Trends and Rapidity of Dose Tapering Among Patients Prescribed Long-term Opioid Therapy, 2008-2017
Open accessAbstract
Importance: A 2016 Centers for Disease Control and Prevention prescribing guideline cautioned against higher-dose long-term opioid therapy and recommended tapering daily opioid doses by approximately 10% per week if the risks outweigh the benefits. Warnings have since appeared regarding potential hazards of rapid opioid tapering. Objectives: To characterize US trends in opioid dose tapering among patients prescribed long-term opioids from 2008 to 2017 and identify patient-level variables associated with tapering and a more rapid rate of tapering. Design, Setting, and Participants: This retrospective cohort study used deidentified medical and pharmacy claims and enrollment records for 100 031 commercial insurance and Medicare Advantage enrollees, representing a diverse mixture of ages, races/ethnicities, and geographical regions across the United States. Adults with stable, higher-dosage (mean, ≥50 morphine milligram equivalents [MMEs]/d) opioid prescriptions for a 12-month baseline period and 2 or more months of follow-up from January 1, 2008, to December 31, 2017, were included in the study. Main Outcomes and Measures: Tapering was defined as 15% or more relative reduction in mean daily MME during any of 6 overlapping 60-day windows within a 7-month follow-up period. The rate of tapering was computed as the maximum monthly percentage dose reduction. Results: Among the 100 031 participants (53 452 [53.4%] women; mean [SD] age, 57.6 [11.8] years), from 2008 to 2015, the age- and sex-standardized percentage of patients tapering daily opioid doses increased from 10.5% to 13.7% (adjusted incidence rate ratio [aIRR] per year, 1.05 [95% CI, 1.05-1.06]) before increasing to 16.2% in 2016 and 22.4% in 2017 (aIRR in 2016-2017 vs 2008-2015, 1.20 [95% CI, 1.16-1.25]). Patient-level covariates associated with tapering included female sex (aIRR, 1.13 [95% CI, 1.10-1.15]) and higher baseline dose (aIRR for ≥300 MMEs/d vs 50-89 MMEs/d, 2.57 [95% CI, 2.48-2.65]). Among patients tapering daily opioid doses, the mean (SD) maximum dose reduction was 27.6% (17.0%) per month, and 18.8% of patients had a maximum tapering rate exceeding 40% per month (ie, faster than 10% per week). More rapid dose reduction was associated with 2016-2017 vs 2008-2015 (adjusted difference, 1.4% [95% CI, 0.8%-2.1%]) and higher baseline dose (adjusted difference, 2.7% [95% CI, 2.2%-3.3%] for 90-149 vs 50-89 MMEs/d). Conclusions and Relevance: Patients using long-term opioid therapy are increasingly undergoing dose tapering, particularly women and those prescribed higher doses; in addition, dose tapering has become more common since 2016. Many patients undergoing tapering reduce daily doses at a rapid maximum rate.
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In another analysis, only 13.7% of patients tapering opioids achieved complete cessation in a 9-year window.
“In another analysis, only 13.7% of patients tapering opioids achieved complete cessation in a 9-year window. 43”
From Tapering and withdrawing opioids: guidance informed by fundamental principles to minimise withdrawal symptoms (2025) · cites this paper as [43]
The Results report that 13.7% was the percentage of patients tapering their daily opioid dose in 2015, not the percentage of tapering patients who stopped opioids. The Methods define tapering as a dose reduction of at least 15% during a seven-month follow-up, and the Limitations say the study did not evaluate whether reductions were sustained. No cessation rate over a nine-year window is reported in these passages. (LLM, conf=0.89)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredMore than a quarter of patients in a study of almost 100,000 were tapering at a rate faster than 40% of their original dose per month, even higher than the maximum rate recommended by the CDC.
“A study of almost 100,000 patients found that the average rate of tapering was 34.0% of the original dose per month and more than a quarter of patients were tapering at a rate faster than 40% of their original dose per month,43,49 even higher than the maximum rate recommended by the CDC. 1”
From Tapering and withdrawing opioids: guidance informed by fundamental principles to minimise withdrawal symptoms (2025) · cites this paper as [43]
The Results report that 18.8% of tapering patients—not more than a quarter—had a maximum dose reduction rate exceeding 40% per month. They also give a mean maximum rate of 27.6% per month, not 34.0%. The Methods do support the comparison with the CDC guideline's recommended rate. (LLM, conf=0.93)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredA study of almost 100,000 patients found that the average rate of tapering was 34.0% of the original dose per month.
