Comparing the effectiveness profile of pharmacological interventions used for orthodontic pain relief: an arm-based multilevel network meta-analysis of longitudinal data

Sandhu, Satpal S; Piepho, Hans‐Peter; Khehra, Harpreet S

doi:10.1093/ejo/cjw088

Cited by 9 publications

(11 citation statements)

References 33 publications

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“…While all of these modifications work to reduce bias, and also help understanding the bias problem associated with ML, they are more tedious to implement with standard software. Also, they would be cumbersome to extend to more complex models with several random effects . Penalized quasi‐likelihood/RSPL and h‐likelihood are much simpler to implement with existing software, also for more complex models, and so will probably be given preference in practical application.…”

Section: Discussionmentioning

confidence: 99%

“…Also, they would be cumbersome to extend to more complex models with several random effects. 40,41 Penalized quasi-likelihood/ RSPL and h-likelihood are much simpler to implement with existing software, also for more complex models, and so will probably be given preference in practical application. Further simulation studies comparing the most promising methods (PQL/RSPL and h-likelihood, REML-type modifications of ML) would certainly be warranted, covering diverse scenarios with more complex networks, larger heterogeneity of binomial sample sizes (n ij ) and smaller variance for heterogeneity.…”

Section: Discussionmentioning

confidence: 99%

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Estimating the variance for heterogeneity in arm‐based network meta‐analysis

Piepho

Madden

Roger

et al. 2018

Pharmaceutical Statistics

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Network meta-analysis can be implemented by using arm-based or contrast-based models. Here we focus on arm-based models and fit them using generalized linear mixed model procedures. Full maximum likelihood (ML) estimation leads to biased trial-by-treatment interaction variance estimates for heterogeneity. Thus, our objective is to investigate alternative approaches to variance estimation that reduce bias compared with full ML. Specifically, we use penalized quasi-likelihood/pseudo-likelihood and hierarchical (h) likelihood approaches. In addition, we consider a novel model modification that yields estimators akin to the residual maximum likelihood estimator for linear mixed models. The proposed methods are compared by simulation, and 2 real datasets are used for illustration. Simulations show that penalized quasi-likelihood/pseudo-likelihood and h-likelihood reduce bias and yield satisfactory coverage rates. Sum-to-zero restriction and baseline contrasts for random trial-by-treatment interaction effects, as well as a residual ML-like adjustment, also reduce bias compared with an unconstrained model when ML is used, but coverage rates are not quite as good. Penalized quasi-likelihood/pseudo-likelihood and h-likelihood are therefore recommended.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Estimating the variance for heterogeneity in arm‐based network meta‐analysis

Piepho

Madden

Roger

et al. 2018

Pharmaceutical Statistics

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“…These results are in agreement with some previous studies. [14][15][16][17]28 Eslamian et al 14 evaluated the effectiveness of 5% naproxen gel administered every 8 hours for 3 days on pain management related to elastic separators in a split-mouth study. They concluded that naproxen gel significantly reduced pain scores assessed by VAS at every time point from 1 hour to 7 days.…”

Section: Discussionmentioning

confidence: 99%

“…A recent systematic review reported that naproxen has a significant effect in OTM pain relieve at 6, 12, and 24 hours. 28 The cited review also concluded that the timing of administration could significantly influence the effectiveness of naproxen.…”

Section: Discussionmentioning

confidence: 99%

The effect of naproxen patches on relieving orthodontic pain by evaluation of VAS and IL-1β inflammatory factor: a split-mouth study

Eslamian

Torshabi

Motamedian

et al. 2019

Dental Press J. Orthod.

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Introduction: Pain related to orthodontic tooth movement is common and cause dissatisfaction and discomfort. Objective: The present study aimed to compare the efficacy of naproxen patches in pain control during orthodontic tooth separation, by means of visual analogue scale (VAS) and interleukin 1β (IL-1β) levels in gingival crevicular fluid (GCF). Methods: In this split-mouth triple-blind clinical trial, with 40 patients following separation, 5% naproxen or placebo patches were randomly placed on the upper right or left first molars every 8 hours. Pain intensity scores were determined after 2 and 6 hours, sleep time, 24 hours, days 2, 3 and 7 by the patients using a 100-mm VAS ruler. IL-1β levels in GCF were evaluated by ELISA at baseline, 1 and 24 hours and 7 days. Paired samples t-tests and two-way repeated measures ANOVA analysis of variance with a significance level of 0.05 were applied. Results: A total number of 30 patients (13 males and 17 females) finished the trial. Significant differences were found in pain scores (p< 0.0001) and IL-1β levels (p= 0.047) between naproxen and placebo groups. Lower pain scores were reported for the patients using naproxen patches at all time points, except 1 hour after separation. IL-1β levels were lower for the patients using naproxen patches only 1 hour after separation (p= 0.047). The peak of pain scores and IL-1β levels were calculated at 24 hours. Conclusion: In the light of VAS scores and IL-1β levels, naproxen patches reduced the pain caused by separator placement.

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“…The traditional approach of analgesic administration at regular intervals does not take into account the timedependent variations in pain intensity and the pharmacokinetics of analgesics. In a recent network meta-analyses, we found that it is important to take into account administration timing as well as the pharmacokinetics (such as plasma half-life) of analgesics while evaluating their effectiveness 16,17 , as the administrative timing has a direct influence on the effectiveness profile. 17 This paper explores diurnal variation in orthodontic pain perception utilizing intensive longitudinal data (ILD) obtained from an earlier published high quality randomized controlled trial (RCT).…”

Section: Introductionmentioning

confidence: 99%

Diurnal variation in orthodontic pain: Clinical implications and pharmacological management

Sandhu

Leckie

2018

Seminars in Orthodontics

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Pain is a bio-physiological phenomenon characterized by a circadian rhythm. A better understanding of diurnal variability in orthodontic pain perception would not only enhance our knowledge about how orthodontic pain intensity fluctuates over the 24-h day, but it also has great potential to improve the clinical management of orthodontic pain. Since the administration timing of pharmacological interventions has a direct influence on their effectiveness, a sound knowledge of the timing of peak pain intensity would allow clinicians to better coordinate the administration timing of analgesics. The objective of this study was to explore and quantify the diurnal variation in orthodontic pain over a period of seven days following initial arch wires placement. A multilevel linear spline model was used for secondary data analysis. Data were obtained from an earlier published high quality randomized controlled trial involving 85 participants (42 males and 43 females; mean age 14.1 years and SD 2.0). Results showed significant diurnal variability in pain intensity during the first two days of force application for both sexes. However, females showed significantly greater diurnal variation in the pain than males. Clinical and research implications of observed diurnal variability in orthodontic pain perception are discussed.

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Comparing the effectiveness profile of pharmacological interventions used for orthodontic pain relief: an arm-based multilevel network meta-analysis of longitudinal data

Cited by 9 publications

References 33 publications

Estimating the variance for heterogeneity in arm‐based network meta‐analysis

Estimating the variance for heterogeneity in arm‐based network meta‐analysis

The effect of naproxen patches on relieving orthodontic pain by evaluation of VAS and IL-1β inflammatory factor: a split-mouth study

Diurnal variation in orthodontic pain: Clinical implications and pharmacological management

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