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pharmaceuticals
Article
Short-Term Medical Cannabis Treatment Regimens
Produced Beneficial Effects among Palliative
Cancer Patients
Joshua Aviram 1, Gil M. Lewitus 1, Yelena Vysotski 1, Anton Uribayev 2, Shiri Procaccia 1,
Idan Cohen 3, Anca Leibovici 2, Mahmud Abo-Amna 3, Luiza Akria 2, Dmitry Goncharov 2,
Neomi Mativ 2, Avia Kauffman 2, Ayelet Shai 2, Or Hazan 1, Gil Bar-Sela 3,4 ,* and David Meiri 1 ,*
1Faculty of Biology, Technion-Israel Institute of Technology, Haifa 32000, Israel;
shukiaviram@gmail.com (J.A.); lgil@technion.ac.il (G.M.L.); lalatrololo@gmail.com (Y.V.);
shiri.procaccia@gmail.com (S.P.); orhazan@gmail.com (O.H.)
2Department of Oncology, Galilee Medical Center, Nahariya 22100, Israel; AntonU@gmc.gov.il (A.U.);
AncaL@gmc.gov.il (A.L.); AkriaL@gmc.gov.il (L.A.); DmitriG@gmc.gov.il (D.G.);
NeomyM@gmc.gov.il (N.M.); AviaK@gmc.gov.il (A.K.); ayelets@gmc.gov.il (A.S.)
3Cancer Center, Emek Medical Center, Afula 18101, Israel; idan5161@gmail.com (I.C.);
mahmud_ab@clalit.org.il (M.A.-A.)
4Faculty of Medicine, Technion-Israel Institute of Technology, Haifa 32000, Israel
*Correspondence: gil_ba@clalit.org.il (G.B.-S.); dmeiri@technion.ac.il (D.M.); Tel.: +972-4-6495723 (G.B.-S.);
+972-77-8871680 or +972-525330031 (D.M.)
Received: 14 November 2020; Accepted: 27 November 2020; Published: 30 November 2020
Abstract:
In the last decade the use of medical cannabis (MC) for palliative cancer treatment has risen.
However, the choice between products is arbitrary and most patients are using Tetrahydrocannabinol
(THC)-dominant cannabis products. In this study, we aimed to assess the short-term outcomes
of MC treatment prescribed by oncologists in relation to the type of cannabis they receive.
A comparative analysis was used to assess the differences in treatment effectiveness and safety
between THC-dominant (n=56, 52%), cannabidiol (CBD)-dominant (n=19, 18%), and mixed
(
n=33
, 30%) MC treatments. Oncology patients (n=108) reported on multiple symptoms in baseline
questionnaires, initiated MC treatment, and completed a one-month follow-up. Most parameters
improved significantly from baseline, including pain intensity, affective and sensory pain, sleep
quality and duration, cancer distress, and both physical and psychological symptom burden.
There was no significant difference between the three MC treatments in the MC-related safety
profile. Generally, there were no differences between the three MC treatments in pain intensity
and in most secondary outcomes. Unexpectedly, CBD-dominant oil treatments were similar to
THC-dominant treatments in their beneficial effects for most secondary outcomes. THC-dominant
treatments showed significant superiority in their beneficial effect only in sleep duration compared
to CBD-dominant treatments. This work provides evidence that, though patients usually consume
THC-dominant products, caregivers should also consider CBD-dominant products as a useful
treatment for cancer-related symptoms.
Keywords: medical cannabis; THC; CBD; palliative cancer treatment; oncology
1. Introduction
Cancer patients suffer from many conditions resulting from the disease or its treatment.
These include cancer-related pain [
1
], anxiety [
2
], depression [
3
], insomnia [
4
], decreased quality of
life [
5
], and increased disability [
6
]. These comorbidities are some of the underlying causes of cancer
Pharmaceuticals 2020,13, 435; doi:10.3390/ph13120435 www.mdpi.com/journal/pharmaceuticals
Pharmaceuticals 2020,13, 435 2 of 16
patients’ suffering while undergoing therapies and some may even lead to worsened prognosis [
3
].
To date, there is still no optimal treatment addressing all of these comorbidities [7].
Currently, Medical Cannabis (MC) is one of the options to alleviate cancer patients’ suffering [
8
].
While the preclinical literature is vast [
9
–
13
], there is a paucity of clinical literature [
14
], leading
to arbitrary MC treatment regimen decisions based mostly on the oncologist experience and on
patient demands. Many oncologists find MC appropriate as the first-line therapy for cancer-related
symptoms [
15
] and a recent study showed that the majority of cancer patients request MC treatment
from their oncologist [
16
]. Nonetheless, there is not enough data on the negative and positive effects of
MC treatment on cancer patients [17].
Importantly, cannabis is not a single compound; it is comprised from many compounds in different
concentrations, including many phytocannabinoids [
18
,
19
] with diverse biological activities [
20
,
21
].
The concentration of these compounds (i.e., chemovar) is also vastly different between different
strains (i.e., cultivars) [
22
–
24
]. This makes traditional treatment by titrating of a single molecule
particularly difficult. Thus far, Randomized Controlled Trials of cancer-related pain focused mainly on
(-)-
∆9
-trans-tetrahydrocannabinol (THC) [
25
–
31
], but currently, probably due to the large media hype
and its more enabling regulation worldwide, there is a major shift of focus to cannabidiol (CBD) [
32
].
Today, most countries that approve MC treatment require cultivators to report and adhere only by the
two major phytocannabinoids, THC and CBD [33].
In this study, we conducted a prospective, short-term study that compared the effectiveness and
safety of the most widely used categorization of MC treatment, conceptualized by Small
et al., (1973)
,
to THC-dominant as type I cannabis, equal THC and CBD as type II, and CBD-dominant as type III [
34
].
2. Results
A total of 293 patients were enrolled to the study, of them, 228 patients completed the baseline
(T
0
) questionnaires and initiated MC treatment (Figure 1, CONSORT flow diagram). A follow-up
questionnaire was completed by 147 patients at T
1
. Of these patients, 108 patients reported on full MC
treatment information, these patients represent the analyzed sample for the current study. About 95%
of the patients provided data online and the rest by telephone calls.
Pharmaceuticals 2020, 13, x FOR PEER REVIEW 2 of 16
and increased disability [6]. These comorbidities are some of the underlying causes of cancer patients’
suffering while undergoing therapies and some may even lead to worsened prognosis [3]. To date,
there is still no optimal treatment addressing all of these comorbidities [7].
Currently, Medical Cannabis (MC) is one of the options to alleviate cancer patients ' suffering [8].
While the preclinical literature is vast [9–13], there is a paucity of clinical literature [14], leading to
arbitrary MC treatment regimen decisions based mostly on the oncologist experience and on patient
demands. Many oncologists find MC appropriate as the first-line therapy for cancer-related
symptoms [15] and a recent study showed that the majority of cancer patients request MC treatment
from their oncologist [16]. Nonetheless, there is not enough data on the negative and positive effects
of MC treatment on cancer patients [17].
Importantly, cannabis is not a single compound; it is comprised from many compounds in
different concentrations, including many phytocannabinoids [18,19] with diverse biological activities
[20,21]. The concentration of these compounds (i.e., chemovar) is also vastly different between
different strains (i.e., cultivars) [22–24]. This makes traditional treatment by titrating of a single
molecule particularly difficult. Thus far, Randomized Controlled Trials of cancer-related pain
focused mainly on (-)-Δ9-trans-tetrahydrocannabinol (THC) [25–31], but currently, probably due to
the large media hype and its more enabling regulation worldwide, there is a major shift of focus to
cannabidiol (CBD) [32]. Today, most countries that approve MC treatment require cultivators to
report and adhere only by the two major phytocannabinoids, THC and CBD [33].
