Concurrent Opioid and Benzodiazepine Prescriptions Among Older Women Diagnosed With Breast Cancer

Why and How to Integrate Early Palliative Care Into Cutting-Edge Personalized Cancer Care

Early palliative care, palliative care integrated with oncology care early in the course of illness, has myriad benefits for patients and their caregivers, including improved quality of life, reduced physical and psychological symptom burden, enhanced prognostic awareness, and reduced health care utilization at the end of life. Although ASCO and others recommend early palliative care for all patients with advanced cancer, widespread implementation of early palliative care has not been realized because of barriers such as insufficient reimbursement and a palliative care workforce shortage. Investigators have recently tested several implementation strategies to overcome these barriers, including triggers for palliative care consultations, telehealth delivery, navigator-delivered interventions, and primary palliative care interventions. More research is needed to identify mechanisms to distribute palliative care optimally and equitably. Simultaneously, the transformation of the oncology treatment landscape has led to shifts in the supportive care needs of patients and caregivers, who may experience longer, uncertain trajectories of cancer. Now, palliative care also plays a clear role in the care of patients with hematologic malignancies and may be beneficial for patients undergoing phase I clinical trials and their caregivers. Further research and clinical guidance regarding how to balance the risks and benefits of opioid therapy and safely manage cancer-related pain across this wide range of settings are urgently needed. The strengths of early palliative care in supporting patients' and caregivers' coping and centering decisions on their goals and values remain valuable in the care of patients receiving cutting-edge personalized cancer care.

Characterising incident opioid use among incident users of prescription sedative hypnotics: A national cohort study

OBJECTIVE

To evaluate co-prescribing of sedatives hypnotics and opioids.

DESIGN

Retrospective study evaluating the association of patient characteristics and comorbidities with coprescribing.

SETTING AND PARTICIPANTS

Using the national Merative MarketScan Database between 2005 and 2018, we identified patients who received an incident sedative prescription with or without subsequent, incident opioid prescriptions within a year of the sedative prescription in the USA.

OUTCOME MEASURES

Coprescription of sedative-hypnotics and opioids.

RESULTS

A total of 2 632 622 patients (mean (SD) age, 43.2 (12.34) years; 1 297 356 (62.5%) female) received incident prescriptions for sedatives over the course of the study period. The largest proportion of sedative prescribing included benzodiazepines (71.1%); however, z-drugs (19.9%) and barbiturates (9%) were also common. About 557 845 (21.2%) patients with incident sedatives also received incident opioid prescriptions. About 59.2% of these coprescribed patients received opioids coprescription on the same day. Multivariate logistic regression findings showed that individuals with a comorbidity index score of 1, 2 or ≥3 (aOR 1.19 (95% CI 1.17 to 1.21), 1.17 (95% C 1.14 to 1.19) and 1.25 (95% C 1.2 to 1.31)) and substance use disorder (1.21 (95% C 1.19 to 1.23)) were more likely to be coprescribed opioids and sedatives. The likelihood of receiving both opioid and sedative prescriptions was lower for female patients (aOR 0.93; 95% CI 0.92 to 0.94), and those receiving a barbiturate (aOR 0.3; 95% CI 0.29 to 0.31) or z-drugs (aOR 0.67; 95% CI 0.66 to 0.68) prescriptions at the index date.

CONCLUSIONS

Coprescription of sedatives with opioids was associated with the presence of comorbidities and substance use disorder, gender and types of sedatives prescribed at the index date. Additionally, more than half of the coprescribing occurred on the same day which warrants further evaluation of current prescribing and dispensing best practice guidelines.

Productivity Loss Among Opioid and Benzodiazepine Users in the United States: A Medical Expenditure Panel Survey From 2010 to 2019

OBJECTIVE

The aim of the study is to estimate the association between productivity losses and the use of prescription opioids and benzodiazepines among employed US adults with painful conditions.

METHODS

Using Medical Expenditures Panel Survey (2010-2019), we used two-part (logistic regression and generalized linear model with zero-truncated negative binomial link) model to compare missed workdays due to illness or injury among employed adults with a painful condition.

