Efficiency of the cross‐over design: an empirical estimation

Garcia-Esteban, Raquel; Benet, Marta; Arnau, Catalina; Cobo, Erik

doi:10.1002/sim.2072

Cited by 36 publications

(28 citation statements)

References 52 publications

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“…Hence good sensitivity of a model is obtained by combining a pain mechanism potently affected by opioids (large effect size or signal), and using a pain assessment that is reliable producing data with modest variance (noise). In general parallel studies give a weaker statistical power than a cross-over design, demanding larger sample sizes [127]. Furthermore, pain measures that only have a small dynamic range allow only a limited sensitivity for detecting analgesic effects.…”

Section: Methodology and Trial Designmentioning

confidence: 99%

Assessing analgesic actions of opioids by experimental pain models in healthy volunteers – an updated review

Staahl

Olesen

Andresen

et al. 2009

Brit J Clinical Pharma

113

131

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AIMExperimental pain models may help to evaluate the mechanisms of action of analgesics and target the clinical indications for their use. This review addresses how the efficacy of opioids can be assessed in human volunteers using experimental pain models. The drawback with the different study designs is also discussed. METHODA literature search was completed for randomized controlled studies which included human experimental pain models, healthy volunteers and opioids. RESULTSOpioids with a strong affinity for the m-opioid receptor decreased the sensation in a variety of experimental pain modalities, but strong tonic pain was attenuated more than short lasting pain and non-painful sensations. The effects of opioids with weaker affinity for the m-opioid receptor were detected by a more narrow range of pain models, and the assessment methods needed to be more sensitive. CONCLUSIONThe way the pain is induced, assessed and summarized is very important for the sensitivity of the pain models. This review gives an overview of how different opioids perform in experimental pain models. Generally experimental pain models need to be designed with careful consideration of pharmacological mechanisms and pharmacokinetics of analgesics. This knowledge can aid the decisions needed to be taken when designing experimental pain studies for compounds entering phase 1 clinical trials.

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Section: Methodology and Trial Designmentioning

confidence: 99%

Assessing analgesic actions of opioids by experimental pain models in healthy volunteers – an updated review

Staahl

Olesen

Andresen

et al. 2009

Brit J Clinical Pharma

113

131

View full text Add to dashboard Cite

show abstract

“…In general, parallel studies give a weaker statistical power than a cross-over design, demanding larger sample sizes. [15] In case of cross-over designed studies, it is important that the investigator is the same in all pain assessments, since gender and appearance of the investigator can influence the pain rating of the volunteers. [16]…”

Section: Discussionmentioning

confidence: 99%

A simple thermal pain model for the evaluation of analgesic activity in healthy subjects

Khambam

Naidu

Rani

et al. 2012

J Anaesthesiol Clin Pharmacol

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Objective:Assessment of the analgesic effect of an agent in an experimental pain model permits a level of control not possible in a clinical pain setting and is an ideal approach for evaluation of analgesic drugs. The aim of the present study was to establish a simple and reliable method of producing experimental pain, which can be used for screening of various analgesic agents.Materials and Methods:The standardized method was followed in all cases, by recording thermal pain threshold in seconds in 24 healthy volunteers using hot air source at two different speeds, which is equipped in an acrylic-made chamber adjustable to three different levels. Reproducibility of the test procedure was evaluated by recording the thermal threshold parameter by a single observer on two sessions (interday reproducibility) and second observer on one session (interobserver reproducibility) separately. Validity of model was further tested by evaluating the analgesic effect of tramadol on 12 healthy volunteers.Results:Thermal pain model was found to produce low variability with coefficient of variation (CV) less than 10%. Interobserver and interday reproducibility were very good, as shown by Bland–Altman plot, with most of the values within ± 2SD. There was a significant increase in pain threshold time with use of tramadol as compared to placebo which was statistically significant (P < 0.05).Conclusion:The newly developed pain model offers a stable and sensitive method for the early assessment of analgesic activity.

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“…We are aware of several conditions, such as Alzheimer's disease, hypercholesteremia, hypertension, and asthma where a body of cross-over studies may exist [9,11,17,20,21]. Here, considering the trials as a group might provide information about carry-over that could be useful either in interpreting existing studies, or planning new studies.…”

Section: Introductionmentioning

confidence: 96%

“…p¡0:05). For example, Garcia and colleagues [9] recently reported that only 45 per cent of cross-over studies published in leading medical journals between 2000 and 2003 provided estimates for the e ect size and its standard error. Additionally we can combine information from di erent types of studies using the information in the p-values.…”

Section: Introductionmentioning

confidence: 97%

“…To achieve the same endpoint, cross-over designs often require substantially fewer patients than a parallel group design, where each subject receives only a single treatment [1,2,8,9]. Moreover cross-over designs can be attractive to patients because each patient is guaranteed to receive both the experimental and standard (or placebo) treatment.…”

Section: Introductionmentioning

confidence: 98%

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Power to detect clinically relevant carry-over in a series of cross-over studies

Putt

2006

Statist. Med.

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The potential for carry-over effects is an important consideration in the design of any cross-over study, and can cause an investigator to abandon the design altogether. In cross-over studies, carry-over is the lingering effect of a treatment into the subsequent period. Carry-over effects are differences in the extent of the carry-over between the treatments under consideration. It is well known that the test for carry-over effects in individual studies has low power. Empirical evidence of carry-over effects, or the absence of carry-over effects, could be useful for investigators considering the design. Here we develop methods for expressing the power to detect carry-over as a function of the power to detect a clinically relevant treatment effect. Our results suggest that for two-treatment, two-period cross-over studies the power to detect clinically relevant carry-over effects is often less than 15 per cent, and the number of studies needed to differentiate this effect from the type I error rate of 10 per cent is prohibitive. For the three-treatment three-period cross-over design, the power to detect carry-over effects was larger than for the two-period study, but still approached the type I error rate in a number of cases. Unequivocal conclusions about the absence of carry-over effects based on collections of hypothesis tests appear unlikely. Similar findings are presented for bioequivalence studies. For bioequivalence studies, small carry-over effects (e.g. 12.5 per cent of the treatment effect) can seriously inflate the type I error rate, particularly when the power to detect equivalence is high.

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Efficiency of the cross‐over design: an empirical estimation

Cited by 36 publications

References 52 publications

Assessing analgesic actions of opioids by experimental pain models in healthy volunteers – an updated review

Assessing analgesic actions of opioids by experimental pain models in healthy volunteers – an updated review

A simple thermal pain model for the evaluation of analgesic activity in healthy subjects

Power to detect clinically relevant carry-over in a series of cross-over studies

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