Exploring the Interplay between Rescue Drugs, Data Imputation, and Study Outcomes: Conceptual Review and Qualitative Analysis of an Acute Pain Data Set
Exploring the Interplay between Rescue Drugs, Data Imputation, and Study Outcomes: Conceptual Review and Qualitative Analysis of an Acute Pain Data Set
0 P. J. Desjardins Desjardins Associates, LLC , Maplewood, NJ , USA
1 D. S. Meske Collegium Pharmaceutical, Inc. , Canton, MA , USA
2 N. K. Singla (&) Lotus Clinical Research, Huntington Hospital, Department of Anesthesiology , Pasadena, CA , USA
In placebo-controlled acute surgical pain studies, provisions must be made for study subjects to receive adequate analgesic therapy. As such, most protocols allow study subjects to receive a pre-specified regimen of open-label analgesic drugs (rescue drugs) as needed. The selection of an appropriate rescue regimen is a critical experimental design choice. We hypothesized that a rescue regimen that is too liberal could lead to all study arms receiving similar levels of pain relief (thereby confounding experimental results), while a regimen that is too stringent could lead to a high subject dropout rate (giving
Acute pain; Analgesia; Bunionectomy; Clinical trials; Clinical trial design; Data imputation; Missing data; Pain; Postoperative pain; Post-surgical pain; Rescue medication
rise to a preponderance of missing data).
Despite the importance of rescue regimen as a
study design feature, there exist no published
review articles or meta-analysis focusing on the
impact of rescue therapy on experimental
outcomes. Therefore, when selecting a rescue
regimen, researchers must rely on clinical factors
(what analgesics do patients usually receive in
similar surgical scenarios) and/or anecdotal
evidence. In the following article, we attempt to
bridge this gap by reviewing and discussing the
experimental impacts of rescue therapy on a
common acute surgical pain population: first
metatarsal bunionectomy. The function of this
analysis is to (1) create a framework for
discussion and future exploration of rescue as a
methodological study design feature, (2) discuss
the interplay between data imputation
techniques and rescue drugs, and (3) inform the
readership regarding the impact of data
imputation techniques on the validity of study
conclusions. Our findings indicate that liberal
rescue may degrade assay sensitivity, while
stringent rescue may lead to unacceptably high
In placebo-controlled acute post-surgical pain
studies, provisions must be made for study
subjects to receive adequate analgesic therapy.
As such, most protocols allow study subjects to
receive a pre-specified regimen of open-label
analgesic drugs (rescue drugs) on an as-needed
1–6, 8–10, 13–15, 17, 19, 20, 25–27,
29–34, 36, 39, 40
]. These drugs are administered
only if the blinded study drug (active or
placebo) fails to adequately relieve the subject’s
When designing experiments, researchers
must select a rescue regimen for their protocol.
This regimen will specify (1) the selected
first-line rescue drug, including its dose and
frequency, and (2) any allowed second-line rescue
drugs. The selection of an appropriate rescue
regimen is a critical experimental design choice
], because a rescue regimen that is too liberal
may lead to all study arms receiving similar
levels of pain relief [
] (thereby confounding
experimental results), while a regimen that is
too stringent may lead to a high subject dropout
rate (giving rise to a preponderance of missing
Despite the importance of rescue regimen as
a study design feature, there exist no published
review articles or meta-analysis focusing
specifically on the topic. Therefore, when selecting a
study protocol’s rescue regimen, researchers
generally provide therapy that would be
considered clinically reasonable. However, the goal
of analgesic therapy in a clinical situation (to
relieve pain) is different from the goal of rescue
analgesic therapy in an experimental situation
(to ethically provide some pain relief while
maintaining study assay sensitivity). As such,
the best clinical choice of analgesic therapy may
not be the best experimental choice of rescue
therapy in a study.
