SHORT TERM EFFECTS OF CANNABINOIDS (THC)

A. Study Aim

Our primary goal is to determine the safety/toxicity profile of cannabinoids in persons with HIV infection. We propose to do this by conducting a randomized, prospective study whose primary goal is to determine the short-term effects of smoked marijuan a on the pharmacokinetics of the HIV protease inhibitors indinavir and nelfinavir, the immune system and the level of HIV-1 viral load in persons with HIV-1 infection. The study will be composed of three successive phases. The first phase will be a 4-day lead-in period in which baseline measurements are obtained. This will be followed immediately by a 21-day intervention phase in which subjects receive either marijuana cigarettes (Group A), dronabinol (Marinol*) capsules (Group B), or placebo capsules (G roup C). Subjects in Group A will smoke one 4% tetrahydrocannabinol (THC)-content marijuana cigarette three times daily, one hour prior to each meal. Group B and C subjects will receive dronabinol (Marinol*) 2.5 mg or placebo three times daily, one hour prior to each meal. In the last phase, subjects will be evaluated as outpatients (with no intervention) on days 30 and 42. Subjects will be hospitalized in the General Clinical Research Center (GCRC) at San Francisco General Hospital for the first two ph ases of the trial (25 nights) because, at present, legal use of smoked marijuana is restricted to medically supervised settings. The inpatient setting also permits us to measure plasma and urine THC levels as a means to assess the total dose delivered, an d to rigorously assess the safety parameters and measures of possible efficacy, including appetite, daily food intake and resting energy expenditure.

Eligible subjects will be experienced marijuana users who are currently receiving indinavir or nelfinavir as part of their antiretroviral regimen. The primary outcomes of the study are change from baseline in (1) viral load and (2) area under the plasm a indinavir or nelfinavir concentration time curve. Because indinavir and nelfinavir as well as cannabinoids are metabolized in the liver, interactions between these treatments could alter the concentration of the protease inhibitor, thus increasing its toxicity or decreasing its efficacy. For example, lower indinavir or nelfinavir concentration could result in an increase in viral load. We include Control Group B, dronabinol (Marinol*) capsules, in order to evaluate these outcomes in subjects treated with oral THC according to a current standard of care. We include Control Group C, placebo capsules, to establish baseline values under our experimental conditions.

B. Background and Significance

B.1 Widespread use of smoked marijuana

Largely on the strength of anecdote alone, and in the absence of any supporting data, smoked marijuana is increasingly used for treatment of HIV-associated anorexia and weight loss. Moreover, legislation passed in the State of California in November 19 96 enables physicians to recommend marijuana for conditions where it reportedly has medical benefit. HIV-associated wasting is one of the four conditions included in the original legislation. Use of smoked marijuana has also been facilitated in the San Fr ancisco Bay Area by the creation of numerous cannabis "buyers clubs" (Goldberg 1996). It has been estimated that these organizations now sell marijuana to over ten thousand clients who present a physician's note documenting that they have HIV infection or another medical condition that may be ameliorated by smoking marijuana. A survey conducted in the San Francisco and Oakland cannabis buyers clubs reveals that 71% of patients with HIV infection reported using marijuana for appetite stimulation, compared to less than 20% of the HIV negative respondents (Child, 1998).

For a number of years, medical providers caring for patients with HIV infection in the San Francisco Bay Area have been concerned about the safety of marijuana smoking by patients with an acquired immune deficiency. Others have noted weight gain and im provement in mood and quality of life in their patients who smoke marijuana. With legislation now being introduced in other states to allow for the medical use of marijuana, the need to assess its impact in patients with HIV infection becomes even more of an imperative.

B.2 Availability of oral THC

Dronabinol, synthetic delta-9-tetrahydrocannabinol (THC) (Marinol*, Roxane) has been available for the treatment of chemotherapy-induced nausea and vomiting since 1985 (Doblin 1991). In 1992, the indication was expanded to include treatment of AIDS-rel ated wasting syndrome (Gorter 1992). A recent nationwide survey shows that dronabinol ranks third in popularity as an intervention for AIDS wasting among primary care providers treating patients with HIV (Abrams, et al. 1996). Many patients have turned to inhaled marijuana, claiming that it is easier to titrate the desired effect. Variable absorption after ingestion of oral THC, which is well recognized, leaves some patients with a minimal drug effect. Smoking is a more efficient route of delivery with a potentially more desirable pharmacokinetic pattern for patients seeking to maximize any potential appetite-stimulating effect (Agurell 1986). Patients also report that the neuropsychiatric effects are more prolonged and dysphoric with the oral THC, than w ith smoked marijuana. A survey of 123 people with HIV infection in Hawaii revealed that 37% had used marijuana in treatment of their HIV/AIDS (Wesner 1996). Of those who had used both marijuana and prescription antiemetics, marijuana was preferred by 80%. The ability to titrate the onset of drug effect and the shorter overall duration of effects are most often cited as reasons for the preference for smoked marijuana compared to oral THC.

B.3 National Institutes of Health Workshop on the Medical Utility of Marijuana

Utility of Marijuana: The recent National Institutes of Health Workshop on the Medical Utility of Marijuana heard AIDS expert John Phair, MD, professor of medicine at Northwestern University Medical School, report that he saw "clear evidence that smoki ng marijuana does affect caloric intake" in persons with AIDS (Roehr 1997). Eight outside experts unanimously agreed that marijuana looks sufficiently promising to recommend that there should be controlled studies to evaluate its use in clinical practice. Dr. Phair, however, emphasized that research studies be designed "to learn its impact on viral replication and the immune system." The California Medical Association also recently passed a number of resolutions to submit to the upcoming meeting of the A merican Medical Association that support further research on the medical utility of smoked marijuana and easier availability of marijuana for clinical trials.

B.4 Interaction with new therapies

Coincident with the increased use of smoked marijuana by HIV-infected patients, has been a revolution in HIV therapeutics. Over the past year, several new potent protease inhibitor therapies were licensed, and there are now widespread reports of the p ositive impact of this new class of drugs on the surrogate markers of HIV infection (CD4+ lymphocyte counts and viral load). In response to these reports, increasing numbers of patients at all stages of HIV infection have begun combination antiretroviral therapies (Deeks 1997). Unfortunately, the new protease inhibitors ­ which can inhibit or stimulate the hepatic cytochrome P450 enzyme system ­ also have a number of significant drug-drug interactions with other agents used in the treatment of HIV infection and its complications. In addition, there are reports of fatalities resulting from the use of a protease inhibitor (ritonavir) in conjunction with a popular recreational drug, MDMA (commonly known as "ecstasy"), appearing in the press (Mirken 1997). Many of these potentially dangerous drug-drug interactions remain unknown. Particularly worrisome is the drug-drug interaction between protease inhibitors and marijuana, since many HIV-infected patients use smoked marijuana as an appetite stimulant or to decrease nausea associated with their antiretroviral therapy. Such a drug-drug interaction is more than just hypothetical, as both classes of agents are metabolized by shared isoenzymes of the hepatic cytochrome P450 systems. Currently, t hough, there is no information available regarding this potentially dangerous interaction between protease inhibitors and cannabinoids.

B.5 HIV-1 RNA viral load as outcome

In addition to the recent introduction of a whole new class of drugs into the AIDS arsenal, new technology that assesses the impact of these therapies has also emerged on the scene. In the past, monitoring of the CD4+ lymphocyte count (the cell lineage ultimately decimated by persistent HIV infection) was the gold standard for evaluating the efficacy of antiretroviral therapies. Within the past few months, however, the new standard of practice is to measure HIV RNA, or "viral load" (Saag 1996). HIV RNA is measured by either a polymerase chain reaction (PCR) based assay or the branched DNA (bDNA) technology. As a result of the introduction of these new diagnostic tools, treatment paradigms have shifted, favoring interventions that drive down HIV RNA le vels with the hopes of reducing viral load until it is undetectable by the current commercially available assays. This treatment strategy, according to recent prospective randomized clinical trials, leads to better clinical outcomes, including prolonged s urvival (Katzenstein 1996). "Treatment failures" are patients whose viral loads were once well controlled by a combination regimen, but who then experienced an increase in HIV RNA. Though it is possible that such patients could regain control of viral replication by modifying therapy ­ by changing at least two of the drugs in the combination regimen, including the protease inhibitor ­ there are still only a finite number of antivirals available for treatment. Therefore, the goal of therap y ­ despite the introduction of new drugs and technology ­ remains to keep the patient on an effective regimen for as long as possible.

