Evidence map›Paper›PMID 40894271›Full record

ArticleLancet regional health. Americas2025

Ten-year trends in opioid prescribing and vaso-occlusive crises in sickle cell disease: a population-based national cohort study (2011-2022).

Kevin Y Xu, Terri V Newman, Lakeya S McGill, Enrico M Novelli, Cheryl A Hillery, Joanna L Buss, Lisa Gong, Ruizhi Huang, Fanghong Dong, Dustin Stwalley and 8 more

Abstract read
In one paragraph

Article in Lancet regional health. Americas, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

18 authors.

Kevin Y XuWashington University School of Public Health, St. Louis, MO, USA.
Terri V NewmanDepartment of Pharmacy and Therapeutics, University of Pittsburgh School of Pharmacy, Pittsburgh, PA, USA.
Lakeya S McGillDivision of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Enrico M NovelliDivision of Classical Hematology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Cheryl A HilleryDivision of Hematology-Oncology, Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Joanna L BussInstitute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO, USA.
Lisa GongDepartment of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
Ruizhi HuangThe Advanced HEAlth Data (AHEAD) Research Institute, Saint Louis University School of Medicine, St. Louis, MO, USA.
Fanghong DongDepartment of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
Dustin StwalleyInstitute for Informatics, Data Science and Biostatistics, Washington University School of Medicine, St. Louis, MO, USA.
Joanne SalasDepartment of Family and Community Medicine, Saint Louis University School of Medicine, St. Louis, MO, USA.
Shiyuan A LiuDivision of Hematology and Oncology, UCSF School of Medicine, San Francisco, CA, USA.
Jeffrey F ScherrerDepartment of Family and Community Medicine, Saint Louis University School of Medicine, St. Louis, MO, USA.
Tashalee R BrownJane and Terry Semel Institute for Neuroscience and Human Behavior at UCLA, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Tae Woo ParkDepartment of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Marc R LaRochelleClinical Addiction Research and Education Unit at Boston University School of Medicine, Boston Medical Center, Boston, MA, USA.
Richard A GruczaDepartment of Family and Community Medicine, Saint Louis University School of Medicine, St. Louis, MO, USA.
Charles R JonassaintDivision of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.

Funding

University of Michigan (UM) HEAL Initiative National K12 Clinical Pain Career Development Program (UM-HCPDP)K12NS130673 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Daniel J Clauw, Steven Edward Harte · 2022 to 2026
$12.5M
PHARMacist and Community Health Support to Optimize Medications After Trauma Surgery (PHARM-C)P50MH122351 · NIMH · WASHINGTON UNIVERSITY · PI Eric J Lenze · 2021 to 2026
$10.8M
Washington University Career Development Program in Drug Abuse and AddictionK12DA041449 · NIDA · WASHINGTON UNIVERSITY · PI Laura J. Bierut, Patricia A Cavazos-Rehg · 2017 to 2026
$4.2M
Using Big Data to Optimize Treatment of Opioid Use Disorder in PregnancyK08DA061258 · NIDA · WASHINGTON UNIVERSITY · PI Kevin Young Xu · 2024 to 2026
$664k
NHLBI NIH HHS L60 HL170453NIDA NIH HHS K08 DA061258NIDA NIH HHS K12 DA041449NIMH NIH HHS P50 MH122351NINDS NIH HHS K12 NS130673
6 · The paper itself

Abstract

Background: Patterns of opioid prescribing and vaso-occlusive crises (VOCs) are poorly characterized among individuals with sickle cell disease (SCD) across diverse insurance types and age groups. We aimed to evaluate opioid prescribing and VOC trends in publicly and commercially insured individuals with SCD over a 10-year time period in the United States (US). Methods: We conducted a retrospective cohort study of US administrative claims (2011-2022), analyzing 45,726 commercial and Medicaid beneficiaries with SCD. Primary outcomes were monthly rates of outpatient opioid prescriptions and VOC-related acute care encounters. We used joinpoint regression models to estimate trends without pre-specifying breakpoints, stratified by insurance type (Medicaid vs commercial) and age group (1-12, 13-17, 18-27, 28-45, 46-64 years). Primary outcomes were monthly rates of outpatient opioid prescriptions and VOC-related acute care encounters. We used joinpoint regression models to estimate trends without pre-specifying breakpoints, stratified by insurance type (Medicaid vs commercial) and age group. Findings: Among 45,726 individuals with SCD (mean age [SD] = 25.1 [16.2]; 39.7% female; 52.9% Medicaid, 47.1% commercial insurance), Medicaid beneficiaries had higher rates than commercial beneficiaries for monthly opioid prescribing (18.3 vs 14.0 per 100) and VOC encounters (16.6 vs 8.2 per 100). Monthly opioid prescribing per 100 people increased with age: 1-12 y = 5.1; 13-17 y = 11.3; 18-27 y = 22.5; 28-45 y = 24.6; 46-64 y = 20.6 per 100. Both Medicaid and commercial beneficiaries experienced declining opioid prescribing beginning in 2011 (commercial monthly percentage change [MPC] = -0.3% [95% CI: -0.3%, -0.2%]; Medicaid MPC = -0.5% [-0.6%, 0.5%]). Down-trending opioid prescribing was not consistently accompanied by up-trending VOCs until the COVID-19 pandemic's onset. Particularly among children and adolescents, VOC-related encounters increased significantly after 2020 across both commercial (MPC = 1.8% [1.5%, 2.2%]) and Medicaid (MPC = 0.6% [0.1%, 1.6%]) beneficiaries. Interpretation: Opioid prescribing and VOC admissions vary by insurance and age. Opioid prescribing declined from 2011 but was not consistently accompanied by increased VOCs until after COVID-19. Funding: Analyses of Merative MarketScan Commercial and Multi-State Medicaid Database were funded by grants NIH K12 DA041449 (PI: KYX; data analysts: JLB, DS). Effort for some personnel was supported by P50 MH122351 (KYX, PI: Eric Lenze MD, Michael Avidan MBBCh), K08 K08 DA061258 (KYX), the American Psychiatric Association (APA) Psychiatric Research Fellowship (with funding by NIDA and the APA, KYX), NIH K12NS130673 (LSM), NIH L60HL170453 (LSM), and the St. Louis University Research Institute Fellowship (RAG, JS, JFS, RH); these grants did not fund Merative MarketScan Commercial and Multi-State Medicaid Database data pull.

Indexed as

Administrative claimsAge disparitiesCOVID-19InsuranceOpioid prescribingSickle cell diseaseVaso-occlusive crises

Identifiers

PMID40894271
PMCPMC12396581

What OpenQuestion holds

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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.