Long-Term Prescription Opioid Use, Cancer Stage, and Economic Burden among Older Cancer Survivors with Non-Cancer Chronic Pain Conditions

Opioids are commonly prescribed to treat pain conditions, which are highly prevalent among older adults (≥65 years). Recent evidence shows that opioids may have carcinogenic effects through immunosuppression and free-radical pathways, which could promote cancer growth. Two population-based studies have reported an association of opioid use with incident cancer. Many individuals with non-cancer chronic pain conditions (NCPCs) may use opioids for a long term. However, the association of long-term prescription opioid (LPO) use with cancer stage at diagnosis is still unknown. Furthermore, evidence suggests that individuals with cancer and pre-existing NCPCs may persistently use opioids, even in the absence of cancer progression due to opioid-induced hyperalgesia and the effects of tolerance. To date, no studies have explored the opioid use trajectory covering before and after cancer diagnosis phases. In addition, prescription opioids are also well-established for their potential adverse effects on multiple organ systems, especially among older adults. These negative effects may result in hospitalization and the need for more medications leading to an additional financial burden. This can lead to a higher out-of-pocket expenditure burden for the patients and families. The literature is limited on the effects of opioid use on the economic burden, especially out-of-pocket expenditure suffered by older adults with cancer and NCPCs. Therefore, this dissertation pursued three specific aims using population-based data on older adults: 1) to investigate the association of duration of prescription opioid use with cancer stage at diagnosis among Medicare beneficiaries with pre-existing NCPCs; 2) to examine trajectories of prescription opioid use over time and factors associated with these trajectories among older cancer survivors with any NCPC; and 3) to estimate the excess out-of-pocket expenditures and out-of-pocket expenditure burden of prescription opioid use among older cancer survivors with NCPCs. This study utilized data from multiple sources to completely understand the outcomes. Aims 1 and 2 were retrospective cohort studies designed using Surveillance, Epidemiology, and End Results (SEER)-Medicare claims data, zip-code and census tract-level data for the beneficiaries living in the SEER-region, and Area Healthcare Resource Use Files (AHRF) from the years 2007 through 2015. Aim 3 was a cross-sectional study using multiple years (2017, 2018, and 2019) of the Medical Expenditure Panel Survey, a nationally representative survey of non-institutionalized civilian population. In the Aim-1 SEER-Medicare study cohort, 10.9% (one in nine) older adults had LPO use during 12 months before cancer, and 19.5% were diagnosed with advanced-stage (stages 3 and 4) cancers. A higher percentage of individuals with LPO use had advanced cancer compared to no opioid users (21% vs. 19%; p \u3c 0.01). The fully adjusted logistic regression revealed that LPO use (AOR: 1.11, 95%CI= 1.03,1.19) was significantly associated with higher odds of advanced-stage cancer than the no-opioid use group. In aim 2, the group-based trajectory modeling (GBTM) identified four distinct trajectories of opioid use: 1) increase-decrease use (6.1%); 2) short-term use after cancer diagnosis (40.6%); 3) low-use (41.0%); and 4) persistent use (12.3%). In the fully adjusted multinomial logistic regression, the SDoH such as Non-Hispanic Black (AOR = 1.69; 95%CI = 1.48, 1.93) and rural residence (AOR=1.49; 95%CI = 1.15, 1.94)], comorbid anxiety (AOR=1.33; 95%CI = 1.18, 1.51), and medication use (NSAIDs- AOR = 1.20; 95%CI = 1.10, 1.30,) were associated with membership in the persistent use group. Persistent use was less likely among those with higher fragmented care index (AOR = 0.95, 95%CI = 0.93, 0.97) and those living in counties with higher Medicare advantage penetration (AOR = 0.96; 95%CI = 0.95, 0.97). In aim 3, 26.7% received at least one opioid prescription. A higher percentage of individuals with opioid use experience a high out-of-pocket expenditure burden (27.2% vs. 16.5%) than those without opioid use. In the IPW-adjusted logistic regression model, opioid users were more likely to have a high out-of-pocket expenditure burden (AOR: 1.76; 95%CI: 1.40, 2.55; p=0.0015). The average out-of-pocket expenditures, including prescription medication (RX) costs were $2,056.28, and without RX costs were $1,489.44. In the GLM and log link (without IPW), we found a significant difference in mean total out-of-pocket expenditures between opioid users and non-users ($2,348.63 vs. $1,949.86, p=0.033); however, no difference was found when out-of-pocket expenditures did not include prescription drug expenditures ($1,619.54 vs. $1,441.45, p=0.266). The IPW-adjusted regression analyses found no significant differences between opioid users and non-users in total out-of-pocket expenditures ($2,237.15 vs. $1,956.31, p=0.152) and out-of-pocket expenditures that did not include prescription drug spending ($1,600.64 vs. $1,425.67, p=0.299). Overall, the findings from this dissertation highlighted the emerging cancer-related risk associated with opioids, the prevalence of “persistent” use of opioids over three years, and the high out-of-pocket expenditure burden of opioid use among older cancer survivors with NCPCs. The findings from the three studies can inform public policy, practice, and research. For example, the finding from the first aim can guide decision-making to reduce the potential for opioids’ negative clinical cancer-related risks and to prevent the misuse/abuse of opioids due to their long-term use. Regarding the subgroup population more likely to be in the “persistent opioid uses,” stakeholders need to provide strategies to begin and maintain opioid high-use recoveries that consider intra- and inter-individual variability. The study findings also reinforce the need for linking opioid prevention and control strategies across multiple sectors (community/social support, infrastructure, education, and employers) and integrating “health in all policies.” Finally, the association of opioid use with high out-of-pocket expenditure burden indicates the necessity to reduce the financial burden of healthcare on individuals and families. Well-designed strategies, e.g., financing mechanisms and health service delivery, may be needed to help cancer survivors reduce out-of-pocket costs