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Selective potentiation of opioid analgesia by nonsteroidal anti-inflammatory drugs
Brain Research 1040 (2005) 151 – 156 www.elsevier.com/locate/brainres
Research report
Selective potentiation of opioid analgesia by nonsteroidal anti-inflammatory drugs Shayna Zelcer, Yuri Kolesnikov, Ivanka Kovalyshyn, David A. Pasternak, Gavril W. PasternakT Departments of Pediatrics, Anesthesiology and Neurology, Laboratory of Molecular Neuropharmacology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10021, USA Accepted 24 January 2005 Available online 2 March 2005
Abstract Opioids are often used in conjunction with nonsteroidal anti-inflammatory drugs (NSAIDs) in the treatment of moderate to severe pain. In this study we have examined interactions between these two classes of drugs. NSAIDs are inactive in the radiant heat tail-flick test, an assay of moderate to severe pain in which opioids are effective. In this assay, ibuprofen potentiated the analgesic actions of hydrocodone and oxycodone, shifting their ED50 values by 2.5-fold and 4.6-fold despite its inactivity when given alone. These opioid/NSAID interactions were dependent upon both the opioid and the NSAID. Neither aspirin nor ketorolac influenced hydrocodone actions in this model and ibuprofen did not potentiate fentanyl or morphine analgesia. Together, these studies demonstrate potent interactions between selected combinations of opioids and NSAIDS and may help explain the clinical utility of combinations. However, the findings also illustrate differences between the drugs within each class. D 2005 Elsevier B.V. All rights reserved. Theme: Sensory systems Topic: Pain modulation: pharmacology Keywords: Opioid; Nonsteroidal anti-inflammatory drugs; Analgesia; Synergy
1. Introduction Nonsteroidal anti-inflammatory drugs (NSAIDs) comprise a group of agents that possess antipyretic, analgesic, and anti-inflammatory properties. There is substantial evidence that NSAID-induced analgesia is due to the inhibition of cyclooxygenase enzymes (COX-1 and COX2), with a resultant decrease in prostaglandin synthesis, a potent inflammatory mediator [40]. Most NSAIDs are nonselective [40]. Selective COX-2 inhibitors, such as celecoxib and rofecoxib, may be associated with fewer adverse effects, in particular gastrointestinal toxicity [6,24]. NSAIDs have limited use in the management of moderate to
T Corresponding author. E-mail address: [email protected] (G.W. Pasternak). 0006-8993/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2005.01.070
severe pain due to a ceiling effect on their analgesic activity. This is consistent with their limited activity in many of the preclinical analgesic assays, which are predictors of strong analgesics, such as the radiant heat tail-flick assay. Opiate agonists, on the other hand, are powerful analgesics with no ceiling effects, but their utility is limited by adverse side effects. Opioids are often used in combination with NSAIDs and a number of combination products are currently widely used in pain management [41,43]. The intent of the combination approach is to utilize agents with different mechanisms of action and thereby enhance analgesic activity with fewer side effects. In clinical studies, NSAIDs lower postoperative opiate use by 20–50%, despite their limited utility alone [1,7,8,13,17,19,23,29]. There is some evidence for synergy between opioids and NSAIDS in animal models of neuropathic and inflammatory pain [14,15,22,25,27,28,46].
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Recently, we demonstrated synergistic interactions between ibuprofen and hydrocodone in a thermal model, the radiant heat tail-flick assay [20]. The objective of the current study was to assess potential interactions in a model of moderate to severe pain, the radiant heat tail-flick assay, and evaluate whether or not NSAID/opiate interactions reflected general drug interactions or whether they were restricted to specific drugs within each class.
2. Materials and methods All in vivo studies were carried out in accordance with the Declaration of Helsinki and with the Guide for Care and Use of Laboratory Animals, as adopted and promulgated by the National Institutes of Health. Male Crl:CD-1R (ICR) BR mice (20–25 g) were purchased from Charles River Laboratories (Raleigh, NC) and were housed in a 12:12-h light–dark cycle temperature-controlled room with food and water freely available. Drugs were obtained from the Research Technology Branch of the National Institute on Drug Abuse (Rockville, MD) and from Sigma (St. Louis, MO, USA). 2.1. Radiant heat tail-flick assay Antinociception, referred to as banalgesiaQ, was assessed in the radiant heat tail-flick test using groups of mice, as previously described [12,38,39]. Baseline latencies typically ranged between 2 and 3 s. Analgesia was defined quantally as the doubling or greater of the baseline latency for each mouse [38,39,45]. The use of quantal analysis goes back to the original studies of D’Amour and Smith [12,26]. Results analyzed quantally corresponded closely to those analyzed using graded responses (data not shown). Drugs were tested at peak analgesic effect, which corresponded to 30 min after the opioid and 45 min after the NSAID. All assays utilized groups of 10 mice and were replicated at least twice, yielding total groups of at least 20 mice for each point. ED50 values and 95% confidence limits were calculated by computerized probit analysis with the aid of Pharm Tools Pro (The McCary Group, Elkins Park, PA).
