Mila Etropolski

Efficacy and Safety of Tapentadol Extended Release Compared with Oxycodone Controlled Release for the Management of Moderate to Severe Chronic Pain Related to Osteoarthritis of the Knee: A Randomized, Double-Blind, Placebo- and Active-Controlled Phase III Study

AbstractBackground: Tapentadol is a novel, centrally acting analgesic with μ-opioid receptor agonist and norepinephrine reuptake inhibitor activity. Objective: To evaluate the efficacy and safety of tapentadol extended release (ER) compared with oxycodone controlled release (CR) for management of moderate to severe chronic osteoarthritis-related knee pain. Methods: This was a randomized, double-blind, active- and placebo-controlled, parallel-arm, multicentre, phase III study during which patients received tapentadol ER, oxycodone CR or placebo for a 3-week titration period followed by a 12-week maintenance period. The study was carried out at sites in Australia, Canada, New Zealand and the US. A total of 1030 patients with chronic osteoarthritis-related knee pain were randomized to receive tapentadol ER 100–250 mg twice daily, oxycodone HCl CR 20–50 mg twice daily or placebo. Primary endpoints (as determined prior to initiation of the study) were the changes from baseline in average daily pain intensity (rated by patients on an 11-point numerical rating scale) over the last week of maintenance and over the entire 12-week maintenance period; last observation carried forward was used to impute missing values after early treatment discontinuation. Results: Efficacy and safety were evaluated for 1023 patients. Tapentadol ER significantly reduced average pain intensity from baseline to week 12 of the maintenance period versus placebo (least squares mean [LSM] difference [95% CI], −0.7 [−1.04, −0.33]), and throughout the maintenance period (−0.7 [−1.00, −0.33]). Oxycodone CR significantly reduced average pain intensity from baseline throughout the maintenance period versus placebo (LSM difference [95% CI], −0.3 [−0.67, −0.00]) but not at week 12 (−0.3 [−0.68, 0.02]). A significantly higher percentage of patients achieved ≥50% improvement in pain intensity in the tapentadol ER group (32.0% [110/344]) compared with the placebo group (24.3% [82/337]; p = 0.027), indicating a clinically significant improvement in pain intensity, while a significantly lower percentage of patients achieved ≥50% improvement in pain intensity in the oxycodone CR group (17.3% [59/342]; p = 0.023 vs placebo). In the placebo, tapentadol ER and oxycodone CR groups, respectively, 61.1% (206/337), 75.9% (261/344) and 87.4% (299/342) of patients reported at least one treatment-emergent adverse event (TEAE); incidences of gastrointestinal-related TEAEs were 26.1% (88/337), 43.0% (148/344) and 67.3% (230/342). Conclusion: Treatment with tapentadol ER 100–250 mg twice daily or oxycodone HCl CR 20–50 mg twice daily was effective for the management of moderate to severe chronic osteoarthritis-related knee pain, with substantially lower incidences of gastrointestinal-related TEAEs associated with treatment with tapentadol ER than with oxycodone CR. [Trial registration number: NCT00421928 (ClinicalTrials.gov Identifier)]

Comparable efficacy and superior gastrointestinal tolerability (nausea, vomiting, constipation) of tapentadol compared with oxycodone hydrochloride

