Bender R, Schachtel H, Revicki D, Rentz A, Kwong J, Marrett E. The impact of nausea on pain and its relief. Poster presented at the 2016 PAINWeek Conference; September 2016. Las Vegas, NV. [abstract] Postgrad Med. 2016 Aug 18; 128(S2):9.

PURPOSE: Opioid-induced nausea and vomiting (OINV) is a common condition associated with the use of opioids to treat moderate-to-severe acute pain. The presence and severity of these opioid-associated side effects can lead to suboptimal pain therapy and patient dissatisfaction, adversely affecting patient well-being. However, the relationship between OINV and pain control has not been previously well-studied. The objective of this analysis was to examine the relationship between 2 patient-reported outcomes, nausea intensity and pain severity.

METHOD: A post-hoc analysis was performed using data from a randomized, double-blind, phase 3 study evaluating the efficacy and safety of CL-108 (hydrocodone 7.5 mg/acetaminophen 325 mg (HC/APAP) with rapid-release promethazine 12.5 mg) compared to HC/APAP and placebo in patients with moderate-tosevere pain following surgical extraction of at least two impacted 3rd molars.

Patients received the first dose of study medication after randomization and then self-dosed, as needed, every 4-6 hours, for a maximum of 6 doses over 24-hours. Antiemetic or analgesic rescue medications were allowed as needed. The Nausea Intensity Scale (NIS) assessed nausea intensity using a 0-to-10 numeric rating scale anchored as ‘no nausea’ and ‘severe nausea’. A Categorical Pain Intensity Scale (PI-CAT) assessed current pain severity using a 4-level scale of no pain to severe pain. Subjects completed both assessments at baseline, half-hourly from 0.5-6 hours in clinic post-initial dosing, and hourly at 7-24 hours as outpatients (while awake). Rescue medication use was also recorded.

Pooled data from 211 patients receiving CL-108 and 205 patients receiving HC/APAP were analyzed. Growth Curve Modeling (GCM) was used to examine the relationship between patient-reported nausea intensity and pain severity. Individual models for the trajectory of pain using the PI-CAT, and the trajectory of nausea using the NIS across the 24-hour treatment period were estimated while controlling for a timevarying covariate for rescue medication use, and covariates for age, gender, and the number of opioid doses used over 24 hours.

RESULTS: The GCM modeling showed a significant positive association between patient-reported nausea intensity and pain severity scores (p<0.001). Patients who experienced more intense nausea reported higher pain severity. Similarly, lower levels of nausea intensity were associated with lower levels of pain severity. This positive association was significant at all assessment time points across the 24-hour period (all p<0.001). Nausea intensity ratings and the number of opioid doses taken were the strongest determinants of pain severity scores at 24 hours, accounting for 6.5% and 6.2% of the model variance, respectively. Younger age (p<0.05) and female gender (p<0.05) were also significant predictors of pain severity, accounting for 1.5% and 1.1% of variance.

The positive association between nausea intensity and pain severity scores was most evident at hour 10, with nausea intensity accounting for 10.2% of the variance and number of opioid doses taken accounting for 14.7% of the variance in pain severity ratings.

The model results showed a strong and consistent positive relationship between the level of nausea and the level of pain after oral surgery. At 24 hours, the nausea intensity score and number of opioid doses taken had nearly the same effect size with regard to prediction of a patient’s pain score. Efforts to reduce the occurrence and intensity of nausea in patients receiving opioids for moderate-to-severe acute pain should improve pain reduction, facilitate recovery and enhance patient satisfaction.

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