Risk factors for indicators of opioid-related harms amongst people living with chronic non-cancer pain: Findings from a 5-year prospective cohort study

doi:10.1016/j.eclinm.2020.100592

. 2020 Oct 16:28:100592.

doi: 10.1016/j.eclinm.2020.100592. eCollection 2020 Nov.

Risk factors for indicators of opioid-related harms amongst people living with chronic non-cancer pain: Findings from a 5-year prospective cohort study

Gabrielle Campbell^{1

2}, Firouzeh Noghrehchi³, Suzanne Nielsen^{1

4}, Phillip Clare¹, Raimondo Bruno^{1

5}, Nicholas Lintzeris^{6

7}, Milton Cohen^{1

8}, Fiona Blyth⁹, Wayne Hall^{10

11}, Briony Larance^{1

12}, Phillip Hungerford¹, Timothy Dobbins¹³, Michael Farrell¹, Louisa Degenhardt^{1

14}

Affiliations

¹ National Drug and Alcohol Research Centre, UNSW, Sydney, Australia.
² School of Health and Sport Sciences, University of the Sunshine Coast, USC, Locked Bag 4, Maroochydore, DC QLD 4558, Australia.
³ School of Medical Sciences-Pharmacology, University of Sydney, NSW, Australia.
⁴ Monash Addiction Research Centre, Monash University, Melbourne, Australia.
⁵ School of Medicine, University of Tasmania, Australia.
⁶ Discipline of Addiction Medicine, University of Sydney, Australia.
⁷ The Langton Centre, South East Sydney Local Health District (SESLHD) Drug and Alcohol Services, Australia.
⁸ St Vincent's Clinical School, Faculty of Medicine, UNSW, Sydney, Australia.
⁹ Centre for Education and Research on Ageing, University of Sydney, Concord Hospital, Sydney, Australia.
¹⁰ Centre for Youth Substance Abuse Research, University of Queensland, QLD, Australia.
¹¹ National Addiction Centre, Kings College, London United Kingdom.
¹² School of Psychology, University of Wollongong, Wollongong, Australia.
¹³ School of Public Health and Community Medicine, UNSW, NSW Australia.
¹⁴ School of Population and Global Health, University of Melbourne, Australia.

PMID: 33294810
PMCID: PMC7700907
DOI: 10.1016/j.eclinm.2020.100592

Risk factors for indicators of opioid-related harms amongst people living with chronic non-cancer pain: Findings from a 5-year prospective cohort study

Gabrielle Campbell et al. EClinicalMedicine. 2020.

. 2020 Oct 16:28:100592.

doi: 10.1016/j.eclinm.2020.100592. eCollection 2020 Nov.

Authors

Affiliations

¹ National Drug and Alcohol Research Centre, UNSW, Sydney, Australia.
² School of Health and Sport Sciences, University of the Sunshine Coast, USC, Locked Bag 4, Maroochydore, DC QLD 4558, Australia.
³ School of Medical Sciences-Pharmacology, University of Sydney, NSW, Australia.
⁴ Monash Addiction Research Centre, Monash University, Melbourne, Australia.
⁵ School of Medicine, University of Tasmania, Australia.
⁶ Discipline of Addiction Medicine, University of Sydney, Australia.
⁷ The Langton Centre, South East Sydney Local Health District (SESLHD) Drug and Alcohol Services, Australia.
⁸ St Vincent's Clinical School, Faculty of Medicine, UNSW, Sydney, Australia.
⁹ Centre for Education and Research on Ageing, University of Sydney, Concord Hospital, Sydney, Australia.
¹⁰ Centre for Youth Substance Abuse Research, University of Queensland, QLD, Australia.
¹¹ National Addiction Centre, Kings College, London United Kingdom.
¹² School of Psychology, University of Wollongong, Wollongong, Australia.
¹³ School of Public Health and Community Medicine, UNSW, NSW Australia.
¹⁴ School of Population and Global Health, University of Melbourne, Australia.

PMID: 33294810
PMCID: PMC7700907
DOI: 10.1016/j.eclinm.2020.100592

Abstract

Background: The literature suggests patient characteristics and higher opioid doses and long-term duration are associated with problematic opioid behaviours but no one study has examined the role of all these factors simultaneously in a long-term prospective cohort study.

Methods: Five-year, community-based, prospective cohort of people prescribed opioids for chronic non-cancer pain (CNCP). Logistic mixed effect models with multiple imputation were used to address missing data. Oral morphine equivalent (OME) mg per day was categorised as: 0 mg OME/day, 1-49 mg OME/day (reference), 50-89 mg OME/day, 90-199 mg OME/day and 200mg+ OME/day. Patient risk factors included: age, gender, substance use, mental health history and pain-related factors. Main outcomes included: Prescribed Opioids Difficulties Scale (PODS), Opioid-Related Behaviours In Treatment (ORBIT) scale, and ICD-10 opioid dependence. Multiple confounders for problematic opioid behaviours were assessed.

