Prompt versus Delayed Triple Therapy in COPD: Solutions to Time-Related Biases in Observational Studies.

Background: Recent observational studies have reported that prompt initiation of single-inhaler triple therapy after a COPD exacerbation is more effective than delayed initiation. We show that their study design, by "peeking into the future" to define the timing of treatment initiation, introduces time-related biases, particularly protopathic bias. These biases can be avoided using the "cloning" approach to emulate a randomized trial approach.

Core Concepts in Pharmacoepidemiology: Multi-Database Distributed Data Networks.

Multi-database distributed data networks for post-marketing surveillance of drug safety and effectiveness use two main approaches: common data models (CDMs) and common protocols. Networks such as the U.S.

Target trial emulation of cardiovascular outcome trials of medications used to treat type 2 diabetes using real-world data: a systematic review of observational studies.

Background And Objectives: Cardiovascular outcome trials are mandated by the US Food and Drug Administration to assess the cardiovascular safety of new antidiabetic medications before entering the market. However, these trials often involve highly selective populations and results may not generalize to routine practice.

Methods: Our study aimed to synthesize observational studies to assess the generalizability of cardiovascular outcome trials to routine practice.

Using methods to extend inferences to specific target populations to improve the precision of subgroup analyses.

Objectives: While subgroup analyses are common in epidemiologic research, restriction to subgroup members can yield imprecise estimates. We aimed to demonstrate how methods extending inferences to external targets improve precision of subgroup estimates under the major assumption effects differ between subgroup members and nonmembers due to measured effect measure modifiers (EMMs) and membership is independent of the effect after conditioning on EMMs.

Study Design And Setting: We applied this approach in the Panitumumab Randomized Trial in Combination with Chemotherapy for Metastatic Colorectal Cancer to Determine Efficacy.

Core Concepts in Pharmacoepidemiology: New-User Designs.

In this article, we review the history and key reasons for new-user comparisons in pharmacoepidemiology, highlighting the target trial framework as a unifying framework. We describe three distinct pharmacoepidemiological new-user study designs: (1) new-user versus non-user; (2) active comparator new-user; (i.e.

Variable selection when estimating effects in external target populations.

External validity is an important part of epidemiologic research. To validly estimate effects in specific external target populations using a chosen effect measure (ie, "transport"), some methods require that one account for all effect measure modifiers (EMMs). However, little is known about how including other variables that are not EMMs (ie, non-EMMs) in adjustment sets affects estimates.

Clarifying the causal contrast: An empirical example applying the prevalent new user study design.

Purpose: The prevalent new user design extends the active comparator new user design to include patients switching to a treatment of interest from a comparator. We examined the impact of adding "switchers" to incident new users on the estimated hazard ratio (HR) of hospitalized heart failure.

Methods: Using MarketScan claims data (2000-2014), we estimated HRs of hospitalized heart failure between patients initiating GLP-1 receptor agonists (GLP-1 RA) and sulfonylureas (SU).

Standardizing to specific target populations in distributed networks and multisite pharmacoepidemiologic studies.

Distributed network studies and multisite studies assess drug safety and effectiveness in diverse populations by pooling information. Targeting groups of clinical or policy interest (including specific sites or site combinations) and applying weights based on effect measure modifiers (EMMs) prior to pooling estimates within multisite studies may increase interpretability and improve precision. We simulated a 4-site study, standardized each site using inverse odds weights (IOWs) to resemble the 3 smallest sites or the smallest site, estimated IOW-weighted risk differences (RDs), and combined estimates with inverse variance weights (IVWs).

External validity in distributed data networks.

Purpose: While much has been written about how distributed networks address internal validity, external validity is rarely discussed. We aimed to define key terms related to external validity, discuss how they relate to distributed networks, and identify how three networks (the US Food and Drug Administration's Sentinel System, the Canadian Network for Observational Drug Effect Studies [CNODES], and the National Patient Centered Clinical Research Network [PCORnet]) deal with external validity.

Methods: We define external validity, target populations, target validity, generalizability, and transportability and describe how each relates to distributed networks.

How Choice of Effect Measure Influences Minimally Sufficient Adjustment Sets for External Validity.

Epidemiologic researchers generalizing or transporting effect estimates from a study to a target population must account for effect-measure modifiers (EMMs) on the scale of interest. However, little attention is paid to how the EMMs required may vary depending on the mathematical nuances of each effect measure. We defined 2 types of EMMs: a marginal EMM, where the effect on the scale of interest differs across levels of a variable, and a conditional EMM, where the effect differs conditional on other variables associated with the outcome.

Comparing Trial and Real-world Adjuvant Oxaliplatin Delivery in Patients With Stage III Colon Cancer Using a Longitudinal Cumulative Dose.

Importance: Delivery of adjuvant chemotherapy can differ substantially between trial and real-world populations. Adherence metrics like relative dose intensity (RDI) cannot capture the timing of modifications and mask differences in the total amount of chemotherapy received.

Objective: To compare oxaliplatin delivery between MOSAIC trial participants and patients treated in the US Oncology Network with stage III colon cancer using a longitudinal cumulative dose (LCD).

A systematic review of whether COVID-19 randomized controlled trials reported on demographic and clinical characteristics.

Purpose: We aim to assess the reporting of key patient-level demographic and clinical characteristics among COVID-19 related randomized controlled trials (RCTs).

