Mahdokht Naghash , Rebecca L. Shaner , Hossein Poustchi , Gholamreza Roshandel , Katrice D. Williams , Abraham Tuachi , Farin Kamangar , Paolo Boffetta , Christian C. Abnet , Elizabeth I. Hamelin , Neal D. Freedman , Reza Malekzadeh , Arash Etemadi
{"title":"尿液中的阿片类生物标志物作为鸦片使用特征的可靠和有效的相关性：一项10年的纵向评估","authors":"Mahdokht Naghash , Rebecca L. Shaner , Hossein Poustchi , Gholamreza Roshandel , Katrice D. Williams , Abraham Tuachi , Farin Kamangar , Paolo Boffetta , Christian C. Abnet , Elizabeth I. Hamelin , Neal D. Freedman , Reza Malekzadeh , Arash Etemadi","doi":"10.1016/j.dadr.2025.100377","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Biomarkers can clarify the mechanistic bases of health effects associated with opiate use and improve evaluating dose-response relationships by quantifying the absorbed dose through different routes and patterns of use, supporting the generalizability of opium research findings to broader opioid use.</div></div><div><h3>Methods</h3><div>We recruited 449 individuals who used opium and 66 individuals who did not, 10 years after baseline evaluation in a cohort study. At both time points, we collected self-reported characteristics of opium use (route, frequency, type, and dose) and measured urinary concentrations of codeine, hydrocodone, hydromorphone, morphine, morphine-3-glucuronide, and morphine-6-glucuronide in spot urine samples. We used multivariate linear regression models to determine the independent effects of each opium use characteristic on biomarker concentrations. Reliability of biomarker concentrations over the 10-year interval was assessed using intraclass correlation coefficients (ICCs) from linear mixed-effect models.</div></div><div><h3>Results</h3><div>At the follow-up, 229 (51.0 %) subjects used opium by ingestion, which showed a significant shift compared with baseline (24.4 % ingestion). In adjusted models, opium ingestion, daily use, and presence of opioid use disorder (OUD) were associated with higher concentrations of all opioid biomarkers compared with opium smoking, non-daily use, and absence of OUD, respectively. All opioid biomarkers showed significant dose-response relationships relative to self-reported doses. Biomarker concentrations peaked when opium was used 3–4<!--> <!-->h before sample collection and declined afterwards, remaining detectable for several days. Biomarker measurements were reliable (ICCs between 0.69 and 0.78) over the 10-year interval.</div></div><div><h3>Conclusions</h3><div>Opioid biomarkers are valid markers of lifetime history, route, frequency, dose, and recency of opium use and OUD diagnosis, and demonstrate good long-term reliability.</div></div>","PeriodicalId":72841,"journal":{"name":"Drug and alcohol dependence reports","volume":"17 ","pages":"Article 100377"},"PeriodicalIF":2.9000,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Opioid biomarkers in urine as reliable and valid correlates of opium use characteristics: A 10-year longitudinal assessment\",\"authors\":\"Mahdokht Naghash , Rebecca L. Shaner , Hossein Poustchi , Gholamreza Roshandel , Katrice D. Williams , Abraham Tuachi , Farin Kamangar , Paolo Boffetta , Christian C. Abnet , Elizabeth I. Hamelin , Neal D. Freedman , Reza Malekzadeh , Arash Etemadi\",\"doi\":\"10.1016/j.dadr.2025.100377\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>Biomarkers can clarify the mechanistic bases of health effects associated with opiate use and improve evaluating dose-response relationships by quantifying the absorbed dose through different routes and patterns of use, supporting the generalizability of opium research findings to broader opioid use.</div></div><div><h3>Methods</h3><div>We recruited 449 individuals who used opium and 66 individuals who did not, 10 years after baseline evaluation in a cohort study. At both time points, we collected self-reported characteristics of opium use (route, frequency, type, and dose) and measured urinary concentrations of codeine, hydrocodone, hydromorphone, morphine, morphine-3-glucuronide, and morphine-6-glucuronide in spot urine samples. We used multivariate linear regression models to determine the independent effects of each opium use characteristic on biomarker concentrations. Reliability of biomarker concentrations over the 10-year interval was assessed using intraclass correlation coefficients (ICCs) from linear mixed-effect models.</div></div><div><h3>Results</h3><div>At the follow-up, 229 (51.0 %) subjects used opium by ingestion, which showed a significant shift compared with baseline (24.4 % ingestion). In adjusted models, opium ingestion, daily use, and presence of opioid use disorder (OUD) were associated with higher concentrations of all opioid biomarkers compared with opium smoking, non-daily use, and absence of OUD, respectively. All opioid biomarkers showed significant dose-response relationships relative to self-reported doses. Biomarker concentrations peaked when opium was used 3–4<!--> <!-->h before sample collection and declined afterwards, remaining detectable for several days. Biomarker measurements were reliable (ICCs between 0.69 and 0.78) over the 10-year interval.</div></div><div><h3>Conclusions</h3><div>Opioid biomarkers are valid markers of lifetime history, route, frequency, dose, and recency of opium use and OUD diagnosis, and demonstrate good long-term reliability.</div></div>\",\"PeriodicalId\":72841,\"journal\":{\"name\":\"Drug and alcohol dependence reports\",\"volume\":\"17 \",\"pages\":\"Article 100377\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Drug and alcohol dependence reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772724625000605\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drug and alcohol dependence reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772724625000605","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Opioid biomarkers in urine as reliable and valid correlates of opium use characteristics: A 10-year longitudinal assessment
Background
Biomarkers can clarify the mechanistic bases of health effects associated with opiate use and improve evaluating dose-response relationships by quantifying the absorbed dose through different routes and patterns of use, supporting the generalizability of opium research findings to broader opioid use.
Methods
We recruited 449 individuals who used opium and 66 individuals who did not, 10 years after baseline evaluation in a cohort study. At both time points, we collected self-reported characteristics of opium use (route, frequency, type, and dose) and measured urinary concentrations of codeine, hydrocodone, hydromorphone, morphine, morphine-3-glucuronide, and morphine-6-glucuronide in spot urine samples. We used multivariate linear regression models to determine the independent effects of each opium use characteristic on biomarker concentrations. Reliability of biomarker concentrations over the 10-year interval was assessed using intraclass correlation coefficients (ICCs) from linear mixed-effect models.
Results
At the follow-up, 229 (51.0 %) subjects used opium by ingestion, which showed a significant shift compared with baseline (24.4 % ingestion). In adjusted models, opium ingestion, daily use, and presence of opioid use disorder (OUD) were associated with higher concentrations of all opioid biomarkers compared with opium smoking, non-daily use, and absence of OUD, respectively. All opioid biomarkers showed significant dose-response relationships relative to self-reported doses. Biomarker concentrations peaked when opium was used 3–4 h before sample collection and declined afterwards, remaining detectable for several days. Biomarker measurements were reliable (ICCs between 0.69 and 0.78) over the 10-year interval.
Conclusions
Opioid biomarkers are valid markers of lifetime history, route, frequency, dose, and recency of opium use and OUD diagnosis, and demonstrate good long-term reliability.
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