DISCUSSION
Our systematic review, based on 126 observational studies using
routinely collected data, provides a comprehensive summary of the use
and applications of LTOT definitions in observational research. We
identified 78 distinct definitions, most of them using a minimum of 90
days of opioid therapy as a threshold for LTOT within a range of
follow-up periods, commonly one year. The rationale cited for the use of
these definitions was based mostly on previous publications and clinical
judgement; a minority of studies used empirical data to derive
definitions or tested the impact of using multiple definitions.
Moreover, we identified the need to improve reporting on methodological
aspects impacting the LTOT definition, such as listing the medicines and
formulations included in the analysis, depicting how overlapping
prescriptions and missing data were addressed, referring to the
follow-up period, and explicitly stating the denominator for LTOT rates.
Whilst our systematic review was not the first to identify variation in
LTOT definitions, the focus on routinely collected data and non-surgical
settings adds complementary insights to prior systematic reviews.[14, 15] A key advantage leveraged from routinely
collected data is to facilitate the characterisation of multiple
patterns of opioid use based on prescription/dispensing information
including its frequency, dose, opioid type and strength.[14, 52] As expected, the duration of opioid use,
commonly based on supply days, was the most common criteria used to
define LTOT (67%) in our systematic review compared to 27%-38% in the
previous ones. [14, 15] We also observed a higher
number of studies using opioid dose (7 vs 0-1 study) to derive LTOT
definitions [14, 15, 134] and reporting how they
accounted for overlapping prescriptions (22 vs 3 studies).[14]
Encouragingly, the commonly used threshold of 90 days of opioid therapy
observed in this and prior studies [14] aligns
with guidelines recommendations for opioid trial duration and has been
tested on empirical data based specifically on routinely collected data.[48, 49] The cumulative number of supply days
(i.e., duration of prescriptions filled) has been identified as one of
the strongest predictors of LTOT compared to other criteria, such as the
number of refills, or OMEs dispensed. [15, 123]However, information on supply days is not typically included in
administrative databases in many countries outside the United States,
such as in Australia, [97] Italy,[35] and Denmark; [111]estimates of treatment duration based on pack size, strength and
quantity dispensed are hindered by the range of possible instructions
for use of prescribed opioid. As an alternative, researchers can use a
threshold based on the length of episodes of opioid use or the frequency
of fills within a time period with or without additional criteria.[35, 97, 108, 112]
Although duration measures suffice to determine LTOT, the nature of
opioid therapy such as the use of long or short-acting opioids and
opioid potency are commonly reported by studies but only included as
part of the LTOT definition in seven studies. Similarly, estimating
opioid dosage can be challenging, explaining in part the small number of
studies using this criteria. This is despite evidence of a
dose-dependent association between opioid use and harm with dosages
greater than 40-50 mg OMEs, which escalates further with dosages over
90-120 mg OMEs. [6, 8-10]
The differences in LTOT definitions and study design resulted in an
approximately 300-fold variation on LTOT rates across studies and
13-fold variation in estimates among studies assessing multiple
definitions in the same study population. [24, 26,
52, 59, 79, 99, 123, 126, 128] This large variability can impair
comparisons across jurisdictions and health conditions; and evidence
resulting from these studies probably should not be summarised in
traditional meta-analysis without careful consideration. Even studies
using similar LTOT definitions may vary in terms of the study population
and denominator used in the analysis, thus restricting comparisons
between studies. We recommend that future studies estimating LTOT from
routinely collected data report the information presented in Box 1 to
increase the reliability and comparability of findings. Whenever
possible, authors should consider conducting a sensitivity analysis to
assess the impact of differing LTOT definitions on their estimates.
However, while proportions and the absolute number of people identified
as using LTOT across different definitions varies widely, overall trends
can be similar when testing definitions in the same study population.[52, 79, 99, 123] For instance, a study evaluating
three measures of LTOT found all of them were useful in identifying
long-term opioid use, with between 0.6%-1.1% of the study population
experiencing LTOT use at a given point in time, of which between
68%-84% remained using opioids two years later.[52] Similarly, a study defining LTOT as an
“Episode of > 90 days supply that began within the first
30 days following opioid index date”[99] compared
their primary outcome with two other common definitions: 1)
> 90 days per year [135] and 2) ≥ 90
days per year with > 120 days supply dispensed or more than
10 prescriptions filled. [49] The authors
identified LTOT rates of 20.4% in 2004 and 18.3% in 2011 using the
primary definition and results using the first alternative definition
were substantially lower (9.4%-8.2%), while the second alternative
definition yielded higher results (26.0%-24.5%). However, trends over
time remained similar, with reduced LTOT rates in the year 2011 compared
to 2004. Another study reported consistent predictors of LTOT despite a
high variation on the percentage of patients identified[123] replicating definitions from Deyo et al.[122] and Shah et al. [106].
Yet, these results should be interpreted with caution since only a few
studies reported data with sufficient detail to enable the comparison of
LTOT rates based on different measures. In addition, evidence from a
systematic review evaluating LTOT in the surgical setting implemented 25
definitions on empirical data and reported a 100-fold variation in
results, with low levels of agreement between
measures.[15]
Undoubtedly, operationalisation definitions should be fit-for-purpose to
achieve study aims since LTOT measures have different interpretations
and applicability for patients, clinicians, researchers, and payers. For
example, rates of LTOT measured at the prescription level are useful to
inform patterns of LTOT prescribing and use but give no information on
the proportion of patients receiving LTOT. Alternatively, studies
reporting LTOT as the proportion of individuals with a specific health
condition (the most common in our systematic review) provide useful
information for clinicians aiming to identify patients at higher risk of
harms and to inform treatment pathways and guidelines. At the payer
perspective, LTOT rates estimated as the proportion of patients
prescribed opioids or health enrolees allow comparisons across
providers. Estimating of rates among the whole population allows
comparison of jurisdictions, the evaluation of trends over time and
policy interventions impacts. Finally, the level of strictness can
identify different groups of LTOT users, with more strict definitions
able to identify those at higher risk of harm. [15,
52]