In this study, we conducted a prospective, short-term study that compared the effectiveness and
safety of the most widely used categorization of MC treatment, conceptualized by Small et al. (1973), to
THC-dominant as type I cannabis, equal THC and CBD as type II, and CBD-dominant as type III [34].
2. Results
A total of 293 patients were enrolled to the study, of them, 228 patients completed the baseline
(T0) questionnaires and initiated MC treatment (Figure 1, CONSORT flow diagram). A follow-up
questionnaire was completed by 147 patients at T1. Of these patients, 108 patients reported on full
MC treatment information, these patients represent the analyzed sample for the current study. About
95% of the patients provided data online and the rest by telephone calls.
Figure 1. Consort flowchart diagram. T0, Baseline; T1, one-month follow-up; MC, medical cannabis;
BL, baseline; AEs, adverse effects.
Figure 1.
Consort flowchart diagram. T
0
, Baseline; T
1
, one-month follow-up; MC, medical cannabis;
BL, baseline; AEs, adverse effects.
Pharmaceuticals 2020,13, 435 3 of 16
2.1. MC Treatment Characteristics
MC treatment information was reported by 108 patients at T
1
and included type I (n=56, 52%;
patients consuming THC-dominant cultivars only; included three products: THC(T)20/CBD(C)4,
T15/C3 and T10/C2), type III (n=19, 18%; patients consuming CBD-dominant cultivars only; included
three products: T1/C20, T5/C10 and T3/C15), and type II (i.e., mixed; n=33, 30%; patients consuming
cultivars with similar THC:CBD ratio that included two products: T10/C10 and T5/C5, or patients
consuming both THC-dominant and CBD-dominant cultivars in the same day) MC treatments.
Sublingual MC oil extract was the most common route of administration for type III and for type
II treatments and less common for type I treatments (n=17, 89%, n=19, 58%, and n=19, 34%,
respectively), whereas patients consuming type I treatments consumed it mostly (n=32, 57%) by
inflorescence inhalation. Inflorescence inhalation was less common for type III and for type II treatments
(n=2, 11% and n=7, 21%, respectively). Some patients consuming type I and type II (n=5, 9% and
n=7, 21%
), but not for type III, utilized both administration routes (
χ2(2)
=26.02, p<0.001). Overall
reported monthly MC dose was similar for all three treatments (20 (20–20) grams).
THC and CBD monthly doses were significantly different between the three treatments
(
χ2(2) =58.07
,p<0.001 and
χ2(2)
=68.28, p<0.001, respectively). Patients consuming type I treatments
consumed 600 (400–725) mg/month of CBD (with weight-adjusted dose of 7.8 (5.7–11) mg/kg/month) and
3000 (2000–3600) mg/month of THC (with weight-adjusted dose of 39 (29–56) mg/kg/month). Patients
consuming type III treatments consumed 2000 (2000–3000) mg/month of CBD (with weight-adjusted
dose of 40 (26–46) mg/kg/month) and 1000 (600–1000) mg/month of THC (with weight-adjusted dose
of 12 (8.4–15) mg/kg/month). Patients consuming type II treatments consumed 2000 (1500–2000)
mg/month of CBD (with weight-adjusted dose of 30 (20–36) mg/kg/month) and 2000 (1400–2000)
mg/month of THC (with weight-adjusted dose of 29 (20–36) mg/kg/month).
2.2. Baseline Demographics and Cancer Characteristics
Sixty-two of the patients in the sample were females (57%) with an average age of 64 (52–72) years.
Demographic characteristics did not differ between the MC treatments (Table 1). Oncology diagnoses
were heterogenous, with breast cancer being the most frequent diagnosis (n=30, 28%), followed by
lung, colon and ovarian cancers (n=15, 14%, n=15, 14%, and n=5, 5%; respectively). Most patients
(n=48, 44%) were categorized as in IV stage cancer where 57 of the patients (53%) were at first-line
of oncology treatment, meaning that most patients were diagnosed and started treatment while in
advanced metastatic disease. Chemotherapy was the most prevalent current treatment protocol (n=56,
52%), followed by biological and immunological cancer treatments protocols (n=15, 14% and n=10,
9%, respectively). Most patients (n=76, 70%) were scored by the oncologist as not disabled (scored
≥
1
based on Eastern Cooperative Oncology Group (ECOG) Performance Status score). Additionally, no
significant differences were found in cancer characteristics between the three MC treatments (Table 2).
Table 1. Demographic characteristics.
Parameters Type I
n=56
Type III
n=19
Type II
n=33
Total
n=108
(χ2)†/Kruskal–Wallis rank ††
(p-value) #
Median (IQR)
Age (years) 62 (49–68) 66 (54–74) 66 (56–72) 64 (52–72) 3.37 †† (0.19)
Unknown 4 2 2 8
No. of patients (%)
Gender Gender
Male 25 (45) 6 (32) 15 (45) Male 25 (45)
Female 31 (55) 13 (68) 18 (55) Female 31 (55)
Pharmaceuticals 2020,13, 435 4 of 16
Table 1. Cont.
Parameters Type I
n=56
Type III
n=19
Type II
n=33
Total
n=108
(χ2)†/Kruskal–Wallis rank ††
(p-value) #
Median (IQR)
Weight (kg) 72 (65–80) 69 (53–77) 66 (55–80) 70 (59–80) 2.12 †† (0.35)
Unknown 7 5 5 17
BMI 25 (22–29) 24 (21–26) 26 (21–28) 25 (22–28) 0.70 †† (0.70)
Unknown 12 7 6 25
No. of patients (%)
Comorbidities (yes) 19 (34) 5 (26) 7 (21) 31 (29) 1.21 †(0.54)
Unknown 1 1 3 5
Past cannabis
experience (yes) 17 (30) 5 (26) 7 (21) 29 (27) 0.88 †(0.64)
†
, Pearson’s Chi-squared test;
††
, Kruskal–Wallis rank sum test; kg, kilograms; BMI, body mass index; IQR,
inter quartile range; n, number of patients; where missing nis not specified, there are no missing data; Type I,
THC-dominant treatments; Type III, CBD-dominant treatments; Type II, equal THC:CBD concentration treatments;
#, Significance between the three different treatment regimens.
Table 2. Cancer characteristics.
Parameters Type I
n=56
Type III
n=19
Type II
n=33
Total
n=108 χ2(p-Value) #
No. of patients (%)
Solid tumor etiology
Breast 19 (34) 3 (16) 8 (24) 30 (28) 10.81 (0.21)
Lung 9 (16) 2 (11) 4 (12) 15 (14)
Colon 8 (14) 5 (26) 2 (6) 15 (14)
Ovaries 1 (2) 2 (11) 2 (6) 5 (5)
Other 18 (32) 6 (32) 17 (52) 41 (38)
Solid tumor staging
I 3 (5) 1 (5) 3 (9) 7 (7) 4.30 (0.64)
II 8 (14) 1 (5) 6 (18) 15 (14)
III 4 (7) 3 (16) 3 (9) 10 (9)
IV 26 (46) 11 (58) 11 (33) 48 (44)
Unknown 15 3 10 28
Oncological treatment line
1st 30 (54) 8 (42) 19 (58) 57 (53) 2.65 (0.26)
≥2nd 18 (32) 10 (53) 9 (27) 37 (34)
Unknown 8 1 5 14
Oncological treatment †
Chemotherapy 27 (48) 11 (58) 18 (55) 56 (52) 0.67 (0.72)
Biological 8 (14) 3 (16) 4 (12) 15 (14) 0.15 (0.93)
Hormonal 7 (12) 0 4 (12) 11 (10) 2.61 (0.27)
Immunological 6 (11) 1 (5) 3 (9) 10 (9) 0.50 (0.78)
Radiation 1 (2) 1 (5) 0 2 (2) 1.84 (0.40)
Pharmaceuticals 2020,13, 435 5 of 16
Table 2. Cont.