Relying on the points above, we assert that a
scientific discussion and analysis of rescue
therapy as an experimental design feature is
needed. An ideal data set that might allow one
to isolate rescue therapy as a dependent variable
of interest would need to control for (1) study
model, (2) study design, and (3) data
imputation techniques. In an attempt to procure such a
data set, the authors performed an extensive
literature search encompassing several acute
and chronic pain models (low back pain,
osteoarthritis, diabetic peripheral neuropathy,
dental extraction, bunionectomy, and joint
replacement surgery). The authors concluded
that, among these models, bunionectomy was
the best candidate for exploration because (1) it
is a common model used for analgesic clinical
trials, (2) it employs a standardized
methodology such that study design features are tightly
homogenized between experiments, and (3) it is
generally used for registration studies (as such,
statistical results utilizing a variety of data
imputation techniques are available on
Seven bunionectomy studies suitable for
review, comparison, and discussion were
identified. The authors acknowledge that while the
data set is too small to be subjected to standard
meta-analysis techniques, it is large enough to
permit a detailed, relevant, and critical
conceptual review. The function of this manuscript,
then, is not to draw definitive conclusions (as a
classic meta-analysis would) but rather to (1)
create a framework for discussion and future
exploration of rescue as a methodological study
design feature, (2) discuss the interplay between
data imputation techniques and rescue drugs,
and (3) inform the readership regarding the
impact of data imputation techniques on the
validity of study conclusions.
The concepts laid out in this manuscript are
iterative. As such, each section of the
manuscript addresses a different topic by presenting
that topic’s relevant results and discussion
Compliance with Ethics Guidelines
This article is based on previously conducted
studies and does not involve any new studies of
human or animal subjects performed by any of
Data Imputation (Background and Nomenclature)
Missing data can be imputed using a variety of
statistical techniques [
12, 21, 35
that truncate data and lead to a high degree of
missing-ness (absent data) are unreliable [
Scientific consensus continues to evolve
regarding the proper handling of missing data; new
techniques are frequently being employed and
12, 21, 35
]. As such, the nomenclature
regarding data imputation techniques is not
firmly established and continues to change. In
order to streamline discussions in this review,
several common imputation techniques are
defined, named, and discussed.
Figure 1a depicts hypothetical data from a
single subject participating in a study in which
scheduled pain intensity assessments are
collected every 4 h for 48 h. This subject received
rescue on six occasions (red arrows). Prior to
each dose of the rescue drug, an unscheduled
pain score was collected (blue X’s). The dotted
line sketched across the graph corresponds to
subject’s baseline pain intensity score. The
summed pain intensity difference (SPID) is
determined by calculating the time-weighted
difference in pain intensity scores from the
initial baseline score. Panels 1b, 1c, and 1d build
off the raw data set in panel 1a in an attempt to
illustrate how different data imputation
methods affect SPID calculations.
Figure 1b represents a SPID48 applying no
data imputation secondary to rescue. When no
imputation is used, the impact of rescue drugs
on a subject’s pain relief is ignored. Note that
Fig. 1 Hypothetical data set illustrating different data imputation methods and their effects on SPID48 values. SPID48
summed pain intensity difference over 48 h after first dose of study medication
pre-rescue pain intensity scores (blue X’s) are
ignored when performing this non-imputed
Figure 1c represents a single imputation
technique [last observation carried forward
(LOCF) after first dose of rescue medication].
This subject reported an unscheduled pain
intensity score of 7 prior to their first dose of
rescue. In order to ensure that the rescue drug
does not statistically impact this subject’s SPID,
the pre-rescue pain intensity score (7) is carried
forward for the remainder of the 48-h efficacy
evaluation period. When a single imputation
technique is used, the efficacy of the rescue drug
cannot impact the statistical outcome of the
study, because as soon as a subject receives even
a single dose of rescue therapy, their data is
statistically truncated. Single imputation
techniques give rise to significant missing data and
are therefore no longer favored or accepted by
the Food and Drug Administration (FDA) [
Figure 1d represents a common multiple
imputation technique (windowed LOCF). With
this technique, unscheduled pre-rescue pain
intensity scores are carried forward for a
window of time equivalent to the expected
duration of action of the rescue therapy. In this
hypothetical case, the window selected is 3 h.
The theory behind this technique is that
scheduled pain intensity scores gathered within
3 h of administration of rescue are
contaminated (i.e., artificially lowered) by the rescue
drug. Therefore, these contaminated pain
intensity assessments are ignored when the
imputed SPID value is calculated.