B.6 Widespread use of protease inhibitors

Four protease inhibitors are now licensed. The first inhibitor, saquinavir, became available in December 1995, but was not recommended by many physicians because ritonavir and indinavir, which are more potent than saquinavir, were available soon after in April 1996. Ritonavir has the highest incidence of untoward side effects, and ­ because it is a potent inhibitor of the hepatic cytochrome P450 enzyme system ­ it is associated with multiple drug-drug interactions and a long list of con traindicated concurrent medications. Ultimately, these qualities make ritonavir less desirable than the equally potent alternative, indinavir. Numerous surveys have demonstrated that HIV care providers preferred indinavir 2 to 1 to the other early licen sed inhibitors because of its better tolerability (Abrams et al. 1996). The most recently approved protease inhibitor, nelfinavir, (March 1997) is, however, now competing for indinavir's market share. Indinavir, still the most widely prescribed protease inhibitor, requires careful monitoring during therapy for drug-drug interactions. Indinavir is extensively metabolized ­ predominantly by hepatic cytochrome 450 (CYP) 3A4 ­ and about 20% of indinavir is excreted unchanged by the kidneys. Certain drugs, such as ketoconazole, inhibit the metabolism of indinavir, leaving more indinavir to be renally excreted. The more indinavir that is renally excreted, the greater the risk of precipitation of indinavir within the kidneys, which can then le ad to nephrolithiasis ­ the most troubling indinavir-related adverse experience. Other drugs, such as rifampin, accelerate the metabolism of indinavir, resulting in subtherapeutic levels of the protease inhibitor, and to ineffective antiretroviral activity. When a particular drug-drug interaction can be predicted, however, therapy can then be modified. For example, when the metabolism of indinavir is inhibited, it is necessary to reduce the dose, and when the metabolism is accelerated, an increas e in dose is required. Knowledge of how a drug will interact with indinavir can greatly assist in such important therapeutic decisions. Similarly, nelfinavir - now the second most frequently prescribed protease inhibitor- is metabolized by the CYP 1A2 i soenzyme and must also be monitored carefully for potential drug-drug interactions.

B.7 Potential effects of marijuana and oral THC on drug metabolism

Marijuana and oral delta-9-THC (Marinol, Roxane) have the potential to affect drug metabolism, including the metabolism of indinavir and nelfinavir. Marijuana ­ which exposes the individual to combustion products similar to those of cigarette smoking ­ can activate the metabolism of a variety of drugs. For the most part, this is a result of induction of CYP1A2, which is also involved in nelfinavir metabolism. Delta-9-THC and cannabidiol, another cannabinoid found in marijuana, have also been found to inhibit the metabolism of antipyrine, pentobarbital, and hexobarbital (Benowitz 1977; Benowitz 1980). It is possible, therefore, that marijuana could have an effect on the 3A4 pathway, which is responsible for the metabolism of indinavir. The proposed trial will examine these pharmacokinetic interactions between smoked marijuana or oral delta-9-THC (dronabinol) and indinavir and nelfinavir. In addition, the trial will examine related safety parameters, such as the effect of cannabinoids o n HIV viral load and immune function. Though there are no current controlled studies of marijuana's impact on immune functions, there is some suggestion that marijuana could impair the immune system. At the same time, there is also the possibility that m arijuana can be beneficial for patients with HIV immune dysregulation, since some studies suggest marijuana can lead to B lymphocyte modulation and tumor necrosis factor inhibition (Friedman 1995). Regardless of its impact on immune functions, marijuana c could potentially lead to an increase in viral burden. If such an increase was coupled with a drug-drug interaction between cannabinoids and protease inhibitors, a significant adverse outcome in HIV-infected patients could occur. The proposed trial will examine this serious possibility.

B.8 Effects of smoked marijuana on testosterone levels

Although the impact of smoked marijuana and oral THC on indinavir and nelfinavir pharmacokinetics, HIV RNA levels and measures of immune function are critical safety issues that warrant study, other potential adverse effects of these agents in patients with HIV infection are also germane. For example, it is known from both animal models and evaluation in humans that marijuana smoking may lead to lowered testosterone levels (Mendelson 1974; Vescovi 1992). Lowering testosterone levels by smoking marijuan a would be a potentially counterproductive effect in patients attempting to reverse HIV-related weight loss, as hypogonadism is known to be associated with AIDS-related wasting syndrome in men (Coodley 1994). The finding of low total testosterone levels h as been the rationale for the increased use of androgen replacement therapy in men with HIV-related weight loss. Testosterone therapy is associated with significant increases in lean body mass in patients without HIV infection (Griggs 1989; Welle 1992; Yo ung 1993; Bhasin 1994, Bhasin 1996), though its effects in AIDS patients are still under investigation. The impact of smoked marijuana and oral THC on sex hormone production has not yet been evaluated in this population.

B.9 Opportunity to identify potential measures to assess efficacy

The proposed study's primary goal is to determine the short-term effects of smoked marijuana on the pharmacokinetics of the protease inhibitors indinavir and nelfinavir, the immune system and the level of HIV-1 viral load in HIV-infected patients. Howe ver, the in-patient setting of our trial creates a rare opportunity to also investigate the impact of cannabinoids on appetite, caloric intake, resting energy expenditure, body composition and weight. We propose to investigate these parameters as secondar y objectives, with the intention of using these data to plan an evaluation of smoked marijuana's efficacy as a treatment for HIV-related anorexia and weight loss. A previous placebo-controlled trial demonstrated that the use of dronabinol (Marinol) result ed in improved appetite but not increased weight (Gorter 1992), and anecdotal evidence suggests that smoked marijuana has a similar, stimulating effect on appetite. This evidence has prompted increasing numbers of HIV-infected patients to use smoked mari juana as a treatment for HIV-related weight loss, despite the fact that there has never been any investigation of smoked marijuana's impact on appetite or weight in HIV-infected subjects. Such an investigation, albeit preliminary, is possible within the p roposed study. While subjects are hospitalized in the General Clinical Research Center (GCRC), we will be able to collect data useful for estimating effect size and individual variability in energy intake, body composition and body weight. If our primary investigation determined that smoked marijuana was safe enough for further clinical evaluation, then our secondary investigation would become extremely useful, as we could then calculate sample sizes and power estimates for future, and larger, clinical s tudies of smoked marijuana's effect on HIV-related weight loss.

B.10 Prior studies of adverse effects of smoked marijuana

The potential detrimental effects of marijuana smoking in patients without HIV infection are numerous. Interestingly, most of the literature is at least twenty years old and often conflicting reports can be found, occasionally by the same author. With regard to patients with HIV infection, the impact of smoked marijuana on immune function and gonadal function have not yet been described and would seem to be particularly critical safety parameters to examine. The proposed study will directly assess the impact of smoked marijuana and oral THC on HIV-1 viral load, immune function and gonadal function.

B.10.1 Overall Safety

The literature describing the adverse effects of smoked marijuana is vast. Many of the reported effects come from animal models. Whether these findings can be extrapolated to humans is unclear. In a study of male and female rats and mice conducted by t he National Toxicology Program (NTP) of the Department of Health and Human Services, the results of a two-year exposure trial were quite surprising (NTP Technical Report, 1996). Compared to control animals, rodents who received large doses of delta-9 THC by gavage were leaner at the end of the two year study period. This was true for rats and mice of either sex. In addition, the treated animals had fewer malignant tumors and survived significantly longer than the controls.

An extensive review of the world's literature was conducted by the Australian government and reported in a monograph on "The health and psychological consequences of cannabis use" (Hall 1995). The work began in 1992 and entailed an extensive, reported ly unbiased investigation of accumulated research. The document's executive summary delineates the major adverse health and psychological effects of acute and chronic cannabis use and groups them Aaccording to degree of confidence in the view that the rel ationship between cannabis use and the adverse effect is a causal one.

Acute effects

- anxiety, dysphoria, panic and paranoia, especially in naive users;

- cognitive impairment, especially of attention and memory, for the duration of intoxication;

- psychomotor impairment, and probably an increased risk of accident if an intoxicated person attempts to drive a motor vehicle, or operate machinery;

- an increased risk of experiencing psychotic symptoms among those vulnerable because of personal or family history of psychosis;

- an increased risk of low birth weight babies if cannabis is used during pregnancy.

Chronic effects

The major health and psychological effects of chronic heavy cannabis use, especially daily use over many years, remain uncertain. On the available evidence, the major probable adverse effects appear to be:

- respiratory diseases associated with smoking as the method of administration, such as chronic bronchitis, and the occurrence of histopathological changes that may be precursors to the development of malignancy.

- development of a cannabis dependence syndrome, characterized by an inability to abstain from or control cannabis use;

- subtle forms of cognitive impairment, most particularly of attention and memory, which persist while the user remains chronically intoxicated, and may or may not be reversible after prolonged abstinence from cannabis.

The following are the major possible adverse effects of chronic, heavy cannabis use which remain to be confirmed by further research:

- an increased risk of developing cancers of the aerodigestive tract, i.e. oral cavity, pharynx and oesophagus;

- an increased risk of leukemia among offspring exposed while in utero;

- a decline in occupational performance marked by underachievement in adults in occupations requiring high level cognitive skills, and impaired educational attainment in adolescents;

- birth defects occurring among children of women who used cannabis during their pregnancies.

A recently published evaluation of clinical information from the large Kaiser Permanente health maintenance organization patient database sheds further light on the question of the overall safety of marijuana. In an article entitled "Marijuana Use and Mortality," Sidney et al (1997) report on a study population of 65,171 HMO patients aged 15 through 49 undergoing multiphasic health checkup examinations between 1979 and 1985. Questionnaires about smoking habits, including marijuana use, were completed as part of the routine exam during those years. Mortality follow-up was conducted through 1991. The Kaiser HMO has extensive computerization of records and excellent follow-up of their members, allowing for meaningful research to be conducted in this retro spective review fashion. The study subjects consisted of 37,090 women and 28,081 men. The cohort comprised 38% nonusers of smoked marijuana, 20% experimenters (ever smoked 1-6 marijuana cigarettes), 20% former users (none now, but > 6 times in past), a nd 22% current users. Compared with non-use or experimentation, current marijuana use was not associated with a significantly increased risk of non-AIDS mortality in men (RR=1.12 [0.89,1.39]) or of total mortality in women (RR=1.09 [0.80,1.49]). Current m arijuana use was found to be associated with an increased risk of AIDS mortality in men with a relative risk of 1.90 [1.33,2.73]; however the authors attribute this to uncontrolled confounding by male homosexual behavior and not to a causal relationship. This interpretation was supported by an analysis of a separate cohort of 214 men in the Kaiser Permanente Medical Care Program AIDS Database. The prevalence of marijuana use in this AIDS cohort was 56%, significantly higher than the 38% prevalence in the unmarried men in the larger study cohort. Interestingly, for these 214 AIDS patients, current use of marijuana was associated with a nonsignificant decrease in relative risk for total mortality (RR=0.78 [0.47,1.30] and for AIDS mortality (RR=0.71[0.41,1.2 3]. These findings are quite provocative, albeit limited by the retrospective methodology. Regardless, the impact of marijuana on specific body systems warrants a prospective evaluation. The proposed study is designed to provide this important prospective information.

