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Patterns and predictors of opioid dispensing among older cancer patients from 2008 to 2015
Yingxi Chen1, Yei-Eun Shin2,3, Susan Spillane1
1Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA.
Background:
Understanding factors associated with opioid dispensing in cancer patients is important for developing tailored guidelines and ensuring equitable access to pain management. We examined patterns and predictors of opioid dispensing among older cancer patients from 2008 to 2015.
Methods:
We analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database linked to Medicare claims. We included the most common cancer types among patients aged 66-95 years. Opioids dispensed within 30 days before and 120 days after cancer diagnosis were assessed. We used logistic regression models to examine trends, adjusted odds ratios (aORs), and 95% confidence intervals (CIs) for opioid dispensing, considering patient demographics, geography, cancer stage, comorbidities, and treatment options. Models were stratified by sex.
Results:
A total of 211,759 cancer patients aged 66-95 years were included in the study. For cancers combined, non-Hispanic Black men had a significantly lower odds of receiving opioids during the 120 days post-diagnosis (aOR = 0.89, 95% CI = 0.84-0.94) compared to non-Hispanic White men. Factors such as pre-diagnosis opioid dispensing, age, geography, cancer stage, comorbidities, and type of cancer treatment were associated with opioid dispensing during the 120 days post-diagnosis. Surgery had the strongest association, with men undergoing surgery being 4.4 times more likely to receive opioids within 120 days post-diagnosis (aOR = 4.41, 95% CI = 4.23-4.60), while women had an odds ratio of 2.72 (95% CI = 2.62-2.83). Chemotherapy and radiotherapy were also positively associated with opioid dispensing, with less pronounced estimates.
Conclusions:
We observed significant variations in opioid dispensing among cancer patients aged 66-95 years across cancer types and demographic and clinical factors.
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