Table 1.
Author, year | Title | Objective | Time, study design and appraisal score | Setting and sample | Opioid use | Opioid misuse and associated factors |
---|---|---|---|---|---|---|
Bertrand, 2016 | Does consumption of tobacco, alcohol, and cannabis in adolescents and young adults with cancer affect the use of analgesics during hospitalizations? | To examine how exposure to tobacco and/or cannabis and/or alcohol is associated with opioid analge sics in AYAs with cancer during hospitalizations | 6 months during 2013 Cross-sectional survey JBI Score 5 | Two cancer centers in France N= 30 age 15–25 years with cancer, active therapy | 40% of low-use consumers and 79% high-use consumers (of alcohol and tobacco) self-reported taking opioids | N/A |
Cheung, 2020 | Prescription Psychoactive Medication Use in Adolescent Survivors of Childhood Cancer and Association With Adult Functional Outcomes | To estimate the prevalence of psychoactive medication use in adolescent survivors of childhood cancer and its associations with functional outcomes at young adulthood | Diagnosed with cancer between 1970 and 1999 Retrospective case control JBI Score: 7 |
The Childhood Cancer Survivor Study N = 5665 survivors of childhood cancer ages 13–16 years; N = 921 siblings |
5.7% of survivors compared to 1.7% of siblings (p < .001) self-reported using opioids for > 1 month in the prior 2 years | N/A |
Ehrentraut, 2014 | Opioid misuse behaviors in adolescents and young adults in a hematology/oncology setting | To examine opioid misuse behaviors in AYAs treated for cancer at a large, pediatric oncology center and to identify risk factors for aberrant use | Jan 2012-May 2013 Retrospective cohort JBI Score: 7 | TN, USA N = 398 age 12–33 years with cancer, active therapy | 24% were prescribed opioids | 12% exhibited aberrant behaviors No significant association between aberrant behaviors and MH/family hx of SU but trend toward significance (p = 0.06) |
Getz, 2018 | Opioid utilization among pediatric patients treated for newly diagnosed acute myeloid leukemia | To examine opioid prescribing and utilization for children with newly diagnosed AML | 2000–2014 Retrospective cohort JBI Score: 8 | PHIS database N = 1600 age 1–20 years with AML, active therapy | 78% received opioids | N/A |
Hewitt, 2008 | Opioid Use in Palliative Care of Children and Young People with Cancer | To examine opioid use for children and adolescents with cancer during the last month of life | 20-month period Prospective, longitudinal cohort JBI Score: 6 | 3 cancer centers in UK N = 185 age 0–19 years, end-of-life | 90% received opioids | N/A |
Madden, 2020 | Patterns of Storage, Use, and Disposal of Prescription Opioids by Parents of Children with Cancer | To describe opioid use and storage patterns reported by parents of children with cancer | Feb-Nov 2018 Cross-sectional survey JBI Score: 6 | TX, USA N = 109 parents of children age <18 years with cancer, active therapy | 97% self-reported their chil dren used opioids | 90% did not store safely; 21% did not use safely with patient; 6% gave to other than patient |
Monteiro, 2005 | Clinical Aspects and Treatment of Pain in Children and Adolescents with Cancer | To examine pain control and analgesic prescribing for children and adolescents with cancer and non-procedure related pain | 2000–2003 Prospective, longitudinal cohort JBI Score: 7 | Pediatric hospital in Brazil N = 135 age 1–20 years, active therapy | 88% received opioids | N/A |
Murphy, 2019 | Pain and opioid prescriptions vary by procedure after breast surgery. | To examine post-operative pain and opioid prescribing for women after breast surgery | 2010–2016 Retrospective cohort JBI Score: 8 | 3 cancer centers in US N = 4021 18 years+ women s/p mastectomy (5% age 18–39 years) | 94% were prescribed opioids | 22% received higher discharge dose (Q4 MME) Age 30–39 y had 1.85 higher odds of receiving higher dose compared to age > 80 years (p < 0.05) |
Orsey, 2009 | Variation in receipt of opioids by pediatric oncology patients who died in children’s hospitals | To describe daily opioid use compared to intermittent use during last week of life for children with cancer who died in the hospital | 2001–2005 Retrospective cohort JBI Score: 7 | PHIS database N = 1466 age 0–24 years with cancer, end-of-life | 56% received daily opioids | N/A |
Smitherman, 2018 | Early Post-Therapy Prescription Drug Usage among Childhood and Adolescent Cancer Survivors | To examine prescription types and quantities for survivors of childhood cancer | Completed treatment between 2000 and 2011 Retrospective case control JBI Score: 8 |
Marketscan database N= 1414 mean age 9.3–17.4 years at least 3 years off-therapy | 12–46% were prescribed opioids by disease type (highest proportion in bone tumors) | N/A |
Thienprayoon, 2017 | Risk Stratification for Opioid Misuse in Children, Adolescents, and Young Adults: A Quality Improvement Project | To use an opioid bundle to increase risk stratification for opioid misuse among patients who present for follow up with Pediatric Advanced Care Team | 2014–2015 Prospective, pre-post JBI Score: 6 | Single cancer center in OH, USA N = 106 age 3–33 years with cancer/BMT; n = 62 were risk-stratified, active therapy | 58% received opioids | 34% were classified as high-risk for opioid misuse |
Wright, 2019 | Use and Misuse of Opioids After Gynecologic Surgical Procedures | To examine the rate of opioid use for gynecologic surgical procedures and to investigate persistent opioid use among those women who received an initial opioid prescription | 2009–2016 Retrospective cohort JBI Score: 7 | Marketscan database N = 729,000 women 6.1% age 18–29 years 25.1% age 30–39 years | Among 18–29 years: 64.5% were prescribed Among 30–39 years: 63.1 % were prescribed opioids |
Among 18–29 years: 9.8% were new, persistent users post— operatively Among 30–39 years: 7.7% were new, persistent users post— operatively Younger patients, Medicaid recipients, and patients with depression, anxiety, and substance use disorder all associated with new persistent use (p < .001) |