Objectives 
To run a systematic review and meta-analysis of randomized clinical trials aiming to answer the clinical question “which analgesic combination and dosage is potentially the most effective and safe for acute post-operative pain control after third molar surgery?”.


Materials and Methods 
A systematic search of computer databases and journals was performed. The search and the evaluations of articles were performed by 2 independent reviewers in 3 rounds. Randomized clinical trials related to analgesic combinations for acute post-operative pain control after lower third molar surgery that matched the selection criteria were evaluated to enter in the final review.


Results 
Fourteen studies with 3521 subjects, with 10 groups (17 dosages) of analgesic combinations were included in the final review. The analgesic efficacy were presented by the objective pain measurements including sum of pain intensity at 6 hours (SPID6) and total pain relief at 6 hours (TOTPAR6). The SPID6 scores and TOTPAR6 scores of the reported analgesic combinations were ranged from 1.46 to 6.44 and 3.24 – 10.3, respectively. Ibuprofen 400mg with oxycodone HCL 5mg had superior efficacy (SPID6: 6.44, TOTPAR6: 9.31). Nausea was the most common adverse effect, with prevalence ranging from 0-55%. Ibuprofen 200mg with caffeine 100mg or 200mg had a reasonable analgesic effect with fewer side effects.


Conclusion 
This systematic review and meta-analysis may help clinicians in their choices of prescribing an analgesic combination for acute post-operative pain control after lower third molar surgery. It was found in this systematic review Ibuprofen 400mg combined with oxycodone HCL 5mg has superior analgesic efficacy when compared to the other analgesic combinations included in this study.

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The Efficacy and Clinical Safety of Various Analgesic Combinations for Post-Operative Pain after Third Molar Surgery: A Systematic Review and Meta-Analysis.

Robust estimation of the location parameter α based on selected order statistics is considered. The distribution function is only known to belong to a subset of a set D of distributions consisting of Tukey's lambda family of symmetric distributions with the inverse distribution function of the form α + β/γ) [λγ – (1 – λ)γ], 0 ≤ λ ≤ 1, and the normal, Cauchy and double exponential distributions. The scale parameter β can be unknown. In the set D, distributions with tail length varying from short to extremely long, when the shape parameter γ varies, are included. The asymptotically best linear estimate (ABLE) based on k (k = 2(1)5) optimally chosen symmetrical sample quantiles is considered. It can be used as a robust estimate and is shown to compete favorably with optimally trimmed and Winsorized means, in the sense of giving a higher guaranteed relative asymptotic efficiency (GRAE) for subsets of D. Tables are provided so that the robust k-ABLE giving the highest GRAE for any subset of D can easily be obt...

Robust Estimation of Location Using Optimally Chosen Sample Quantiles

Statistical considerations are discussed for the application of alternative methods to a clinical trial involving repeated ordinal ratings and multiple dosage levels of active drugs. Analyses included summary measures traditionally employed in studies of acute pain: sum of pain intensity differences from baseline, total pain relief, and total pain half gone. Estimators and confidence intervals of relative potency are developed for univariate and multivariate situations, using weighted least squares analysis with mean response and variances from Taylor series linearizations. The estimates from these methods are compared to those from traditional methods, such as ordinary least squares regression and Fieller's method for confidence intervals, as well as those from more recent developments, such as generalized estimating equations and sample survey data regression. A double-blind, two-center, randomized clinical trial of acute pain relief comparing placebo with two analgesics, each at two dosage levels, over...

Statistical evaluation of relationships between analgesic dose and ordered ratings of pain relief over an eight-hour period.

SUMMARY In many situations it is useful to have a low-dimensional representation of the space of distributions. This paper gives one-, two- and three-dimensional representations which are particularly relevant to the study of robust estimation of location based on rank estimators. The distances are defined as functions of the asymptotic relative efficiency of the most efficient rank estimator for one distribution when used on data from another distribution. Values of these distance functions are computed for a large number of pairs

Representations of the space of distributions useful in robust estimation of location

Publisher Summary This chapter reviews that the measurement of pain depends on the subjective report of the person experiencing it, communicated through descriptions or behavior. Pain measurement scales are often interpreted in different ways by different researchers and clinicians, depending on the criteria they choose to apply. The chapter discusses that for pain therapeutic trials, improvement in pain intensity will most likely be the primary outcome. Some measure of the effect the pain is having on the other important aspects of life will be an important secondary outcome, measured on a pain interference scale, a quality of life scale, or separate scales for each of the individual components of either of these constructs. It reviews that the clinician and researcher should be confident that there are a number of excellent, reliable, well validated, and responsive pain measures that can be used. The chapter concludes that it is appropriate to measure pain as accurately as possible and on multiple dimensions, but then it is the job of the healthcare provider and pain researcher to interpret the clinical or scientific importance of the response and act accordingly.

Chapter 56 The measurement and analysis of pain symptoms.

Statistical problems in clinical trials frequently involve fitting regression lines when the underlying data are categorical or ordinal response variables Usually an ad hoc a priori quantification is used to assign values to these ordinal responses For pain intensity data collected in analgesic trials, the usual approach is to set none equal to 0, mild equal to 1, moderate equal to 2, and severe equal to 3 While this scheme has been generally accepted, on the basis that for similar clinical trials reasonably similar results are obtained by different investigators, concern exists that the distances between pain scores are probably not equal A method is presented for quantifying categorical responses so that the resulting scores maximize the simultaneous fit of the dose-response regression lines The optimal scores derived by this technique may then be used in a bioassay analysis to estimate the relative potency of 2 compounds As illustrative examples, this method was applied to data from 2 clinical trials and the results were compared to the usual method

An Analytic Approach To Quantifying Pain Scores

Asymptotic efficiencies of four classes of estimators of location are evaluated for a family of distributions consisting of t, lambda and contaminated normal densities. For the class of estimators derived from signed rank tests, maximin efficiencies between pairs of distributions in the family are computed using a formula of Gastwirth ( 1966 ). Asymptotic efficiencies are also evaluated for the scale dependent estimators of the form proposed by Hubcr ( 1964 ) and the efficiencies of procedures utilizing interquantiie ranges.are evaluated. Efficiencies of linear estimators such as trimmed means, BLUE's for the lambda family are computed for each density considered. Efficiencies of linear, polynomial and trigonometric approximations to BLUE weight functions are determined. Using the method of Birnbaum and Laska ( 1967 ) maximin efficiencies are computed using four linear or polynomial terms. On the basis of comparisons of these numerical results, suggestions for robust estimators are given

Kei Takeuchi

Papers

An Analytic Approach To Quantifying Pain Scores

Asymptotic efficiencies of estiamtors of location a comutational study