Alcohol use disorder (AUD) is a chronic relapsing condition characterized by an impaired ability to stop or control use despite clinically significant impairment, distress, and/or adverse consequences (APA, 2013, Grant, 2015). In individuals with an AUD, exposure to alcohol-related cues, such as the sight, smell, or taste of alcohol, is thought to elicit a conditional response characterized by heightened subjective cravings/urges and psychophysiological response (i.e., salivation, heart rate, blood pressure) (Monti, 1987, Ray and Roche, 2018). This phenomenon is known as alcohol cue-induced craving, or cue reactivity, and has been associated with AUD severity and drinking outcomes (Monti et al., 2000, Payne, 1992, Rohsenow, 1994, Glautier and Drummond, 1994, Cooney, 1997). Given the ubiquity of alcohol cues in the real world, understanding and managing reactivity to alcohol-related cues is critical for the treatment of AUD. As such, alcohol cue reactivity has been a focal point of AUD research for decades (Ray and Roche, 2018, Rosenberg, 2009, Venegas and Ray, 2020, Meredith, 2023).

Alcohol cue exposure paradigms are widely used in experimental laboratory studies to examine alcohol cue reactivity and to model high-risk situations that may lead to relapse (Ray and Roche, 2018, Niaura, 1988, Reynolds and Monti, 2013). These paradigms involve systematically exposing individuals to alcohol-related and control (i.e., water, juice) cues and assessing their “reactivity,” or their subjective urge to drink alcohol, and in some studies, psychophysiological response (Monti, 1987, Ray and Roche, 2018, Szegedi, 2000). These paradigms have also been tailored to explore factors influencing cue reactivity, such as negative mood and stress (Cooney, 1997, Rubonis, 1994, Litt, 1990). Alcohol cue reactivity is commonly used as an endpoint in human laboratory medication trials to establish initial efficacy for promising pharmacotherapies for AUD (Ray, 2018, Plebani, 2012, Mason and Higley, 2013). Medication-related reductions in alcohol cue reactivity are thought to signal early efficacy and inform whether a medication should advance to the next stage of clinical testing (Ray, 2018, Plebani, 2012, Mason and Higley, 2013, Litt and Cooney, 1999). Despite the widespread utilization of cue exposure paradigms to screen pharmacotherapies for AUD (Reynolds & Monti, 2013), the degree to which it is actually predictive of clinical efficacy remains unclear (Ray, 2018, Miranda, 2020, Yardley and Ray, 2017). As recently described in a systematic review and quantitative synthesis of the literature (Meredith, 2023), there are a number of factors in cue reactivity testing that introduce heterogeneity, which may ultimately influence the translational and predictive utility of this paradigm.

One central consideration is that not all individuals with an AUD are cue reactive (Rohsenow, 1994, Rubonis, 1994, Litt, 1990). A handful of studies revealed that ∼ 22–65 % of individuals with an AUD are cue reactive, as indicated by subjective cue reactivity (Venegas and Ray, 2020, Szegedi, 2000, Rubonis, 1994, Plebani, 2012, Rohsenow, 1992). Despite these findings, the application of alcohol cue exposure paradigms often assumes uniform cue reactivity among individuals with an AUD (i.e., all individuals with AUD uniformly exhibit greater reactivity following exposure to alcohol, compared with control, cues) (Monti, Rohsenow, & Hutchison, 2000). This assumption may be problematic, particularly in the context of treatment studies that assess changes in cue reactivity before versus after treatment. If individuals are not cue reactive to begin with, the study will lack power to determine whether a medication can reduce cue reactivity. Although not widely implemented, some studies have screened for cue reactivity prior to enrollment in order to minimize heterogeneity and enhance signal detection (Rubonis, 1994, Mason, 2009). These screening procedures typically involve an abbreviated cue reactivity paradigm and consider individuals cue reactive if they exhibit a ≥ 1 standard deviation increase in subjective alcohol craving when exposed to alcohol, compared with control, cues (Venegas and Ray, 2020, Miranda, 2020, Mason, 2009). This approach may produce a stronger signal for investigating treatment effects, but limits generalizability of findings to individuals with AUD who are cue reactive. Therefore, it is critical to understand differences in the clinical presentation of individuals with AUD based on their alcohol cue reactivity.

The present study characterized alcohol cue reactive (CR+) and cue non-reactive (CR-) individuals with current moderate-to-severe AUD by comparing them on clinical variables and drinking outcomes during a quit attempt. This study leveraged data from a recent human laboratory pharmacotherapy trial (NCT04249882) involving two weeks of treatment with varenicline, naltrexone, or placebo (Ray, 2023). Randomized participants completed a standard alcohol cue exposure paradigm, followed by a 1-week medication titration period and 1-week “practice quit” attempt. The objectives of the present study were to: 1) identify CR+ and CR- groups, as determined via a self-reported, subjective assessment of alcohol urge, during an alcohol cue-reactivity paradigm, and their clinical correlates (i.e., alcohol use/problems and demographic, smoking, and mood characteristics); and 2) determine how CR+ and CR- individuals differ in drinking over the course of the study. Based on research suggesting alcohol cue-induced craving is an important mechanism underlying AUD (including alcohol use and relapse) (Vafaie & Kober, 2022), we hypothesized that CR+ individuals would 1) report heavier drinking and higher levels of AUD severity compared with CR- individuals and 2) report more drinks per drinking day and fewer percent days abstinent during the trial compared with CR- individuals.