| Verf.angabe: | Addiction Cue-Reactivity Initiative (ACRI) Network ; Arshiya Sangchooli, MD, Mehran Zare-Bidoky, MD, Ali Fathi Jouzdani, MD, Joseph Schacht, PhD, James M. Bjork, PhD, Eric D. Claus, PhD, James J. Prisciandaro, PhD, Stephen J. Wilson, PhD, Torsten Wüstenberg, PhD, Stéphane Potvin, PhD, Pooria Ahmadi, MD, Patrick Bach, PhD, Alex Baldacchino, MD, PhD, Anne Beck, PhD, Kathleen T. Brady, MD, PhD, Judson A. Brewer, MD, PhD, Anna Rose Childress, PhD, Kelly E. Courtney, PhD, Mohsen Ebrahimi, MSc, Francesca M. Filbey, PhD, Hugh Garavan, PhD, Dara G. Ghahremani, PhD, Rita Z. Goldstein, PhD, Anneke E. Goudriaan, PhD, Erica N. Grodin, PhD, Colleen A. Hanlon, PhD, Amelie Haugg, PhD, Markus Heilig, MD, PhD, Andreas Heinz, MD, PhD, Adrienn Holczer, PhD, Ruth J. Van Holst, PhD, Jane E. Joseph, PhD, Anthony C. Juliano, PsyD, Marc J. Kaufman, PhD, Falk Kiefer, MD, PhD, Arash Khojasteh Zonoozi, MD, Rayus T. Kuplicki, PhD, Marco Leyton, PhD, Edythe D. London, PhD, Scott Mackey, PhD, F. Joseph McClernon, PhD, William H. Mellick, PhD, Kirsten Morley, PhD, Hamid R. Noori, PhD, Mohammad Ali Oghabian, PhD, Jason A. Oliver, PhD, Max Owens, PhD, Martin P. Paulus, MD, PhD, Irene Perini, PhD, Parnian Rafei, MSc, Lara A. Ray, PhD, Rajita Sinha, PhD, Michael N. Smolka, MD, PhD, Ghazaleh Soleimani, PhD, Rainer Spanagel, PhD, Vaughn R. Steele, PhD, Susan F. Tapert, PhD, Sabine Vollstädt-Klein, PhD, Reagan R. Wetherill, PhD, Katie Witkiewitz, PhD, Kai Yuan, PhD, Xiaochu Zhang, PhD, Antonio Verdejo-Garcia, PhD, Marc N. Potenza, MD, PhD, Amy C. Janes, PhD, Hedy Kober, PhD, Anna Zilverstand, PhD, Hamed Ekhtiari, MD, PhD |
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| Abstract: | In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in the neurobiology of drug addiction. However, no FDCR-derived biomarkers have been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment of the FDCR literature evidence, its heterogeneity, and an evaluation of possible clinical uses of FDCR-derived biomarkers.To summarize the state of the field of FDCR, assess their potential for biomarker development, and outline a clear process for biomarker qualification to guide future research and validation efforts.The PubMed and Medline databases were searched for every original FDCR investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, FDCR task design, and whether each study provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, or severity biomarkers for 1 or more addictive disorders.There were 415 FDCR studies published between 1998 and 2022. Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), or cocaine (46 [11.1%]), and most used visual cues (354 [85.3%]). Together, these studies recruited 19311 participants, including 13812 individuals with past or current substance use disorders. Most studies could potentially support biomarker development, including diagnostic (143 [32.7%]), treatment response (141 [32.3%]), severity (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), and susceptibility (2 [0.5%]) biomarkers. A total of 155 interventional studies used FDCR, mostly to investigate pharmacological (67 [43.2%]) or cognitive/behavioral (51 [32.9%]) interventions; 141 studies used FDCR as a response measure, of which 125 (88.7%) reported significant interventional FDCR alterations; and 25 studies used FDCR as an intervention outcome predictor, with 24 (96%) finding significant associations between FDCR markers and treatment outcomes.Based on this systematic review and the proposed biomarker development framework, there is a pathway for the development and regulatory qualification of FDCR-based biomarkers of addiction and recovery. Further validation could support the use of FDCR-derived measures, potentially accelerating treatment development and improving diagnostic, prognostic, and predictive clinical judgments. |
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