Parameters Type I
n=56
Type III
n=19
Type II
n=33
Total
n=108 χ2(p-Value) #
No. of patients (%)
ECOG score
≤1 39 (70) 12 (63) 25 (75) 76 (70) 0.15 (0.92)
≥2 14 (25) 5 (26) 8 (24) 27 (25)
Unknown 3 2 0 5
χ2
, Pearson’s Chi-squared test; n, Number of patients; ECOG, Eastern Cooperative Oncology Group Performance
Status;
†
, numbers does not add up to 100% due to concomitant treatments; where missing nis not specified,
there are no missing data;
#
, Significance between the three different treatment regimens; Type I, THC-dominant
treatments; Type III, CBD-dominant treatments; Type II, equal THC: CBD concentration treatments.
2.3. MC Treatment Safety
Fourteen patients stopped MC treatment due to Adverse Effects (AEs), such as dizziness (n=2),
hallucinations (n=2), anxiety (n=1), faints (n=1), fatigue (n=1), nausea (n=1), combination of
bad taste and drowsiness (n=1), and combination of restlessness and weakness (n=1); four patients
did not specify the AEs that led to MC treatment discontinuation. Therefore, these patients are not
analyzed in the T1dataset.
Overall, 24 patients (22%) reported on at least one MC-related AE that did not led to MC treatment
discontinuation. In a descending order, AEs consisted of central nervous system (CNS; n=14, 13%),
gastrointestinal (GI, n=9, 8%), psychological (n=7, 7%), musculoskeletal (n=4, 4%), ophthalmic
(
n=4, 4%
), cardiovascular (n=2, 2%), and auditory (n=2, 2%) AEs. No significant differences were
found between the three MC treatment regimens in MC-related AEs by affected systems (Table 3).
Table 3. Medical cannabis treatment regimen-related adverse effects.
Parameters Type I
n=56
Type III
n=19
Type II
n=33 χ2(p-Value) #
No. of patients (%)
Overall adverse effects 10 (18) 3 (16) 11 (33) 3.02 (0.22)
Central nervous system 6 (11) 1 (5) 7 (21) 2.94 (0.23)
Gastrointestinal 3 (5) 2 (11) 4 (12) 1.30 (0.52)
Psychological 2 (4) 1 (5) 4 (12) 2.37 (0.30)
Musculoskeletal 1 (2) 0 3 (9) 3.78 (0.15)
Ophthalmic 1 (2) 1 (5) 2 (6) 1.17 (0.56)
Cardiovascular 0 0 2 (6) 4.44 (0.11)
Auditory 0 0 2 (6) 4.44 (0.11)
χ2
, Pearson’s Chi-squared test; AEs, adverse effects;
#
, significance between the three different treatment
regimens; Type I, THC-dominant treatments; Type III, CBD-dominant treatments; Type II, equal THC:CBD
concentration treatments.
The most frequent specific AEs were dizziness and tiredness (n=9, 8%; for both) (Table 4). Due to
the non-frequent reports of specific AEs, we could not assess the differences between them for the three
MC treatments.
Notably, 21 (13%) patients that are not analyzed in the T
1
dataset died during the first month of
MC treatment. Therefore, their MC treatment type is unknown.
Pharmaceuticals 2020,13, 435 6 of 16
Table 4. Reported non-serious, MC-related adverse events.
Total n=108
Central nervous system No. of patients (%)
Confusion 4 (4)
Disorientation 4 (4)
Impaired attention 3 (3)
Dizziness 9 (8)
Falls 3 (3)
Feeling drunk 6 (6)
Decreased physical sensation 4 (4)
Impaired balance 6 (6)
Impaired memory 5 (5)
Impaired psychomotor functions 5 (5)
Impaired coordination 5 (5)
Increased awareness 5 (5)
Impaired speech 5 (5)
Tiredness 9 (8)
Vertigo 5 (5)
Gastrointestinal No. of patients (%)
Abdominal discomfort 7 (7)
Abdominal pain 6 (6)
Decreased appetite 7 (7)
Increased appetite 3 (3)
Loss of appetite 5 (5)
Bad taste 8 (7)
Constipation 5 (5)
Diarrhea 6 (6)
Dry mouth 6 (6)
Heartburn 5 (5)
Decreased mouth sensation 5 (5)
Mouth ulcers 5 (5)
Nausea 6 (6)
Vomiting 6 (6)
Mouth pain 5 (5)
Thirst 6 (6)
Psychological No. of patients (%)
Unusual thinking 4 (4)
Anxiety 4 (4)
Bad mood 6 (6)
Sweet craving 5 (5)
Depression 4 (4)
Decreased interest 5 (5)
Euphoria 4 (4)
Forgetfulness 4 (4)
Hallucinations 4 (4)
Hyperactivity 3 (3)
Loss of time sensation 4 (4)
Nervousness 4 (4)
Nightmares 3 (3)
Paranoia 3 (3)
Weird dreams 2 (2)
Psychosis * 2 (2)
Pharmaceuticals 2020,13, 435 7 of 16
Table 4. Cont.
Total n=108
Musculoskeletal No. of patients (%)
Bone pain 3 (3)
Joint pain 3 (3)
Jaw stiffness 2 (2)
Decreased motor ability 2 (2)
Limb weakness 3 (3)
Muscle pain 3 (3)
Tremor 1 (<1)
Cardiovascular No. of patients (%)
Hypertension 1 (<1)
Hypotension 2 (2)
Irregular pulse 1 (<1)
Orthostatic hypotension 2 (2)
Palpitations 2 (2)
Ophthalmic No. of patients (%)
Blurred vision 4 (4)
Red eyes 1 (<1)
Vision alterations 1 (<1)
Itchy Eyes 1 (<1)
Light sensitivity 3 (3)
Auditory No. of patients (%)
Ears buzzing 2 (2)
Decreased hearing 2 (2)
Noise sensitivity 1 (<1)
* diagnosed by psychiatrist; some of the adverse effect reports are concomitant.
2.4. MC Treatment Regimens’ Effect
Assessing the effect of MC treatment (the change from T
0
to T
1
), for all of the evaluated parameters,
demonstrated that there was a significant (p<0.05) improvement for several of the parameters.
Specifically, significant improvement from baseline was reported for weekly average pain intensity,
affective and sensory pain intensities, sleep quality and duration and in MSAS distress, physical
(p<0.01) and psychological indexes. Additionally, a decrease in analgesics consumption was also
demonstrated. Notably, we found no significant change from T
0
to T
1
for least and worst pain
intensities, weight, body mass index (BMI), pain catastrophizing scale, sleep latency, depression,
disability, QoL, and for anxiety (p>0.05) (Table 5).
For the above-mentioned parameters that improved significantly from T
0
to T
1
, we analyzed
the differences between the three MC treatments. We found that the median change from T
0
to T
1
between the three MC treatments was significantly different in MSAS physical index (
χ2(2)
=6.91,
p<0.05) and in sleep duration (
χ2(2)
=6.02, p<0.05). Specifically, for MSAS physical index, post
hoc analyses showed a trend for superiority of type III and type I treatments (
−
16 (
−
2 to 19) and
−
8 (+0.25 to
−
20)), respectively) compared to mixed treatments (
−
1 (+8 to
−
12)). Moreover, for MSAS
physical index
≥
30% clinical improvement, patients consuming type III treatments reported higher
rate of response (
n=14, 74%
), compared to type I (n=28, 50%) and type II (n=10, 30%) treatments
(
χ2(2) =9.24
,
p<0.01
). For sleep duration, post hoc analyses showed significance of superiority for
type I treatments (+0.5 (0 to +2) h) compared to type III treatments (0 (−1 to +0.5) h) (Figure 2).
