Executive Summary
Colorado leads the country in implementation and legislation of medical and retail
cannabis; however, there is a dearth of scientifically rigorous studies on usage, safety, and
efficacy particularly with newer high potency strains and novel routes of administration. This
proposal will create a large cohort of frequent cannabis users who can be followed
prospectively. The cohort will be used to conduct four nested observational studies that test
therapeutic efficacy and assess the safe use of modern cannabis strains and methods of use
for pain, sleep, maternal/fetal health, and obstructive lung disease (asthma and COPD),
which are some of the most common indications and safety concerns for users.
Rational for the proposal: Although the National Institutes of Health (NIH) through the National
Institute of Drug Abuse (NIDA) has a well establish research program for federally funded
research, gold-standard randomized-control studies relevant to Colorado users cannot be
performed because the products that NIDA distributes for research have little relevance to actual
patterns of usage in states that have medical or retail cannabis sales. For instance, NIDA cannabis
cigarettes are produced using a single cloned strain, which has a maximum potency of 4% and
represents a single combination of cannabinoids. Many Colorado users smoke higher potency
(15% or greater) strains. Furthermore, there has been an explosion of non-traditional methods of
use such as oral (edible) and vaporizing (hash oils) and interest in non-THC cannabinoids such as
cannabidiol (CBD) for therapeutic use. Non-THC cannabinoids are claimed to exhibit therapeutic
effects with low psychotropic effects. There are virtually no publications in this area and the
explosive growth of these new strains and methods of administration has left a knowledge gap for
instruments that quantitatively assess the method of use, use patterns and total exposure to
specific cannabinoids. In preliminary work to address these knowledge gaps, we have developed
an improved usage questionnaire that will be refined and validated using blood and urine
biomarkers in a large prospective cohort of moderate-to-heavy cannabis users. This
instrument will more accurately reflect actual usage and serve as reference for epidemiologic data
collection for safety and efficacy studies. In preparation we obtained IRB approval and an NIH
confidentiality certificate and have started recruiting study participants into the Colorado
Cannabis Cohort (CCC). Large cohorts such as the CCC are the most efficient and cost
effective resource for conducting multiple observational studies such as those proposed and opens
the door for collaboration into future therapeutic claims beyond those described in this proposal.
Methods: Efficacy studies will enroll subjects from the CCC and smaller number of never users to
test the following hypotheses using a prospective, case-control study design: (1) cannabis will
reduce opioid and NSAID use for chronic musculoskeletal pain; (2) cannabis use reduces
insomnia; (3) smoking cannabis will be associated with no difference in control of asthma and
heavy smoking (but not vaporizing) will be associated with poorer lung health; (4) cannabis
consumption during pregnancy may reduce nausea, but cannabinoids persist in breast milk.
Feasibility and benefits to Coloradans: Our research group has extensive experience and an
existing infrastructure for recruiting and following large (>10,000 subjects) NIH-supported
cohorts of tobacco users (COPDGene, SPIROMICS, GRADS, etc.). This expertise will facilitate
our recruiting 1,500 subjects. Recruitment strategies include multiple large networks of
community partners and local dispensaries. Each participant will be extensively phenotyped
including assessment of cannabinoid biomarkers in blood and/or urine. In addition to addressing
the safety and efficacy hypotheses, the CCC will benefit Coloradans by creating a large
collaborative resource for Colorado researchers interested in future cannabis research.
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Specific Aims:
SA 1: Recruit and thoroughly characterize 1,500 frequent cannabis users (>3 days/week for
greater than one year) into the Colorado Cannabis Cohort (CCC)
SA 2: Develop and validate a detailed cannabis use instrument (questionnaire) that can measure
acute and long-term cannabis usage with cannabinoid biomarkers in blood and urine as a
reference standard to improve characterization and validity in future cannabis research
SA 3: Test therapeutic efficacy and safety of modern cannabis
a. Prospective observational case-control efficacy studies of cannabis intended to test:
i. Pain control of chronic musculoskeletal disease
ii. Sleep initiation and quality
iii. Improved control and reduced severity of asthma
b. Safety assessments of chronic cannabis use for
i. Lung health (airflow obstruction, chronic bronchitis, emphysema)
ii. Metabolism (clearance of cannabinoids in blood, urine, breast milk)
Year 1 N = 500
Year 3 N = 500
Year 3 N = 500
SA1
Coloardo Cannabis Cohort
N=1,500
SA2
Cannabis Use Instrument
Validation
N=150
SA3a
Efficacy in MSK
N=100+ 100 control
SA3
Safety (MSK, Lung)
N=1,500
SA2
Cannabis in Breast Milk
N = 30 + 30 control
SA3
Efficacy for Sleep
N = 75+ 75control
SA3
Efficacy for Asthma
N= 50 + 50 control
A. Background and Significance
Background: Over 271,325 Coloradans (as of August, 2014) have applied for medical cannabis
cards and 6-29% of the US population currently uses cannabis for relief from debilitating medical
conditions (8). Some of the most common self-reported uses are musculoskeletal (MSK) pain,
sleep, nausea and asthma; however, there are few studies testing the therapeutic claims of these
common uses. The most common route of cannabis administration is inhalation of burned plant
material, but newer strains and methods (vaping, edibles) are in use with unknown significance.
