Distinct neural networks predict cocaine versus cannabis treatment outcomes
Lichenstein S, Kohler R, Ye F, Potenza M, Kiluk B, Yip S. Distinct neural networks predict cocaine versus cannabis treatment outcomes. Molecular Psychiatry 2023, 28: 3365-3372. PMID: 37308679, PMCID: PMC10713861, DOI: 10.1038/s41380-023-02120-0.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelingCognitive behavior therapyCognitive behavioral therapySubstance use disordersCannabis abstinenceNeural mechanismsBehavior therapyDistinct neural networksComputer-based trainingCannabis use disorderFMRI scanningNeural predictorsStudy 1Study 2Treatment outcomesContingency managementPrior workComparison subjectsNetwork strengthUse disordersNovel treatment targetsAbstinenceIndependent samplesCocaine abstinenceTreatment respondersPercentage of negative urine drug screens as a clinically meaningful endpoint for RCTs evaluating treatment for cocaine use
Loya J, Babuscio T, Nich C, Alessi S, Rash C, Kiluk B. Percentage of negative urine drug screens as a clinically meaningful endpoint for RCTs evaluating treatment for cocaine use. Drug And Alcohol Dependence 2023, 248: 109947. PMID: 37276806, PMCID: PMC10498479, DOI: 10.1016/j.drugalcdep.2023.109947.Peer-Reviewed Original ResearchConceptsUrine drug screensClinical trialsMeaningful endpointsCocaine useLong-term clinical benefitBetter long-term outcomesDrug screensPsychosocial functioningNegative urine drug screensLong-term outcomesRandomized clinical trialsFuture clinical trialsBetter psychosocial functioningClinical benefitPharmacological treatmentContinuous abstinenceTreatment periodTreatment respondersSustained abstinenceSubstance useTrialsTreatmentMeaningful thresholdPooled datasetAbstinence