Evidence map›Paper›PMID 41642627›Full record

ArticleJAMA network open2026

Prevalence of Illicit Drug Detection in 5 US Cities Among Out-of-Treatment People Who Inject Drugs.

Nabila El-Bassel, Steven Shoptaw, Timothy Skalland, Brett Hanscom, William Clarke, Mark A Marzinke, Jessica M Fogel, Paul Richardson, Rahul Paul Choudhury, Cecile Denis and 10 more

Abstract read
In one paragraph

Article in JAMA network open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Nabila El-BasselSchool of Social Work, Columbia University, New York, New York.
Steven ShoptawDepartment of Family Medicine, University of California, Los Angeles.
Timothy SkallandVaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington.
Brett HanscomVaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington.
William ClarkeDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Mark A MarzinkeDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Jessica M FogelDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Paul RichardsonDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Rahul Paul ChoudhuryStatistical Center for HIV/AIDS Research, Fred Hutchinson Cancer Center, Seattle, Washington.
Cecile DenisDepartment of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
David Goodman-MezaKirby Institute, University of New South Wales, Sydney, New South Wales, Australia.
Irene KuoDepartment of Epidemiology, Milken Institute School of Public Health, George Washington University, Washington, DC.
Jordan E LakeUTHealth Houston, Houston, Texas.
Ellen A B MorrisonICAP, Mailman School of Public Health, Columbia University, New York, New York.
Amy M RichardsDepartment of Family Medicine, University of California, Los Angeles.
Jayla Harris-WisecarverFHI 360, Durham, North Carolina.
Melissa CummingsStatistical Center for HIV/AIDS Research, Fred Hutchinson Cancer Center, Seattle, Washington.
Redonna ChandlerAddiction Policy Forum, Bethesda, Maryland.
Philip AndrewFHI 360, Durham, North Carolina.
HPTN 094 Study Team

Funding

LC: HIV Prevention Trials Network - Laboratory Support for the SARS-CoV-2 Seroprevalence Study (CoVPN 5002)UM1AI068613 · NIAID · JOHNS HOPKINS UNIVERSITY · PI SUSAN H ESHLEMAN, Mark A Marzinke · 2011 to 2026
$100.2M
UCLA Rapid, Relevant, Rigorous Implementation Science HubP30MH058107 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI RAPHAEL J LANDOVITZ · 1997 to 2026
$53.5M
UCLA AIDS Prevention and Treatment Clinical Trials UnitUM1AI069424 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Judith S. Currier, RAPHAEL J LANDOVITZ · 2012 to 2026
$51.8M
ICAP Clinical Trials UnitUM1AI154468 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI WAFAA M. EL-SADR, JESSICA E. JUSTMAN · 2021 to 2026
$13.0M
The District of Columbia Clinical Trials Unit (DC CTU)UM1AI154466 · NIAID · GEORGE WASHINGTON UNIVERSITY · PI Sarah Henn, Manya Magnus · 2021 to 2026
$12.5M
NIAID NIH HHS UM1 AI068613NIAID NIH HHS UM1 AI069424NIAID NIH HHS UM1 AI154466NIAID NIH HHS UM1 AI154468NIMH NIH HHS P30 MH058107
6 · The paper itself

Abstract

Importance: In the US, the overdose crisis continues to be driven by fentanyl, xylazine, and stimulant-involved polysubstance use among people who inject drugs, especially those who are not engaged in medical care. Objective: To estimate the overall prevalence of illicit drugs detected among people who inject drugs in 5 US cities by city and sociodemographic characteristics and assess trends in drug detection over a 2-year period. Design, Setting, and Participants: This cross-sectional study included data from individuals enrolled in HIV Prevention Trials Network (HPTN) 094, a randomized clinical trial to evaluate an integrated mobile unit engaging adults aged 18 years or older who inject drugs in HIV services between June 2021 and September 2023 in New York City; Houston, Texas; Los Angeles, California; Philadelphia, Pennsylvania; and Washington, DC. All analyses were completed between August 2021 and August 2025. Main Outcomes and Measures: Baseline prevalence of toxicologic detection was assessed using liquid chromatography-high-resolution mass spectrometry. Differences in toxicologic detection by sociodemographic characteristics (age, race and ethnicity, housing status, and incarceration history), study site, and illicit drug type over time were analyzed using generalized linear models. Results: Across 444 participants, 303 (68.2%) were male, 267 (60.1%) were aged 30 to 49 years, 203 of 440 (46.1%) were unhoused, and 91 of 442 (20.6%) had a recent incarceration history. In all, 414 participants (93.2%) tested positive for fentanyl, 328 (73.9%) for cocaine, 299 (67.3%) for amphetamine-type stimulants, and 234 (52.7%) for xylazine. Nearly all participants (421 [94.8%]) tested positive for polysubstance drugs (fentanyl or opioids with stimulants, benzodiazepines, cocaine, and/or xylazine). Fentanyl detection was high across all sites; xylazine was most common in New York City (68 of 94 [72.3%]), Philadelphia (111 of 112 [99.1%]), and Washington, DC (31 of 41 [75.6%]). Every 6 months, xylazine detection increased in New York City by 10.3% (95% CI, 4.0%-16.5%; P = .001), and its prevalence stayed high in Philadelphia. Amphetamine-type stimulant detection increased in Washington, DC, by 15.0% (95% CI, 2.9%-27.1%) every 6 months over the enrollment period (P = .02). Across all sites, cocaine prevalence was higher among unhoused than housed participants (difference, 11.4%; 95% CI, 3.6%-19.2%; P = .004), and stimulant detection was elevated among those recently incarcerated vs not (difference, 9.9%; 95% CI, 1.4%-18.5%; P = .02). Conclusions and Relevance: This cross-sectional study found widespread fentanyl and polysubstance detection, with rising xylazine and stimulant detection that varied by sociodemographic and structural vulnerabilities and may be due to adulteration within the unregulated drug supply. These findings highlight urgent public health needs for real-time drug supply surveillance, targeted harm-reduction services, and integrated treatment approaches to reduce overdose risk and address social and structural vulnerabilities.

Indexed as

Illicit DrugsSubstance Abuse DetectionSubstance Abuse, IntravenousAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedNew York CityPrevalenceUnited StatesIllicit Drugs

Identifiers

PMID41642627
PMCPMC12878425

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.