RESULTS

Of the eligible sample of 57,413 working US individuals, 14.65% were prescription opioid users, 2.95% were benzodiazepine users, and 1.59% were both opioid and benzodiazepine users. The predicted missed workdays were 5.75 (95% Confidence Limit [CL]: 5.58-5.92) days for benzodiazepine users, 13.06 (95% CL: 12.88-13.23) days among opioid users, and 15.18 (95% CL: 14.46-15.90) days for opioid and benzodiazepine concomitant users.

CONCLUSIONS

Concomitant use of prescription opioids and benzodiazepines was significantly associated with having more missed workdays among employed adults with documented painful conditions.

Opioid use by cancer status and time since diagnosis among older adults enrolled in the Prostate, Lung, Colorectal, and Ovarian screening trial in the United States

BACKGROUND

Dosing limits in opioid clinical practice guidelines in the United States are likely misapplied to cancer patients, however, opioid use may be difficult to ascertain as they are largely excluded from opioid use studies.

METHODS

The primary objective was to determine whether cancer patients were more likely to be chronic opioid users after diagnosis. We described prescription opioid use among U.S. older adult cancer patients during two time periods, within 2 years of diagnosis (short-term) and at least 2 years beyond diagnosis (long-term), compared to those without cancer (controls). Among participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) screening trial with linkages to Medicare Part D data during 2011-2015, we used multivariable logistic regression to estimate the association between cancer diagnosis and opioid use outcomes controlling for demographics. The primary outcome of opioid use was measured with the following metrics: Any opioid use, chronic use (90 consecutive days supply of opioid use while allowing for a 7-day gap between refills), high use (average daily morphine equivalent (MME) ≥120 mg for any 90-day period), and total MME dose above 2,000 mg (MME₂₀₀₀ ).

RESULTS

The short-term cohort included 1,491 cancer patients and 24,930 controls. Any use in the 2-year post-diagnosis period was higher among cancer patients OR 3.3 (95% CI: 3.0-3.7). Chronic use rates were similar by cancer status (4.6% vs. 3.8% for cases and controls, respectively). The long-term cohort included 4,377 cancer patients and 27,545 controls. Rates of any use were similar among cancer patients and controls (63% vs. 59%).

CONCLUSIONS

Any opioid use was similar among long-term cancer survivors compared to controls, but differed among short-term survivors for any opioid use and marginally for chronic opioid use.

The Use and Concurrent Use of Side Effect Controlling Medications Among Women on Aromatase Inhibitors

Background: Women on aromatase inhibitors (AIs) as part of their breast cancer treatment often experience difficult to control side effects. Although there are several medications to manage the side effects of AI therapy, many of them are associated with their own risk, particularly sedation. The objective of this study was to describe the prescribing practices for side effect managing (SE) medications among women with breast cancer on AI therapy and to assess for combinations of medications that may present a clinical risk to patients. Methods: Retrospective data analysis using Surveillance, Epidemiology and End Results (SEER)-Medicare data of all women aged 66-90 years with stage I-III hormone positive breast cancer diagnosed between 2008 and 2014 who initiated AI therapy within 12 months of their diagnosis. We determined the percentage of patients prescribed an SE medication in the 12 months prior and in the 24 months after the initiation of AI therapy. We calculated the number of prescriptions and the number of days of overlapping (i.e., >1 SE) prescriptions, and examined predictors of overlapping prescriptions. Results: The use of SE medications was pervasive and increased after initiation of AI therapy. The most commonly prescribed medications were opiates (55.1%), selective serotonin reuptake inhibitors (22.6%), benzodiazepines (18.4%), tramadol (17.7%) and gabapentin (14.6%). In total 15.5% of patients had overlapping prescriptions; among those, 36.2% had three overlapping prescriptions. Prior use was the strongest predictor of overlapping prescriptions with an odds ratio of 7.9 (95% confidence interval: 7.17-8.77). Conclusion: Among women on AI therapy, the use of SE medications is common and many have overlapping prescriptions raising concern for potential harm from polypharmacy.