We propose to leverage our infrastructure and experience in conducting large observational
studies of tobacco smokers to address these knowledge deficits. Colorado is the ideal locale
because it is the first state to allow retail cannabis, one of the first to allow medical cannabis, and
has a well-organized cannabis community.
Cannabis for pain: Musculoskeletal (MSK) pain (osteoarthritis, chronic tendonitis, peripheral
neuropathy, fibromyalgia and incomplete recovery from fractures or trauma) affects more than
half of the aging population [1]. In Colorado, 93% of medical cannabis users cite chronic pain
as a reason for its use (CDPHE, August, 2014); however, little is known about the epidemiology
of MSK conditions associated with cannabis use, nor is there information regarding its
effectiveness (e.g. reducing dependence on opioids and NSAIDS). This proposal will assess
clinical features of cannabis use for MSK pain and conduct a prospective, observational case
control study to assess potential efficacy in MSK diseases.
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Cannabis for sleep: Insomnia is the most common sleep disorder and affects 10-15% of the US
population. Although it is not an approved diagnosis for medical cannabis, many patients take
cannabis before bedtime to promote sleep. For instance, a survey in Hawaii found that 45% of
respondents use medical cannabis for relief of insomnia [2]; however, a small study (18 frequent
cannabis users) revealed that stopping cannabis increases total sleep time, but increases waking
and periodic limb movement [3]. These conflicting reports suggest that a study with formal sleep
testing is necessary to determine whether cannabis reduces insomnia and promotes quality sleep.
Cannabis and obstructive lung disease (asthma and COPD): Current literature strongly supports
tobacco causing airflow obstruction (COPD/Asthma), frequent cough and mucus (chronic
bronchitis), and destruction of lung tissue (emphysema); however, there is a paucity of literature
in heavy or older cannabis users and existing literature is conflicting. For instance, the widely
cited Wellington NZ cohort [4] included 75 cannabis-only subjects. There were no data provided
on frequency of use; however, the authors found evidence of increased airflow limitation
(COPD), but only mild emphysema on high resolution CT (HRCT). In the Dunedin NZ study of
28 heavy cannabis only users (> daily use), there was more cough, wheezing, chest tightness,
sputum production and worse airflow obstruction [5]. The BOLD study in Canada had 81
cannabis only smokers and nearly all subjects had lifetime smoking of less than 1 joint year (1
joint per day for a year); despite the small number of subjects and low frequency users, the
authors conclude “Smoking only cannabis was not associated with an increased risk of respiratory
symptoms or COPD” [6]. A study of 144 young heavy cannabis smokers (mean age 32) found
more cough and sputum [7]. In summary, these studies are limited by the small number of heavy
users and did not include new strains or methods of use such as vaporizing (“vaping”).
Furthermore, one study of 8 subjects published in 1975 that suggests smoking cannabis has
bronchodilatory effects [8] and has been widely cited in the lay literature as supporting smoking
cannabis as a treatment of asthma, but there have been no follow up studies during the modern era
of asthma therapy. This focus on heavy users and large number of subjects will permit us to
determine whether heavy cannabis consumption is associated with adverse lung health. A
prospective study of asthma subjects will generate additional evidence (for/against cannabis for
asthma treatment.
Cannabis during pregnancy and lactation: Cannabis and its pharmaceuticals relieve nausea and
vomiting and are frequently used by women during pregnancy[9]. THC and its metabolites pass
freely across the placental barrier and enter fetal circulation [11]; however human studies on fetal
consequences remain inconclusive [12-16] and little is known about THC and lactation. This
proposal will extensively characterize cannabis use during pregnancy through a questionnaire
administered to pregnant and lactating women and will measure cannabinoid levels in breast milk.
Deliverables, publication plans, and future funding: SA 2 and 3 and their subaims will each
lead to manuscripts at the end of the third year (minimum 5 manuscripts). The CCC (SA 1) will
generate many ancillary cannabis publications and multiple large NIH grants to Colorado
investigators).
References
1.
2.
3.
Palazzo, C., et al., The burden of musculoskeletal conditions. PLoS One, 2014. 9(3): p. e90633.
Webb, C.W., et al., Therapeutic benefits of cannabis: a patient survey. Hawaii J Med Public
Health, 2014. 73(4): p. 109-11.
Bolla, K.I., et al., Polysomnogram changes in marijuana users who report sleep disturbances
during prior abstinence. Sleep Med, 2010. 11(9): p. 882-9.
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Aldington, S., et al., Effects of cannabis on pulmonary structure, function and symptoms.
Thorax, 2007. 62(12): p. 1058-63.
Taylor, D.R., et al., The respiratory effects of cannabis dependence in young adults. Addiction,
2000. 95(11): p. 1669-77.
Tan, W.C., et al., Marijuana and chronic obstructive lung disease: a population-based study.
CMAJ, 2009. 180(8): p. 814-20.
Tashkin, D.P., et al., Respiratory symptoms and lung function in habitual heavy smokers of
marijuana alone, smokers of marijuana and tobacco, smokers of tobacco alone, and
nonsmokers. Am Rev Respir Dis, 1987. 135(1): p. 209-16.
Tashkin, D.P., et al., Effects of smoked marijuana in experimentally induced asthma. Am Rev
Respir Dis, 1975. 112(3): p. 377-86.
Westfall, R.E., et al., Survey of medicinal cannabis use among childbearing women: patterns
of its use in pregnancy and retroactive self-assessment of its efficacy against 'morning
sickness'. Complement Ther Clin Pract, 2006. 12(1): p. 27-33.