assay, including aspirin and ketorolac at doses up to 500 mg/ kg and naproxen at a dose as high as 200 mg/kg (data not shown). Higher doses of these drugs could not be examined due to toxicity. We next examined possible interactions between the NSAIDs and hydrocodone in which increasing doses of NSAIDs were administered with a fixed low dose of hydrocodone in the tail-flick assay (Fig. 1). Hydrocodone alone gave a very low response, 13%. Both ibuprofen and naproxen significantly increased the analgesic response of hydrocodone in a dose–dependent manner. Doses of the NSAIDs greater than 200 mg/kg sc could not be examined due to toxicity, so that it is not clear whether or not greater effects would be seen if the ibuprofen or naproxen dose could have been increased further. In contrast, neither ketorolac nor aspirin significantly enhanced hydrocodone analgesia at any of the doses examined, clearly differentiating the ability of various NSAIDs to interact with opioids. To more fully define the ibuprofen/hydrocodone interaction, we determined the ED50 values of hydrocodone alone and with various ibuprofen doses (Table 1). Although the lowest ibuprofen doses did not significantly alter the ED50, we observed an enhanced analgesic response (Fig. 1). The highest dose (200 mg/kg sc) of ibuprofen significantly shifted the hydrocodone ED50 by 2.5-fold. Neither aspirin nor ketorolac at the high dose (200 mg/kg) significantly shifted the hydrocodone ED50 (Table 2), consistent with their inactivity with the fixed dose hydrocodone seen earlier (Fig. 1). However, naproxen was even more effective than ibuprofen, shifting the hydrocodone dose–response curve 4.6-fold. Thus, the interactions of these drugs with hydrocodone were markedly dependent upon which NSAID was examined. To determine whether ibuprofen showed a similar potentiation of other opioids, we next examined the combination of ibuprofen with a series of opiates, including fentanyl, oxycodone, methadone, morphine, and levorphanol (Table 3).
3. Results The first objective of the current study was to characterize the interactions between combinations of nonsteroidal anti-inflammatory drugs (NSAIDs) and opioids in the radiant heat tail-flick assay, a model of moderate to severe pain that correlates well to the clinical situation in which the combination is most commonly used. In this assay, ibuprofen alone was inactive at doses up to 200 mg/kg sc, the highest dose that could be tested due to toxicity [21]. Similarly, doses of a variety of other NSAID drugs given alone also were without effect in the radiant heat tail-flick
Fig. 1. Hydrocodone analgesia alone and in combination with NSAIDs. Mice were administered hydrocodone at a fixed dose (2.5 mg/kg sc) in combination with the indicated dose of NSAID (n z 24) and tested in the tail-flick assay. Hydrocodone alone (n = 90) gave a response of 13%. Ibuprofen and naproxen both significantly increased the analgesic response of hydrocodone despite their inactivity alone ( P b 0.05). Ketorolac and aspirin were without significant effect at all doses examined.
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Table 1 Effect of different Ibuprofen doses on hydrocodone analgesia (tail-flick assay) Drug
ED50
CL
Shift
Hydrocodone alone +Ibuprofen (100 mg/kg) +Ibuprofen (150 mg/kg) +Ibuprofen (200 mg/kg)
5.7 4.4 5.5 2.3
4.8–6.8 2.9–6.0 4.0–6.4 1.4–3.1
1.0 1.3 1.0 2.5
Groups of mice received a dose of hydrocodone (1.25–10 mg/kg) alone or in combination with the indicated dose of ibuprofen. ED50 values with 95% confidence limits of hydrocodone were calculated from the dose–response curve, as described in Materials and methods. At least three doses of drug were used for each dose–response curve. The shift of the opiate ED50 was determined by the ratio of two ED50 values. The inclusion of ibuprofen at 200 mg/kg sc significantly shifted the ED50 value ( P b 0.05), as indicated by the lack of overlap of the 95% confidence limits.