“A study of almost 100,000 patients found that the average rate of tapering was 34.0% of the original dose per month and more than a quarter of patients were tapering at a rate faster than 40% of their original dose per month,43,49 even higher than the maximum rate recommended by the CDC. 1”
From Tapering and withdrawing opioids: guidance informed by fundamental principles to minimise withdrawal symptoms (2025) · cites this paper as [43]
The Results report a cohort of 100,031 patients, supporting the study-size description. But the reported mean maximum tapering rate was 27.6% per month, not 34.0%; the Results also say 18.8% exceeded 40% per month, not more than a quarter. Page numbers were not available in our copy. (LLM, conf=0.91)
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Cites
Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data
Quan, H., Sundararajan, V., Halfon, P., Fong, A., Burnand, B., Luthi, J.-C., Saunders, L. D., Beck, C. A., Feasby, T. E., & Ghali, W. A. (2005) · Medical Care · doi:10.1097/01.mlr.0000182534.19832.83 · Cited by 10,669 · see citing works
Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence
Singer, J. D., & Willett, J. B. (2003) · doi:10.1093/acprof:oso/9780195152968.001.0001 · Cited by 10,647 · see citing works
CDC Guideline for Prescribing Opioids for Chronic Pain—United States, 2016
Dowell, D., Haegerich, T. M., & Chou, R. (2016) · JAMA · doi:10.1001/jama.2016.1464 · Cited by 5,161 · see citing works
Association Between Opioid Prescribing Patterns and Opioid Overdose-Related Deaths
Bohnert, A. S. B. (2011) · JAMA · doi:10.1001/jama.2011.370 · Cited by 1,509 · see citing works
Trends in Opioid Prescribing by Race/Ethnicity for Patients Seeking Care in US Emergency Departments
Pletcher, M. J., Kertesz, S. G., Kohn, M. A., & Gonzales, R. (2008) · JAMA · doi:10.1001/jama.2007.64 · Cited by 826 · see citing works
Patterns of abuse among unintentional pharmaceutical overdose fatalities
Hall, A. J. (2008) · JAMA · doi:10.1001/jama.2008.802 · Cited by 815 · see citing works
Covariance Analysis of Censored Survival Data Using Log-Linear Analysis Techniques
Laird, N. M., & Olivier, D. (1981) · Journal of the American Statistical Association · doi:10.1080/01621459.1981.10477634 · Cited by 580 · see citing works
Park, T. W., Saitz, R., Ganoczy, D., Ilgen, M. A., & Bohnert, A. S. B. (2015) · BMJ · doi:10.1136/bmj.h2698 · Cited by 579 · see citing works
Sun, E. C., Dixit, A., Humphreys, K., Darnall, B. D., Baker, L. C., & Mackey, S. (2017) · BMJ · doi:10.1136/bmj.j760 · Cited by 534 · see citing works
Bohnert, A. S. B., Guy, G. P., & Losby, J. L. (2018) · Annals of Internal Medicine · doi:10.7326/m18-1243 · Cited by 413 · see citing works
No Shortcuts to Safer Opioid Prescribing
Dowell, D., Haegerich, T., & Chou, R. (2019) · New England Journal of Medicine · doi:10.1056/nejmp1904190 · Cited by 408 · see citing works
Singhal, A., Tien, Y.-Y., & Hsia, R. Y.-J. (2016) · PLoS ONE · doi:10.1371/journal.pone.0159224 · Cited by 305 · see citing works
Gender and prescription opioids: Findings from the National Survey on Drug Use and Health
Back, S. E., Payne, R. L., Simpson, A. N., & Brady, K. T. (2010) · Addictive Behaviors · doi:10.1016/j.addbeh.2010.06.018 · Cited by 240 · see citing works
Pain Management and the Opioid Epidemic
Board on Health Sciences Policy, Division, H. A. M., & National Academies of Sciences, E. (2017) · National Academies Press eBooks · doi:10.17226/24781 · Cited by 231 · see citing works