B.10.2 Immune Function

Studies of the effect of marijuana on immunity have been contradictory and, when viewed in the aggregate, difficult to interpret. On the one hand, the major psychoactive component of marijuana, delta-9-tetrahydrocannabinol (THC), has been known to (1) suppress immune functions such as lymphocyte proliferation, antibody production, natural killer cell activity and macrophage function, (2) dysregulate production of such pro-inflammatory cytokines as interferon and tumor necrosis factor (TNF) (Friedman 19 95), and (3) confer altered susceptibility in vivo to infection with intracellular organisms such as Legionella pneumophilia (Klein 1994; Klein 1995) and in vivo to herpes simplex virus type-1 infected cells (Cabral 1992; Fischer-Stenger 1992). With Munro 's discovery of a new type of cannabinoid receptor present not in the brain but only in peripheral tissues (particularly reticuloendothelial tissues), the potential for interactions of THC with the immune system was further validated (Munro 1993). In a co mmentary on the discovery of the receptor, an industry pharmacologist poses the question, "Is the second cannabinoid receptor only in the spleen? The level of expression, probably high in the active macrophages, in a region where the outside world meets t he immune system, suggests a possible role in inflammatory and immune responses to infection or other foreign antigens." (Iverson 1993).

It has been hypothesized that these effects may be related to THC-induced shifts in the balance of ATh1" and ATh2" cells (Newton 1994). However, many of the effects so documented for THC have been observed in conditions, both in vivo and in vitro, in w hich supraphysiologic doses of the compound are used and/or without inclusion of controls which have similar lipophilic properties (Hollister 1992). Even relatively simple observations (e.g., that phytohemagglutinin and mixed lymphocyte culture responses are suppressed in young, chronic marijuana smokers) (Nahas 1974), have been difficult to reproduce (White 1975; Lau 1976). More recently, conflicting reports have been generated regarding the impact of THC on levels of TNF-alpha. Whereas some investigato rs report THC inhibition of tumor necrosis factor (TNF) (Friedman 1995), another study utilizing ELISA (enzyme-linked immunoabsorbant assay) techniques demonstrated decreased interleukin-6, but increased TNF levels in a mouse macrophage system (Shivers 19 94). As these cytokines, particularly TNF, have been implicated in the pathogenesis of HIV-related wasting, determining the impact of THC on levels of TNF and related cytokines in human subjects smoking marijuana would be a significant contribution to med icine.

No controlled investigations of the impact of marijuana on immune function in patients with HIV infection have been conducted to date; however, information suggesting impaired cellular immune function is certainly worrisome. Interestingly, suggestions of B lymphocyte modulation and TNF inhibition could, in fact, have potential beneficial effects in patients with HIV-induced immune dysregulation over the long term. Whether a stimulant or suppressant of immune function, marijuana could potentially lead t o increased viral burden. This potential effect, as well, has never been investigated in a prospective, controlled fashion. Retrospective analyses from the Multicenter AIDS Cohort Study evaluating outcomes in 1662 seropositive users of psychoactive drugs found that none of the drugs used by participants was associated with enhanced clinical or immunologic expression of HIV infection (Kaslow 1989). Of note, use of marijuana in the preceding two years was reported by 89% of the seropositive men in the cohor t. Similar findings have been reported in studies of patients at San Francisco General Hospital (Roland 1987).

The disparate results on the effects of THC on the immune system may be related to differences in study populations, drug composition, drug concentration, or assay conditions. Taking a conservative approach, it is perhaps reasonable at this juncture to assume that marijuana can exert immunosuppressive effects under certain experimental conditions. >From the standpoint of this study, the key question will be whether cannabinoids exert demonstrable immunosuppressive effects when administered as three 4% THC cigarettes or oral delta-9-THC daily over a period of 21 days. If warranted, future studies may assess whether chronic exposure to similar doses exert additional effects not observed after short term exposure.

B.10.3 Endocrine Effects

It has been demonstrated that men with HIV infection may become hypogonadal during the course of their disease (Dobs 1988; Croxson 1989; Raffi 1991; Christeff 1992). It is conceivable that agents such as marijuana may have an impact on changes in male sex hormones. Testosterone synthesis in rats is decreased by THC. In a four week exposure study in men conducted in the 1970's, a decrease in luteinizing hormone (LH) occurred first, followed by decreases in testosterone and follicle-stimulating hormone ( FSH). A more recent evaluation in ten chronic marijuana users demonstrated that basal and stimulated levels of LH were reduced in comparison to age-matched controls, with no difference in FSH and prolactin levels and responses (Vescovi 1992). The authors postulate that chronic marijuana use may selectively impair the hypothalamic mechanism regulating LH secretion. In the current study, this information is relevant as hypogonadism has been associated with AIDS-related wasting (Coodley 1994). Marijuana smok ing could precipitate or exacerbate the hypogonadal state necessitating testosterone replacement therapy. The impact of dronabinol on gonadal function is also not well characterized.

B.11 Prior Studies of Cannabinoids and Appetite Stimulation

An extensive literature regarding the impact of smoked marijuana on appetite has accumulated, although much of it was published 20 to 50 years ago. Anecdotal accounts of increased food intake have always been reported by marijuana smokers. A study eval uating body weight and caloric intake in 12 "casual" and 15 "heavy" marijuana users reported weight gains of 2.8 and 3.7 pounds, respectively, during the first five days of a 21 day smoking trial (Greenberg 1976). Control subjects, without access to marij uana or other drugs but otherwise exposed to the identical ward experimental conditions, gained only 0.2 pounds during the same time interval. Despite the absence of sophisticated body composition analysis technologies (such as BIA or DEXA), the investiga tors believed that water retention was not a major factor in the weight gain, contradicting an earlier report by a member of our group (Benowitz 1975). An increase in caloric intake accompanied the initial weight gain; however, caloric intake was noted to decrease subsequently during the remainder of the 21 day trial. Foltin has investigated the impact of smoking marijuana on food intake in men confined in residential laboratories under various conditions (Foltin 1986). He reported that smoking marijuana compared to placebo was more likely to lead to increased food intake during social access periods when the subject interacted with others as opposed to when the marijuana was smoked in isolation. The average mean caloric daily intake increased by 758 kca l (p<0.001) across the nine subjects under active marijuana as compared to placebo conditions during social access periods. The increased intake was noted to be consumed between meals as snack foods. In a subsequent study of six subjects confined to th e residential laboratory for 13 days, smoked active marijuana significantly increased total daily caloric intake by 40%, with increased food intake evident during both private and social periods (Foltin 1988). The increase was again noted to be confined t o between meal snacks as a consequence of an increased number of snacking occasions, principally in the sweet, solid item category. The investigators noted that during this short trial, smoking active marijuana significantly increased body weight. Weight increased an average of 3 kg over the three day active smoking periods and decreased subsequently by nearly the same amount over the three day placebo smoking periods. In their experience, smoking marijuana led to reduced physical activity levels and incr eased sleeping time which could explain why increases in body weight during periods of active marijuana smoking were greater than predicted by caloric intake alone.

B.12 Oral THC versus Smoked Marijuana

Dronabinol was approved in 1985 by the FDA for use as an anti-emetic in patients receiving cytotoxic chemotherapy. In 1992, it was approved for treatment of anorexia in patients with HIV-associated wasting. The experience of patients using dronabinol h as been mixed. Variable absorption after oral ingestion, which is well recognized, leaves some patients with a minimal drug effect. Smoking is a more efficient route of delivery with a more desirable pharmacokinetic pattern for patients seeking to maximiz e any potential appetite-stimulating effect (Agurell 1986). The smoking curve tends to parallel the effects of intravenous administration at about half the concentration. Plasma drug levels and heart rate peak within 15 minutes of an inhaled dose and rapi dly decline. Oral THC increases heart rate to a lesser extent than smoked marijuana with a peak occurring two to three hours after ingestion (Chait 1992). Heart rate remained elevated four hours after ingestion. It is the combination of these features - d elayed onset, prolonged duration and less ability to titrate the effect - that has led patients with HIV infection to turn in increasing numbers to utilization of smoked marijuana as a self-medication for this condition.

