. One-sample Mendelian randomization analyses showed a causal association between KCNQ1OT1 and SSBP. Our findings suggest that rs10832417 and rs3782064 might be associated with a lower risk of SSBP through influencing the KCNQ1OT1 secondary structure and miRNA binding, resulting in changes in KCNQ1OT1 expression.

Toward a better understanding about real-world evidence

BACKGROUND

There has been an interest in real-world evidence (RWE) in recent years. RWE is usually generated from data derived from routine healthcare, such as electronic healthcare records and disease registries. While RWE has many advantages, it is often open to various biases, which may distort results. Appropriate understanding and interpretation are critical to the best use of RWE in healthcare decisions.

METHODS

On the basis of a literature review and empirical research experience, we summarised the concept and methodological framework of RWE, and discussed in detail methodological issues specific to routinely collected healthcare data and observational studies using such data.

RESULTS

RWE is derived from a spectrum of data generated from the real-world setting, using two broad study designs including observational studies and pragmatic clinical trials. Real-world data may usually be collected through routine practice or sometimes actively collected with a research purpose. Observational studies using routinely collected data (RCD) are the most common type of RWE, although they are prone to biases. When planning and implementing RWE studies, coherent working steps are warranted, including definition of a clear and answerable research question, development of a research team, selection of a fit-for-purpose data source, choice of state-of-the-art study design, establishing a database with transparent data processing, performing multiple statistical analysis to control bias, and reporting results in accordance with established guidelines.

CONCLUSIONS

RWE has been mounting over the years. The appropriate interpretation and use of such evidence often warrant adequate understanding about methodology. Researchers and policymakers should be aware of the methodological pitfalls when generating and interpreting RWE.

Regression discontinuity analysis for pharmacovigilance: statin example reflected trial findings showing little evidence of harm

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RDA can be used with routine healthcare data, resulting in findings similar to Randomized controlled trials.

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Application of regression discontinuity analysis (RDA) in epidemiology should include examination of the assumptions.

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RDA should employ sensitivity analyses and negative control analyses.

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RDA should carefully consider choice of model and bandwidth.

Objectives

The study aims to explore the use of regression discontinuity analysis (RDA) to examine effects of prescription of statins on total cholesterol and adverse outcomes (type 2 diabetes, rhabdomyolysis and myopathy, myalgia and myositis, liver disease, CVD, and mortality).

Study Design and Setting

We conducted a prospective cohort study using the Clinical Practice Research Datalink including patients with QRISK scores of 10 to 30 in 2010 to 2013 who were last followed-up in October 2016. Comparing patients with QRISK≥20 and QRISK<20, we explored RDA assumptions, provided proof of concept analyses (total cholesterol as outcome), and investigated the effect of statins prescription on adverse outcomes.

Result

RDA confirmed statin prescription reduced total cholesterol (Mean difference (MD) -1.33 mmol/L, 95%Confidence Interval (CI) -1.93 to -0.73). RDA provided little evidence for adverse effects on diabetes, myalgia and myositis, liver disease, CVD, or mortality. The RDA analysis findings are similar to RCT results. Findings from non-RDA analysis agree with published observational studies.

Conclusion

RDA can be used with large routine clinical datasets to provide evidence on effects of medications which are prescribed according to a threshold. Testable RDA assumptions were satisfied, but confidence intervals were wide, partly due to the low compliance with the prescribing threshold.

Big data registries in spine surgery research: the lurking dangers

Spine surgery research has improved considerably over the last few decades. Its' most recent growth is in large part due to the mounting increase in studies conducted using national databases and registries. With easy access to a large number of patients, the benefit of these registries has become evident. However, as with any research, this type of data must be used responsibly with the appropriate strengths and limitations kept in mind. Inappropriate use of these registries continues to be a growing concern as potentially false or inaccurate conclusions can adversely impact clinical practice. It is, therefore, the author and the readers' responsibility to acknowledge and understand the limitations of this type of data. Knowledge of methodological requirements in the use and analyses of registry data is essential to ensuring quality evidence with proper interpretation.

Analytical methods to assess the impacts of activity-based funding (ABF): a scoping review

BACKGROUND

Activity-Based Funding (ABF) has been implemented across many countries as a means to incentivise efficient hospital care delivery and resource use. Previous reviews have assessed the impact of ABF implementation on a range of outcomes across health systems. However, no comprehensive review of the methods used to generate this evidence has been undertaken. The aim of this review is to identify and assess the analytical methods employed in research on ABF hospital performance outcomes.

METHODS

We conducted a scoping review in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. Five academic databases and reference lists of included studies were used to identify studies assessing the impact of ABF on hospital performance outcomes. Peer-reviewed quantitative studies published between 2000 and 2019 considering ABF implementation outside the U.S. were included. Qualitative studies, policy discussions and commentaries were excluded. Abstracts and full text studies were double screened to ensure consistency. All analytical approaches and their relative strengths and weaknesses were charted and summarised.