Methods: We queried English-language articles from PubMed, Web of Science, clinicaltrials.gov, and the CDC library of gray literature databases using keywords of "coronavirus," "covid," "clinical trial" and "randomized controlled trial" from January 2020 to June 2021.

The Timing, the Treatment, the Question: Comparison of Epidemiologic Approaches to Minimize Immortal Time Bias in Real-World Data Using a Surgical Oncology Example.

Background: Studies evaluating the effects of cancer treatments are prone to immortal time bias that, if unaddressed, can lead to treatments appearing more beneficial than they are.

Methods: To demonstrate the impact of immortal time bias, we compared results across several analytic approaches (dichotomous exposure, dichotomous exposure excluding immortal time, time-varying exposure, landmark analysis, clone-censor-weight method), using surgical resection among women with metastatic breast cancer as an example. All adult women diagnosed with incident metastatic breast cancer from 2013-2016 in the National Cancer Database were included.

Meta-analysis with sample-standardization in multi-site studies.

Purpose: To conceptualize a particular target population and estimand for multi-site pharmacoepidemiologic studies within data networks and to analytically examine sample-standardization as a meta-analytic method compared with inverse-variance weighted meta-analyses.

Methods: The target population of interest is all and only all individuals from the data-contributing sites. Standardization, a general conditioning technique frequently employed for confounding control, was adopted to estimate the network-wide causal treatment effect.

Nondifferential Treatment Misclassification Biases Toward the Null? Not a Safe Bet for Active Comparator Studies.

Active comparator studies are increasingly common, particularly in pharmacoepidemiology. In such studies, the parameter of interest is a contrast (difference or ratio) in the outcome risks between the treatment of interest and the selected active comparator. While it may appear treatment is dichotomous, treatment is actually polytomous as there are at least 3 levels: no treatment, the treatment of interest, and the active comparator.

Alternative analytic and matching approaches for the prevalent new-user design: A simulation study.

Purpose: To describe the creation of prevalent new user (PNU) cohorts and compare the relative bias and computational efficiency of several alternative analytic and matching approaches in PNU studies.

Methods: In a simulated cohort, we estimated the effect of a treatment of interest vs a comparator among those who switched to the treatment of interest using the originally proposed time-conditional propensity score (TCPS) matching, standardized morbidity ratio weighting (SMRW), disease risk scores (DRS), and several alternative propensity score matching approaches. For each analytic method, we compared the average RR (across 2000 replicates) to the known risk ratio (RR) of 1.

B-cell cytopenia and time to last B-cell-depleting therapy predict response to SARS-COV-2 vaccines in patients with lymphoproliferative disorders.

Patients with B-non-Hodgkin lymphoma (NHL) are at increased risk of morbidity and mortality from SARS-CoV-2. We investigated the relationship between B cell cytopenia and the SARS-CoV-2 vaccine response in B-NHL patients. We measured anti-RBD antibodies and the lymphocyte immunophenotype in 19 controls, 22 lymphoma patients on observation (cohort 1) and 55 lymphoma patients receiving their vaccines post B-cell depleting therapy (cohort 2).

Introducing longitudinal cumulative dose to describe chemotherapy patterns over time: Case study of a colon cancer trial.

Adjuvant chemotherapy regimens take months to complete. Despite this, studies evaluate chemotherapy adherence via measures assessed at the end of treatment (eg, number of patients missing any dose, relative dose intensity [RDI]). This approach ignores information like the timing of treatment delays.

Propensity Score Weighting and Trimming Strategies for Reducing Variance and Bias of Treatment Effect Estimates: A Simulation Study.

To extend previous simulations on the performance of propensity score (PS) weighting and trimming methods to settings without and with unmeasured confounding, Poisson outcomes, and various strengths of treatment prediction (PS c statistic), we simulated studies with a binary intended treatment T as a function of 4 measured covariates. We mimicked treatment withheld and last-resort treatment by adding 2 "unmeasured" dichotomous factors that directed treatment to change for some patients in both tails of the PS distribution. The number of outcomes Y was simulated as a Poisson function of T and confounders.

Target validity: Bringing treatment of external validity in line with internal validity.

Purpose Of Review: "Target bias" is the difference between an estimate of association from a study sample and the causal effect in the target population of interest. It is the sum of internal and external bias. Given the extensive literature on internal validity, here, we review threats and methods to improve external validity.

Using propensity scores to estimate effects of treatment initiation decisions: State of the science.

Confounding can cause substantial bias in nonexperimental studies that aim to estimate causal effects. Propensity score methods allow researchers to reduce bias from measured confounding by summarizing the distributions of many measured confounders in a single score based on the probability of receiving treatment. This score can then be used to mitigate imbalances in the distributions of these measured confounders between those who received the treatment of interest and those in the comparator population, resulting in less biased treatment effect estimates.

Initiator Types and the Causal Question of the Prevalent New-User Design: A Simulation Study.

New-user designs restricting to treatment initiators have become the preferred design for studying drug comparative safety and effectiveness using nonexperimental data. This design reduces confounding by indication and healthy-adherer bias at the cost of smaller study sizes and reduced external validity, particularly when assessing a newly approved treatment compared with standard treatment. The prevalent new-user design includes adopters of a new treatment who switched from or previously used standard treatment (i.