Ebrahim, S.H., et al., Pregnancy-related substance use in the United States during 1996-1998.
Obstet Gynecol, 2003. 101(2): p. 374-9.
Fride, E., Multiple roles for the endocannabinoid system during the earliest stages of life: preand postnatal development. J Neuroendocrinol, 2008. 20 Suppl 1: p. 75-81.
English, D.R., et al., Maternal cannabis use and birth weight: a meta-analysis. Addiction, 1997.
92(11): p. 1553-60.
Day, N., et al., Prenatal marijuana use and neonatal outcome. Neurotoxicol Teratol, 1991.
13(3): p. 329-34.
Hatch, E.E., et al., Effect of marijuana use in pregnancy on fetal growth. Am J Epidemiol, 1986.
124(6): p. 986-93.
Hurd, Y.L., et al., Marijuana impairs growth in mid-gestation fetuses. Neurotoxicol Teratol,
2005. 27(2): p. 221-9.
Fergusson, D.M., et al., Maternal use of cannabis and pregnancy outcome. BJOG, 2002. 109(1):
p. 21-7.
Hagg, O., et al., The clinical importance of changes in outcome scores after treatment for
chronic low back pain. Eur Spine J, 2003. 12(1): p. 12-20.
Wells, J.M., et al., Pulmonary arterial enlargement and acute exacerbations of COPD. N Engl J
Med, 2012. 367(10): p. 913-21.
Bowler, R.P., et al., Prediction of acute respiratory disease in current and former smokers
with and without COPD. Chest, 2014.
Han, M.K., et al., Chronic obstructive pulmonary disease exacerbations in the COPDGene
study: associated radiologic phenotypes. Radiology, 2011. 261(1): p. 274-82.
Kim, Y.I., et al., Gender differences of airway dimensions in anatomically matched sites on CT
in smokers. COPD, 2011. 8(4): p. 285-92.
B. Capacity/Program Infrastructure
Overview: with the exception of offices for CU collaborators (Drs. Kinney, Crume) and
Cannabinoid Testing (Dr. Christians), all work will take place at National Jewish Health (NJH),
which has been ranked one of the top research hospitals for 17 years in a row. NJH is located at
1400 Jackson Street, Denver, CO, 80206. The hospital has a large outpatient clinic focused on
research. NJH has a NIH funded Clinical Translational Research Center (CTRC) with 3 exam
rooms, a procedure room (phlebotomy, and spirometry), an interview room, and coordinator
offices on the third floor of the Goodman Building (K341). An adjacent laboratory is available for
handling clinical samples. Chest imaging includes multi-detector CT scanners (Siemens 64 and
128 detector HRCT). The institutional biobank description can be found at
(www.nationaljewish.org/professionals/research/support/facilities/bioinfo/).
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IRB and approvals: NJH has a fully functional IRB, with Federalwide Assurance #:
FWA00000778 (expires February 23, 2017) and IRB Registration #: IORG0000018 (expires
January 28, 2017). The NJH IRB shares protocols with CO-MIRB. The protocol for this study has
already received an NIH certificate of confidentiality, has been approved by the IRB (#HS-2854),
and is actively enrolling subjects.
Research space and infrastructure: Dr. Bowler has research and office space in the Goodman
Building (K715a). The Research Coordinators have office space sufficient for 5 coordinators in
K012. There are sufficient password-protected desktop computers (Mac or PCs) with Microsoft
Office 2011 and other necessary software.
Experience with similar studies: Our group has > 10 year history of collaboration on multiple
large NIH-supported clinical cohorts (e.g.
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COPDGene, SPIROMICS, GRADS, SARP, etc.).
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Industry Partners: Our team has established
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collaborations with 14 dispensaries (Medicine Man,
1000
800
RiverRock, etc.). These dispensaries have begun
600
distributing our flyers to recruit into the CCC.
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Community Partners: Drs. Wamboldt and Bowler
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have multiple well-established partners with
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community providers and research groups
including: North East Denver and North Aurora
Family Resource and Healthcare Partners, Colorado
Marijuana Advisory Group, Colorado Community
Figure 1. NJH recruitment for
Advocacy and Clean Air Partners, etc.).
COPDGene (similar to the Colorado
C. Research Design and Methods
Cannabis Cohort). 1400 subjects were
C. SA 1: Expansion of Colorado Cannabis Cohort
recruited from 2008-2011 (3 years).
to 1,500 moderate-to-heavy users.
C.1.a.i. Rationale: There are no large cohorts of moderate-to-heavy cannabis users. Creation of
such a cohort will make Colorado a leader in epidemiologic studies of cannabis. Our research
group has extensive experience and infrastructure in creating similar cohorts, which can be costeffectively leveraged as comparison groups for the proposed cohort.
C.1.a.ii. Preliminary studies and methods: The paradigm for building a large well-characterized
cohort is our work recruiting current, former and never tobacco smokers (e.g. NIH-supported
COPDGene, SPIROMICS, CCRN). For example, in 3 years our research group screened more
than 2900 subjects and enrolled 1400 never, current, and former tobacco smokers for the NIH
funded COPDGene cohort (Figure 1).
