Add-On Regimes and Their Relevance for Quantifying the Effects of Opioid-Sparing Treatments

TL;DR

This paper introduces a new way to measure how adding NSAIDs to opioid treatments can reduce opioid use, using add-on regimes that adapt to patient treatment history, with easier-to-assess assumptions and real-world application.

Contribution

It proposes a novel add-on regime framework for quantifying opioid-sparing effects, improving upon static and dynamic regimes with more practical assumptions.

Findings

Add-on regimes effectively measure opioid-sparing effects.

Method applied to Norwegian trauma patient data.

Easier assumptions facilitate real-world implementation.

Abstract

Medical researchers and practitioners want to know if supplementing opioid treatments with other analgesics, such as nonsteroidal anti-inflammatory drugs (NSAIDs), can reduce opioid consumption. However, quantifying opioid-sparing effects is challenging; even coming up with a policy-relevant estimand requires care. We propose defining these effects in terms of add-on regimes. An add-on regime assigns NSAIDs over time based on the opioid and NSAID treatments a patient would naturally take without any intervention. The regime uses the physician's decision to administer opioids as a clinically meaningful, and practically feasible, indication for NSAID administration. In contrast, static regimes assign NSAIDs at predefined time points, regardless of clinical context. When opioids are not administered, the add-on regime requires no intervention, thereby preserving the natural level of NSAIDs. This differs from conventional dynamic regimes, which define treatment decisions at every time point during the treatment period. We identify the effect of add-on regimes under assumptions that are easier to assess than those used in existing methods. Finally, we apply the methods to estimate opioid-sparing effects of NSAIDs in a cohort of Norwegian trauma patients using national registry data.