A recent report describes a number of small related trials comparing different routes of THC administration for their effects on appetite stimulation (Mattes 1994). Eleven subjects received single doses by oral, sublingual and inhaled routes. In anothe r component of the trial, a 2.5 mg dose was administered twice daily for three days by oral and rectal suppository routes. There was a high level of variability in plasma drug levels, particularly in subjects with oral drug administration. Two of the 11 ( 18%) subjects in the oral trial of the multiroute study and 18/57 (32%) of subjects in the larger, acute oral study showed no detectable plasma THC or metabolite level in the four hours following ingestion of the active drug. For patients receiving oral T HC in this study, the time course of peak levels and the concentration area under the curve (AUC) values were highly variable across subjects. The suppository led to the highest AUC, followed by inhalation. The metabolite AUC was highest for the oral and lowest following inhalation. Mean energy intake after inhalation of THC was 2719 +/- 359 kcal; 481 kcal more than after oral dosing and 603 kcal greater than sublingual dosing effects. (This analysis eliminates two inhalation subjects who experienced "hig hs" that caused them to sleep through lunch and had the lowest daily intakes.) The investigators conclude that inhalation of THC led to more consistent elevations of plasma drug concentration and tended to promote intake, although due to the sample size t he results were not statistically significant. They note, as well, that "because this form of delivery requires smoking the drug and is not currently legal, it is objectionable to many patients." It is evident that patients with HIV infection are risking potential legal consequences in hopes of reversing the devastation of the wasting syndrome, and that they and their health care providers would clearly benefit from concrete information on the potential risks and benefits of this controversial treatment m odality.

C. Research Design and Methods

C.1. Lead-in phase

The purpose of the 4-day lead-in phase is to acclimate subjects to GCRC conditions, to allow those who believe they cannot comply with the 25-day stay to drop out prior to randomization, to establish eligibility and baseline values of study endpoints, and to collect baseline covariate data. In particular, a subject's baseline viral load level will be defined as the average of two samples, drawn on days -4, and 0. To be eligible, subjects will be asked not to smoke marijuana within 30 days of enrollment . A urine cannabinoid screen, which will verify that subjects have not smoked marijuana for at least ten days, will be performed prior to randomization. A cotinine level, which will verify that the patient has not smoked tobacco, will also be drawn.

C.2. Intervention phase

Randomization and initiation of treatment will occur on Day 0. Eligible subjects will be asked if they will continue with the protocol. Baseline data will be collected from those who consent. After baseline data are collected, subjects will be randomi zed with equal probability to one of the following groups by the study biostatistician:

A. 4% THC-content marijuana cigarettes, three times daily

B. Dronabinol capsules, 2.5 mg, three times daily

C. Placebo capsules, three times daily

Although all subjects will be prior users of marijuana, they will be given information about the range of subjective effects they may experience from cannabinoids. Subjects randomized to Group A will be instructed to follow the guidelines for the unif orm puff procedure, described by Foltin (1988), to inhale for 5 seconds, hold the inhalation for 10 seconds prior to exhaling, then wait 45 seconds before repeating the cycle. This will be repeated to the amount tolerated by the subject to a maximum marij uana smoking time of ten minutes.

The selection of the 4% THC cigarette is based on the strength of marijuana that is currently available from the National Institute of Drug Abuse that most closely approximates the strength available in the community. It is difficult to anticipate what the systemic dose of THC will be from this cigarette, since people tend to titrate their amount of marijuana smoking to take in the amount of THC they desire. One of the results of our trial will be to provide data on the relative exposure of individuals to THC and the active metabolite 11OH THC from smoking marijuana, compared to taking dronabinol capsules. It should also be noted that the systemic dose of THC per se might be greater after smoking marijuana compared to after oral THC, because there is s ubstantial first pass metabolism of the latter. However, THC is metabolized to 11OH THC, which is also pharmacologically active, so the total pharmacological impact of THC plus its metabolite is likely to be similar via both routes of administration.

The use of placebo dronabinol capsules is to provide a "no cannabinoid" control group. Although we will be enrolling subjects with stable viral load measurements on a stable antiretroviral regimen, the possibility exists that the experimental condition s of 25 nights of confinement in the GCRC may, in some way, impact on our outcomes of interest. Hence, in an effort to decrease potential confounding, we will follow patients on placebo dronabinol. We believe that this is superior to having patients smoke placebo marijuana. These experienced marijuana smokers will be likely to discern the fact that they are smoking inactive marijuana. Prior studies employing placebo dronabinol, however, have shown that some subjects may experience subjective THC effects. Thus, we have chosen to use placebo dronabinol (as opposed to the alternative "no treatment" option) as the "no cannabinoid" control.

The usual dose of dronabinol for appetite stimulation is 5 mg/day, although doses in clinical trials have ranged from 2.5 - 20 mg/day. We propose to dose dronabinol 2.5 mg, 3 times per day, given before breakfast, lunch and dinner, to provide a compara ble dosing schedule to that of the smoked marijuana. Drugs will be dosed approximately one hour before each meal.

C.3. Followup phase

After the lead-in and intervention phases are completed, follow-up data will be obtained by having subjects return to the GCRC to have blood samples drawn on days 30 and 42. These samples will be evaluated for HIV-1 viral load, immune system parameter s and gonadal function.

C.4 Study Population

C.4.1. Inclusion criteria

1. Evidence of HIV-1 infection, including either of the following: Documented positive serology for HIV-1 infection, or documented history of HIV disease/AIDS as defined by the Revised Case Definition for AIDS Surveillance Purposes (1993).

2. Stable treatment regimen for at least 8 weeks that includes antiretroviral therapy, of which one of the protease inhibitors, indinavir or nelfinavir, (and no additional protease inhibitor) is a component.

3. Viral load stable for at least 8 weeks (<3-fold change in viral copies/ml from -16 weeks to enrollment) by either Roche or Chiron assays.

4. Prior history of use of marijuana. Subjects will report having smoked marijuana at least six times at any time in their lifetime.

5. AST(SGOT) < 5 x upper limit of normal.

6. Hematocrit > 25%.

C.4.2 Exclusion criteria

1. Active opportunistic infections or opportunistic malignancies requiring acute treatment.

2. Unintentional weight loss of >10% of body weight during past 6 months.

3. Concurrent use of megestrol acetate, nandrolone decanoate, oxandrolone, oxymetholone, stanozolol, DHEA, human growth hormone, thalidomide, pentoxifylline, prednisone, interleukin-2, chemotherapy, radiotherapy, or other anabolic steroids or invest igational agents that may alter immune system function within the past eight weeks.

4. Current substance dependence (e.g. alcohol, opiates, methamphetamines, cocaine)

5. Methadone maintenance.

6. Tobacco smokers - no tobacco for at least 30 days.

7. Pulmonary complications (e.g., tuberculosis, asthma, COPD, carcinoma).

8. Use of smoked marijuana within 30 days of enrollment.

9. Diagnosis of AIDS Dementia Complex (Stage II or higher).

10. Pregnancy

C.5.1 Recruitment, Screening and Enrollment

Subjects will be recruited through referrals from the more than 250 physicians who are members of the Community Consortium and through advertisements in local newspapers. Community Consortium providers care for the majority of the estimated 30,000 peop le with HIV-1 infection living in the San Francisco Bay Area. A Community Consortium clinical research nurse will contact potentially eligible patients who have been referred by community providers or who respond to advertisements in local newspapers. Th e clinical research nurse will arrange a meeting with the patient in order to review the study and to obtain informed consent and consent to release medical records from interested patients. After informed consent is obtained, the research nurse will conf irm eligibility.

Laboratory values necessary for inclusion in the study will either be verified through the patients' records or performed by the Community Consortium. Evaluation of laboratory values will insure that subjects have adequate organ function to participa te in the study. As a general guideline the patient should be in reasonably good health at the time of study entry and able to comply with the protocol.

Patients must be willing to remain in the GCRC for 25 nights without receiving visitors.

C.5.2 Study measurements (see Appendix A for Schedule of Events)

C.5.2.1 HIV-1 RNA

Analysis of HIV-1 RNA will be determined utilizing the branched DNA (bDNA) technology (Chiron Corporation, Emeryville, CA). The Chiron version 3.0 assay will be utilized. This method is able to detect as few as 50 copies/ml of HIV-1 viral RNA. Although we expect many patients enrolled to have "undetectable" viral loads using the commercially available assay (limit of detection <500 copies/mL), the method we use here will allow us to quantitate the levels between 50 - 500 copies/mL.

Baseline viral load determinations will be collected in duplicate to assure greater accuracy of the initial determination. From a recent Community Consortium trial evaluating the impact of antiretroviral therapies utilizing the Chiron bDNA assay (Folla nsbee 1996), we know that most significant responses of viral load to therapeutic interventions can occur within 7 - 14 days of the initiation of treatment; hence determinations after 21 days of cannabinoids could be expected to show variation if a signif icant effect occurs. We are collecting blood samples on days 30 and 42 to determine if there are any delayed effects of the study treatments on viral load.

Samples will be logged in and stored at -70oC. All freezers are connected to a central temperature monitor system and Dr. Elbeik will maintain a pager 24 hours a day to insure the integrity of these samples in the event of a freezer failure. Samples will be batch tested by Dr. Elbeik in his laboratory, and all results will be reviewed before being sent to the Protocol Statistician and other team members. Plasma samples with discrepant results (i.e. high coefficient of variation) will be re-assayed.< /P>

C.5.2.2 Indinavir and Nelfinavir kinetics

Subjects will be studied on two occasions: once prior to receiving marijuana, oral THC or placebo, and then again on day 14 of treatment. Subjects will be studied in the morning after an overnight fast. Indinavir 800 mg or Nelfinavir 750 mg will be adm inistered at 8:00 am. Blood samples (5ml) for measurement of the concentration of indinavir and nelfinavir will be obtained prior to dosing and then at 30,60, 90, 120 minutes and 3, 4, 5, 6, and 8 hours after the dose. Plasma indinavir and nelfinavir conc entrations will be measured in the laboratory of Drs. Gamertoglio and Aweeka, using HPLC methodology (reverse-phase isocratic procedure with UV detection at 210 nm). The limit of quantitation of this assay is 10 ng/ml (coefficient of variation 5-7%).