Experimental Approach:
C.1.a.ii. Recruitment for the Colorado Cannabis Cohort (CCC): The CCC received a NIH letter
of confidentiality, has been IRB approved (#HS 2854), and has started recruitment (unfunded) to
demonstrate feasibility. Although just starting, the median age (55) and gender (50% male) are
similar to the other NIH-cohorts. Subjects are recruited by flyer from local dispensaries and
community health programs (see section B). We plan to recruit 500 subjects per year for 3 years
for a total of 1500 subjects. Inclusion: Colorado residents, age 21-80 years, who have used any
cannabis (smoked, vaped, edible, etc.) on average more than 3 days per week for at least 1 year,
who are able to provide written consent in either Spanish or English. Exclusion (rationale):
Tobacco pack-year > 30 pack-years (confounding with tobacco-induced COPD); cancer under
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active treatment in past 12 months or other disease with median life expectancy < 5 years (low
probability of follow up); previous lung surgery (unable to do accurate lung phenotyping).
C.1.a.iii. Protocol. Subjects will be screened over telephone and invited to NJH. Consent will
occur at first visit (visit 1) in exam rooms used for clinical research (CCTSI infrastructure). Six
month follow up contacts will be by email and telephone for repeat usage questionnaire and
comorbidity assessment. Procedures at visit 1: questionnaires (cannabis usage questionnaire (see
SA2), medical questionnaire (including comorbidities), respiratory health questionnaire, SF-36,
SGRQ, medications, pain survey), physiology (spirometry after bronchodilator, DLco, 6-minute
walk, grip strength, range of motion), and biosampling (blood and urine). The study visit takes 2
hours and subjects will be compensated $75. Rationale. We have recruited more than 10,300
subjects using these protocols and MOPs which can be found at http://www.copdgene.org.
C.1.a.v. Determine congruence between prescribed and actual indications of use for medical
cannabis. Multiple states have reported indications for medical cannabis based on Red Card data.
For instance, “severe pain”, “muscle spasm”, and “severe nausea” account for >95% of
prescriptions. There are few data on the actual reasons for cannabis use and no data on
medical indications for retail cannabis. We will compare actual and self-reported prescribed
categories of WHO International Classification of Disease (ICD-9) code using Chi-square testing
by strain and method of use.
C.1.a.vi. Power calculations. Because of the varied nature of cannabis use in Colorado (smoke,
vape, edible) and the multiple hypotheses that will be tested in this proposal, we need large
recruitment. For instance, to detect a 5% change (from 10-15%) in a symptom such as cough in
40% of subjects compared (e.g. those who vape), we would have approximately 81.4% power to
detect a difference at P < 0.05 if we recruit 1,500 subjects. See SA 2 and 3 for additional power
calculations.
C.1.vii. Anticipated outcomes and alternative approaches: In preliminary data we have shown
that we can screen and enroll nearly 500 subjects per year for the COPDGene cohort including
blood sampling and storage. In pilot data we have demonstrated that we can enroll cannabis users
in the CCC.
C. SA #2: Development of Cannabis Use (CU) instrument and biomarker measurement
C.2. a. Rationale: Existing survey instruments such as the one developed by the UCLA > 20 years
[7] are limited by incomplete assessment of chronic use, dated language (e.g. older cannabis strain
names), and do not take into account newer delivery methods (vaping, dabbing, edibles), which
are most relevant to Colorado cannabis research. Furthermore, enrollment of subjects who used
well-characterized strains can lead to more standard assessment of cannabinoid content.
C.2.b. General approach. We will refine and validate a usage instrument with subjects who
regularly use well-characterized cannabis strains and with one of 4 predominant methods of use:
(1) smoking; (2) vaping; (3) edibles; (4) and other (e.g. dabbing). Short term and long term usage
will be correlated with cannabinoid biomarkers in blood and urine. Women who are currently
pregnant, breastfeeding or intending to become pregnant will be recruited into a substudy to
characterize cannabinoid use during pregnancy and lactation.
C.2.c.Hypotheses: The usage instrument will detect a dose-response relationship between
reported cannabis use and levels of cannabinoids in blood and urine. Furthermore, the instrument
will work for multiple methods of use (e.g. smoking, vaping, etc.) and the biomarkers may
distinguish between species of cannabis (e.g. Indica predominant versus Sativa predominant.).
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C.2.d. Preliminary Data: In preliminary unfunded work, we have developed a draft instrument,
which can be found at https://redcap.ucdenver.edu/surveys/?s=jgFfaYugoy. This instrument was
piloted on 10 frequent medical and recreational cannabis users and refined to its current version.
The instrument has currently been used for the first enrollees into the CCC (see SA1). The usage
questionnaire has taken approximately 10 minutes to complete.
C.2.e. Detailed study design: Study population. From CCC, we will recruit five groups of
subjects: (1) controls who report no cannabis or tobacco use (see Aim 3 for control recruitment);
(2) cannabis users who exclusively smoke joints or pipes; (3) users who exclusively vape; (4)
those who only use edibles; (5) other predominant uses (e.g. dabbing). We will attempt to enroll
30 subjects per group with approximately half using predominantly Indica species and half using
Sativa (essentially all strains of cannabis are hybrids of Indica and Sativa but one or the other
tends to predominate). Groups (2-5) will be recruited through a single dispensary (e.g. Medicine
Man) since all strains produced by this dispensary are clones that have well characterized
cannabinoid concentrations. Study visit. Subjects must have stable usage for one week. There will
be 4 timed blood draws (one hour before self dosing, then 30 minutes, 2 hours, and 24 hours after
a single self dosing) and one timed overnight urine collection. Participants will record the time of
final void and collect urine until their waking void. The urine sample will be transferred to storage
tubes and shipped overnight using a freezer cold pack and processed by the study upon receipt.
