ArticleBMJ oncology2023
Long-term opioid therapy trajectories and overdose in patients with and without cancer.
Article in BMJ oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Care Models to Improve Pain and Reduce Opioids Among Patients Prescribed Long-Term Opioid Therapy: The VOICE Randomized Clinical Trial.JAMA internal medicine · 2025Trial
- Prescription Monitoring Program Mandates and Opioids Dispensed to Patients Dying of Cancer.JCO oncology practice · 2026Article
- Initial Long-Term Opioid Prescriptions Among Veterans With and Without Kidney Disease.Journal of pain and symptom management · 2025Article
- Opioid prescribing trends and pain scores among adult patients with cancer in a large health system.Cancer · 2025Article
- How Racialized Approaches to Opioid Use Disorder and Opioid Misuse Management Hamper Pharmacoequity for Cancer Pain.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2025Article
- Long-term opioid therapy trajectories in veteran patients with and without substance use disorder.Addictive behaviors · 2024Article
- Benefits, Harms, and Stakeholder Perspectives Regarding Opioid Therapy for Pain in Individuals With Metastatic Cancer: Protocol for a Descriptive Cohort Study.JMIR research protocols · 2024Article
Corrections and comments
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Authors and funding
14 authors at 8 institutions in 1 country.
Funding
Abstract
Objective: Pain is experienced by most patients with cancer and opioids are a cornerstone of management. Our objectives were (1) to identify patterns or trajectories of long-term opioid therapy (LTOT) and their correlates among patients with and without cancer and (2) to assess the association between trajectories and risk for opioid overdose, considering the potential moderating role of cancer. Methods and Analysis: We conducted a retrospective cohort study among individuals in the US Veterans Health Administration (VHA) database with incident LTOT with and without cancer (N=44,351; N=285,772, respectively) between 2010-2017. We investigated the relationship between LTOT trajectory and all International Classification of Diseases-9 and 10-defined accidental and intentional opioid-related overdoses. Results: Trajectories of opioid receipt observed in patients without cancer and replicated in patients with cancer were: low-dose/stable trend, low-dose/de-escalating trend, moderate-dose/stable trend, moderate-dose/escalating with quadratic downturn trend, and high-dose/escalating with quadratic downturn trend. Time to first overdose was significantly predicted by higher-dose and escalating trajectories; the two low-dose trajectories conferred similar, lower risk. Conditional hazard ratios (99% CI) for the moderate-dose, moderate-dose/escalating with quadratic downturn and high-dose/escalating with quadratic downturn trends were 1·84 (1·18, 2·85), 2·56 (1·54, 4·25), and 2·41 (1·37, 4·26), respectively. Effects of trajectories on time to overdose did not differ by presence of cancer; inferences were replicated when restricting to patients with stage 3/4 cancer. Conclusion: Patients with cancer face opioid overdose risks like patients without cancer. Future studies should seek to expand and address our knowledge about opioid risk in cancer patients. Trial registration: None.
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Registered trials
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.