Full dose–response curves were performed with each opiate alone and in combination with ibuprofen (200 mg/kg sc). Like hydrocodone, oxycodone and methadone analgesia were significantly potentiated by ibuprofen, but not the others. Although levorphanol showed a shift, it did not reach significance. Thus, NSAID/opioid interactions also were extremely dependent upon opioids examined, with some revealing no shift at all.
4. Discussion Nonsteroidal anti-inflammatory drugs are widely used alone clinically to treat mild to moderate pain, but their analgesic ceiling effect often makes them inadequate against severe pain. Yet, they remain widely used in combination with opioids in situations in which they are ineffective alone [41,43], raising the question of whether they significantly contribute to the overall analgesic activity seen with these combinations. The results of studies have been conflicting. While some studies have failed to observe more than
Table 2 Effect of various NSAIDS on hydrocodone analgesia (tail-flick assay) d
Hydrocodone ED50 value (mg/kg)
Ratio*
(95% confidence limits) Hydrocodone alone +Naproxen +Ibuprofen +Aspirin +Ketorolac
5.7 1.3 2.3 4.4 6.1
4.8–6.8 1.1–1.5 1.4–3.1 2.4–6.0 5.4–6.8
4.6 2.5 1.3 0.9
Groups of mice received hydrocodone (0.625–10 mg/kg ) alone or in combination with the indicated NSAID (200 mg/kg). The ibuprofen results are also shown in Table 1. ED50 values with 95% confidence limits were calculated, as described in Materials and methods. All dose–response curves included at least three doses of hydrocodone, with 24 mice/dose. The shift of the ED50 was determined by the ratio of two ED50 values. The inclusion of naproxen and ibuprofen significantly shifted the ED50 value, as indicated by the lack of overlap of the 95% confidence limits. Aspirin and ketorolac were without effect.
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Table 3 Effect of Ibuprofen on a series of opiate analgesics (tail-flick assay) Opiate
Hydrocodone Oxycodone Methadone Levorphanol Morphine Fentanyl
ED50 (mg/kg) (CL)
Shift
Opiate alone
Opiate + Ibuprofen
5.7 1.9 2.8 0.92 4.0 0.017
2.3 0.53 1.7 0.57 3.7 0.016
4.8–6.8 1.5–2.3 2.5–3.2 0.67–1.1 3.4–5.0 0.012–0.021
1.4–3.1 0.42–0.64 1.3–2.1 0.35–0.77 3.0–4.9 0.008–0.023
2.5 3.6 1.6 1.6 1.1 1.1
ED50 values were determined for hydrocodone (1.25–10 mg/kg), oxycodone: (0.2–5 mg/kg), methadone: (1–4 mg/kg), levorphanol (0.4–2.5 mg/ kg), morphine (1–8 mg/kg), and fentanyl (10–30 Ag/kg) alone and in combination with ibuprofen (200 mg/kg). At least four doses were used for all the opioids, except for fentanyl that had three, with at least 24 mice/dose. The shift induced by ibuprofen was calculated from the ratio of the ED50 values. Ibuprofen significantly shifted the ED50 values of hydrocodone, oxycodone, and methadone ( P b 0.05), as indicated by the lack of overlap of the 95% confidence limits of the values. Levorphanol, morphine, and fentanyl showed no significant shift.