Biologic measurements. Plasma and urine analytes measured (see D). A plasma/urine creatnine
ratio with urine volume will be used to quantitate 24 hour excretion of biomarkers.
Breast milk substudy: These vulnerable subjects will be protected under federal guidelines and
will not undergo potential harmful procedures such as CT scan or spirometry. This substudy (run
by Dr. Crume) will include 30 pregnant subjects who regularly use cannabis during breastfeeding
and 30 controls who do not. Individuals will be enrolled into CCC during their pregnancy with a
return visit approximately 2 months post-partum for repeat blood and urine sample. The breast
milk sample will be collected with a 1 ml timed mid-expression of breast milk (see above for
time) using a breast pump (the rest remaining for baby).
2.f. Data analysis: Bolus pharmacokinetics (first order) will be used from blood (or breast milk)
concentration (baseline adjusted to account for chronic use) to calculate dosage from a single
cannabinoid (e.g. delta-9-THC); urine pharmacokinetics will be used to assess steady state dosing
(e.g. THC-COOH-Glucuronide). A mixed effects model (including covariates such as age and
gender) will be used to determine strain (Indica or Sativa) and method of use (smoke, vape, edible,
dabbing) effects for each biologic biomarker. We will assume that subjects who report never
using cannabinoids will have near zero levels for biomarkers. Those who do not meet this
definition will be excluded. We will use random forest and regression models to refine the usage
questionnaire to select the most parsimonious set of questions (using Akaike Information
Criterion) that predict urinary concentrations of cannabinoids.
2.g. Anticipated outcomes and alternative approaches: Our initial cannabis usage instrument is
comprehensive and long, but should correlate with use among heavy users in Colorado. Data
analysis will refine the instrument to shorter length without losing significant accuracy.
Confounding medical diseases (liver or renal failure) would be expected to alter cannabinoid
metabolism and subjects who report these diseases will be excluded. We would anticipate that
vaping will have similar peak and troughs to smoking and that edible use will lead to more stable
blood levels. Because human breast milk has a high fat content, we anticipate that cannabinoids
may be present > 24 after last use. If this is the case for the first few subjects, we will continue to
extend our last collection time to identify the time at which cannabinoids become undetectable in
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breast milk. Since every member of the cohort will have the usage instrument and urinary
biomarkers, this will become an invaluable research database and recruitment source for Colorado
researchers. We also plan to administer the validated instrument to other large NIH supported
cohorts (e.g. COPDGene, SPIROMICS, etc.) and will be free to the public after publication.
C.SA3. Efficacy and safety of medical cannabis
3.a. – Assessment of medical cannabis in relieving musculoskeletal-associated chronic pain
Hypotheses: Chronic medical cannabis use reduces pain severity, opioid and NSAID use and
improves quality of life and physical function, but is associated with more balance problems,
falls, injuries, DUI charges or motor vehicle accidents.
Rationale: Chronic musculoskeletal (MSK) pain is difficult for many people to manage and
effective treatments are limited. It is common for patients to use multi-drug regimens including
opiates as well as physical modalities.
3.a.i.Preliminary data: We find that 10,300 COPDGene subjects report a high prevalence MSK
symptoms and diagnoses (20% osteoarthritis; 26% stiffness or pain in the legs or back that limits
their walking; 29% back pain; 47% chronic joint pain).
3.a.ii.General experimental approach. All 1,500 CCC participants will complete a questionnaire
identifying specific MSK diagnoses and symptoms as well as those that are being treated with
regular cannabis. A subset of these subjects and matched non-cannabis using controls will be
recruited for an efficacy study. Broad diagnostic categories will include: osteoarthritis of
peripheral joints, back pain, disc disease, spinal stenosis, scoliosis, neck pain, radiculopathy,
chronic joint symptoms without arthritis, rotator cuff rupture or disease, chronic foot pain, reflex
sympathetic dystrophy (RSD) or regional pain syndrome (RPS), inflammatory arthritis,
fibromyalgia, neuropathic pain, muscle spasms/spasticity and “other”.
3.a.iii. Data collection: All subjects will complete a visual analogue scale (VAS) (0-100) of pain
severity at time of visit and average pain over the past 30 days, Medical Outcomes Study, Short
form 36 (MOS SF-36) will be recorded at each visit. Subjects will be asked about falls, difficulty
with balance, memory trouble, motor vehicle accidents, and DUI charges/conviction.
Baseline cross-sectional visit: We will confirm primary pain complaint and related symptoms
(paresthesias, dysesthesias, muscle spasms, weakness, joint instability, stiffness, fatigue, and
functional impairments), use of walking aids, wheelchair, scooter, prostheses, and adaptive
equipment will be noted. Subjects will provide baseline data on history of falls, difficulty with
balance, memory trouble and motor vehicle accidents. Secondary outcomes: Six minute walk
distance; grip strength; active range of motion screen (reach over head, squat, touch toes, toe and
heel walk); Romberg test, tandem gait and finger to nose testing for balance/proprioception.