Pharmaceuticals 2020,13, 435 8 of 16
Table 5. Difference from baseline in outcome parameters.
Parameters T0T1n=108
Two-Sample
Kolmogorov-Smirnov
Test (p-Value)
Decrease in
Score Indicates
Median (IQR) Unknown
Weight (Kg) 72 (60–80) 70 (59–80) 17 0.10 (0.72) Worsening
BMI (weight (kg)/[height (m)]2)26 (22–29) 25 (22–28) 25 0.07 (0.97) Worsening
Weekly least pain intensity (NPS, 0–10) 5 (2–7.2) 3 (1–6) 35 0.16 (0.27) Improvement
Weekly worst pain intensity (NPS, 0–10) 8 (6–9) 6 (5–8) 35 0.20 (0.10) Improvement
Weekly average pain intensity (NPS, 0–10) 7 (3–8.8) 5 (1.5–7) 5 0.22 (<0.05) Improvement
Affective pain intensity (McGill questionnaire, 0–12) 7 (4.5–9) 4 (2–7) 43 0.34 (<0.01) Improvement
Sensory pain intensity (McGill questionnaire, 0–33) 18 (14–24) 13 (7–20) 45 0.28 (<0.05) Improvement
Pain catastrophizing scale (PCS, 0–52) 28 (15–37) 22 (7–36) 17 0.13 (0.47) Improvement
Sleep quality (PSQI global score, 0–21) 12 (9–15) 9 (5.2–12) 30 0.29 (<0.01) Improvement
Sleep duration (h) 5 (4–6.5) 6 (5–7.5) 8 0.25 (<0.05) Worsening
Sleep latency (min) 45 (30–60) 30 (15–60) 11 0.17 (0.10) Improvement
Depression (BDI, 0–63) 17 (10–24) 15 (9–21) 10 0.10 (0.64) Improvement
Quality of life (EQ-5, 0–10) 4 (3–6) 3 (2–5) 5 0.13 (0.37) Improvement
Anxiety (GAD-7, 0–21) 8 (2.8–14) 5 (2–11) 8 0.14 (0.28) Improvement
MSAS distress index (0–100) 44 (25–64) 34 (19–46) 0 0.20 (<0.05) Improvement
MSAS physical index (0–120) 38 (18–50) 27 (12–40) 0 0.23 (<0.01) Improvement
MSAS psychological index (0–60) 24 (14–40) 16 (8–32) 0 0.22 (<0.05) Improvement
No. of patients (%)
Analgesics consumption (yes) 60 (56) 40 (37) 1 6.8 (<0.01) Improvement
BL, Baseline; m, meter; NPS, Numerical pain scale; PSQI, Pittsburgh Sleep Quality Index; BDI, Beck depression
index; EQ-5, EuroQol questionnaire; GAD-7, General anxiety disorder questionnaire; IQR, Inter quartile range; Kg,
Kilograms; BMI, Body mass index; MSAS, Memorial Symptom Assessment Scale; n, Number of patients; Range is
indicated next to each parameter.
While there was a general decrease in analgesic medications consumption, there were no significant
differences between the three MC treatments in the rates of patients that consumed them at T
0
and
stopped at T1(χ2(2) =0.28, p=0.87).
As patients can consume either sublingual oil extract or inflorescence by inhalation, we also
compared between these different routes of administration. No significant differences were found
between patients that consumed only type I cultivars by sublingual oil extract (n=19) and patients
that consumed only type I cultivars by inflorescence inhalation (n=32) in the median change from T
0
to T
1
of all parameters (p>0.05). In addition, comparative analysis between patients that consumed
only type III cultivars by sublingual oil extract (n=17) and patients that consumed only type I
cultivars by inflorescence inhalation (n=32) demonstrated that there was no significant difference in
the median change from T
0
to T
1
of most parameters, excluding sleep duration. Overall, we found
superiority for consumption of type I treatments by inflorescence inhalation (+1 (0.31 to +2.4) h)
compared to consumption of type III treatments by sublingual oil extract in sleep duration extension
(0 (−1 to +0.5) h) (χ2(1) =0.50, p<0.05).
Pharmaceuticals 2020,13, 435 9 of 16
Pharmaceuticals 2020, 13, x FOR PEER REVIEW 9 of 16
Figure 2. MC Treatment regimens significant differential effects. (A) Differences between the three
MC treatments in weekly average pain intensity; (B) Differences between the three MC treatments in
affective pain intensity; (C) Differences between the three MC treatments in sensory pain intensity; (D)
Differences between the three MC treatments in sleep quality; (E) Differences between the three MC
treatments in sleep duration; (F) Differences between the three MC treatments in MSAS general distress
index; (G) Differences between the three MC treatments in MSAS physical index; (H) Differences
between the three MC treatments in MSAS psychological index; CBD, Cannabidiol; THC, (−)-Δ9-trans-
tetrahydrocannabinol; MSAS, Memorial Symptom Assessment Scale; The dashed lines represent the
baseline (T0) values of their corresponding parameters; The box-plot values represent the raw median
change from baseline (T0) to one-month follow-up (T1); n, Number of patients; n.S, Non-significant; Type
I, THC-dominant treatments; Type III, CBD-dominant treatments; Type II, equal THC:CBD
concentration treatments; Median and IQR change from baseline are calculated individually for each
patient, the presented change from BL is the median of all individual patients and not the difference
between the medians of BL and one-month follow-up; p values are adjusted for multiple comparisons;
The direction of the arrows indicates the desired symptoms improvement trajectory.
While there was a general decrease in analgesic medications consumption, there were no
significant differences between the three MC treatments in the rates of patients that consumed them
at T0 and stopped at T1 (χ²(2) = 0.28, p = 0.87).
As patients can consume either sublingual oil extract or inflorescence by inhalation, we also
compared between these different routes of administration. No significant differences were found
between patients that consumed only type I cultivars by sublingual oil extract (n = 19) and patients
that consumed only type I cultivars by inflorescence inhalation (n = 32) in the median change from T0
to T1 of all parameters (p > 0.05). In addition, comparative analysis between patients that consumed
only type III cultivars by sublingual oil extract (n = 17) and patients that consumed only type I
cultivars by inflorescence inhalation (n = 32) demonstrated that there was no significant difference in
the median change from T0 to T1 of most parameters, excluding sleep duration. Overall, we found
superiority for consumption of type I treatments by inflorescence inhalation (+1 (0.31 to +2.4) h)
Figure 2.
MC Treatment regimens significant differential effects. (
A
) Differences between the three
MC treatments in weekly average pain intensity; (
B
) Differences between the three MC treatments in
affective pain intensity; (
C
) Differences between the three MC treatments in sensory pain intensity;
(
D
) Differences between the three MC treatments in sleep quality; (
E
) Differences between the
three MC treatments in sleep duration; (
F
) Differences between the three MC treatments in MSAS
general distress index; (
G
) Differences between the three MC treatments in MSAS physical index;
(
H
) Differences between the three MC treatments in MSAS psychological index; CBD, Cannabidiol;
THC, (
−
)-
∆9
-trans-tetrahydrocannabinol; MSAS, Memorial Symptom Assessment Scale; The dashed
lines represent the baseline (T
0
) values of their corresponding parameters; The box-plot values represent
the raw median change from baseline (T
0
) to one-month follow-up (T
1
); n, Number of patients; N.S,
Non-significant; Type I, THC-dominant treatments; Type III, CBD-dominant treatments; Type II, equal
THC:CBD concentration treatments; Median and IQR change from baseline are calculated individually
for each patient, the presented change from BL is the median of all individual patients and not the
difference between the medians of BL and one-month follow-up; pvalues are adjusted for multiple
comparisons; The direction of the arrows indicates the desired symptoms improvement trajectory.