additive effects, some have suggested synergy, including the combination of morphine and the selective COX-2 inhibitor rofecoxib [14], ketorolac and morphine [28], tramadol and aspirin [46], morphine and diclofenac [15], and ibuprofen and hydrocodone [21]. Some of these reports appear contradictory, with drugs showing interactions in some studies but not others. These differences may be due to the type of pain being assessed. For example, the interaction between morphine and ketorolac reported in a visceral pain model [28] was not seen in a thermal nociception assay using the immersion tail-flick assay [25]. The goal of the current study was to examine these interactions in a model of moderate to severe pain, the tailflick assay [12,26,49]. As in previous studies [4,21], we again failed to observe analgesic activity for any of the NSAIDs in this model, presumably reflecting the ceiling effect of this class of drug. Previously, our laboratory documented that ibuprofen potentiated hydrocodone analgesia despite its inactivity when given alone [21]. In the current study, we again observed that ibuprofen potentiated hydrocodone analgesia in the radiant heat tail-flick assay and found a similar result with naproxen. The inclusion of either ibuprofen or naproxen to a fixed, low dose of hydrocodone raised the analgesic response from around 15% to over 70%, results that were confirmed with full hydrocodone dose–response curves. However, these opioid/ NSAID interactions were limited to selected drugs. Unlike both ibuprofen and naproxen, neither aspirin nor ketorolac displayed any interactions with hydrocodone. Equally interesting, not all opioids interacted with ibuprofen. Ibuprofen shifted the dose–response curves for hydrocodone and oxycodone the most, with methadone showing a smaller, but significant, shift. Levorphanol, a mixed mu/kappa3 analgesic [48], also had a modest shift in the ED50 value similar to methadone, but fell short of significance. However, neither morphine nor fentanyl showed any meaningful
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interactions with ibuprofen, with ratios near unity. Thus, these results reveal a complexity in these interactions that had not been previously appreciated. It is interesting that various mu opioids show such wide differences in their ability to interact with ibuprofen in the tail-flick assay. For example, both morphine and methadone are well-established mu opioids. Yet, methadone analgesia was enhanced by ibuprofen in this model while morphine was not. Hydrocodone and oxycodone also act predominantly through mu mechanisms and their interactions were even more profound than those of methadone. Differences among mu opioids have been noted both clinically and in animal models. Clinically, most of the opioids used to treat pain fall within the mu opioid family. Yet, clinicians are well aware of subtle, but significant, differences among them. Potency differences for various mu opioids among patients are often seen, but more interesting is the anecdotal evidence suggesting that some patients respond better to one mu opioid than another. Side effects also vary among the drugs. For example, it is not uncommon for morphine to elicit incapacitating nausea and vomiting in a patient who can then take methadone, another mu opioid, without a problem [11,16,41]. Opioid Rotation is widely used to restore analgesic sensitivity in highly tolerant patients and probably reflects incomplete cross-tolerance among the drugs [11]. Animal studies reveal similar observations [3,10,42,44,45]. For example, the sensitivity of various strains of mice to morphine can vary markedly. Perhaps the most telling is the marked difference in analgesic sensitivity of the inbred CXBK mouse between morphine and several other mu opioids, including methadone, heroin and morphine-6h-glucuronide [3,10,42,44,45], and the retention of heroin and morphine-6h-glucuronide analgesia in an MOR1 knockout mouse that was insensitive to morphine [47]. All these drugs are highly mu selective in receptor binding assays and selectively reversed by mu antagonists. One possible explanation for the differences in their action involves subtypes of mu opioid receptors. Initially proposed on the basis of detailed binding studies [34,50] and the actions of selective antagonists [18,35,36], the concept has been supported by the identification of multiple splice variants of MOR-1. Indeed, at least 20 splice variants have been identified in mice [5,30–32], 10 in humans [2,33] and 5 in rats [37,51]. All the full-length MOR-1 variants with the traditional seven transmembrane domain receptors are highly selective for mu opioids and show similar binding affinities for them. Yet, the mu opioids display widely variable intrinsic activities and efficacies among the splice variants. Thus, their functional differences among the variants may help explain some of the subtle pharmacological differences among these mu opioids previously noted, as well in the current studies. The differences in the ability of the NSAIDs to potentiate hydrocodone also was intriguing, particularly the inability of ketorolac to enhance hydrocodone analgesia. NSAIDs inhibit cyclooxygenase. Most, including the ones examined
in this study, are not selective and thought to antagonize both COX-1 and COX-2 isoforms [40]. Another isoform, COX-3, also has been reported [9]. Thus, there are at least three cyclooxygenase enzymes that may be targeted by the NSAIDs. While the analgesic actions of these agents are often attributed to the blockade of COX-2, the isoforms responsible for potentiating hydrocodone analgesia remain unclear. Potential differences among the NSAIDs in the drug combination models may reflect intrinsic differences in their interactions among the COX isoforms or other, as yet unidentified, targets. Future studies will be needed to address these questions. The current study demonstrates a clear potentiation of opioid analgesia by NSAIDs. Combinations are widely used clinically. However, it remains to be determined whether or not the drugs show the same synergy combination profile clinically that we observed in the preclinical radiant heat tail-flick model. Thus, the results of the current study may not predict which combinations to use clinically and underscored the need to examine more than one combination. A hallmark of pain management is the need to individualize therapy. The complexity of the interactions seen in these current mouse studies underscores this concept. In the clinical setting, changing combinations of opioids and NSAIDs may identify therapies that provide better pain control.
Acknowledgments This work was supported, in part, by a grant (DA07242) and a Senior Scientist Award (DA00220) from the National Institute on Drug Abuse to GWP and a Core Grant (CA08748) from the National Cancer Institute to MSKCC.
