Prevalent new user designs: A literature review of current implementation practice

Abstract

PurposePrevalent new user (PNU) designs extend the active comparator new user design by allowing for the inclusion of initiators of the study drug who were previously on a comparator treatment. We performed a literature review summarising current practice.MethodsPubMed was searched for studies applying the PNU design since its proposal in 2017. The review focused on three components. First, we extracted information on the overall study design, including the database used. We summarised information on implementation of the PNU design, including key decisions relating to exposure set definition and estimation of time‐conditional propensity scores. Finally, we reviewed the analysis strategy of the matched cohort.ResultsNineteen studies met the criteria for inclusion. Most studies (73%) implemented the PNU design in electronic health record or registry databases, with the remaining using insurance claims databases. Of 15 studies including a class of prevalent users, 40% deviated from the original exposure set definition proposals in favour of a more complex definition. Four studies did not include prevalent new users but used other aspects of the PNU framework. Several studies lacked details on exposure set definition (n = 2), time‐conditional propensity score model (n = 2) or integration of complex analytical techniques, such as the high‐dimensional propensity score algorithm (n = 3).ConclusionPNU designs have been applied in a range of therapeutic and disease areas. However, to encourage more widespread use of this design and help shape best practice, there is a need for improved accessibility, specifically through the provision of analytical code alongside guidance to support implementation and transparent reporting.

Matching study design to prescribing intention: The prevalent new‐user design for studying abuse‐deterrent formulations of opioids

“…14 To account for exposure history, comparators can be chosen based on similar prior cumulative exposure history, considering factors such as (1) time since initial exposure; (2) number of prescriptions; and (3) type of initiator (direct or delayed switch). 14,15 However, trajectories of exposure history may be highly nuanced, as further demonstrated in this analysis. Researchers should carefully consider substantive and methodological implications in specifying the causal estimand when implementing the PNU design.…”

“…This design, when thoughtfully implemented, can mitigate potential bias from confounding by “indication” and healthy‐user bias through careful selection of comparators 14 . To account for exposure history, comparators can be chosen based on similar prior cumulative exposure history, considering factors such as (1) time since initial exposure; (2) number of prescriptions; and (3) type of initiator (direct or delayed switch) 14,15 . However, trajectories of exposure history may be highly nuanced, as further demonstrated in this analysis.…”

“…Many implementations of the ACNU design in opioid research require no observed exposure to any or certain types of opioids in a pre‐specified timeframe before cohort entry 12 ; hence, people with incident ADF use in this type of study design may not be representative of the overall ADF patient population. The prevalent new‐user (PNU) design 13,14 expands upon the traditional ACNU study, allowing for inclusion of patients previously prescribed a comparator treatment before starting the new treatment, and may better represent how the treatment is used in real‐world practice 15 . Further, when designing pharmacoepidemiologic studies and selecting the study population, it is important to identify appropriate comparators and address confounding by “indication” 16 observable in claims data 7,8,17 …”

“…The prevalent new-user (PNU) design 13,14 expands upon the traditional ACNU study, allowing for inclusion of patients previously prescribed a comparator treatment before starting the new treatment, and may better represent how the treatment is used in real-world practice. 15 Further, when designing pharmacoepidemiologic studies and selecting the study population, it is important to identify appropriate comparators and address confounding by "indication" 16 observable in claims data. 7,8,17 In this study, we evaluated the implications of study design choice for estimating post-market effectiveness of ADFs and examined patterns of ADF and non-ADF ER/LA initiation.…”

Matching Study Design to Prescribing Intention: The Prevalent New-User Design for Studying Abuse-Deterrent Formulations of Opioids

“…The prevalent new-user (PNU) design 13,14 expands upon the traditional ACNU study, allowing for inclusion of patients previously prescribed a comparator treatment before starting the new treatment, and may better represent the intended patient population. 15 Further, when designing pharmacoepidemiologic studies and selecting the study population it is important to identify appropriate comparators and address confounding by "indication" 16 observable in claims data. 7,8,17 In this study, we evaluated the implications study design choice for estimating post-market effectiveness of ADFs and examined patterns of ADF and non-ADF ER/LA initiation.…”