3. Discussion
In this “real-world” study on palliative care in oncology patients, we found a significant
improvement in most of the assessed parameters, including reduced pain intensity, improved
sleep, alleviated cancer symptoms and a decrease in pharmaceutical analgesics consumption.
We demonstrated that this improvement from baseline is rapid and apparent, already at one month after
MC initiation. This symptom relief profile is supported by previous studies [
35
–
40
], while it is opposite
to the expected trajectory of symptoms in palliative cancer patients [
41
]. However, unlike previous
studies that demonstrated an increase of appetite and weight gain [
42
,
43
], as well as anxiolytic [
44
],
antidepressant [
45
], and quality of life (QoL) improvement properties [
46
]; we found no significant
short-term improvement for those in the allocated time. These findings may be explained by the
inherent nature of the parameters, they may require additional treatment duration for the effects to be
apparent. Another possibility is the patients’ demographics, as these are palliative oncology patients
Pharmaceuticals 2020,13, 435 10 of 16
with high rates of advanced metastatic disease. These results can assist oncologists to facilitate patients’
expectations regarding the short-term effects of MC treatment.
Additionally, patients reported a mostly non-serious adverse effects profile. Our findings are in
line with previous results concluding that cannabinoid treatment for cancer-related pain is safe [
47
].
A previous study of recreational cannabis users demonstrated that THC is a major contributor to
the psychoactive effects of cannabis, with dose-dependent properties [
48
], whereas CBD is generally
described in psychiatric clinical studies as safe or as the phytocannabinoid that attenuates THCs’
psychoactive effects [
49
]. Moreover, the American Pain Society (APS) guidelines prefer to direct patients
to low-THC and high-CBD content MC cultivars due to THC-related AEs [
50
]. In our study, we found
no significant differences between MC treatment regimens in MC-related AEs. Thus, the dominance of
THC/CBD phytocannabinoids within the MC treatments, at least for short-term treatment of palliative
cancer patients, does not play a clinical role in the safety profile of MC.
Currently, oncologists in Israel are required to prescribe MC treatment deciding on the
administration route and on THC:CBD ratio of products. We found that most of the prescriptions for
palliative oncology patients were for type I cultivars, which might be explained by previous clinical
trials demonstrating that cultivars with higher THC content provide a better therapeutic response for
pain reduction [
51
]. In the current study we found that except for sleep duration, type III treatments
were as good as type I treatments. In fact, for most assessed parameters, there was no superiority
of any specific MC treatment. Additionally, a trend of significance was found for both type I and
type III treatments compared to type II treatments for cancer-related physical symptoms reduction,
with higher clinical response rate for type III treatments. Hence, we can assume, based on our results,
that for amelioration of physical cancer symptoms, and for most cancer-related parameters (other than
sleep duration extension), there is no added therapeutic value for type I treatments and physicians
can prescribe type III cultivars. Additionally, Portenoy et al., (2012) showed that lower THC and
CBD concentrations of Nabiximoles were associated with higher pain reduction efficacy in cancer
patients [
29
]. Hence, the higher response rate for physical cancer burden by type III MC may be
attributed to its low THC concentrations, rather than for its high CBD concentrations. Nevertheless,
the THC:CBD ratio is not a good enough predictor for treatment response and other MC components
(e.g., concentration of other phytocannabinoids or terpenoids) should be assessed and matched for
some cancer symptoms. Hence, keeping in mind that we found no superior beneficial effects for type
I MC treatments other than for sleep duration and due to the abuse potential of THC [
52
], type III
MC treatments may be preferred for palliative oncology patients. Notably, previous clinical trials
that compared cannabis-based medications, such as THC, CBD and equal THC:CBD products for
chronic non-cancer pain patients, demonstrated superiority for equal THC:CBD products [
53
,
54
].
As whole-plant medical cannabis treatment is more complex than just its THC/CBD concentrations,
with more than 500 components, of which over 100 are phytocannabinoids [
20
], the comparison to the
relative inferiority of type II treatments in our study cannot be assessed.
This study has few limitations. First, no control or placebo groups were assigned. Hence, prudent
interpretation of the results is needed. Second, self-report bias may have occurred. To diminish this
bias, only validated questionnaires were utilized and patient responses were kept anonymous from
their physician. Third, since we investigated palliative cancer patients, with a short life expectancy
prognosis, a relatively short duration of follow-up was conducted. Future studies should attempt to
extend the follow-up period. Fourth, the heterogeneity of our sample prevents us from making any
generalization of our findings to a specific cancer etiology. Fifth, survival bias may have occurred,
since patients that discontinued MC treatment, due to ineffectiveness or AEs and patients that passed
away could not contribute their follow-up status. Fifth, selection bias might have also occurred, since
extremely advanced patients might have not been included due to the study design. Lastly, we suggest
repeating this study in a placebo-controlled randomized clinical trial, using standardized cannabis
products with known phytocannabinoid and terpenoid composition.
Pharmaceuticals 2020,13, 435 11 of 16
4. Materials and Methods
4.1. Study Design
This is an intermittent subgroup study of an ongoing, multi-center, prospective study that is
being conducted since January 2019, and was analyzed at September 2020. The institutional Ethics
Committees of the Haemek Medical Center, Israel (#0137–18-EMC) and of the Galil Medical Center,
Israel (#0010–19-NHR) approved the study. This was a pure observational study with no interventional
component whatsoever, so registration at the Clinical Trials Register was not required. Importantly,
no recognizable information on participating patients is published in this article.
Hebrew speaking patients aged
≥
18 years licensed for the first time for MC for treating metastatic
cancer pain and for chemotherapy-related nausea, vomiting and/or pain, were eligible for participation
in the study. After explaining the study procedures, participating oncologists who regularly issue MC
licenses on their own clinical discretion obtained written informed consents from eligible patients.
Copies of the consent forms along with the patients’ cancer diagnoses, cancer treatment and contact
information were sent to the study coordination center. To avoid any possible influence of collected
data on physicians’ decisions regarding clinical management of their patients, prescribing physicians
had no access to data collected on individual patients.
Patients were instructed to complete the study questionnaires at baseline, before MC treatment
initiation (T
0
; within few days from MC prescription), and at one (T
1
), three- and six-months following
treatment initiation. In this subgroup analysis, we selected to present only the short-term (T
1
) effects of
MC treatment. The baseline questionnaire consisted of 174 questions at baseline and a variable number
of about 220 follow-up questions, which were presented in a dynamic format customized to individual
responses where responses on a particular question determined the subsequent questions asked.
In order to further reduce study burden, patients were also given the choice to skip questions. Hence,
each patient completed a unique set of questions and each question received a different number of
responses. Data was collected online by the secured survey technology Qualtrics
®
(Provo, Utah, version
12018) [
55
]. Whenever patients had difficulties with the use of the web platform, the questionnaires
could be completed by phone, with the assistance of the study coordinator. No financial compensation
was offered to participating patients. The STROBE statement checklist for cohort studies is presented
in the Supplementary Materials.
4.2. Study Questionnaires
Physician reported information included cancer diagnosis, classification of malignant tumors
(TNM), cancer treatment protocol and the Eastern Cooperative Oncology Group (ECOG) Performance
Status score. Patient reported information included demographics, analgesics consumption,
MC treatment characteristics as well as Hebrew validated oncology-related questionnaires, including
(1) the study’s primary outcome measure of “average weekly pain intensity” on a 0–10 numerical pain
scale (NPS) and the weekly average worst and least pain intensities; (2) Memorial Symptom Assessment
Scale (MSAS) [
56
]; (3) The short-form McGill Pain Questionnaire (SF-MPQ) [
57
]; (4) Pain Disability
Index (PDI) [
58
]; (5) Quality of life—EuroQol (EQ5) [
59
]; (6) Pittsburgh Sleep Quality Index (PSQI) [
60
];
(7) Beck Depression Inventory II (BDI-II) [
61
]; (8) Pain Catastrophizing Scale (PCS) [
62
]; and (9) General
Anxiety Disorder (GAD-7) [
63
]. Using a predetermined list [
14
], patients were requested to report
adverse effects (AEs) at each follow-up time-point that they could attribute directly to MC treatment.