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Research report
Selective potentiation of opioid analgesia by nonsteroidal anti-inflammatory drugs Shayna Zelcer, Yuri Kolesnikov, Ivanka Kovalyshyn, David A. Pasternak, Gavril W. PasternakT Departments of Pediatrics, Anesthesiology and Neurology, Laboratory of Molecular Neuropharmacology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10021, USA Accepted 24 January 2005 Available online 2 March 2005
Abstract Opioids are often used in conjunction with nonsteroidal anti-inflammatory drugs (NSAIDs) in the treatment of moderate to severe pain. In this study we have examined interactions between these two classes of drugs. NSAIDs are inactive in the radiant heat tail-flick test, an assay of moderate to severe pain in which opioids are effective. In this assay, ibuprofen potentiated the analgesic actions of hydrocodone and oxycodone, shifting their ED50 values by 2.5-fold and 4.6-fold despite its inactivity when given alone. These opioid/NSAID interactions were dependent upon both the opioid and the NSAID. Neither aspirin nor ketorolac influenced hydrocodone actions in this model and ibuprofen did not potentiate fentanyl or morphine analgesia. Together, these studies demonstrate potent interactions between selected combinations of opioids and NSAIDS and may help explain the clinical utility of combinations. However, the findings also illustrate differences between the drugs within each class. D 2005 Elsevier B.V. All rights reserved. Theme: Sensory systems Topic: Pain modulation: pharmacology Keywords: Opioid; Nonsteroidal anti-inflammatory drugs; Analgesia; Synergy
1. Introduction Nonsteroidal anti-inflammatory drugs (NSAIDs) comprise a group of agents that possess antipyretic, analgesic, and anti-inflammatory properties. There is substantial evidence that NSAID-induced analgesia is due to the inhibition of cyclooxygenase enzymes (COX-1 and COX2), with a resultant decrease in prostaglandin synthesis, a potent inflammatory mediator [40]. Most NSAIDs are nonselective [40]. Selective COX-2 inhibitors, such as celecoxib and rofecoxib, may be associated with fewer adverse effects, in particular gastrointestinal toxicity [6,24]. NSAIDs have limited use in the management of moderate to
T Corresponding author. E-mail address: [email protected] (G.W. Pasternak). 0006-8993/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.brainres.2005.01.070
severe pain due to a ceiling effect on their analgesic activity. This is consistent with their limited activity in many of the preclinical analgesic assays, which are predictors of strong analgesics, such as the radiant heat tail-flick assay. Opiate agonists, on the other hand, are powerful analgesics with no ceiling effects, but their utility is limited by adverse side effects. Opioids are often used in combination with NSAIDs and a number of combination products are currently widely used in pain management [41,43]. The intent of the combination approach is to utilize agents with different mechanisms of action and thereby enhance analgesic activity with fewer side effects. In clinical studies, NSAIDs lower postoperative opiate use by 20–50%, despite their limited utility alone [1,7,8,13,17,19,23,29]. There is some evidence for synergy between opioids and NSAIDS in animal models of neuropathic and inflammatory pain [14,15,22,25,27,28,46].
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Recently, we demonstrated synergistic interactions between ibuprofen and hydrocodone in a thermal model, the radiant heat tail-flick assay [20]. The objective of the current study was to assess potential interactions in a model of moderate to severe pain, the radiant heat tail-flick assay, and evaluate whether or not NSAID/opiate interactions reflected general drug interactions or whether they were restricted to specific drugs within each class.
2. Materials and methods All in vivo studies were carried out in accordance with the Declaration of Helsinki and with the Guide for Care and Use of Laboratory Animals, as adopted and promulgated by the National Institutes of Health. Male Crl:CD-1R (ICR) BR mice (20–25 g) were purchased from Charles River Laboratories (Raleigh, NC) and were housed in a 12:12-h light–dark cycle temperature-controlled room with food and water freely available. Drugs were obtained from the Research Technology Branch of the National Institute on Drug Abuse (Rockville, MD) and from Sigma (St. Louis, MO, USA). 2.1. Radiant heat tail-flick assay Antinociception, referred to as banalgesiaQ, was assessed in the radiant heat tail-flick test using groups of mice, as previously described [12,38,39]. Baseline latencies typically ranged between 2 and 3 s. Analgesia was defined quantally as the doubling or greater of the baseline latency for each mouse [38,39,45]. The use of quantal analysis goes back to the original studies of D’Amour and Smith [12,26]. Results analyzed quantally corresponded closely to those analyzed using graded responses (data not shown). Drugs were tested at peak analgesic effect, which corresponded to 30 min after the opioid and 45 min after the NSAID. All assays utilized groups of 10 mice and were replicated at least twice, yielding total groups of at least 20 mice for each point. ED50 values and 95% confidence limits were calculated by computerized probit analysis with the aid of Pharm Tools Pro (The McCary Group, Elkins Park, PA).