C.5.2.3 Plasma THC

The assays will be performed by Gas Chromatography - Mass Spectrometry at the Center for Human Toxicology at the University of Utah. With a 1 ml sample, THC levels of 0.5 ng/ml can be measured, which is well below the expected levels after smoking a ma rijuana cigarette. The Center for Human Toxicology has a long-standing contract with NIDA for THC assays. On Day 14, we will sample THC levels after the second dose of the day. A trough level will be obtained just prior to the second marijuana cigarette. Additional levels will be drawn 2 minutes after smoking the marijuana cigarette, at 60 minutes after smoking and then again 6 hours after smoking, which would be just before dinner. The rationale for this sampling schedule is to inscribe the area under th e plasma concentration time-curve, based on plasma level data reported by Chiang and Barnett (1994). For the oral dronabinol and placebo recipients, a trough level will be obtained just prior to the noon dose, with subsequent levels obtained 2, 4 and 6 h ours following the second dose. This schedule is based on the plasma level data reported for THC in sesame oil by Wall et al (1983). In our analysis, the measure will be the 6 hour area under the plasma concentration time curve around the second dose of t he day of either smoked marijuana or dronabinol (or placebo). We will evaluate the delta-9-THC levels alone as well as the sum of delta-9-THC plus 11OH THC. Because 11OH THC is also active, we can thus evaluate the sum of the two for an estimate of total psychoactivity. In addition we will collect a 24 hour urine sample for THC and its metabolites on Day 16 which will also be analyzed at the University of Utah Center for Human Toxicology.

Expired carbon monoxide (CO) levels will be measured by using an Ecolyzer on day -4 and day 7. Expired CO levels throughout the day will provide another measure of smoke exposure. Plasma delta-9-THC levels will be measured as the most direct way to e stimate systemic exposure. Plasma concentrations are also expected to best predict pharmacologic responses.

C.5.2.4 Immune System Parameters

We will use many of the same assays that have been used previously in subjects without HIV-1 infection to address the effects of marijuana on immune function in individuals with HIV-1 infection. These assays are relatively straightforward and have alre ady been established and standardized in the SFGH Core Immunology Lab. We propose to minimize the effect of interassay variation by obtaining two baseline determinations from each subject (on days -4, and 0). The assays that will be run for all subjects i nclude:

1. Phenotypic analyses: Specimens will be analyzed for markers of cell subpopulations (including CD3, CD4, CD8, CD45RA, and CD62L for naive and memory T cell activation (including CD38, CD69 and major histocompatibility Class II antigens).

2. Functional analyses:

a. T cell proliferative responses will be measured by isolating PBMC and challenging them with stimuli including mitogens (e.g., phytohemagglutinin), alloantigens (e.g., mitomycin C-treated peripheral blood mononuclear cells pooled from three donors ), and recall antigens (e.g., tetanus toxoid, CMV). Bulk responses will be determined by incorporation of 3H-thymidine.

b. Natural killer cell function will be determined using a standard chromium release assay.

c. Cytokine production will be assayed intracellularly after stimulation with SEB or CMV in the presence of brefeldin A (an inhibitor of protein secretion). After permeabilization of the cells, accumulated intracellular cytokine will be detected by flow cytometry using fluoresceinated anti­cytokine antibodies.

C.5.2.5 Endocrine function

We will examine the short-term effect of marijuana smoking on the hypothalamic-pituitary-gonadal axis by measuring total testosterone, luteinizing hormone and follicle stimulating hormone levels of male subjects utilizing assays available in the GCRC c ore laboratory. Blood samples will be analyzed in the GCRC core laboratory.

C.5.2.6 Appetite and Mood

Appetite will be assessed at each meal using a 100mm Visual Analog Scale (VAS). The VAS items are sensitive to small changes in ratings, and can be used repeatedly with the same participant, thus allowing for frequent assessment of self-reported hunger (Hetherington 1994, Plasse 1990, Beal, 1995). Mood will be assessed weekly using the Profile of Mood States (POMS). The POMS has displayed high reliability and validity across a variety of time periods and has been used extensively in psychiatric and gen eral population research (McNair 1971).

C.5.2.7 Energy intake

Food intake will be assessed through objective measures. All meals will be prepared in the metabolic kitchen of the GCRC. Subjects will be allowed to select food items for each meal from a list of foods prepared by the kitchen. The nutrient analysis da tabase used by the GCRC contains detailed information for all of these food items, including mixed dishes. Food portions will be weighed during preparation, and uneaten food will be returned to the kitchen and weighed. Thus, exact portion sizes will be us ed in the calculation of the energy and macronutrient content of meals. In addition to the regular meals, a variety of prepackaged snack items and beverages will be available to the subjects at all times. Subjects will be allowed to consume these items ad libitum and instructed to save all uneaten portions and packaging for periodic collection by the dietary staff. Examples of snack items that will be available are fruit juices, chips, cookies, yogurt, candy, crackers, soda, etc.

C.5.2.8 Body composition

The composition of changes in weight, should they occur during either the lead-in or intervention periods, will be characterized by performing measurements of dual-energy X-ray absorptiometry (DEXA) and bioelectrical impedance analysis (BIA).

Dual-energy X-ray absorptiometry (DEXA)

Patients will be scanned on a Lunar model DPX (Madison, WI) absorptiometer. For this measurement, patients lie on a padded scanning table while wearing only a standard hospital gown, underwear and pajama bottoms that contain no snaps or other material that may interfere with attenuation. The procedure takes about 20 minutes; X-ray exposure is <0.5% of that of a chest X-ray. In our hands, the coefficients of variation for lean body mass ( LBM) and fat measured by DEXA in patients on constant weight-m aintaining diets are 0.2 and 3.4%, respectively.

Bioelectrial Impedance Analysis (BIA)

Measurements will be performed with an RJL (Clinton Twp, MI) single frequency analyzer. With the patient lying supine on a nonconductive surface with legs and arms spread apart, electrode pads will be placed on the right hand and foot, and a weak curre nt passed through the body. Measured values of resistance and reactance will be used to calculate fat, LBM, and body cell mass (BCM) using gender-specific equations that have been validated in healthy individuals and those with HIV infection (Kotler 1996) . In our hands, coefficients of variation for measurements of LBM, BCM and fat by BIA are 0.8, 0.7 and 5.5%, respectively.

C.5.2.9 Resting energy expenditure

Subjects will be instructed to rest quietly for at least 30 minutes preceding this measurement. During this time they should not move around, use the telephone, or interact with persons other than the research staff. Resting oxygen consumption (VO2) a nd carbon monoxide production (VCO2) will be measured by indirect calorimetry, using a ventilated canopy system (DeltaTrac Monitor, SensorMedics, Yorba Linda, CA). After adjusting VO2 and VCO2 for protein oxidation (estimated from urinary nitrogen excret ion) these values will be used to calculate REE and substrate oxidation rates using stoichiometrically derived equations (Ferranini 1988). In earlier studies, within-subject variability of daily REE measured in HIV-1 infected individuals during metabolic ward studies has been 2.5-3.0%. Biologic variation in REE is estimated to be 2.2 to 2.5% (Soares 1986)

C.5.2.10 Body weight

Patients will be weighed under fasting conditions on the same calibrated scale each morning after voiding. Patients will wear only a hospital gown for these measurements.

C.6 Statistical Considerations

Our study design allows us to estimate, for each of three treatment groups, change from baseline (Day 0) to follow-up (Day 21) in viral load (Aim 1), in indinavir or nelfinavir concentration (Aim 2), and in measures associated with HIV wasting syndrome (Aim 3). The analyses of each of the arms will be the same: we will estimate change over time within group, and will compare these changes across groups. The contrasts of interest are:

Group B (dronabinol capsules) vs Group C (placebo capsules), to determine acute adverse effects of oral THC, and

Group A (marijuana cigarettes) vs Group B (dronabinol capsules), to determine acute adverse effects of smoked THC

The sample size estimates for aims 1 and 2 show that 63 subjects will be adequate to test both of the primary hypotheses of this study. We anticipate that most dropouts from the study will occur during Phase 1, the lead-in period, when they find they are not willing to be confined to the GCRC for three additional weeks. Subjects who drop out during Phase 1 and are not randomized will not be included in the primary analyses of study endpoints. Enrollment characteristics (at Day -4) of these subjects wi ll be compared with enrollment characteristics of subjects who are randomized to evaluate any selection biases that may occur, and thus whether the results are generalizable to all eligible persons or to a subset of these. GCRC experience, however, indica tes that inability to withstand that environment typically occurs in no more than 10% of subjects.

Aim 1

To determine if the metabolic interaction between cannabinoids and indinavir or nelfinavir, or cannabinoids and the immune system, after 21-days' exposure, is sufficient to alter HIV-1 RNA viral load at 21, 30, and/or 42 days.

Hypothesis: Individuals taking protease inhibitors and cannabinoids will show higher HIV-1 RNA viral load and altered immune system parameters compared to individuals taking protease inhibitors and placebo.