AEs were later classified as serious or non-serious, according to the FDA definition [64].
4.3. Phytocannabinoids Dose Assessment
Since the Israeli MCU reform [
65
], MC cultivators in Israel are required to accurately indicate the
THC and CBD concentrations in their products [
33
]. We calculated the monthly doses of THC and
CBD only for patients that reported fully on their MC treatment regimen, according to the products
that patients reported to consume, alongside with their total and product specific monthly doses.
Pharmaceuticals 2020,13, 435 12 of 16
For example, if a patient reported on consuming 10 g of THC10/CBD10 product and another 10 g
of THC20/CBD4 product, the patient calculated amount of monthly consumption is 6000 mg and
2800 mg of THC and CBD, respectively. Notably, MC cultivators in Israel are not required to report on
terpenoids concentrations in their MC products.
4.4. Statistical Analysis
R software (V.1.1.463) with atable [
66
], ggstatsplot [
67
] and tidyverse [
68
] packages were used to
analyze differences between three MC treatments: Type I (patients consuming THC-dominant cultivars
only), type III (patients consuming CBD-dominant cultivars only; Type III) and type II (patients
consuming either hybrid cultivars with similar THC:CBD ratio; Type II, or patients consuming a
combination of THC-dominant and CBD-dominant cultivars in the same month) [
34
]. Chi square or
Kruskal–Wallis rank tests were conducted to establish similarity of demographic data between the
three treatments. The Shapiro-Wilk test of normality demonstrated non-normal distribution for all
measures. Thus, data is presented as median (IQR, Q1-Q3, i.e., quartiles 25 and 75). Differences were
considered significant at the p<0.05 level. Incidences are presented as numbers and percentages of
patients. Notably, due to the exploratory nature of the study and many potential subgroup analyses,
no sample size was determined a priori.
4.5. Data Sharing
All data requests should be submitted to the corresponding author for consideration. Access to
anonymized data may be granted following review of the request.
5. Conclusions
In conclusion, this prospective, short-term cohort of palliative cancer patients demonstrated
an overall mild improvement of most investigated parameters, regardless of its phytocannabinoid
dominance. This is the first study that investigated the variability between three different classes of
regulated and accurately labelled MC products, using precise doses of both phytocannabinoids, THC
and CBD. Keeping in mind our relatively small sample size, short-term follow-up and lack of control
and placebo groups, we could not elucidate any differences in beneficial effects between MC treatments
for most outcomes, but we were able to demonstrate some differential effects between them. Thus,
we can cautiously recommend type III treatments and not type I or type II treatments be prescribed
for oncology patients with a high burden of physical cancer symptoms. However, if the patient’s
main complaint is short sleep duration, type I treatments are preferred. Future studies should further
investigate the role of different MC treatments in order to better elucidate our understanding of MC
treatment complexities.
Supplementary Materials:
The following are available online at http://www.mdpi.com/1424-8247/13/12/435/s1,
Methods S1: STORBE checklist.
Author Contributions:
Conceptualization, J.A., G.M.L., G.B.-S. and D.M.; Data curation, J.A., A.U., I.C., A.L.,
M.A.-A., G.B.-S., L.A., D.G., N.M., A.K., A.S. and O.H.; Formal analysis, J.A. and Y.V.; Funding acquisition, D.M.;
Investigation, J.A. and D.M.; Methodology, J.A., G.M.L., G.B.-S., Y.V. and D.M.; Project administration, G.M.L. and
D.M.; Resources, D.M.; Supervision, G.M.L. and D.M.; Validation, J.A. and Y.V.; Visualization, J.A., Y.V., S.P. and
D.M.; Writing—original draft, J.A.; Writing—review & editing, J.A., G.M.L., Y.V., Anton Uribayev, S.P., I.C., A.L.,
M.A.-A., G.B.-S., L.A., D.C., N.M., A.K., A.S., O.H. and D.M. All authors participated in data collection, discussed
the results and commented on the manuscript. All authors have read and agreed to the published version of
the manuscript.
Funding:
The study was funded by the Evelyn Gruss Lipper Charitable Foundation. The funder had no role in
the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in
the decision to publish the results.
Acknowledgments:
We would like to thank Ella Lutbak and Reut Peled in their administrative assistance in
the study.
Conflicts of Interest: The authors declare no conflict of interest.
Pharmaceuticals 2020,13, 435 13 of 16
References
1.
Portenoy, R.K.; Ahmed, E. Cancer Pain Syndromes. Hematol. Oncol. Clin. N. Am.
2018
,32, 371–386.
[CrossRef]
2.
Curran, L.; Sharpe, L.; Butow, P. Anxiety in the context of cancer: A systematic review and development of
an integrated model. Clin. Psychol. Rev. 2017,56, 40–54. [CrossRef]
3.
Bortolato, B.; Hyphantis, T.N.; Valpione, S.; Perini, G.; Maes, M.; Morris, G.; Kubera, M.; Köhler, C.A.;
Fernandes, B.S.; Stubbs, B.; et al. Depression in cancer: The many biobehavioral pathways driving tumor
progression. Cancer Treat. Rev. 2017,52, 58–70. [CrossRef]
4.
Savard, J.; Morin, C.M. Insomnia in the context of cancer: A review of a neglected problem. J. Clin. Oncol.
2001,19, 895–908. [CrossRef]
5.
Allart-Vorelli, P.; Porro, B.; Baguet, F.; Michel, A.; Cousson-G
é
lie, F. Haematological cancer and quality of life:
A systematic literature review. Blood Cancer J. 2015,5, e305. [CrossRef]
6.
Neo, J.; Fettes, L.; Gao, W.; Higginson, I.J.; Maddocks, M. Disability in activities of daily living among adults
with cancer: A systematic review and meta-analysis. Cancer Treat. Rev. 2017,61, 94–106. [CrossRef]
7.
Levit, L.; Balogh, E.; Nass, S.; Ganz, P.A. Delivering High-Quality Cancer Care: Charting a New Course for
a System in Crisis Committee on Improving the Quality of Cancer Care: Addressing the Challenges of an Aging
Population Board on Health Care Services; National Academic Press: Washington, DC, USA, 2013.
8.
Mirelman, D.; Waissengrin, B.; Goldway, N.; Sharon, H.; Brill, S.; Wolf, I. Knowledge, attitude and practices
regarding the use of medical cannabis: A national survey among Israeli oncologists. J. Clin. Oncol.
2020
,38.
[CrossRef]
9.
Khasabova, I.A.; Gielissen, J.; Chandiramani, A.; Harding-Rose, C.; Odeh, D.A.; Simone, D.A.; Seybold, V.S.
CB1 and CB2 receptor agonists promote analgesia through synergy in a murine model of tumor pain.
Behav. Pharmacol. 2011,22, 607–616. [CrossRef]
10.
Marino, S.; Idris, A.I. Emerging therapeutic targets in cancer induced bone disease: A focus on the peripheral
type 2 cannabinoid receptor. Pharmacol. Res. 2017,119, 391–403. [CrossRef]
11.
Elikottil, J.; Gupta, P.; Gupta, K. The analgesic potential of cannabinoids. J. Opioid Manag.
2009
,5, 341–357.
[CrossRef]
12.
Guerrero, A.V.; Quang, P.; Dekker, N.; Jordan, R.C.K.; Schmidt, B.L. Peripheral cannabinoids attenuate
carcinoma-induced nociception in mice. Neurosci. Lett. 2008,433, 77–81. [CrossRef]
13.