assay, including aspirin and ketorolac at doses up to 500 mg/ kg and naproxen at a dose as high as 200 mg/kg (data not shown). Higher doses of these drugs could not be examined due to toxicity. We next examined possible interactions between the NSAIDs and hydrocodone in which increasing doses of NSAIDs were administered with a fixed low dose of hydrocodone in the tail-flick assay (Fig. 1). Hydrocodone alone gave a very low response, 13%. Both ibuprofen and naproxen significantly increased the analgesic response of hydrocodone in a dose–dependent manner. Doses of the NSAIDs greater than 200 mg/kg sc could not be examined due to toxicity, so that it is not clear whether or not greater effects would be seen if the ibuprofen or naproxen dose could have been increased further. In contrast, neither ketorolac nor aspirin significantly enhanced hydrocodone analgesia at any of the doses examined, clearly differentiating the ability of various NSAIDs to interact with opioids. To more fully define the ibuprofen/hydrocodone interaction, we determined the ED50 values of hydrocodone alone and with various ibuprofen doses (Table 1). Although the lowest ibuprofen doses did not significantly alter the ED50, we observed an enhanced analgesic response (Fig. 1). The highest dose (200 mg/kg sc) of ibuprofen significantly shifted the hydrocodone ED50 by 2.5-fold. Neither aspirin nor ketorolac at the high dose (200 mg/kg) significantly shifted the hydrocodone ED50 (Table 2), consistent with their inactivity with the fixed dose hydrocodone seen earlier (Fig. 1). However, naproxen was even more effective than ibuprofen, shifting the hydrocodone dose–response curve 4.6-fold. Thus, the interactions of these drugs with hydrocodone were markedly dependent upon which NSAID was examined. To determine whether ibuprofen showed a similar potentiation of other opioids, we next examined the combination of ibuprofen with a series of opiates, including fentanyl, oxycodone, methadone, morphine, and levorphanol (Table 3).
3. Results The first objective of the current study was to characterize the interactions between combinations of nonsteroidal anti-inflammatory drugs (NSAIDs) and opioids in the radiant heat tail-flick assay, a model of moderate to severe pain that correlates well to the clinical situation in which the combination is most commonly used. In this assay, ibuprofen alone was inactive at doses up to 200 mg/kg sc, the highest dose that could be tested due to toxicity [21]. Similarly, doses of a variety of other NSAID drugs given alone also were without effect in the radiant heat tail-flick
Fig. 1. Hydrocodone analgesia alone and in combination with NSAIDs. Mice were administered hydrocodone at a fixed dose (2.5 mg/kg sc) in combination with the indicated dose of NSAID (n z 24) and tested in the tail-flick assay. Hydrocodone alone (n = 90) gave a response of 13%. Ibuprofen and naproxen both significantly increased the analgesic response of hydrocodone despite their inactivity alone ( P b 0.05). Ketorolac and aspirin were without significant effect at all doses examined.
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Table 1 Effect of different Ibuprofen doses on hydrocodone analgesia (tail-flick assay) Drug
ED50
CL
Shift
Hydrocodone alone +Ibuprofen (100 mg/kg) +Ibuprofen (150 mg/kg) +Ibuprofen (200 mg/kg)
5.7 4.4 5.5 2.3
4.8–6.8 2.9–6.0 4.0–6.4 1.4–3.1
1.0 1.3 1.0 2.5
Groups of mice received a dose of hydrocodone (1.25–10 mg/kg) alone or in combination with the indicated dose of ibuprofen. ED50 values with 95% confidence limits of hydrocodone were calculated from the dose–response curve, as described in Materials and methods. At least three doses of drug were used for each dose–response curve. The shift of the opiate ED50 was determined by the ratio of two ED50 values. The inclusion of ibuprofen at 200 mg/kg sc significantly shifted the ED50 value ( P b 0.05), as indicated by the lack of overlap of the 95% confidence limits.