For each subject, the response is the change between mean follow-up and mean baseline viral load values, with these means calculated over three replicates. For each group, the response is the mean change across subjects. To contrast groups, we define a s clinically important any difference between means, ?1 - ?2, that is greater than one standard deviation of this difference. Using a two-sided t-test for independent samples, with type 1 error rate ? = .05 and 80% power, we would need 63 subjects (21 per group, on average) to complete the study (have both baseline and follow-up data). This calculation includes a Bonferroni correction of the ? level to adjust for the two tests that are planned: the contrast between Groups B and C, and the contrast between Groups A and B.

Our sample size calculations are based on simple t-tests, since this is the statistic proposed for the primary analysis. In addition, however, we will examine the distribution of the response data across all subjects to determine if the changes in vira l load are approximately normally distributed or if they must be normalized before applying the t-tests. If a suitable transformation is not found, rank-based tests will be used instead of t-tests (Wilcoxon's rank-sum and signed-rank tests).

The primary analysis, based on a simple t-test, will be supplemented by a multivariate analysis to identify subgroups in which the effects are particularly large. One multivariate model of viral load will include treatment group (A/B or B/C) and protea se inhibitor (indinavir/nelfinavir) and the group-by-inhibitor interaction. We do not anticipate differential effects by inhibitor; however, this model will indicate if there is reason to differentially model these effects in the future.

Aim 2

To determine if there is a significant metabolic interaction between protease inhibitors and cannabinoids, whether delivered via inhalation or orally, after 21-days' exposure.

Hypothesis: Marijuana smoking and/or dronabinol will alter the hepatic metabolism and alter the concentrations of indinavir or nelfinavir, thus increasing their toxicity or decreasing their efficacy.

For each subject, plasma concentration data will be analyzed as area under the plasma concentration-time curve (AUC), estimated using the trapezoidal rule. Renal clearance will be measured as A/AUC, where A is the recovery of indinavir or nelfinavir i n the 8-hour urine collection and AUC is the area under the plasma concentration-time curve over the same 8-hour interval. Plasma concentration data also will be analyzed as peak concentration (Cmax) and time to peak concentration (Tmax).

Aim 3

To summarize the short-term effects of smoked marijuana on variables associated with HIV-1 wasting syndrome by measuring changes over 21 days of use in: endocrine function, appetite, energy intake, resting energy expenditure, body composition and body weight.

Rationale: If the current study demonstrates that smoked marijuana does not have the serious short-term side effects studied here, we would next research the chronic effects of smoked marijuana as a treatment for HIV-associated anorexia and weight los s. Preliminary data on these measures will help to identify the most powerful measure for assessing efficacy and provide preliminary estimates of effect size and variance.

The focus of the Aim 3 analyses will be on parameter estimation rather than on hypothesis testing. Estimates of treatment effects on immune and endocrine system parameters, as well as measures associated with HIV-wasting, will be produced via repeated- measures analysis of variance models, along with estimates of the variances of these estimates.

C.7 Study Treatments

C.7.1 Supply

The marijuana required for this study will be provided by the National Institute of Drug Abuse (NIDA). The marijuana will be sterilized prior to its distribution to eliminate any contamination with Aspergillus. Dronabinol and its placebo will be provid ed by Roxane Laboratories, Columbus, OH.

C.7.2 Dosage

With approval from NIDA, Dr. Mohammed El-Sohly at the University of Mississippi will supply marijuana to the Research Triangle Institute (Research Triangle Park, North Carolina) where 3.95% THC-content marijuana cigarettes will be prepared. Marijuana c igarettes will be rehydrated on the GCRC. They will be weighed prior to and shortly after smoking. Subjects randomized to smoked marijuana will smoke one marijuana cigarette before each meal. We propose to dose dronabinol 2.5 mg, 3 times per day, given before each meal.

C.7.3 Storage and dispensing

Marijuana and dronabinol will be received, stored and dispensed by the pharmacy service at San Francisco General Hospital. Accountability records will be maintained according to policies and procedures for both Schedule I and II and investigational dru gs. The final disposition of each dose will be recorded. Residual drug supplies will be disposed of as directed by the NIDA.

C.7.4 Concomitant medications

PCP prophylaxis and treatment of opportunistic infections, per standard of care, will be allowed. Antiretroviral medications will be allowed except for protease inhibitors other than either nelfinavir or indinavir. Concomitant medications will be recor ded during lead-in and intervention phases of the study. Use of anabolic steroids, or agents that might alter immune system parameters will not be allowed during the study.

C.7.5 Drug toxicity and grading

For the purposes of study monitoring and analysis, all Adverse Events (AE's) at a toxicity Grade 3 or higher associated with use of the study treatments will be graded according to severity as listed in the NIH/Division of AIDS (DAIDS)/CPCRA Toxicity T ables for grading adverse events (AES). For AEs not listed in the Toxicity Table, the severity grade may be estimated by the investigator using generic definitions also listed on the DAIDS Toxicity Table. Patients will be closely monitored for signs and symptoms of study treatment toxicity during the in-patient study in the GCRC. For toxicities that require the study treatment to be temporarily or permanently discontinued, relevant clinical and laboratory tests will be repeated, as necessary, until the re is final resolution or stabilization of the toxicity. All enrolled patients will be monitored for adverse events to the study treatment until completion of their participation in the study (i.e., completion of both lead-in and intervention phases of t he inpatient study). During the follow up phase, adverse events will be monitored by the Consortium clinical research nurse or GCRC staff at follow up visits on day 30 and 42.

D. Human Subjects

This protocol will receive approval from the University of California, San Francisco Committee on Human Research and the Research Advisory Panel of California before implementation. Informed consent will be obtained from all subjects by the Community C onsortium clinical research nurse. The study will be explained to participants by Dr. Abrams or another research provider and subjects' questions will be answered.

Subjects will be given copies of their signed consent form and the University of California, San Francisco Experimental Subject's Bill of Rights to keep. It will be stated that participation in research is voluntary, and that subjects have the right to decline to participate or withdraw at any point in this study without jeopardy to their medical care. If participation is then desired, the subject will sign and date the consent form. The persons obtaining consent will also sign and date the consent for m.

Code numbers will be used on all case report forms (no subject names will be used). Copies of the signed informed consent documents will be kept in a locked file in the Consortium central office. Names of subjects that inadvertently appear on clinical laboratory reports or other documents will be blacked out. Subjects' records on the GCRC will be treated with the same considerations as to confidentiality as any other medical records.

If a subject is injured as a result of being in this study, treatment will be available from his doctor. The cost of this treatment will be covered in the same way as it would be if the subject were not in this study. There is no provision for free med ical care or monetary compensation from the Community Consortium.

Subjects who successfully complete this study will be reimbursed at a rate of $20/day up to a total of $500 for 25 nights in the GCRC) and an additional $400. for completing the full 25 night stay in the GCRC. Subjects will be reimbursed an additional $50 for each of two follow-up visits. Reimbursement will total $1000 for their participation in this study. Payment will be made at completion of the study.

G. Literature Cited

1. Abrams DI, Brosgart CL, Dyner T, Mitchell T. Community Patterns of Care for HIV Disease: A National Survey of Primary Care Providers? Preferred Regimens of Drug Therapy for HIV Disease and its Complications. Community Consortium, UC San Francisco , 1996.

2. Abrams DI, Child CC, and Mitchell T. Marijuana, the AIDS wasting syndrome and the US government. N Engl J. Med 333:670-671, 1995.

3. Acheson KJ, Campbell IT, Edholm OG, Miller DS, and Stock MJ. The measurement of food and energy intake in man - an evaluation of some techniques. Am J Clin Nutr, 1980; 33:1147-1154.

4. Agurell S, Halldin M, Lindgren J, Ohlsson A, Widman M, Gillespie H, and Hollister L.Pharmacokinetics and metabolism of delta- tetrahydrocannabinol and other cannabinoids with emphasis on man. Pharmacological Reviews, 1986; 38(1):21-43.

5. Arcavi L, Jacob P, Hellerstein M, Benowitz NL. Divergent tolerance to metabolic and cardiovascular effects of nicotine in smokers with low and high levels of cigarette consumption. Clin Pharm Thera, 1994; 56(1):55-64.

6. Arciero PJ, Gardner AQ, Calles-Escandon J, Benowitz N, and Poehlman ET. Effects of caffeine ingestion on NE kinetics, fat oxidation, and energy expenditure in younger and older men. Am.J. Physiol., 1995; 288:E1192-E1198.

7. Azorlosa JL, Heishman SJ, Stitzer ML, and Mahaffey JM. Marijuana smoking: effect of varying delta 9-tetrahydrocannabinol content and number of puffs. Journal of Pharmacology and Experimental Therapeutics, 1992; 261(1):114-22.

8. Benowitz NL, Jones RT. Cardiovascular effects of prolonged delta-9-tetrahydrocannabinol ingestion. Clinical Pharmacology and Therapeutics, 1975; 18(3):287-97.

9. Benowitz NL, Jones RT. Effects of delta-9-tetrahydrocannabinol on drug distribution and metabolism. Antipyrine, pentobarbital, and ethanol. Clin Pharmacol Thera, 1977; 22:259-268.

10. Benowitz NL, Nguyen TL, Jones RT, Herning RI, Bachman J. Metabolic and psychophysiologic studies of cannabidiolhexobarbital interaction. Clin Pharmacol Thera, 1980; 28:115-120.

