Does opioid agonist treatment reduce overdose mortality risk in people who are older or have physical comorbidities? Cohort study using linked administrative health data in New South Wales, Australia, 2002-17

Differences in heroin overdose deaths in Australia by age, 2020-2022: Disease and estimated survival times

Background

The age of people who use illicit opioids has increased, with a clinical picture of accelerated ageing. The study aimed to determine, stratified by age: 1. The circumstances and characteristics of heroin-related toxicity deaths in Australia, 2020-2022; 2. The toxicological profile and autopsy findings; 3. The proportion of cases in which blood 6-acetyl morphine (6AM) was detected, as a measure of survival time.

Methods

Retrospective study of 610 cases of fatal heroin-related drug toxicity in Australia, 2020-2022. Cases were stratified as: <30 years, 30-39 years, 40-49 years, ≥50 years.

Results

Compared to the youngest group, those aged ≥50 years were more likely to have a history of chronic pain (12.4 v 3.3 %), to have their death attributed to combined drug toxicity/disease (20.1 v 3.3 %), and to have evidence of a sudden collapse (21.3 v 11.1 %). There were no differences in free morphine concentrations or glucuronide concentrations. Compared to the youngest group, however, the two older groups were significantly more likely to have 6AM present in blood, a proxy measure of a shorter survival time (52.0, 55.2 v 34.5 %). Compared to the youngest group, cases aged ≥50 years were more likely to be diagnosed with cardiomegaly (44.0 v 16.7 %), coronary artery disease (46.0 v 15.0 %), emphysema (35.0 v 5.1 %), hepatic steatosis (15.4 v 3.4 %), hepatic fibrosis (17.6 v 3.4 %), and cirrhosis (19.8 v 0.0 %).

Conclusions

Older cases of heroin overdose had more extensive heart, lung, and liver disease, and appeared more likely to have shorter survival times.

Estimating effects of time-varying exposures on mortality risk

Administrative databases have become an increasingly popular data source for population-based health research. We explore how mortality risk is associated with some health service utilization process via linked administrative data. A generalized Cox regression model is proposed using a time-dependent stratification variable to summarize lifetime service utilization. Recognizing the service utilization over time as an internal covariate in the survival analysis, conventional likelihood methods are inapplicable. We present an estimating function based procedure for estimating model parameters, and provide a testing procedure for updating the stratification levels. The proposed approach is examined both asymptotically and numerically via simulation. We motivate and illustrate the proposed approach using an on-going program pertaining to opioid agonist treatment (OAT) management for individuals identified with opioid use disorders. Our analysis of the OAT data indicates that the OAT effect on mortality risk decreases in successive OAT attempts, in which two risk classes based on an individual's treatment episode number are established: one with 1-3 OAT episodes, and the other with 4+ OAT episodes.