Full dose–response curves were performed with each opiate alone and in combination with ibuprofen (200 mg/kg sc). Like hydrocodone, oxycodone and methadone analgesia were significantly potentiated by ibuprofen, but not the others. Although levorphanol showed a shift, it did not reach significance. Thus, NSAID/opioid interactions also were extremely dependent upon opioids examined, with some revealing no shift at all.
4. Discussion Nonsteroidal anti-inflammatory drugs are widely used alone clinically to treat mild to moderate pain, but their analgesic ceiling effect often makes them inadequate against severe pain. Yet, they remain widely used in combination with opioids in situations in which they are ineffective alone [41,43], raising the question of whether they significantly contribute to the overall analgesic activity seen with these combinations. The results of studies have been conflicting. While some studies have failed to observe more than
Table 2 Effect of various NSAIDS on hydrocodone analgesia (tail-flick assay) d
Hydrocodone ED50 value (mg/kg)
Ratio*
(95% confidence limits) Hydrocodone alone +Naproxen +Ibuprofen +Aspirin +Ketorolac
5.7 1.3 2.3 4.4 6.1
4.8–6.8 1.1–1.5 1.4–3.1 2.4–6.0 5.4–6.8
4.6 2.5 1.3 0.9
Groups of mice received hydrocodone (0.625–10 mg/kg ) alone or in combination with the indicated NSAID (200 mg/kg). The ibuprofen results are also shown in Table 1. ED50 values with 95% confidence limits were calculated, as described in Materials and methods. All dose–response curves included at least three doses of hydrocodone, with 24 mice/dose. The shift of the ED50 was determined by the ratio of two ED50 values. The inclusion of naproxen and ibuprofen significantly shifted the ED50 value, as indicated by the lack of overlap of the 95% confidence limits. Aspirin and ketorolac were without effect.
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Table 3 Effect of Ibuprofen on a series of opiate analgesics (tail-flick assay) Opiate
Hydrocodone Oxycodone Methadone Levorphanol Morphine Fentanyl
ED50 (mg/kg) (CL)
Shift
Opiate alone
Opiate + Ibuprofen
5.7 1.9 2.8 0.92 4.0 0.017
2.3 0.53 1.7 0.57 3.7 0.016
4.8–6.8 1.5–2.3 2.5–3.2 0.67–1.1 3.4–5.0 0.012–0.021
1.4–3.1 0.42–0.64 1.3–2.1 0.35–0.77 3.0–4.9 0.008–0.023
2.5 3.6 1.6 1.6 1.1 1.1
ED50 values were determined for hydrocodone (1.25–10 mg/kg), oxycodone: (0.2–5 mg/kg), methadone: (1–4 mg/kg), levorphanol (0.4–2.5 mg/ kg), morphine (1–8 mg/kg), and fentanyl (10–30 Ag/kg) alone and in combination with ibuprofen (200 mg/kg). At least four doses were used for all the opioids, except for fentanyl that had three, with at least 24 mice/dose. The shift induced by ibuprofen was calculated from the ratio of the ED50 values. Ibuprofen significantly shifted the ED50 values of hydrocodone, oxycodone, and methadone ( P b 0.05), as indicated by the lack of overlap of the 95% confidence limits of the values. Levorphanol, morphine, and fentanyl showed no significant shift.