Khasabova, I.A.; Khasabov, S.; Paz, J.; Harding-Rose, C.; Simone, D.A.; Seybold, V.S. Cannabinoid type-1
receptor reduces pain and neurotoxicity produced by chemotherapy. J. Neurosci.
2012
,32, 7091–7101.
[CrossRef]
14.
Aviram, J.; Samuelly-Leichtag, G. Efficacy of cannabis-based medicines for pain management: A systematic
review and meta-analysis of randomized controlled trials. Pain Physician 2017,20, E755–E796.
15.
Mirelman, D.; Waissengrin, B.; Goldway, N.; Sharon, H.; Brill, S.; Wolf, I. Use of medical cannabis: Perceptions
of Israeli oncologists. Lancet Oncol. 2019,20, 475–477. [CrossRef]
16.
Coyne, Z.; Cowzer, D.; Hennessy, M.; Linehan, A.; Hennessy, B.T.; Grogan, W.; Breathnach, O.S.; Morris, P.G.
Cannabis and cancer: Examining the use and perceived benefits in an Irish cancer cohort. J. Clin. Oncol.
2020,38. [CrossRef]
17.
Kleckner, A.S.; Kleckner, I.R.; Kamen, C.S.; Tejani, M.A.; Janelsins, M.C.; Morrow, G.R.; Peppone, L.J.
Opportunities for cannabis in supportive care in cancer. Ther. Adv. Med. Oncol. 2019,11, 1–29. [CrossRef]
18.
Berman, P.; Futoran, K.; Lewitus, G.M.; Mukha, D.; Benami, M.; Shlomi, T.; Meiri, D. A new ESI-LC/MS
approach for comprehensive metabolic profiling of phytocannabinoids in Cannabis. Sci. Rep. 2018,8, 1–15.
[CrossRef]
19. Shapira, A.; Berman, P.; Futoran, K.; Guberman, O.; Meiri, D. Tandem mass spectrometric quantification of
93 terpenoids in Cannabis using static headspace (SHS) injections. Anal. Chem. 2019, 1–9. [CrossRef]
20.
Baram, L.; Peled, E.; Berman, P.; Yellin, B.; Besser, E.; Benami, M.; Louria-Hayon, I.; Lewitus, G.M.; Meiri, D.
The heterogeneity and complexity of cannabis extracts as antitumor agents. Oncotarget
2019
,10, 4091–4106.
[CrossRef]
21.
Russo, E.B.; Marcu, J. Cannabis pharmacology: The usual suspects and a few promising leads. In Advances in
Pharmacology; Elsevier: Amsterdam, The Netherlands, 2017; Volume 80, pp. 67–134.
Pharmaceuticals 2020,13, 435 14 of 16
22.
Brown, M.R.D.; Farquhar-Smith, W.P. Cannabinoids and cancer pain: A new hope or a false dawn? Eur. J.
Intern. Med. 2018,49, 30–36. [CrossRef]
23.
Hazekamp, A.; Fischedick, J.T. Cannabis—from cultivar to chemovar. Drug Test. Anal.
2012
,4, 660–667.
[CrossRef] [PubMed]
24.
Milay, L.; Berman, P.; Shapira, A.; Guberman, O.; Meiri, D. Metabolic profiling of cannabis secondary
metabolites for evaluation of optimal postharvest storage conditions. Front. Plant Sci.
2020
,11, 1–15.
[CrossRef] [PubMed]
25.
Noyes, R., Jr.; Brunk, S.F.; Avery, D.A.; Canter, A.C. The analgesic properties of delta-9-tetrahydrocannabinol
and codeine. J. Clin. Pharma. 1975,18, 84–89. [CrossRef] [PubMed]
26.
Noyes, R.; Brunk, S.; Baram, D.A.; Canter, A. Analgesic effect of delta-9-tetrahydrocannabinol. J. Clin. Pharma.
1975,15, 139–143. [CrossRef]
27.
Jochimsen, P.R.; Lawton, R.L.; VerSteeg, K.; Noyes, R., Jr. Effect of benzopyranoperidine, a delta-9-THC
congener, on pain. Int. J. Clin. Pharmacol. Ther. 1978,24, 223–227. [CrossRef]
28.
Staquet, M.; Gantt, C.; Machin, D. Effect of a nitrogen analog of tetrahydrocannabinol on cancer pain. Int. J.
Clin. Pharmacol. Ther. 1978,23, 397–401. [CrossRef]
29.
Portenoy, R.K.; Ganae-Motan, E.D.; Allende, S.; Yanagihara, R.; Shaiova, L.; Weinstein, S.; McQuade, R.;
Wright, S.; Fallon, M.T. Nabiximols for opioid-treated cancer patients with poorly-controlled chronic pain: A
randomized, placebo-controlled, graded-dose trial. J. Pain 2012,13, 438–449. [CrossRef]
30.
Fallon, M.T.; Lux, E.A.; Mcquade, R.; Rossetti, S.; Sanchez, R.; Sun, W.; Wright, S.; Lichtman, A.H.;
Kornyeyeva, E. Sativex oromucosal spray as adjunctive therapy in advanced cancer patients with chronic
pain unalleviated by optimized opioid therapy: Two double-blind, randomized, placebo-controlled phase 3
studies. Br. J. Pain 2017,11, 119–133. [CrossRef]
31.
Lynch, M.E.; Cesar-Rittenberg, P.; Hohmann, A.G. A double-blind, placebo-controlled, crossover pilot
trial with extension using an oral mucosal cannabinoid extract for treatment of chemotherapy-induced
neuropathic pain. J. Pain Symptom Manag. 2014,47, 166–173. [CrossRef]
32.
Good, P.; Haywood, A.; Gogna, G.; Martin, J.; Yates, P.; Greer, R.; Hardy, J. Oral medicinal cannabinoids to
relieve symptom burden in the palliative care of patients with advanced cancer: A double-blind, placebo
controlled, randomised clinical trial of efficacy and safety of cannabidiol (CBD). BMC Palliat. Care
2019
,
18, 110. [CrossRef]
33.
Landshaft, Y.; Albo, B.; Mechoulam, R.; Afek, A. The Updated Green Book (May 2019): The Official Guide to
Clinical Care in Medical Cannabis. Available online: https://www.health.gov.il/hozer/mmk154_2016.pdf
(accessed on 8 June 2020).
34.
Small, E.; Beckstead, H. Cannabinoid phenotypes in Cannabis sativa. Nature
1973
,245, 147–148. [CrossRef]
35.
Tram
è
r, M.R.; Carroll, D.; Campbell, F.A.; Reynolds, D.J.; Moore, R.A.; McQuay, H.J. Cannabinoids for control
of chemotherapy induced nausea and vomiting: Quantitative systematic review. BMJ
2001
,323, 16–21.
[CrossRef]
36.
Machado Rocha, F.C. Therapeutic use of Cannabis sativa on chemotherapy-induced nausea and vomiting
among cancer patients: Systematic review and meta-analysis. Eur. J. Cancer. Care
2008
,17, 431–443.
[CrossRef]
37.
Whiting, P.F.; Wolff, R.F.; Deshpande, S.; Di Nisio, M.; Duffy, S.; Hernandez, A.V.; Keurentjes, J.C.; Lang, S.;
Misso, K.; Ryder, S.; et al. Cannabinoids for medical use: A systematic review and meta-analysis. J. Am.
Med. Assoc. 2015,313, 2456–2473. [CrossRef]
38.
Pawasarat, I.M.; Schultz, E.M.; Frisby, J.C.; Mehta, S.; Angelo, M.A.; Hardy, S.S.; Kim, T.W.B. The efficacy of
medical marijuana in the treatment of cancer-related pain. J. Palliat. Med. 2020, 1–8. [CrossRef]
39.