11. Bhasin S, Storer T, Strakova J, Phillips J, Phillips C, Berman N, Bunnell T, Casaburi R. Testosterone increases lean body mass, muscle size and strength in hypogonadal men. Clinical Research, 1994; 42:74A.

12. Bhasin S, Storer T, Berman N, Callegari C, Clevenger B, Phillips J, Bunnell T, Triker R, Shirazi A and Casaburi R. The effects of supraphysiologic doses of testosterone on muscel size and strenght in normal men. N Engl J Med, 1996; 335: 1-7.

13. Bingham SA. The dietary assessment of individuals; methods, accuracy, new techniques and recommendations. Nutr Abstr Rev, 1987; 57:705-742.

14. Bruder N, Dumont JC, and Francois G. Evolution of energy expenditure and nitrogen excretion in severe head-injured patients. Crit Care Med, 1991; 19:43-48.

15. Buschke H. Selective reminding for analysis of memory and learning. Journal of Verbal Learning and Verbal Behavior, 1973; 12:543-550.

16. Cabral GA and Vasquez R. Delta 9-Tetrahydrocannabinol suppresses macrophage extrinsic antiherpes virus activity. Proceedings of the Society for Experimental Biology and Medicine, 1992; 199(2):255-63.

17. Chait LD and Zacny JP. Reinforcing and subjective effects of oral delta9 - THC and smoked marijuana in humans. Psychopharmacology, 1992; (107): 255-262.

18. Chesney M, Folkman S, Chambers D. Coping effectiveness training for men living with HIV disease. Inter J of STDS and AIDS, 1996; 7:75-82.

19. Chiang CN, Barnett G. Marijuana effect and delta-9-tetrahydrocannbinol plasma level. Clin Pharm Therap, 1984; 36:234-238.

20. Child CC, Mitchell TF, Abrams DI. Patterns of Therapeutic Marijuana Use in Two Community-Based Cannabis Buyers' Cooperatives. Abstract submitted to 12th World AIDS Conference, Geneva, June 28-July 3, 1998.

21. Christeff N, Gharakhanian S, Thobie N, Rozenbaum W, and Nunez EA. Evidence for changes in adrenal and testicular steroids during HIV infection. Journal of Acquired Immune Deficiency Syndromes, 1992; 5(8):841-6.

22. Coodley GO, Loveless MO, Nelson HD, and Coodley MK. Endocrine function in the HIV wasting syndrome. Journal of Acquired Immune Deficiency Syndromes, 1994; 7(1): 46-51.

23. Croxson TS, Chapman WE, Miller LK, Levit CD, Senie R, and Zumoff B. Changes in the hypothalamic-pituitary-gonadal axis in human immunodeficiency virus-infected homosexual men. Journal of Clinical Endocrinology and Metabolism, 1989; 68(2):317-21 .

24. Deeks SG, Smith MS, Holodniy MH, Kahn JO. HIV-1 Protease Inhibitors: A Review for Clinicians. JAMA, 1997; 277: 144-153.

25. DeWit, H. Personal communication, 1996.

26. Doblin RE and Kleiman MAR. Marijuana as Antiemetic Medicine: A survey of Oncologists? experiences and attitudes. Journal of Clinical Oncology, 1991; 9:(7):1314-1319.

27. Dobs AS, Dempsey MA, Ladenson PW, and Polk BF. Endocrine disorders in men infected with human immunodeficiency virus. American Journal of Medicine, 1988; 84(3 Pt2):611-6.

28. Dulloo AG, Jacquet J, Girardier L: Autoregulation of body composition during weight recovery in human: the Minnesota Experiment revisited. Int J Obes 20: 393-405, 1996.

29. Ferrannini E. The theoretical bases of indirect calorimetry: A review. Metabolism, 1988; 3:287-301.

30. Fischer-Stenger K, Updegrove AW, and Cabral GA. Delta 9-tetrahydrocannabinol decreases cytotoxic T lymphocyte activity to herpes simplex virus type 1-infected cells. Proceedings of the Society for Experimental Biology and Medicine, 1992; 200(3 ):422-30.

31. Follansbee SE, Mitchell TF, Charlebois E, Child C, Pell P, Chernoff D, and Abrams DI. The Impact of Initiation or Change in Antiretroviral Therapy on HIV Plasma RNA Load as Measured by bDNA Assay. 3rd National Conference on Human Retroviruses and Related Infections, 1996; Washington, DC.

32. Foltin RW, Fischman MW, and Byrne MF. Effects of smoked marijuana on food intake and body weight of humans living in a residential laboratory. Appetite, 1988; 11, 1-14.

33. Foltin RW, Brady JV, and Fischman. Behavioral analysis of marijuana effects on food intake in humans. Pharmacology Biochemistry & Behavior, 1986; 25, 577-582.

34. Forbes GB: Human body composition: Growth, Aging, Nutrition and Activity. New York: Springer-Verlag, 1987

35. Friedman H, Klein TW, Newton C, and Daaka Y. Marijuana, receptors and immunomodulation. Advances in Experimental Medicine and Biology, 1995; 373:103-13.

36. Goldberg C. Marijuana Club Helps Those in Pain. New York Times, Sunday, Feb. 25, 1996, National Report, p16.

37. Going SB, Masset MP, Hall MC, Bare LA, Root PA, Williams LP, Lohman TG: Detecton of small changes in body composition by dual-energy x-ray absorptiometry. Am J Clin Nutr 57: 845-850, 1993.

38. Gorter R, Seefried M, and Volberding P. Dronabinol effects on weight in patients with HIV infection. AIDS, 1992; 6:127.

39. Greenberg I, Kuehnle J, Mendelson JH, and Bernstein JG. Effects of marihuana use on body weight and caloric intake in humans.. Psychopharmacology, 1976; 49:79-84.

40. Griggs RC, Kingston W, Jozefowicz RF, Herr BE, Forbes G, Halliday D. Effect of testosterone on muscle mass and muscle protein synthesis. Journal of Applied Physiology, 1989; 66:498-503.

41. Haarbo J, Gotfredsen A, Hassager C, Christiansen C: Validation of body composition by dual energy X-ray absorptiometry (DEXA). Clin Phys 11: 331-341, 1991.

42. Hall W, Solowij N, Lemon J. The health and psychological consequences of cannabis use. Mongograph series no.25, National Drug and Alcohol Research Centre, Australia, 1995.

43. Hetherington MM, Altemus M, Nelson ML, Bernat AS, Gold PW. Eating behavior in bulimia nervosa: multiple meal analyses. Am J Clin Nut, 1994; 60(6):864-73.

44. Hollister LE. Marijuana and immunity. Journal of Psychoactive Drugs, 1992; 24(2):159-64.

45. Horber FF, Thomi F, Casez JP, Fonteille J, Jaeger P: Impact of hydration status on body compostion as measured by dual energy x-ray absorptiometry in normal volunteers and patients on haemodialysis. Br J Radiol 65: 598-900, 1992.

46. Hughes MD, Johnson VA, Hirsch MS, Bremer JW, Elbeik T, Erice A, Kuritzkes DR, Scott WA, Spector SA, Basgoz N, Fischl MA, D'Aquila RT. Monitoring plasma human immunodeficiency virus (HIV-1) RNA levels in addition to CD4+ lymphocyte count improves assessment of antiretroviral therapeutic response. Annals of Internal Medicine.

47. Iverson LL. Medical uses of marijuana?, Nature, 1993, 365:12-13.

48. Kaslow RA, Blackwelder WC, Ostrow DG, Yerg D, Palenicek J, Coulson AH, and Valdiserri RO. No evidence for a role of alcohol or other psychoactive drugs in accelerating immunodeficiency in HIV-1-positive individuals. JAMA, 1989; (261)23.

49. Katzenstein D, Hammer S, Hughes M, Gundacker H, Jackson B, Fiscus S, Lathey J, Rasheed S, Reichman R, Elbeik T, Japour A, D'Aquila R, Scott W, Griffiths B, Winters M, Merigan T, Hirshc M. Suppression of plasma HIV RNA by reverse transcriptase in hiborts prevents AIDS and death in ACTG 175; Combination and monotherapy with ADV, ddI and DDC. Eleventh International Congress on AIDS, Vancouver, Canada, 1996. Abstr. #Mo.B293.

50. Katzenstein D, Hammer S, Hughes M, Gundacker H, Jackson B, Fiscus S, Rasheed S, Elbeik T, Reichman R, Japour A, Merigan T, Hirsch M. The relation of virologic and immunologic markers to clinical outcomes after nucleoside therapy in HIV-infected adults with 200 to 500 CD4 cells per cubin millimeter. N Engl J Med 1996; Oct 10, 335: 1091-1098.

51. Kirvela O, Katila A, Aantaa R, Kanto J, and Himberg JJ. Metabolic and subjective responses to oral diazepam and midazolam. European Journal of Anaesthesiology, 1994; 11:365-369.

52. Kirvela O and Kanto JH. Clinical and metabolic responses to different kinds of premedication in ASA III patients. Acta Anaesthesiologica Scandinavica, 1992; 36:779-783.

53. Klein TW, Newton C, Zhu W, Daaka Y, and Friedman H. delta9-Tetrahydrocannabinol, cytokines, and immunity to legionella pneumophila(43897A). P.S.E.B.M., 1995; 209:205-212.

