Dosing profiles of concurrent opioid and benzodiazepine use associated with overdose risk among US Medicare beneficiaries: group-based multi-trajectory models

Association between trajectories of prescription opioid use and risk of opioid use disorder and overdose among US nonmetastatic breast cancer survivors

PURPOSE

To examine the association between prescription opioid use trajectories and risk of opioid use disorder (OUD) or overdose among nonmetastatic breast cancer survivors by treatment type.

METHODS

This retrospective cohort study included female nonmetastatic breast cancer survivors with at least 1 opioid prescription fill in 2010-2019 Surveillance, Epidemiology and End Results linked Medicare data. Opioid mean daily morphine milligram equivalents (MME) calculated within 1.5 years after initiating active breast cancer therapy. Group-based trajectory models identified distinct opioid use trajectory patterns. Risk of time to first OUD/overdose event within 1 year after the trajectory period was calculated for distinct trajectory groups using Cox proportional hazards models. Analyses were stratified by treatment type.

RESULTS

Four opioid use trajectories were identified for each treatment group. For 38,030 survivors with systemic endocrine therapy, 3 trajectories were associated with increased OUD/overdose risk compared with early discontinuation: minimal dose (< 5 MME; adjusted hazard ratio [aHR] = 1.73 [95% CI  1.43-2.09]), very low dose (5-25 MME; 2.67 [2.05-3.48]), and moderate dose (51-90 MME; 6.20 [4.69-8.19]). For 9477 survivors with adjuvant chemotherapy, low-dose opioid use was associated with higher OUD/overdose risk (aHR = 7.33 [95% CI 2.52-21.31]) compared with early discontinuation. For 3513 survivors with neoadjuvant chemotherapy, the differences in OUD/OD risks across the 4 trajectories were not significant.

CONCLUSIONS

Among Medicare nonmetastatic breast cancer survivors receiving systemic endocrine therapy or adjuvant chemotherapy, compared with early discontinuation, low-dose or moderate-dose opioid use were associated with six- to sevenfold higher OUD/overdose risk. Breast cancer survivors at high-risk of OUD/overdose may benefit from targeted interventions (e.g., pain clinic referral).

Deprescribing Strategies for Opioids and Benzodiazepines with Emphasis on Concurrent Use: A Scoping Review

While the Food and Drug Administration's black-box warnings caution against concurrent opioid and benzodiazepine (OPI-BZD) use, there is little guidance on how to deprescribe these medications. This scoping review analyzes the available opioid and/or benzodiazepine deprescribing strategies from the PubMed, EMBASE, Web of Science, Scopus, and Cochrane Library databases (01/1995-08/2020) and the gray literature. We identified 39 original research studies (opioids: n = 5, benzodiazepines: n = 31, concurrent use: n = 3) and 26 guidelines (opioids: n = 16, benzodiazepines: n = 11, concurrent use: n = 0). Among the three studies deprescribing concurrent use (success rates of 21-100%), two evaluated a 3-week rehabilitation program, and one assessed a 24-week primary care intervention for veterans. Initial opioid dose deprescribing rates ranged from (1) 10-20%/weekday followed by 2.5-10%/weekday over three weeks to (2) 10-25%/1-4 weeks. Initial benzodiazepine dose deprescribing rates ranged from (1) patient-specific reductions over three weeks to (2) 50% dose reduction for 2-4 weeks, followed by 2-8 weeks of dose maintenance and then a 25% reduction biweekly. Among the 26 guidelines identified, 22 highlighted the risks of co-prescribing OPI-BZD, and 4 provided conflicting recommendations on the OPI-BZD deprescribing sequence. Thirty-five states' websites provided resources for opioid deprescription and three states' websites had benzodiazepine deprescribing recommendations. Further studies are needed to better guide OPI-BZD deprescription.

Substance use disorders and social determinants of health from electronic medical records obtained during Kentucky's "triple wave"

Social determinants of health (SDOH) play a critical role in the risk of harmful drug use. Examining SDOH as a means of differentiating populations with multiple co-occurring substance use disorders (SUDs) is particularly salient in the era of prevalent opioid and stimulant use known as the "Third Wave". This study uses electronic medical records (EMRs) from a safety net hospital system from 14,032 patients in Kentucky from 2017 to 2019 in order to 1) define three types of SUD cohorts with shared/unique risk factors, 2) identify patients with unstable housing using novel methods for EMRs and 3) link patients to their residential neighborhood to obtain quantitative perspective on social vulnerability. We identified patients in three cohorts with statistically significant unique risk factors that included race, biological sex, insurance type, smoking status, and urban/rural residential location. Adjusting for these variables, we found a statistically significant, increasing risk gradient for patients experiencing unstable housing by cohort type: opioid-only (n = 7385, reference), stimulant-only (n = 4794, odds ratio (aOR) 1.86 95 % confidence interval (CI): 1.66-2.09), and co-diagnosed (n = 1853, aOR = 2.75, 95 % CI: 2.39 to 3.16). At the neighborhood-level, we used 8 different measures of social vulnerability and found that, for the most part, increasing proportions of patients with stimulant use living in a census tract was associated with more social vulnerability. Our study identifies potentially modifiable factors that can be tailored by substance type and demonstrates robust use of EMRs to meet national goals of enhancing research on social determinants of health.

Development of the gut microbiota in healthy twins during the first 2 years of life and associations with body mass index z-score: Results from the Wuhan twin birth cohort study

The gut microbiota undergoes rapid and vital changes to microbial community structure and the microbial-immune crosstalk during the first 3 years of life, which is thought to be involved in the pathobiology of later-life disease. Compared to single-born children, little is known about the gut microbiota of twins in early childhood. Based on the Wuhan Twin Birth Cohort study, 344 stool samples from 204 twin families were analyzed to investigate the difference in gut microbiota composition at 6, 12, and 24 months of age. Furthermore, this study evaluated the association between gut microbiota development curves and body mass index z-score (BMI_Z) curves at 6, 12, and 24 months of age. The predominant microbiota phyla identified in twins were Proteobacteria, Actinobacteriota, Firmicutes, Bacteroidota, and Verrucomicrobiota. The richness and diversity of gut microbiota increased from 6 to 24 months old (alpha diversity with p < 0.05). Beta diversity revealed 61 gut microbiota genera that were significantly different in relative abundance among the three age groups. Among the 61 gut microbiota genera, 30 distinct trajectory curves (DTCs) were generated by group-based trajectory models after log2 transformation of their relative abundance. Subsequently, Spearman correlation analysis revealed that only five gut microbiota DTC were correlated with the BMI_Z DTC. Therefore, we further examined the association between the five gut microbiota genera DTC and BMI_Z DTC using generalized estimation equation models. The results revealed a significant association between the DTC groups of Parabacteroides and that of BMI_Z (coefficient = 0.75, p = 0.04). The results of this study validated the hypothesis that the richness and diversity of gut microbiota developed with age in twins. Moreover, participants with a higher DTC of log2-transformed Parabacteroides had a higher BMI_Z DTC during the first 2 years of life. Further studies are needed to confirm the association between Parabacteroides and BMI_Z in other populations.