Kroenke, K., Alford, D. P., Argoff, C. E., Canlas, B. R., Covington, E. C., Frank, J. W., Haake, K. J., Hanling, S. R., Hooten, W. M., Kertesz, S. G., et al. (2018) · Pain Medicine · doi:10.1093/pm/pny307 · Cited by 220 · see citing works
Tapering Long-term Opioid Therapy in Chronic Noncancer Pain
Berna, C., Kulich, R. J., & Rathmell, J. P. (2015) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2015.04.003 · Cited by 217 · see citing works
Reuben, D. B., Alvanzo, A. A. H., Ashikaga, T., Bogat, G. A., Callahan, C. M., Ruffing, V., & Steffens, D. C. (2015) · Annals of Internal Medicine · doi:10.7326/m14-2775 · Cited by 191 · see citing works
Opioid Prescribing After Nonfatal Overdose and Association With Repeated Overdose
Larochelle, M. R., Liebschutz, J. M., Zhang, F., Ross‐Degnan, D., & Wharam, J. F. (2015) · Annals of Internal Medicine · doi:10.7326/m15-0038 · Cited by 185 · see citing works
Patterns of Opioid Use and Risk of Opioid Overdose Death Among Medicaid Patients
Garg, R. K., Fulton‐Kehoe, D., & Franklin, G. M. (2017) · Medical Care · doi:10.1097/mlr.0000000000000738 · Cited by 159 · see citing works
Prescription Opioid Taper Support for Outpatients With Chronic Pain: A Randomized Controlled Trial
Sullivan, M. D., Turner, J. A., DiLodovico, C., D'Appollonio, A., Stephens, K. A., & Chan, Y.-F. (2016) · Journal of Pain · doi:10.1016/j.jpain.2016.11.003 · Cited by 146 · see citing works
Opioid use behaviors, mental health and pain—Development of a typology of chronic pain patients
Banta‐Green, C. J., Merrill, J. O., Doyle, S. R., Boudreau, D. M., & Calsyn, D. A. (2009) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2009.03.021 · Cited by 137 · see citing works
Racial disparities in the monitoring of patients on chronic opioid therapy
Hausmann, L., Gao, S.-S., Lee, E. S., & Kwoh, K. (2013) · Pain · doi:10.1016/j.pain.2012.07.034 · Cited by 125 · see citing works
Darnall, B. D., Juurlink, D. N., Kerns, R. D., Mackey, S., Dorsten, B. V., Humphreys, K. N., Gonzalez-Sotomayor, J. A., Furlan, A. D., Gordon, A. J., Gordon, D. B., et al. (2018) · Pain Medicine · doi:10.1093/pm/pny228 · Cited by 119 · see citing works
Chermack, S. T., Walton, M. A., Fuller, B. E., & Blow, F. C. (2001) · Psychology of Addictive Behaviors · doi:10.1037/0893-164x.15.2.140 · Cited by 117 · see citing works
Gaither, J. R., Gordon, K. S., Crystal, S., Edelman, E. J., Kerns, R. D., Justice, A. C., Fiellin, D. A., & Becker, W. C. (2018) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2018.05.033 · Cited by 94 · see citing works
Jeffery, M. M., Hooten, W. M., Henk, H. J., Bellolio, F., Hess, E. P., Meara, E. R., Ross, J. S., & Shah, N. D. (2018) · BMJ · doi:10.1136/bmj.k2833 · Cited by 93 · see citing works
Opioid Cessation and Multidimensional Outcomes After Interdisciplinary Chronic Pain Treatment
Murphy, J. L., Clark, M. E., & Banou, E. (2013) · The Clinical Journal of Pain · doi:10.1097/ajp.0b013e3182579935 · Cited by 81 · see citing works
A Systematic Review of Insulin Adherence Measures in Patients with Diabetes
Stolpe, S., Kroes, M. A., Webb, N., & Wisniewski, T. (2016) · Journal of Managed Care & Specialty Pharmacy · doi:10.18553/jmcp.2016.22.11.1224 · Cited by 77 · see citing works
Medication-Assisted Treatment and Opioid Use Before and After Overdose in Pennsylvania Medicaid
Frazier, W. T., Cochran, G., Lo‐Ciganic, W., Gellad, W. F., Gordon, A. J., Chang, C. H., & Donohue, J. M. (2017) · JAMA · doi:10.1001/jama.2017.7818 · Cited by 72 · see citing works