A PubMed search was conducted of all articles
through May 2015 using the search term
‘‘bunionectomy.’’ This list was limited to
randomized controlled trials. Abstracts obtained
using these search criteria were reviewed, and
manuscripts that met the following criteria were
included in our data set: (1) in English, (2)
placebo-controlled, (3) randomized, (4)
double-blind, (5) bunionectomy model data
presented, and (6) pain as the primary or
secondary endpoint. References from papers
obtained via this search were assessed for any
other relevant manuscripts.
Next, a search of the FDA database
(drugs@fda) was conducted for Summary Basis
of Approval (SBA) and Statistical Reviews for all
drugs described in the collected manuscripts, as
well as for any other FDA-approved drugs for
the treatment of acute pain. This search yielded
one additional study (identified as ‘‘Jensen 2013
In an effort to obtain a homogenous
multi-dose set, we pruned articles to those matching
the following secondary criteria: (1) provided an
SPID48 and (2) were postoperative day 1 (POD1)
studies. SPID48 was chosen, as it is the most
common endpoint in this model and contains
multi-dose information. POD1 (a study in
which the first dose of study medication is
administered on the day following surgery) was
chosen, as it is also the most common and
contains a specific pain trajectory that is not
comparable to studies done on postoperative
day 0 (POD0; studies in which the first dose of
study drug is administered on the same day the
surgery is completed). Table 1 provides a
summary of all investigations included in the
SPID48 values were extracted from manuscripts
and SBA Statistical Reviews based on the type of
data imputation method used. Data were sorted
by imputation method for presentation in this
manuscript. Manuscripts that employed a
100-mm visual analog scale (VAS) were
converted to a 10-point numeric pain rating scale
(NPRS) by dividing the score by 10.
Acute Pain Studies: Rescue Is Frequent and Prevalent
In these acute pain studies, rescue was quite
prevalent in both the placebo and active
Boxes highlighted in blue = no rescue; red = weak rescue; green = liberal rescue
APAP acetaminophen, HC hydrocodone, mg milligram, mm millimeter, NPRS numerical pain rating scale, OC oxycodone,
VAS visual analog scale
a Weak rescue = APAP only; Liberal rescue = moderately potent short acting opioids, opioid/APAP combinations or
b Number of patients randomized
c When multiple doses the value from the lowest overall daily dose is provided
treatment arms. In our data set, 95.0% percent
of placebo subjects required protocol-mandated
rescue drugs (an average of 4.6 doses over 48 h;
Table 2). A significant proportion of subjects
allocated to the treatment arms also received
rescue drugs (85.6%); the mean number of doses
received per subject was 2.8 (Table 2).
Typical immediate-release rescue drugs [e.g.,
ibuprofen, acetaminophen (APAP),
hydrocodone/APAP, oxycodone/APAP] have at least
4 h of moderately potent analgesic efficacy
]. After multiple doses, the efficacy of
these drugs may be prolonged secondary to
accumulation (i.e., steady-state plasma levels
]. Acute pain studies are
generally short (48–72 h). Therefore, subjects
enrolled in such studies routinely receive
multiple doses of efficacious rescue drugs during a
relatively short (48–72 h) study evaluation period.
Placebo-Arm Pain Relief Is Influenced by Rescue
The amount of pain relief experienced by
subjects in the placebo arm of acute pain studies is,
in part, a function of the rescue regimen utilized
in the experiment. This fact is not surprising
considering the frequency and prevalence of
rescue usage amongst placebo subjects (as
In Table 3, the rescue regimen for each
experiment in our data set is displayed
alongside the corresponding SPID48 value for the
placebo arm. The SPID48 values in the
table were calculated with no imputation
secondary to rescue (non-imputed data permit an
objective assessment of the effect of rescue on
the pain trajectory of subjects receiving
placebo). Studies that allowed no rescue or weak
rescue generally had low placebo SPID48 values
(small placebo response), while studies that
allowed liberal rescue had high SPID48 values
(large placebo response; Table 3).