IntroductionTwo randomized, double-blind, placebo-controlled studies in acute and chronic pain treatment, powered to assess noninferiority of the efficacy of tapentadol immediate release (IR) (50 mg, 75 mg) versus oxycodone hydrochloride (HCl) IR (10 mg), established comparable efficacy of tapentadol IR with oxycodone HCl IR, and suggested tapentadol IR’s improved gastrointestinal tolerability. The impact of these equianalgesic doses of tapentadol and oxycodone HCl on bowel function and gastrointestinal tolerability was then directly assessed in the current study, using a validated bowel function diary to comprehensively assess opioid-induced constipation symptoms and outcomes.MethodsIn this double-blind study, patients with end-stage joint disease were randomized to tapentadol IR (50 mg or 75 mg), oxycodone HCl IR 10 mg, or placebo. Treatment with IR formulations (14 days) was followed by treatment (28 days) with extended-release (ER) formulations of active drugs (or placebo).ResultsOxycodone HCl IR treatment significantly decreased (P<0.001) mean (SD) number of spontaneous bowel movements over the 14-day period (average per week: [6.7 (5.44)] versus tapentadol IR 50 mg [9.0 (4.04)], tapentadol IR 75 mg [8.6 (4.65)], and placebo [9.9 (5.16)]) (primary measure), confirming the tolerability findings of the earlier studies. Additionally, incidences of nausea and vomiting were significantly lower over the 14-day period (nominal P<0.001) for tapentadol IR 50 and 75 mg, versus oxycodone HCl IR 10 mg. Results with ER formulations of tapentadol and oxycodone HCl over a longer treatment period were consistent with those of IR formulations.ConclusionTapentadol IR (50 mg, 75 mg) consistently demonstrated superior gastrointestinal tolerability, including for the most commonly reported events, such as nausea, vomiting, and constipation at doses that provide comparable efficacy with oxycodone HCl IR 10 mg. These findings validate and extend the tolerability findings of the two earlier studies that established comparable efficacy of these tapentadol and oxycodone HCl doses.

Patient phenotyping in clinical trials of chronic pain treatments: IMMPACT recommendations.

Abstract There is tremendous interpatient variability in the response to analgesic therapy (even for efficacious treatments), which can be the source of great frustration in clinical practice. This has led to calls for “precision medicine” or personalized pain therapeutics (ie, empirically based algorithms that determine the optimal treatments, or treatment combinations, for individual patients) that would presumably improve both the clinical care of patients with pain and the success rates for putative analgesic drugs in phase 2 and 3 clinical trials. However, before implementing this approach, the characteristics of individual patients or subgroups of patients that increase or decrease the response to a specific treatment need to be identified. The challenge is to identify the measurable phenotypic characteristics of patients that are most predictive of individual variation in analgesic treatment outcomes, and the measurement tools that are best suited to evaluate these characteristics. In this article, we present evidence on the most promising of these phenotypic characteristics for use in future research, including psychosocial factors, symptom characteristics, sleep patterns, responses to noxious stimulation, endogenous pain-modulatory processes, and response to pharmacologic challenge. We provide evidence-based recommendations for core phenotyping domains and recommend measures of each domain.

Validation of a bowel function diary for assessing opioid-induced constipation

OBJECTIVES:Validated tools to assess opioid-induced constipation (OIC) are needed. The aim of this study was to validate a Bowel Function Diary (BF-Diary) that includes patient-reported outcomes (PROs) associated with OIC.METHODS:In a multicenter, observational study, opioid-naive or recently untreated (≥14 days) adults with nonmalignant, chronic pain who were prescribed oral opioid and usual care completed an electronic diary daily for 2 weeks. Test–retest reliability was assessed. Validity was evaluated for two composite end points—number of spontaneous bowel movements (SBM) and complete SBMs (SCBM)—and for other relevant PROs.RESULTS:Of 238 patients (mean age 54 years, 58% women), 63% reported constipation. The intraclass correlation coefficient for numbers of SBM and SCBM, and other BF-Diary PROs was ≥0.71 for all items except stool consistency. Mean (s.d.) number of SBM per week was significantly less in each week for patients with vs. without constipation (5.6±4.3 and 7.3±3.6, respectively over week 1, P=0.0012; similarly, P=0.0096 over week 2). Validity of individual items in the BF-Diary was supported (P<0.05, stool consistency; P<0.0001, all others).CONCLUSIONS:BF-Diary items are generally reliable and valid assessments for OIC research. Specifically, number of SBM is a valid measure for differentiating opioid-treated patients with and without constipation.

Pain intensity rating training: results from an exploratory study of the ACTTION PROTECCT system.