Vigano, A.; Aprikian, S.; Kasvis, P.; Bacis, V.; Al Harrasi, A.; Aubin, N.M.; Vigano, M.; Borod, M. Safety and
effectiveness of medical cannabis as a complementary option for supportive cancer care: Results from the
Cannabis Pilot Project. J. Clin. Oncol. 2020,38, 12106. [CrossRef]
40.
Schleider, L.B.-L.; Mechoulam, R.; Lederman, V.; Hilou, M.; Lencovsky, O.; Betzalel, O.; Shbiro, L.; Novack, V.
Prospective analysis of safety and efficacy of medical cannabis in large unselected population of patients
with cancer. Eur. J. Intern. Med. 2018,49, 37–43. [CrossRef]
41.
Seow, H.; Barbera, L.; Sutradhar, R.; Howell, D.; Dudgeon, D.; Atzema, C.; Liu, Y.; Husain, A.; Sussman, J.;
Earle, C. Trajectory of performance status and symptom scores for patients with cancer during the last six
months of life. J. Clin. Oncol. 2011,29, 1151–1158. [CrossRef]
Pharmaceuticals 2020,13, 435 15 of 16
42. Gorter, R.W. Cancer cachexia and cannabinoids. Complement. Med. Res. 1999,6, 21–22. [CrossRef]
43.
Wang, J.; Wang, Y.; Tong, M.; Pan, H.; Li, D. Medical cannabinoids for cancer cachexia: A systematic review
and meta-analysis. BioMed Res. Int. 2019,2019, 1–6. [CrossRef]
44.
Zuardi, A.W.; de Souza Crippa, J.A.; Hallak, J.E.C.; Campos, A.C.; Guimar
ã
es, F.S. The anxiolytic effects of
cannabidiol (CBD). Handb. Cannabis Relat. Pathol. 2017, e131–e139. [CrossRef]
45.
Feingold, D.; Brill, S.; Goor-Aryeh, I.; Delayahu, Y.; Lev-Ran, S. Depression and anxiety among chronic pain
patients receiving prescription opioids and medical marijuana. J. Affect. Disord.
2017
,218, 1–7. [CrossRef]
[PubMed]
46.
Haroutounian, S.; Meidan, R.; Davidson, E. The effect of medicinal cannabis on pain and quality of life
outcomes in chronic pain: A prospective open-label study. Clin. J. Pain
2016
,32, 1036–1043. [CrossRef]
[PubMed]
47.
Darkovska-Serafimovska, M.; Serafimovska, T.; Arsova-Sarafinovska, Z.; Stefanoski, S.; Keskovski, Z.;
Balkanov, T. Pharmacotherapeutic considerations for use of cannabinoids to relieve pain in patients with
malignant diseases. J. Pain Res. 2018,11, 837. [CrossRef] [PubMed]
48.
Fogel, J.S.; Kelly, T.H.; Westgate, P.M.; Lile, J.A. Pharmacology, Biochemistry and behavior sex differences
in the subjective effects of oral
∆
9-THC in cannabis users. Pharmacol. Biochem. Behav.
2017
,152, 44–51.
[CrossRef] [PubMed]
49.
Zhornitsky, S.; Potvin, S. Cannabidiol in humans—The quest for therapeutic targets. Pharmaceuticals
2012
,5,
529–552. [CrossRef] [PubMed]
50.
Savage, S.R.; Romero-Sandoval, A.; Schatman, M.; Wallace, M.; Fanciullo, G.; McCarberg, B.; Ware, M.
Cannabis in pain treatment: Clinical & research considerations. J. Pain 2016,17, 654–668.
51.
Borgelt, L.M.; Franson, K.L.; Nussbaum, A.M.; Wang, G.S. The pharmacologic and clinical effects of medical
cannabis. Pharmacother. J. Hum. Pharmacol. Drug Ther. 2013,33, 195–209. [CrossRef]
52.
Tanda, G.; Goldberg, S.R. Cannabinoids: Reward, dependence, and underlying neurochemical
mechanisms—A review of recent preclinical data. Psychopharmacology 2003,169, 115–134. [CrossRef]
53.
Wade, D.T.; Robson, P.; House, H.; Makela, P.; Aram, J. A preliminary controlled study to determine whether
whole-plant cannabis extracts can improve intractable neurogenic symptoms. Clin. Rehabil.
2003
,17, 21–29.
[CrossRef]
54.
Notcutt, W.; Price, M.; Miller, R.; Newport, S.; Phillips, C.; Simmons, S.; Sansom, C. Initial experiences with
medicinal extracts of cannabis for chronic pain: Results from 34 ‘N of 1
0
studies. Anaesthesia
2004
,59, 440–452.
[CrossRef] [PubMed]
55. Qualtrics; Version 12018; Qualtrics, L.L.C.: Provo, UT, USA, 2015.
56.
Webber, K.; Davies, A.N. Validity of the memorial symptom assessment scale-short form psychological
subscales in advanced cancer patients. J. Pain Symptom Manage. 2011,42, 761–767. [CrossRef] [PubMed]
57. Melzack, R. The short-form McGill pain questionnaire. Pain 1987,30, 191–197. [CrossRef]
58.
Pollard, C.A. Preliminary validity study of the pain disability index. Percept. Mot. Skills
1984
,59, 974.
[CrossRef] [PubMed]
59. Brooks, R.; Group, E. EuroQol: The current state of play. Health Policy 1996,37, 53–72. [CrossRef]
60.
Shochat, T.; Tzischinsky, O.; Oksenberg, A.; Peled, R. Validation of the Pittsburgh Sleep Quality Index Hebrew
translation (PSQI-H) in a sleep clinic sample. Isr. Med. Assoc. J. 2007,9, 853–856.
61. Beck, A.T.; Steer, R.A.; Brown, G.K. Beck depression inventory-II. San Antonio 1996,78, 490–498.
62.
Sullivan, M.J.L.; Bishop, S.R.; Pivik, J. The pain catastrophizing scale: Development and validation.
Psychol. Assess. 1995,7, 524. [CrossRef]
63.
Spitzer, R.L.; Kroenke, K.; Williams, J.B.W.; Löwe, B. A brief measure for assessing generalized anxiety
disorder: The GAD-7. Arch. Intern. Med. 2006,166, 1092–1097. [CrossRef]
64.
Moore, T.; Cohen, M.; Furberg, C. Serious adverse drug events reported to the Food and Drug Administration,
1998–2005. Arch. Intern. Med. 2007,167, 1752–1759. [CrossRef]
65.
Sznitman, S.R. Trends in medical cannabis licensure, Israel, 2013–2018. Drug Alcohol Rev.
2020
, 1–5. [CrossRef]
[PubMed]
66.
R Statistics, Version 1.1.463; Ströbel, A.; Haynes, A. R Package Table: Create Tables for Reporting Clinical Trials,
Version 0.1.5; Comprehensive R Archive Network (CRAN), 2019. Available online: https://cran.r-project.org/
web/packages/atable/atable.pdf (accessed on 29 November 2020).
Pharmaceuticals 2020,13, 435 16 of 16
67.
R Statistics, Version 1.1.463; Patil, I.; Powell, C. Ggstatsplot: “ggplot2” Based Plots with Statistical Details;
Comprehensive R Archive Network (CRAN), 2008. Available online: https://cran.r-project.org/web/packages/
ggplot2/ggplot2.pdf (accessed on 29 November 2020).
68.
R Statistics, Version 1.1.463; Wickham, H. Easily Install and Load “Tidyverse” Packages, Version 1.3.0; Tidyverse:
Comprehensive R Archive Network (CRAN), 2019. Available online: https://cran.r-project.org/web/packages/
tidyverse/tidyverse.pdf (accessed on 29 November 2020).
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