Findings: Of 1,514 participants 44.4% were male (95%CI 41.9-46.9) and their mean age was 58 years (IQR 48-67). Participants had a mean duration of pain of 10 years (IQR 4.5-20.0) and had been taking strong opioids for a median of four years (IQR 1.0-10.0). At baseline, median OME/day was 73 (IQR 35-148). At 5-years, 85% were still taking strong opioids. PODS moderate-high scores reduced from 59.9% (95%CI 58.8-61.0) at baseline to 51.5% (95%CI 50.0-53.0) at 5-years. Around 9% met criteria for ICD-10 opioid dependence at each wave. In adjusted mixed effect models, the risk factors most consistently associated with problematic opioid use were: younger age, substance dependence, mental health histories and higher opioid doses.

Interpretation: Both patient risk factors and opioid dose are associated with problematic opioid use behaviours.

Keywords: Chronic non-cancer pain; Cohort; Dependence; Extra medical use; Pharmaceutical opioid.

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Conflict of interest statement

GC, LD, MF, RB, MC and SN report grants for the conduct of this study from the National Health and Medical Research Centre (NHMRC). The funder had no input into the design, conduct, data collection, analyses or publication of study findings In the past 36 months some authors have received investigator-driven untied educational grants for unrelated work from Indivior (LD, BL, MF, SN), Mundipharma (MF, RB, NL), Seqirus (LD, MF, BL, SN) and Camurus AB (NL). No company had input into the design, conduct, data collection, analyses or publication of study findings. All other authors have no conflicts of interest to declare.

Figures

**Fig. 1**
STROBE flow diagram for the pain and opioids IN treatment (POINT) cohort.

**Fig. 2**
Average daily opioid utilisation (oral morphine equivalent (OME) mg per day) in the POINT cohort. Note: coloured bands show 95% confidence interval around each point. Only data is presented on people who reported opioid use in the past week via the medication diary. Since all participants were prescribed opioids at baseline entry there is no participants on 0 OME at baseline (see Appendix A for details).

**Fig. 3**
Prevalence of problematic outcomes according to average daily opioid utilisation (oral morphine equivalent (OME) per day) in the POINT cohort (non-imputed data) (95%CI). Notes: Opioid dependence are presented for lifetime for baseline and past 12 months for other waves. Opioid dependence not collected at 1-year. Since all participants were prescribed opioids at baseline entry there is no participants on 0 OME at baseline See Appendix C for details.

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References

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[1] Kolodny A., Courtwright D.T., Hwang C.S. The prescription opioid and heroin crisis: a public health approach to an epidemic of addiction. Annu Rev Public Health. 2015;36:559–574. - PubMed

[2] Kolodny A., Courtwright D.T., Hwang C.S. The prescription opioid and heroin crisis: a public health approach to an epidemic of addiction. Annu Rev Public Health. 2015;36:559–574. - PubMed

[3] Busse J.W., Craigie S., Juurlink D.N. Guideline for opioid therapy and chronic noncancer pain. CMAJ. 2017;189(18):E659–E666. - PMC - PubMed

[4] Busse J.W., Craigie S., Juurlink D.N. Guideline for opioid therapy and chronic noncancer pain. CMAJ. 2017;189(18):E659–E666. - PMC - PubMed

[5] Curtis H.J., Croker R., Walker A.J., Richards G.C., Quinlan J., Goldacre B. Opioid prescribing trends and geographical variation in England, 1998–2018: a retrospective database study. Lancet Psychiatry. 2019;6(2):140–150. - PubMed

[6] Curtis H.J., Croker R., Walker A.J., Richards G.C., Quinlan J., Goldacre B. Opioid prescribing trends and geographical variation in England, 1998–2018: a retrospective database study. Lancet Psychiatry. 2019;6(2):140–150. - PubMed

[7] Karanges E.A., Blanch B., Buckley N.A., Pearson S.A. Twenty-five years of prescription opioid use in Australia: a whole-of-population analysis using pharmaceutical claims. Br J Clin Pharmacol. 2016;82(1):255–267. - PMC - PubMed

[8] Karanges E.A., Blanch B., Buckley N.A., Pearson S.A. Twenty-five years of prescription opioid use in Australia: a whole-of-population analysis using pharmaceutical claims. Br J Clin Pharmacol. 2016;82(1):255–267. - PMC - PubMed

[9] Chou R., Turner J.A., Devine E.B. The effectiveness and risks of long-term opioid therapy for chronic pain: a systematic review for a national institutes of health pathways to prevention workshop. Ann Intern Med. 2015;162(4):276–286. - PubMed

[10] Chou R., Turner J.A., Devine E.B. The effectiveness and risks of long-term opioid therapy for chronic pain: a systematic review for a national institutes of health pathways to prevention workshop. Ann Intern Med. 2015;162(4):276–286. - PubMed

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Risk factors for indicators of opioid-related harms amongst people living with chronic non-cancer pain: Findings from a 5-year prospective cohort study

Affiliations

Risk factors for indicators of opioid-related harms amongst people living with chronic non-cancer pain: Findings from a 5-year prospective cohort study

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Affiliations

Abstract

Conflict of interest statement

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