Abstract Clinical trial participants often require additional instruction to prevent idiosyncratic interpretations regarding completion of patient-reported outcomes. The Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION) public–private partnership developed a training system with specific, standardized guidance regarding daily average pain intensity ratings. A 3-week exploratory study among participants with low-back pain, osteoarthritis of the knee or hip, and painful diabetic peripheral neuropathy was conducted, randomly assigning participants to 1 of 3 groups: training with human pain assessment (T+); training with automated pain assessment (T); or no training with automated pain assessment (C). Although most measures of validity and reliability did not reveal significant differences between groups, some benefit was observed in discriminant validity, amount of missing data, and ranking order of least, worst, and average pain intensity ratings for participants in Group T+ compared with the other groups. Prediction of greater reliability in average pain intensity ratings in Group T+ compared with the other groups was not supported, which might indicate that training produces ratings that reflect the reality of temporal pain fluctuations. Results of this novel study suggest the need to test the training system in a prospective analgesic treatment trial.

A standard database format for clinical trials of pain treatments: An ACTTION–CDISC initiative

A standard database format for clinical trials of pain treatments: An ACTTION–CDISC initiative Robert H. Dworkin a,⇑, Robert Allen , Stephen Kopko , Yun Lu , Dennis C. Turk , Laurie B. Burke , Paul Desjardins , Mila Etropolski , David J. Hewitt , Shyamalie Jayawardena , Allison H. Lin , Richard Malamut , Denis Michel , James Ottinger , Paul Peloso , Frank Pucino , Bob A. Rappaport , Vladimir Skljarevski , David St. Peter , Susan Timinski , Christine R. West , Hilary D. Wilson e

On Average: Data Exploration Based on Means Can Be Misleading

INTRODUCTIONOn the basis that “a picture is worth a thousand words,”data are often presented graphically in order to convey someof the information that they contain. Modelers use graphicalrepresentations of data for numerous purposes, two of themost important being, to inform and drive the modelingprocess and to communicate with their clients who are theend users of their models. However, it is not always clearwhich graphic should be used for a particular set of data andfor a particular purpose. As such, it is very well possible thatchoosing the wrong graph may mislead rather than enlighten,which is obviously a situation to be avoided if at all possible.Part of the difficulty lies in the fact that exploratory dataanalysis (EDA), which incorporates graphical exploration ofthe data, is perceived to be as much an art as it is a science.The artistic aspect of EDA is based on human creativity andintuition, and it is our intuition that can sometimes fail on us.One of the most intuitive graphs is one in which the dataare averaged in some way and the averages plotted. This useof averages is so intuitive that it is frequently used withoutvery much thought or consideration. It must be acknowledgedthat in many cases, this proves to be a good strategy thoughthere are occasions when it can be misleading. This paperexamines some commonly encountered situations in whichsuch graphics may be misleading. The reasons why they aremisleading are explored and explained. In addition, analternative strategy is suggested.In order to maintain the confidence of the end users in amodel, it is important that any apparent contradictionbetween the model and the graphical presentation of thedata is carefully explained. It is hoped that the followingsections will go some way in helping with that explanation.For the purposes of the following discussion, it will beassumed that the response variable (Y) is recorded on acontinuous scale. The independent variable (x)maybecontinuous or discrete.The next section describes a general approach tobuilding a mixed effects model. The following two sectionsdiscuss the use of data averages and their limitations. Analternative to data averaging is introduced in the followingsection. The data averaging and alternative methods arecompared by means of a simulated trial and a real caseexample. The paper finishes with a discussion.MIXED EFFECTS MODELWhen the data are grouped in such a way thatobservations within a group are correlated, the model needsto take account of such correlation. Longitudinal data are, ofcourse, grouped and correlated in this way because repeatedobservations on the same subject (experimental unit) arecorrelated. This correlation is due to the fact that suchobservations reflect the individual characteristics of thesubject. There are several options available for modelingcorrelated data (1), one of which is the use of a mixed effectsmodel incorporating both random and fixed effects. The useof mixed effects models is limited to situations where thecorrelation between observations within a group is positive,which is the case for many datasets. These mixed effectsmodels are widely used in pharmacometrics and will form thebasis of our discussion.Consider a situation where data were collected from nsubjects with m