RESULTS

We identified 19 studies that assessed hospital performance outcomes from introduction of ABF in England, Korea, Norway, Portugal, Israel, the Netherlands, Canada, Italy, Japan, Belgium, China, and Austria. Quasi-experimental methods were used across most reviewed studies. The most commonly used assessment methods were different forms of interrupted time series analyses. Few studies used difference-in-differences or similar methods to compare outcome changes over time relative to comparator groups. The main hospital performance outcome measures examined were case numbers, length of stay, mortality and readmission.

CONCLUSIONS

Non-experimental study designs continue to be the most widely used method in the assessment of ABF impacts. Quasi-experimental approaches examining the impact of ABF implementation on outcomes relative to comparator groups not subject to the reform should be applied where possible to facilitate identification of effects. These approaches provide a more robust evidence-base for informing future financing reform and policy.

Efficacy and safety of corticosteroids for septic shock in immunocompromised patients: A cohort study from MIMIC

BACKGROUND

Corticosteroids have been widely used as adjunct therapy for septic shock for many decades, but both the efficacy and safety remain unclear. The study was designed to investigate overall benefits and potential risks of corticosteroids in immunocompromised patients with septic shock.

METHODS

The Medical Information Mart for Intensive Care III (MIMIC-III) database was employed to conduct a cohort study. Immunocompromised patients with septic shock were enrolled and categorized by whether exposure to intravenous corticosteroids. Cox Proportional-Hazards models were used to control for confounders and assess the relationship between corticosteroids use and mortality.

RESULTS

A total of 866 patients were enrolled in this study, including 395 in the corticosteroids group and 471 in the non-corticosteroids group. Corticosteroids infusion was not associated with improved 30-day mortality in overall immunocompromised population [34.7% vs 32.1%; adjusted hazard ratio (HR) 1.11, 95% confidence interval (CI) 0.87-1.43, p = 0.37]. The mortality effects were similar in 90-day, 180-day, 1-year and hospital mortality. For the subgroup of patients with metastatic cancer, corticosteroids infusion was associated with a statistically significant increase in the 30-day mortality risk (HR 1.58, 95% CI 1.06-2.37; p = 0.02). Corticosteroids had adverse effects on hemodynamic stability, prolonged ICU and hospital duration, and increased risk of hyperglycemia.

CONCLUSIONS

Corticosteroids therapy for the maintenance of blood pressure was not associated with improved mortality or hemodynamic stability in overall immunocompromised population with septic shock. Future randomized clinical trials are required to validate the effects of corticosteroids for septic shock in the special immunocompromised population.

Long-term use of hydrocodone vs. oxycodone in primary care

BACKGROUND

Hydrocodone and oxycodone are the Schedule II opioids most often prescribed in primary care. Notwithstanding the dangers of prescription opioid use, the likelihood of long-term use with either drug is presently unknown.

METHODS

Using a retrospective cohort design and data from a commerical healthcare claims repository, we compared the likelihood of long-term use of hydrocodone and oxycodone in primary care patients presenting with acute back pain. Treatment was categorized as long-term if the prescription dates spanned ≥90 days from initial prescription to the run-out date of the last prescription, and included ≥120 days' supply or ≥10 fills. Instrumental variable methods and probit regression were used to model the effect of drug choice on long-term use, estimate the average treatment effect, and correct for confounding by indication.

RESULTS

A total of 3,983 patients who were prescribed only hydrocodone or only oxycodone were followed for 270 days in 2016. Long-term opioid use was observed in 320 patients (8%). Controlling for potential confounders including morphine milligram equivalents and dosage, an estimated 12% (95 CI, 10%-14%) treated with hydrocodone transitioned to long-term use vs. 2% (95 CI, 1%-3%) on oxycodone. Among patients who received more than one prescription (n = 1,866), an estimated 23% (95 CI, 19%-26%) treated with hydrocodone transitioned to long-term use vs. 5% (95 CI, 3%-7%) on oxycodone. The difference between drugs was supported in sensitivity and subgroup analyses. Sample selection bias was not detected.

CONCLUSIONS

Long-term use was substantially greater for patients treated with hydrocodone than oxycodone, despite equianalgesia.

Using Mendelian randomisation to assess causality in observational studies

OBJECTIVE

Mendelian randomisation (MR) is a technique that aims to assess causal effects of exposures on disease outcomes. The paper aims to present the main assumptions that underlie MR, the statistical methods used to estimate causal effects and how to account for potential violations of the key assumptions.

METHODS

We discuss the key assumptions that should be satisfied in an MR setting. We list the statistical methodologies used in two-sample MR when summary data are available to estimate causal effects (ie, Wald ratio estimator, inverse-variance weighted and maximum likelihood method) and identify/adjust for potential violations of MR assumptions (ie, MR-Egger regression and weighted Median approach). We also present statistical methods and graphical tools used to evaluate the presence of heterogeneity.

RESULTS

We use as an illustrative example of a published two-sample MR study, investigating the causal association of body mass index with three psychiatric disorders (ie, bipolar disorder, schizophrenia and major depressive disorder). We highlight the importance of assessing the results of all available methods rather than each method alone. We also demonstrate the impact of heterogeneity in the estimation of the causal effects.

CONCLUSIONS

MR is a useful tool to assess causality of risk factors in medical research. Assessment of the key assumptions underlying MR is crucial for a valid interpretation of the results.