additive effects, some have suggested synergy, including the combination of morphine and the selective COX-2 inhibitor rofecoxib [14], ketorolac and morphine [28], tramadol and aspirin [46], morphine and diclofenac [15], and ibuprofen and hydrocodone [21]. Some of these reports appear contradictory, with drugs showing interactions in some studies but not others. These differences may be due to the type of pain being assessed. For example, the interaction between morphine and ketorolac reported in a visceral pain model [28] was not seen in a thermal nociception assay using the immersion tail-flick assay [25]. The goal of the current study was to examine these interactions in a model of moderate to severe pain, the tailflick assay [12,26,49]. As in previous studies [4,21], we again failed to observe analgesic activity for any of the NSAIDs in this model, presumably reflecting the ceiling effect of this class of drug. Previously, our laboratory documented that ibuprofen potentiated hydrocodone analgesia despite its inactivity when given alone [21]. In the current study, we again observed that ibuprofen potentiated hydrocodone analgesia in the radiant heat tail-flick assay and found a similar result with naproxen. The inclusion of either ibuprofen or naproxen to a fixed, low dose of hydrocodone raised the analgesic response from around 15% to over 70%, results that were confirmed with full hydrocodone dose–response curves. However, these opioid/ NSAID interactions were limited to selected drugs. Unlike both ibuprofen and naproxen, neither aspirin nor ketorolac displayed any interactions with hydrocodone. Equally interesting, not all opioids interacted with ibuprofen. Ibuprofen shifted the dose–response curves for hydrocodone and oxycodone the most, with methadone showing a smaller, but significant, shift. Levorphanol, a mixed mu/kappa3 analgesic [48], also had a modest shift in the ED50 value similar to methadone, but fell short of significance. However, neither morphine nor fentanyl showed any meaningful
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interactions with ibuprofen, with ratios near unity. Thus, these results reveal a complexity in these interactions that had not been previously appreciated. It is interesting that various mu opioids show such wide differences in their ability to interact with ibuprofen in the tail-flick assay. For example, both morphine and methadone are well-established mu opioids. Yet, methadone analgesia was enhanced by ibuprofen in this model while morphine was not. Hydrocodone and oxycodone also act predominantly through mu mechanisms and their interactions were even more profound than those of methadone. Differences among mu opioids have been noted both clinically and in animal models. Clinically, most of the opioids used to treat pain fall within the mu opioid family. Yet, clinicians are well aware of subtle, but significant, differences among them. Potency differences for various mu opioids among patients are often seen, but more interesting is the anecdotal evidence suggesting that some patients respond better to one mu opioid than another. Side effects also vary among the drugs. For example, it is not uncommon for morphine to elicit incapacitating nausea and vomiting in a patient who can then take methadone, another mu opioid, without a problem [11,16,41]. Opioid Rotation is widely used to restore analgesic sensitivity in highly tolerant patients and probably reflects incomplete cross-tolerance among the drugs [11]. Animal studies reveal similar observations [3,10,42,44,45]. For example, the sensitivity of various strains of mice to morphine can vary markedly. Perhaps the most telling is the marked difference in analgesic sensitivity of the inbred CXBK mouse between morphine and several other mu opioids, including methadone, heroin and morphine-6h-glucuronide [3,10,42,44,45], and the retention of heroin and morphine-6h-glucuronide analgesia in an MOR1 knockout mouse that was insensitive to morphine [47]. All these drugs are highly mu selective in receptor binding assays and selectively reversed by mu antagonists. One possible explanation for the differences in their action involves subtypes of mu opioid receptors. Initially proposed on the basis of detailed binding studies [34,50] and the actions of selective antagonists [18,35,36], the concept has been supported by the identification of multiple splice variants of MOR-1. Indeed, at least 20 splice variants have been identified in mice [5,30–32], 10 in humans [2,33] and 5 in rats [37,51]. All the full-length MOR-1 variants with the traditional seven transmembrane domain receptors are highly selective for mu opioids and show similar binding affinities for them. Yet, the mu opioids display widely variable intrinsic activities and efficacies among the splice variants. Thus, their functional differences among the variants may help explain some of the subtle pharmacological differences among these mu opioids previously noted, as well in the current studies. The differences in the ability of the NSAIDs to potentiate hydrocodone also was intriguing, particularly the inability of ketorolac to enhance hydrocodone analgesia. NSAIDs inhibit cyclooxygenase. Most, including the ones examined
in this study, are not selective and thought to antagonize both COX-1 and COX-2 isoforms [40]. Another isoform, COX-3, also has been reported [9]. Thus, there are at least three cyclooxygenase enzymes that may be targeted by the NSAIDs. While the analgesic actions of these agents are often attributed to the blockade of COX-2, the isoforms responsible for potentiating hydrocodone analgesia remain unclear. Potential differences among the NSAIDs in the drug combination models may reflect intrinsic differences in their interactions among the COX isoforms or other, as yet unidentified, targets. Future studies will be needed to address these questions. The current study demonstrates a clear potentiation of opioid analgesia by NSAIDs. Combinations are widely used clinically. However, it remains to be determined whether or not the drugs show the same synergy combination profile clinically that we observed in the preclinical radiant heat tail-flick model. Thus, the results of the current study may not predict which combinations to use clinically and underscored the need to examine more than one combination. A hallmark of pain management is the need to individualize therapy. The complexity of the interactions seen in these current mouse studies underscores this concept. In the clinical setting, changing combinations of opioids and NSAIDs may identify therapies that provide better pain control.
Acknowledgments This work was supported, in part, by a grant (DA07242) and a Senior Scientist Award (DA00220) from the National Institute on Drug Abuse to GWP and a Core Grant (CA08748) from the National Cancer Institute to MSKCC.
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