3.a.iv. Efficacy sub-study: Fifty arthritis and fifty fibromyalgia cannabis-using subjects will be
recruited from the CCC and 50 matched (age, gender, race, disease severity) non-cannabis control
subjects will be recruited from clinic and by flyer (N=200 total) to participate in a 6-month
efficacy study. Each subject will be asked to provide pain data pre- and post-cannabis use using
the smartphone application “My Pain Diary” (chronicpainapp.com) that allows the subjects to
record pain severity on a VAS scale at time points throughout the day. These reports can be
downloaded to the CCC study daily. They will be asked to record daily use of opioids, NSAIDs
and other pain management modalities and the time administered in addition to their pain before
and after each therapeutic treatment with either cannabis or other analgesic over a two week
period. Subjects will be asked to repeat the 2-week data collection at 3 and 6 months for a total of
three intervals.
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3.a.v. Statistical analysis. For chronic pain, the minimum clinically important change in VAS
score associated with pain relief has been shown to be 18-19 points [17]. This will be the degree
of change that we expect to see in response cannabis. Overall mean (SD) change in pain score
will be calculated by group and separately for each of the three testing intervals by group, The
analyses of change in pain score will utilize linear mixed-effects models, including random
coefficient models, to examine changes in pain score values before and after use of either
cannabis or other medications, across each two week period and across each of the study visits.
Mixed effects models allow modeling of between-subjects effects as well as within-subject errors
and can incorporate both random and fixed effects, including repeated measures over time and
time varying covariates. These models are superior to traditional repeated measures ANOVA in
that they allow for unbalanced data with unequal measurement intervals and also missing data.
The random coefficient models will be used to estimate a subject-specific intercept and subjectspecific slope for change in pain score for each subject in the data set. These models can
simultaneously estimate the associations between a risk factor of interest and baseline pain (the
random intercept) and between the risk factor of interest and change in pain score over time (the
slope). The associations between the risk factors and change in pain score over time will be
modeled by including interaction terms between the risk factors and time. The primary outcome
will be mean change in pain score after therapeutic use of either cannabis or other medications.
Power calculations. A sample size of 50 achieves 74% power to detect a mean of paired
differences of 15.0 in VAS score with an estimated standard deviation of differences of 40.2 and
with a significance level (alpha) of 0.05 using a two-sided paired t-test. Observed differences in
pain reports in excess of 19 points on VAS are expected in patients reporting adequate pain
control on analgesics. Our use of linear mixed effects models will reduce the standard error of this
estimate and allow us to observe smaller differences in VAS score. We will examine other
important outcomes as well such as quality of life and functional capacity.
3.a.vi. Anticipated outcomes and alternative approaches: We anticipate that subjects who are
currently using cannabis to manage MSK pain are stable on their current regimen and that we will
find that pre cannabis VAS pain scores will be significantly higher (worse) than post treatment
scores. The SF-36 instrument is an excellent supplement to the use of a VAS pain scale that can
inform us of the overall pain severity and we expect that these subjects will have fairly stable pain
and function scores over the six months of the efficacy study. We will compare usage of opioids,
NSAIDs and other pain modalities in the cannabis group to the control group and expect to see
reduced use of opioids and/or NSAIDs with cannabis use. We anticipate differences between the
arthritis and fibromyalgia groups and we may identify that one has greater improvement in pain
scores after cannabis treatment. Subjects who use higher doses or more frequent dosing regimens
should have greater frequency of side effects including falls, injuries and MVA. We will look for
trends in the demographic characteristics associated with better and worse responses.
3.b.i. –Cannabis use for sleep initiation and maintenance
Hypothesis: Cannabis use decreases sleep onset latency, increases sleep quality and daytime
functional measures and reduces central nervous system (CNS) adverse events.
3.b.ii. Rationale and preliminary data: Cannabis is commonly used for insomnia despite virtually
no studies documenting its efficacy for sleep onset latency (SOL) and quality. In preliminary
work, we find 10% (720/7,200) of 2014 National Jewish Health Sleep Center patients use
cannabis and 2% (n=144) use it specifically to initiate sleep.
Experimental Approach:
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3.b.iii. Cross sectional assessment of prevalence of cannabis use for sleep: All 1,500 CCC
participants will complete an insomnia questionnaire and the Pittsburgh Sleep Quality Index
(PSQI; scored 0-21), which is a widely used tool that provides a measure of global sleep quality
based on a respondent’s retrospective appraisal (past month) of an array of sleep measures: sleep
latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication,
and daytime dysfunction (3). The questionnaire can be completed in 5 minutes.
3.b.iv. 75 subjects (moderate-to-heavy cannabis users) scoring > 5 on PSQI (98.7 sensitive and
84.4 specific sleep disturbances) will be recruited from CCC and 75 control subjects (no
cannabis) will be recruited from NJH sleep center. Subjects will be age, gender, BMI, and tobacco
use matched. Eligibility: Exclusion criteria will consist of subjects not identifying “sleep” as their
primary indication for cannabis use. Study procedures: Polysomnography will be performed using
a portable, unattended monitor set up in the patient’s home (Embletta MPR PG®; Natus Inc.,
Kanata, Ontario Canada). Study subjects will come to NJH to have electrodes and equipment
attached by the study coordinator for electroencephalogram, electroocculogram (bilateral),
electrocardiogram, chin electromyogram, abdominal and thoracic effort belts, oxyhemoglobin
saturation (finger pulse oximetry; Nonin, Minneapolis, Minnesota), airflow (oral-nasal thermistor)
and pressure transducer. Explicit instructions will be reviewed with each subject prior to leaving
NJH in regards to directions and timing for completing each questionnaire. Daytime function
using a visual analogue score (VAS: 1 to 5) will be completed the night of the home sleep test.