Treatment Response May Be Less
Influenced by Rescue
Rescue drugs are received by subjects in both
placebo and treatment study arms in an
investigation (Table 2). Therefore, one could argue
Table 3 Rescue medication and SPID48 values for
Boxes highlighted in blue = no rescue; red = weak rescue;
green = liberal rescue
N/A not available, # number, POD1 post-operative day 1,
SD standard deviation, Unk unknown
Weak = Acetaminophen only; Liberal = Moderately
potent short acting opioids, opioids/APAP combinations
or non-steroidal anti-inflammatories
a Rescue medication data presented for lowest dose of
study drug when multiple doses of study drug were
that both the placebo and treatment response
are influenced by rescue, and to the same
degree. If this were true, the observed net
treatment effect (treatment response–placebo
response) would not be negatively impacted by
efficacious and/or frequent rescue. However, if
rescue disproportionately affects the placebo
arm, then efficacious rescue will erode net
In the data set, there are two studies that can
be compared to allow one to draw preliminary
conclusions regarding the presence or absence
of differential impacts of rescue on placebo
versus treatment study arms. During the
development of Tapentadol, two large (n = 901 and
n = 603) replicate bunionectomy studies were
performed [4, 8]. The study design features were
essentially identical except for the selection of
rescue regimen. One of the studies 
prohibited any use of rescue, while the other 
allowed rescue of up to two 1000-mg doses of
APAP. Figure 3 displays the salient results of
these two investigations. One can see that while
pain relief in the placebo arm is doubled by the
provision of APAP rescue (versus no rescue),
treatment response remains unaltered.
Weak = acetaminophen only, Liberal = moderately
potent short acting opioids, opioids/APAP combinations
or non-steroidal anti-inflammatories
SPID48 summed pain intensity difference from baseline
during the 48 h after the first dose
Boxes highlighted in blue= no rescue, red= weak rescue;
green= liberal rescue
a No imputation secondary to rescue
Boxes highlighted in blue= no rescue, in red= weak rescue;
in green= liberal rescue
a Weak = rescue acetaminophen only, Liberal = rescue
moderately potent short acting opioids, opioid/APAP
combinations and non-steroidal anti-inflammatories
b Dropout rate presented for lowest dose when multiple
doses of study drug were used
Rescue Regimen Is Correlated with Efficacy Dropouts
In acute pain studies, efficacy dropouts are
correlated with the rescue regimen allowed by
the protocol (Table 4). Liberal use of rescue
reduces efficacy dropouts (Table 4), but may
negatively impact assay sensitivity (Fig. 2).
Stringent rescue regimens give rise to
unacceptably high placebo dropout rates (29.0% for
weak rescue and 50.4% for no rescue) but may
improve assay sensitivity. An ideal rescue
regimen balances these two phenomena by
providing enough pain relief to prevent high
placebo dropout rates, but not so much pain
relief that the experiment is unduly confounded
Published Literature Can Be Misleading
In much of the currently published acute pain
literature, the reported results have been
calculated using single imputation techniques
1, 2, 8, 14, 25, 28, 29, 34, 36
]. With single
imputation techniques (like LOCF), all data
after the first use of rescue are replaced with
Fig. 4 Comparison of SPID48 values [mean ± standard
error (SE)] using no imputation or windowed imputation
techniques. Data sets from five of seven articles included in
this analysis; two remaining manuscripts did not provide
windowed imputation data to allow for comparisons.
Altman  and Jensen  used windowed baseline
observation carried forward (6 h); Altman [
], and Singla [
] used windowed last observation
carried forward (6 h). SPID48 summed pain intensity
difference in 48 h following first dose of study drug
imputed data (Fig. 1c). This statistical technique
masks the impact of efficacious rescue regimens
on assay sensitivity [
12, 21, 35
]. Studies utilizing
single imputation techniques can therefore use
rescue with impunity. Even if rescue regimens
are gratuitous, assay sensitivity will not be
There is growing scientific consensus that
single imputation methods are unreliable in
multi-dose studies [
]. Modern scientific
standards require the use of imputation
techniques that minimize missing data (i.e.,
windowed LOCF; Fig. 1d). Researchers designing
clinical trials that will employ modern
imputation techniques often select rescue regimens
that have been utilized with success in previous
experiments. However, previously successful
experiments that utilized liberal rescue
regimens and calculated results via a single
imputation technique may not have been successful
if their results had been calculated with a
currently acceptable multiple imputation
technique. Therefore, modern-day researchers
should pay special attention to the data
imputation techniques utilized in previous
investigations before relying on those investigations to
guide their choice of rescue regimen.