Sex Differences Among Opioid-Abusing Patients With Chronic Pain in a Clinical Trial
Manubay, J. M., Davidson, J. W., Vosburg, S. K., Jones, J. D., Comer, S. D., & Sullivan, M. A. (2014) · Journal of Addiction Medicine · doi:10.1097/adm.0000000000000086 · Cited by 61 · see citing works
Race and Gender Are Associated with Opioid Dose Reduction Among Patients on Chronic Opioid Therapy
Buonora, M. J., Perez, H. R., Heo, M., Cunningham, C. O., & Starrels, J. L. (2018) · Pain Medicine · doi:10.1093/pm/pny137 · Cited by 52 · see citing works
Prescription Opioid Aberrant Behaviors
Back, S. E., Payne, R. A., Waldrop, A. E., Smith, A. D., Reeves, S. T., & Brady, K. T. (2009) · Clinical Journal of Pain · doi:10.1097/ajp.0b013e31819c2c2f · Cited by 50 · see citing works
Fitting Parametric Counting Processes by Using Log-Linear Models
Lindsey, J. K. (1995) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2986345 · Cited by 49 · see citing works
Choo, E. K., Benz, M. B., Rybarczyk, M. M., Broderick, K. B., Linden, J. A., Boudreaux, E. D., & Ranney, M. L. (2014) · Academic Emergency Medicine · doi:10.1111/acem.12525 · Cited by 16 · see citing works
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Avery, N., McNeilage, A. G., Stanaway, F., Ashton-James, C. E., Blyth, F. M., Martin, R., Gholamrezaei, A., & Glare, P. (2022) · BMJ · doi:10.1136/bmj-2021-066375 · Cited by 56 · see citing works
Abie Horowitz, M., Framer, A., Strang, J., & Taylor, D. (2025) · Therapeutic Advances in Psychopharmacology · doi:10.1177/20451253251371504
“…34.0% of the original dose per month and more than a quarter of patients were tapering at a rate faster than 40% of their original dose per month, 43,49 even higher than the maximum rate recommended by the CDC. 1 Another study in China had similar findings: with 50.4% of patients tapered faster…”
Influential
- Authors
- Fenton, J. J., Agnoli, A. L., Xing, G., Hang, L., Altan, A. E., Tancredi, D. J., Jerant, A., & Magnan, E.
- Affiliations
- University of California, Davis (US)
- OptumLabs, Cambridge, Massachusetts
- Corresponding author
- Fenton, Joshua J.
- ORCID
- Venue
- JAMA Network Open
- Publisher
- American Medical Association (AMA)
- Published
- 2019-11-15
- Volume
- 2
- Issue
- 11
- Pages
- e1916271
- ISSN
- 2574-3805 (ISSN-L)
- PMC
- PMC6902834
- OpenAlex
- W2986258467
- Cited by
- 97
- References
- 34
- Citations by year
- 2026: 9 · 2025: 14 · 2024: 11 · 2023: 14 · 2022: 21 · 2021: 17 · 2020: 11
- FWCI
- 11.28
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JAMA Network Open (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- University of California, Davis
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (K12AR084220)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (K12HD051958)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Opioid Use Disorder Treatment
- Health Sciences › Medicine › Anesthesiology and Pain Medicine › Pain Management and Opioid Use
- Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
- Keywords
- long-term opioid therapy, opioid prescribing trends, morphine milligram equivalents, sex differences, chronic pain management, opioid prescribing guidelines, Medicare Advantage enrollees, opioid overdose risk, opioid use disorder risk, opioid-related deaths
- MeSH terms
- Adolescent, Adult, Age Factors, Aged, Analgesics, Opioid, Female, Medicare, Humans, Male, Middle Aged, Practice Patterns, Physicians', Retrospective Studies, Sex Factors, United States, Young Adult
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