The sleep diary, Epworth Sleepiness Scale (ESS) score and documentation of any adverse events
(headaches, nausea, and hallucinations) will be completed within 30 minutes of waking the
following morning. Subjects will be asked to return the home sleep test monitor to NJH the
morning following their sleep study where a registered polysomnographic technologist (RPSGT)
will download and inspect the signal of the recording prior to scoring the data.
3.b.v. Data analysis and power calculations: The primary efficacy endpoint will be SOL, (time
from the start of the PSG recording to the first epoch of sleep). Secondary endpoints include sleep
efficiency (the number of non-wake epochs from the beginning of recording to the end of
recording or total sleep time in min, divided by total recording time in min x 100), and wake after
sleep onset (the number of minutes of wakefulness after the onset of persistent sleep to the end of
the PSG recording). Additional secondary endpoints will include 2 PSG measures of sleep
maintenance, subjective daytime symptoms of insomnia, objective wake time during sleep and
number of awakenings/arousals that are non-respiratory related (spontaneous arousals: SA). With
the given sample size, we will have 100% power to detect a 22 minute difference in SOL (the
minimal clinically important difference) between cannabis subjects relative to non-cannabis
subjects at α=0.05. Secondary analyses will include examining differences in sleep efficiency
(SE) between cannabis and non-cannabis subjects. We will have 94.8% power to detect a 59%
difference in SE between cannabis subjects relative non-cannabis subjects with further reduction
in SE in subjects using inhaled cannabis compared to oral cannabis. We will also correlate
cannabinoid biomarkers with each sleep metric to validate our results.
3.b.vi. Anticipated outcomes and alternative approaches: We anticipate that higher cannabinoid
biomarkers (particularly THC metabolites) will be associated with improved SOL but also greater
adverse symptoms. We expect that cannabis use will improve sleep metrics although there will be
a distinct difference by method of use. Given the high prevalence of cannabis use indicated for
pain, it is possible that insomnia symptoms reported by subjects are the result of pain and not
primary insomnia. If we determine this is the case, then we will include subjects reporting both
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pain as a primary indication and sleep as a secondary indication and conduct regression models
adjusting for the effects of those conditions.
3.c.i. – Efficacy and safety of cannabis for obstructive lung disease
Hypothesis: Frequent users of inhaled cannabis will experience more respiratory complications
compared to non-users who have never smoked tobacco, but better respiratory health and fewer
complications compared to heavy tobacco smokers. Cannabis is associated with mild reduction in
bronchial hyperactivity, which is not clinically significant compared to typical asthma treatment
outcomes.
Rationale: Cannabis has traditionally and still is predominantly consumed through the lung by
smoking. There are two major controversies in the literature regarding cannabis and lung health.
First, several small studies have reported conflicting results regarding whether smoking cannabis
increases the risk of chronic lung disease (chronic bronchitis, airflow obstruction, and
emphysema). These studies have been limited by including few heavy users and thus are biased to
detect mild-to-no impact on lung health. Furthermore, there are no published data on new
methods of use (vaping, edibles) or modern circulating strains. Second, older and small studies (8
subjects), suggest that cannabis is a bronchodilator and there is persistent community belief that
cannabis is an effective asthma treatment (see background and significance for more details).
General approach: All CCC subjects will have spirometry and carbon monoxide diffusing
capacity (DLco) measurements. We are fortunate to have no-cost access to control subjects from
the NIH-funded COPDGene cohort (10,300 never, current and former tobacco smokers), and
SPIROMICS cohort, (3,200 never, current, and former tobacco smokers). These cohorts were
recruited using comparable protocols and trained personnel that will be used for the CCC.
Subjects who report using cannabis for asthma will be invited to participate in an asthma efficacy
study in which lung function is measured before and after cannabis use and compared to lung
function measured before and after standard care.
Preliminary studies and methods.
3.c.ii. In the NIH-funded COPDGene study we assessed 10,300 never, current and former
smokers for COPD (by
spirometry), cough and sputum
(chronic bronchitis) and
emphysema (by quantitative CT
scan). Although the never
smokers have virtually none of
these adverse lung health effects,
we find that there is substantial
heterogeneity in current and
former smokers (Figure 2). In
recent NEJM [18], Chest [19],
and Radiology [20, 21]
publications, we used these data
to create statistical models for
these outcomes. In pilot work
from our unfunded Colorado
Figure 2: Disease phenotype heterogeneity among a large population of
Cannabis Cohort, we have begun
current and former smokers (COPDGene). Airflow obstruction
(FEV1%), emphysema, and exacerbation/chronic bronchitis are only
collecting identical data in
weakly correlated.
cannabis users (see preliminary
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data in SA1). Although only a few subjects have been enrolled to date, our data suggest that daily
multiple use (including vaping) was not associated with severe impairment of airflow obstruction
(though lower DLco suggests some emphysema).