Windowed Imputation May Not Be the Answer
Windowed imputation is a technique that is
commonly employed to account for and
mathematically reverse the impact of rescue
therapy on placebo arm pain relief (Fig. 1d). In
Fig. 4, non-imputed data are compared to data
that have been analyzed using a windowed
technique. One can see that in our data set,
windowed techniques have mixed results. In
three of five cases, they resulted in lower
placebo SPID48 values (the desired and predicted
statistical outcome; Fig. 4). In two
circumstances, however, windowed techniques led to
an increase in placebo SPID48 values (a
counterintuitive and surprising outcome; Fig. 4).
The Ethics of Rescue Therapy
Subjects in analgesic clinical trials must have
adequate mechanisms for obtaining pain relief.
When left untreated, pain can lead to
significant postoperative sequelae (e.g., hypertension,
impaired wound healing.) [
]. The clinical
situation, determined by the surgical insult and
the study population’s expected comorbidities,
will dictate the rescue options that are adequate
for the study under question.
It is important to understand that the
provision of pain-relieving drugs to a subject in a
research study can be accomplished in two
ways: first, through administration of rescue
medication as allowed/described in the study
protocol, and second, through subject
withdrawal. In other words, if the subject has
received protocol-mandated rescue but has not
experienced adequate pain relief, they can/
should withdraw from the study. After study
withdrawal, subjects can receive any analgesic
deemed appropriate per the investigator’s
The ethical implications of rescue should be
considered with this two-tiered approach in
mind. For example, in the Daniels Upmalis 
study, no rescue therapy was allowed. While
this provision may seem unethical, it is
important to consider the clinical situation for
subjects on postoperative day 1 after bunionectomy
(they are generally young, healthy, and lucid),
as these subjects are able to effectively verbalize
their desire to withdraw from the study.
In contrast, a no-rescue-allowed approach
would be inappropriate for subjects undergoing
cardiac surgery, because (1) the sequela from
untreated pain (e.g., hypertension) may be
quite serious, and (2) subjects post-cardiac
surgery may not be entirely lucid and, as such, may
be unable to express a desire for withdrawal in a
timely fashion. Therefore, researchers must
consider the clinical implications of their
experimental models when adjudicating the
ethics of any potential rescue paradigm.
LIMITATIONS AND CONCLUSIONS
The rescue regimen utilized in an acute surgical
pain study has an impact on the experimental
outcomes. Despite the importance of rescue as a
protocol design feature, researchers currently
lack the evidence required to select ideal rescue
regimens for their experiments. In this review,
we attempted to analyze a homogeneous set of
studies; as such, our sample size was small and
included only one surgical model. Therefore, we
acknowledge that our results must be
interpreted with caution. Further work from
colleagues and collaborators will be needed to
validate the preliminary conclusions we have
drawn in this manuscript.
No funding or sponsorship was received for this
study or publication of this article. The article
processing charges were funded by the authors.
All named authors meet the International
Committee of Medical Journal Editors (ICMJE)
criteria for authorship for this manuscript, take
responsibility for the integrity of the work as a
whole, and have given final approval for the
version to be published. The authors would like
to acknowledge the clinical and CRO personnel
at Lotus Clinical Research for their consistent
dedication to obtaining quality data and
pursuing scientific excellence, as well as previous
analgesic methodologists who have advanced
the field to its current state. There were no
conflicts of interest.
Disclosures. Neil K. Singla, Diana S. Meske
and Paul J. Desjardins have nothing to disclose
pertaining to this manuscript.
Compliance with Ethics Guidelines. This
article is based on previously conducted studies
and does not involve any new studies of human
or animal subjects performed by any of the
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