Mortality prior to, during and after opioid maintenance treatment (OMT): A national prospective cross-registry study
Introduction
Mortality among untreated opioid dependents is internationally estimated with relatively wide variations; between 1 and 4 per 100 person years (Amato et al., 2005, Bargagli et al., 2006, Concool et al., 1979, Darke et al., 2007, Hser et al., 1993, Oppenheimer et al., 1994, Rossow and Lauritzen, 1999). As the majority of deaths among opiate dependents are reported to be overdose-related (Darke and Hall, 2003, Digiusto et al., 2004, Gossop et al., 2002), the level of overdose mortality is particularly influential.
Further, the level of mortality in a given population will be influenced by gender, age, drug administration, personality, general health status and treatment availability (Darke et al., 2007). The extent to which drug treatment is provided and easily accessible to dependent drug users, will impact substantially upon the rates of drug-related mortality amongst these populations (Darke et al., 2007). As risk reduction is influenced by baseline mortality, variation in mortality levels across different populations of illicit drug users is thus the result.
Opioid maintenance treatment (OMT) is generally considered to be the most important harm-reducing measure (Darke et al., 2007, van den Brink and Haasen, 2006, Zador, 2007), and it is often stated that “OMT saves lives” (Brugal et al., 2005, Gunne and Gronbladh, 1981). While the evidence favours this view, there are several weaknesses in the research that underlie these results, particularly in regard to level of risk reduction. Still, estimating the level of risk reduction might be important both in treatment policy, in balancing the need for control with the need for availability, and in the management of the individual patients.
However tragic, overdose deaths occur statistically infrequently, and research will need both adequate population size and follow-up period to attain sufficient statistical strength. Mortality has been included in the outcome measures of some randomized clinical trials (RCTs) with short follow-up periods, with little or no significant mortality reducing effects found (Dole et al., 1969, Strain et al., 1993). Even within opioid-dependent populations, research designs with large samples and long-term follow-up are needed, but difficult to apply in RCTs, in order to firmly examine mortality reducing effects. (Faggiano et al., 2003). A systematic review concludes that it is not proven that OMT significantly reduces mortality (Amato et al., 2005). Nonetheless, the results from OMT research have been divergent on the issue. In a Swedish study, a clinical trial comparing buprenorphine maintenance to medically supervised buprenorphine withdrawal, observed a statistically significant difference in mortality rates favouring buprenorphine maintenance (Kakko et al., 2003). However, there are some problems comparing mortality after detoxification with that in treatment, and the findings might be disputed as the study size was rather small. Some years ago, Gunne compared a population-denied entrance to OMT with a group accepted for methadone maintenance treatment and found marked differences in mortality (Gunne and Gronbladh, 1981). However, that study was performed in a situation of policy conflict in Sweden and the group-denied treatment were in a rather vulnerable situation.
The mortality-reducing effects of OMT are primarily established through observational studies. However, these often exclude dropouts, sometimes lack clear selection criteria for treatment or might be seen as local area studies difficult to generalise from (Hser et al., 1993, Kleinman et al., 1977, Nich and Carroll, 2002). Findings are, as a result, mostly applicable to those selected by the treatment unit and maintained in treatment. Even well designed cohort studies face challenges with persons lost to follow-up (Soyka et al., 2006, Termorshuizen et al., 2005).
Programme characteristics such as treatment approach, inclusion and exclusion criteria may vary. Comparison of effect of different OMT programmes in different countries or regions is therefore not always appropriate. For example, a recent study from Stockholm found no opiate overdose deaths in their OMT population. However, the Stockholm programme did not include polydrug users and excluded patients with concurrent use of drugs (Fuglestad et al., 2007). The in-treatment effects of such a programme will be favourable, but the generalization is difficult.
In Norway, OMT is founded as a national system encompassing all systematic maintenance treatment offered (Waal, 2007). Applicants wait for treatment for some time, enabling a waiting list design, and establishing a pre-treatment mortality level within the study population.
Patient registers include information on periods both in and out of treatment.
According to current estimates there are between 8200 and 12 500 injecting opiate addicts in Norway (Bretteville-Jensen and Amundsen, 2006). Approximately 4600 persons are in OMT, of whom 90–95% are intravenous drug users. (Statistics from National OMT competence centre 2006). Buprenorphine was registered as a therapeutic OMT drug in 2001 and by 2003; 23% used buprenorphine, the rest used methadone. The average dosing of methadone and buprenorphine was 112 mg and 20 mg, respectively in 2005 (Statistics from National OMT competence centre 2006) (Waal, 2007).
Statistics Norway (SSB) receives all death certificates concerning deceased Norwegians (SSB, 2006). The relatively high quality and accessibility of electronic public registries in Norway permit a cross-registry study between an OMT patient registry and the death registry.
In this paper the mortality reducing effect in an entire national OMT population, with calculated baseline mortality prior to treatment, including all programme dropouts, is studied. The study is prospective and with a population size sufficient for appropriate statistical analysis. As nation wide registers are available, it is possible to study the effects of treatment in an “intention-to-treat” design. Our results complement previous findings.
- (1)
To assess differences in mortality rates prior to, during and after OMT.
- (2)
To evaluate mortality reductions in an “intention-to-treat” perspective.
- (3)
To examine the distribution of drug overdose versus non-overdose as cause of death.
Section snippets
Sample and data collection
The Norwegian OMT programme is designed to reach the population of severely addicted heroin users not benefiting from other types of treatment (Waal, 2007). The inclusion criteria for OMT are “several years of addiction dominated by opioid dependence”, verified prior to treatment. There has been a 25-year age limit for inclusion, although exceptions have been made. Persons with severe somatic or psychiatric co-morbidity have been given priority. Treatment is based on cooperation between social
Sample characteristics
Table 1 presents the study population and the treatment status at the end of 2003.
Female subjects constituted 31.9%. Ages ranged from 23 to 66 years of age. Twenty-three percent of the subjects, who had commenced OMT, terminated the treatment without restarting within the observation period. The mean age of male subjects was slightly higher than for the female subjects (live males 2.1 years (mean) older than females). This was true for all groups except for deceased subjects, which had similar
Discussion of main results
The core trait of this study is the approach that allows an examination of mortality reduction from a defined baseline level both within OMT and post-OMT with overall mortality separated from overdose mortality. The study confirms earlier findings of reduced mortality in treatment and points to the change in pattern with overdose mortality dominant before and after and non-overdose mortality in treatment. Further, the approach enables calculation of concrete risk reductions in relation to the
Conflict of interest
None.
Acknowledgements
Thanks to all Norwegian OMT centres, providing patient lists, and to Statistics Norway performing the cross-registry data coupling.
Thanks to Magne Thoresen (University of Oslo) for statistical advice.
Thanks to Hege Kornør (Norwegian Knowledge Centre for the Health Services) for participation in design and discussions leading to the paper.
Funding: The project is carried by employees at the Institute of Psychiatry, University of Oslo, with no separate external funding.
Contributors: Thomas Clausen
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