3.c.iii. Experimental Approach:
3.c.iii.clinical phenotyping: All subjects in the Colorado Cannabis Cohort undergo baseline
evaluation including assessment of respiratory health (using SGRQ, MMRC) and lung physiology
(spirometry, DLco, 6 minute walk). A subset of 300 subjects will have quantitative high
resolution CT scan for well accepted assessment of emphysema (%lung attenuation < 950 HU)
and airway disease (pi10). These subjects will be recruited equally by primary route of
administration: smoking, vaping, and edibles/other. To improve the likelihood of finding changes
on CT scan, we will perform CT scans in subjects >50 years old who are in the highest quartile of
cumulative use for comparability to the existing cigarette smoking cohorts. Data analysis:
Subjects will be matched to never smokers and heavy tobacco smokers within the NIH-funded
COPDGene cohort. Primary lung health outcomes that will be assessed include: airflow limitation
(COPD), cough and sputum (chronic bronchitis), emphysema, and exacerbations. Statistical
modeling of these outcomes and covariates are as previously described {see [18-21]}. Since many
cannabis users are also tobacco users, additional adjustments will be made for tobacco use based
on well-established ATS pack year assessment. Power calculations. Anticipating a minimum of
300 subjects (100 for CT) in each group (edible/other, vaping, smoked compared to never
smokers) we will have 100% power to detect a mean clinical important difference in FEV1 (120
ml), a 1% increase in CT emphysema, and >90% power to detect a 5% increase in chronic
bronchitis.
3.c.iii.1.Efficacy in asthma: 30 CCC subjects who have not had an asthma exacerbation in past 30
days and who use cannabis daily (predominant smoking, but no tobacco) for asthma (physician
diagnosed) and 30 age, race, gender, and severity matched controls (no cannabis) recruited from
NJH clinic will be invited to participate. Study procedures. Visits will occur in the morning only
to improve reproducibility. Methacholine challenge will follow most recent ATS guidelines and
will be performed on separate days before (>24 hours since) and after cannabis use (within 2
hours for cannabis users). The test is stopped after subject drops 20% in FEV1 or 25% SGaw.
Inhaled bronchodilators are held for 48-hours (long acting) and 8 hours (short-acting). Subjects
will also be given an electronic peak flow meter/spirometer (PIKO) and Asthma Control Test
(ACT) assessment to complete at 4-week interval for 3 months. Blood cannabinoid measurements
will be assessed at each visit. Data analysis. The primary endpoint will be correlation between
ACT score and peak flow with cannabis use as measured by questionnaire and biomarkers; coprimary will be methacholine dose to cause >20% reduction airway conductance (SGaw).
Secondary endpoint will include exacerbations, rescue inhaler use, and time to return to baseline
SGaw and FEV1. Power calculations. With 30 subjects, we will have 80% power to detect single
dose improvement in methacholine concentration at a two tailed  of 0.05. Secondary analysis
will include improvement in ACT and peak flow scores compared to controls.
3.c.iv.Anticipated outcomes and alternative approaches: We anticipate that exclusive
consumption of edible cannabis will have no adverse lung effects when adjusted for tobacco
exposure. We expect that vaping will have minimal-to-no effect on lung function. Based on our
pilot data and review of the literature, we anticipate that heavy smokers of cannabis will have
mild evidence of COPD, emphysema, and chronic cough and sputum (chronic bronchitis)
14
compared to never smokers, but less disease than heavy tobacco smokers. This study design is
highly cost-effective because the protocols are nearly identical to the NIH-funded COPDGene
study that includes 10,300 subjects (never tobacco, current tobacco, and former tobacco) who
have been clinically phenotyped with identical instruments including quantitative CT scans. A
limitation to the COPDGene cohort is that minimum age is > 45 years; thus, we will restrict the
CT and asthma substudies to those >50 years of age for better matching and would not anticipate
any significant lung disease other than bronchitis symptoms in those < 45 years of age. Based on
very old published data, we would anticipate that cannabis will cause mild rapid improvement in
lung function, but will have no significant effect on long-term control of asthma due to
improvements in asthma therapy over the past 30 years (e.g. inhaled corticosteroids, long acting
bronchodilators).
D. Laboratory Testing
Cannabinoid testing in biologic specimens (serum, urine, breast milk): Biologic samples will be
tested in the laboratory of Uwe Christians (see enclosed Biosketch) a University of Colorado
Service Center. The laboratory is compliant with the rules of good laboratory practice (cGLP, 21
CFR part 58) and it is accredited by the College of American Pathologists (LAP number 7176093,
AU-ID 1374604, CLIA 06D0985306). Accordingly, all assays are validated and all analyses are
carried out following our standard operation procedures which are based on all applicable CAP,
CLSI, ICH, OECD and FDA guidances. The laboratory uses mass spectrometry and internal
standards to quantitate THC, 11-COOH-THC, 11-OH-THC, THC-COOH-Glucuronide, CBD
(Cannabidiol), CBN (Cannabinol). The laboratory is high throughput and can easily accommodate
>1,500 biologic samples that are proposed. Additional qualifications for Dr. Christians laboratory
can be found in the enclosed biosketch.
Anticipated time line and milestones
Year
Year 1
SA1: Cohort Building
500 subjects
SA2: Usage instrument
Testing
SA3a: pain efficacy
Recruitment
SA3b: sleep efficacy
Recruitment
SA3c: lung health/asthma Recruitment
Year 2
500 subjects
Validation
Efficacy/Analysis
Efficacy/Analysis
Efficacy/Analysis
Year 3
500 subjects
Breast Milk THC
Publication
Publication
Publication
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