54. Klein TW, Newton C, and Friedman H. Resistance to Legionella pneumophila suppressed by the marijuana component, tetrahydrocannabinol. Journal of Infectious Diseases, 1994; 169(5):1177-9.

55. Kotler DP, Burastero S, Wang J, Person RN Jr: Prediciton of body cell mass, fat-free mass, and total body water with bioelectrical impedance analysis: effects of race, sex, and disease. Am J Clin Nutr 64(suppl): 489S-497S, 1996.

56. Kotler DP, Wang J, Pierson RN Jr: Body composition studies in patients with the acquired immunodeficiency syndrome. Am J Clin Nutr 42: 1255-1265, 1985.

57. Lau RJ, Tubergen DG, Barr M, Domino EF, Benowitz N, Jones RT. Phytohemagglutinin-induced lymphocyte transformation in humans receiving delta9-tetrahydrocannabinol. Science, 1976 May 21;192(4241):805-7.

58. Leoung G, Feigal D, Montgomery AB, Corkery K, Wardlaw L, Adams M, Busch D, Gordon S, Jacobson M, Volberding P, Abrams DI, and the San Francisco County Community Consortium. Aerosolized pentamidine for prophylaxis against Pneumocystis Carinii pn eumonia. The San Francisco Community Prophylaxis Trial. NEJM, 1990; 323:769-775.

59. Mattes RD, Engelman K, Shaw LM, and Elsohly MA. Cannabinoids and appetite stimulation. Pharmacology Biochemistry and Behavior, 1994; 49(1):187-195.

60. Mazess RB, Barden HS, Bisek JP, Hanson J: Dual energy x-ray absorptiometry for total-body and regional bone-mineral and soft-tissue composition. Am J Clin Nutr 51: 1106-1112, 1991.

61. McNair DM, Lorr M, Droppleman LF. EITS Manual for the Profile of Mood States. San Diego: Educational and Industrial Testing Service, 1971.

62. Melnick SL, Sherer R, Louis T, Hillman D, Rodriguez EM, Lackman C, Capps L, Brown LS, Carlyn M, Korvick JA, Deyton L. Survival and disease progression according to gender of patients with HIV infection. JAMA, 1994; 272(24):1915-21.

63. Mendelson JH, Kuehnle J, Ellingboe J, Babor TF. Plasma testosterone levels before, during and after chronic marihuana smoking. N Engl J Med 1974; 291:1051-55.

64. Mirken B. Danger: Possible Fatal Interactions Between Ritonavir and "Ecstasy", Some Other Psychoactive Drugs. AIDS Treatment News, 1997; 265: Feb 21.

65. Mulligan K, Grunfeld C, Hellerstein MK, Neese RA, and Schambelan M. Anabolic effects of recombinant human growth hormone in patients with wasting associated with human immunodeficiency virus infection. J Clin. Endocrinol Metab, 1993; 77(4):956- 962.

66. Mulligan K, Tai VW, Greenblatt R, Schambelan M: Body composition and resting energy expenditure in women with HIV infection. XI Int Conf AIDS 1996. (Abstract)

67. Mulligan K, Tai VW, Schambelan M: Cross-sectional and longitudinal evaluation of body composition in men with HIV infection. J Acquire Immune Defic Syndr, 1997 (in press).

68. Mulligan K, Tai VW, Schambelan M. Energy expenditure in human immunodeficiency virus infection. N Engl J Med 336: 70-71, 1997.

69. Munro S, Thomas KL, and Abu-Shaar M. Tashkin DP, Simmons MS, Chang P, Liu H, and Coulson AH. Effects of smoked substance abuse on nonspecific airway hyperresponsiveness. Am. Rev. Respir Dis., 1993; 147:97-103.

70. Nahas GG, Sucla-Foca N, Armand JP, and Morishima A. Inhibition of cellular mediated immunity in marijuana smokers. Science, 1974; 183:419-420.

71. National Toxicology Program Technical Report on the Toxicology and Carcinogensis studies of 1-Trans-Delta9-Tetrahydrocannabinol in F344/N Rats and B6C3F Mice. NTP TR 446, 1996; Nov.

72. Newton CA, Klein TW, and Friedman H. Secondary immunity to legionella pneumophila and the activity are suppressed by delta-9-tetrahydrocannabinol injection. Infection and Immunity, 1994; 62(9):4015-20.

73. Raffi F, Brisseau JM, Planchon B, Remi JP, Barrier JH, and Grolleau JY. Endocrine function in 98 HIV-infected patients; a prospective study. AIDS, 1991; 5(6):729-33.

74. Roehr B. Medical Marijuana Minuet Plays On in DC. Bay Area Reporter, 1997; Feb 27.

1.

75. Roland A, Feigal DW, Abrams DI, Volberding PA, Hollander H, Ziegler J, and Conant MA. Recreational drug use does not cause AIDS progression, the UCSF AIDS Registry Cohort. Proceedings of the Third International Conference on AIDS. Washington, DC, 1987.

76. Saag MS, Holodniy M, Kuritzkes DR, O'Brien WA, Coombs R, Poscher ME, Jacobsen DM, Shaw GM, Richman DD, Volberding PA. HIV viral load markers in clinical practice. Nat Med, 1996; 2: Jun, 625-9.

77. Saget B, Elbeik T, Guthrie J, Drews B, Scheibel S. Dramatic suppression of HIV-1 plasma RNA using a combination of zidovudine, didanosine, zalcatabine, epivir and interferon-alpha in subjects with recent HIV-1 infection. Eleventh International Congress on AIDS, Vancouver, Canada, 1996. Abstr. #We.B.533.

78. Schambelan M, LaMarca A, Mulligan K. Grunfeld C, Kennedy S, Breitmeyer J, and Daar E. Growth hormone therapy of AIDS wasting. Xth Int Conf AIDS, 1994; (Abstract).

79. Scheibel S, Saget B, Elbeik T, Guthrie J, Drews B. Extreme suppression of HIV-1 plasma RNA using a combination of zidovudine, didanosine, zalcatabine, epivir and interferon-alpha in subjects with recent HIV-1 infection. Eleventh International Co ngress on AIDS, Vancouver, Canada, 1996. Abstr. #We.B.3128.

80. Schoeller DA. Limitations in the assessment of dietary energy intake by self-report. Metabolism,1995; 44:18-22.

81. Shivers SC, Newton C, Friedman H, and Klein TW. Delta 9-Tetrahydrocannabinol (THC) modulates IL-1 bioactivity in human monocyte/macrophage cell lines. Life Sciences, 1994; 54(17):1281-9.

82. Soares MJ, and Shetty PS. Intra-individual variations in resting metabolic rates of human subjects. Hum Nutr Clin Nutr, 1986; 40C:365-369.

83. Staprans SI, Hamilton BL, Follansbee SE, Elbeik T, Barbosa P, Grant RM, Feinberg MB. Activation of virus replication after vaccination of HIV-1-infected individuals. J of Experimental Medicine 1995; 182(6):1727-37.

84. Svendsen OL, Haarbo J, Hassager C, Christiansen C: Accuracy of measurements of body compostion by dual-energy x-ray absorptiometry. Am J Clin Nutr 57: 605-608, 1993.

85. Svendsen OL, Haarbo J, Heitmann BL, Gotfredsen A, Christiansen C: Measurement of body fat in elderly subjects by dual-energy x-ray absorptiometry, bioelectrical impedance, and anthropometry. Am J Clin Nutr 53: 1117-1123.

86. Sydney SX. Marijuana use and Mortality. Am J Public Health 1997;87:587-592.

87. Tai V, Mulligan K, Culp J, and Schambelan M. The effects of chronic growth hormone therapy on dietary intake in patients with HIV-associated weight loss. Submitted to the XI International Conference on AIDS, 1996; Vancouver, Canada.

88. Vescovi PP, Pedrazzoni M, Michelini M, Maninetti L, Bernardelli F, and Passeri M. Chronic effects of marijuana smoking on luteinizing hormone, follicle-stimulating hormone and prolactin levels in human males. Drug and Alcohol Dependence, 1992; (10):59-63.

89. Wall NE, Sadler BM, Brine D, Taylor H, Perez-Reyes M. Metabolism, disposition, and kineteics of delta-9-tetrahydrocannabinol in men and women. Clin Pharm Therap 1983; 34:352-362.

90. Wang J, Kotler DP, Russell M, Burastero S, Mazariegos M, Thornton J, Dilmanian FA, Pierson RN Jr: Body-fat measurement in patients with acquired immunodeficiency syndrome: which method should be used? Am J Clin Nutr 56: 963-967, 1992.

91. Welle S, Jozefowicz R, Forbes G, Friggs RC. Effect of testosterone on metabolic rate and body composition in normal men and men with muscular dystrophy. J Clin Endocrinology and Metabolism, 1992; 74:332-5.

92. Wesner B. The Medical Marijuana Issue among PWAs: Reports of Therapeutic Use and Attitudes Toward Legal Reform. Working Paper Series #3. University of Hawaii at Minoa, 1996; Jun.

93. White SC, Brin SC, Janicki BW. Mitogen-induced blastogenic responses of lymphocytes from marihuana smokers. Science, 1975 Apr 4;188 (4183):71-2.

94. Young NR, Baker HWG, Liu G, Seeman E. Body composition and muscle strength in healthy men receiving testosterone enanthate for contraception. Journal of Clinical Endocrinolgy and Metabolism, 1993; 77:1028-32.