Acupuncture treatment for pain: systematic review of randomised clinical trials with acupuncture, placebo acupuncture, and no acupuncture groups

Objectives To study the analgesic effect of acupuncture and placebo acupuncture and to explore whether the type of the placebo acupuncture is associated with the estimated effect of acupuncture

Discrepancies in sample size calculations and data analyses reported in randomised trials: comparison of publications with protocols

Objective To evaluate how often sample size calculations and methods of statistical analysis are pre-specified or changed in randomised trials

Empirical evidence of study design biases in randomized trials:Systematic review of meta-epidemiological studies

To synthesise evidence on the average bias and heterogeneity associated with reported methodological features of randomized trials.Systematic review of meta-epidemiological studies.We retrieved eligible studies included in a recent AHRQ-EPC review on this topic (latest search September 2012), and searched Ovid MEDLINE and Ovid EMBASE for studies indexed from Jan 2012-May 2015. Data were extracted by one author and verified by another. We combined estimates of average bias (e.g. ratio of odds ratios (ROR) or difference in standardised mean differences (dSMD)) in meta-analyses using the random-effects model. Analyses were stratified by type of outcome ("mortality" versus "other objective" versus "subjective"). Direction of effect was standardised so that ROR < 1 and dSMD < 0 denotes a larger intervention effect estimate in trials with an inadequate or unclear (versus adequate) characteristic.We included 24 studies. The available evidence suggests that intervention effect estimates may be exaggerated in trials with inadequate/unclear (versus adequate) sequence generation (ROR 0.93, 95% CI 0.86 to 0.99; 7 studies) and allocation concealment (ROR 0.90, 95% CI 0.84 to 0.97; 7 studies). For these characteristics, the average bias appeared to be larger in trials of subjective outcomes compared with other objective outcomes. Also, intervention effects for subjective outcomes appear to be exaggerated in trials with lack of/unclear blinding of participants (versus blinding) (dSMD -0.37, 95% CI -0.77 to 0.04; 2 studies), lack of/unclear blinding of outcome assessors (ROR 0.64, 95% CI 0.43 to 0.96; 1 study) and lack of/unclear double blinding (ROR 0.77, 95% CI 0.61 to 0.93; 1 study). The influence of other characteristics (e.g. unblinded trial personnel, attrition) is unclear.Certain characteristics of randomized trials may exaggerate intervention effect estimates. The average bias appears to be greatest in trials of subjective outcomes. More research on several characteristics, particularly attrition and selective reporting, is needed

Fortolkning af resultater fra randomiserede kliniske forsøg med komplementære og alternative behandlinger

I denne artikel diskuterer vi en række centrale problemer, der kan opstå i forbindelse med fortolkning af resultater fra randomiserede kliniske forsøg med komplementære og alternative behandlinger. Det drejer sig dels om forhold ved design og udførelsen af forsøg, og dels hvilken rolle forhåndstiltro, herunder baggrundsteoriens plausibilitet, spiller for fortolkning af resultaterne. Vi argumenterer for, at der er god grund til at være skeptisk i vurderingen af såvel komplementære og alternative behandlinger som konventionelle behandlinger, når forsøgsdesignet og udførelsen har væsentlige mangler, eller hvis behandlingen er baseret på en uplausibel teori

Evaluation of the Cochrane tool for assessing risk of bias in randomized clinical trials:Overview of published comments and analysis of user practice in Cochrane and non-Cochrane reviews

Appendices - Evaluation of the Cochrane tool for assessing risk of bias in randomized clinical trials. (DOCX 229 kb

Ghost Authorship in Industry-Initiated Randomised Trials

BACKGROUND: Ghost authorship, the failure to name, as an author, an individual who has made substantial contributions to an article, may result in lack of accountability. The prevalence and nature of ghost authorship in industry-initiated randomised trials is not known. METHODS AND FINDINGS: We conducted a cohort study comparing protocols and corresponding publications for industry-initiated trials approved by the Scientific-Ethical Committees for Copenhagen and Frederiksberg in 1994–1995. We defined ghost authorship as present if individuals who wrote the trial protocol, performed the statistical analyses, or wrote the manuscript, were not listed as authors of the publication, or as members of a study group or writing committee, or in an acknowledgment. We identified 44 industry-initiated trials. We did not find any trial protocol or publication that stated explicitly that the clinical study report or the manuscript was to be written or was written by the clinical investigators, and none of the protocols stated that clinical investigators were to be involved with data analysis. We found evidence of ghost authorship for 33 trials (75%; 95% confidence interval 60%–87%). The prevalence of ghost authorship was increased to 91% (40 of 44 articles; 95% confidence interval 78%–98%) when we included cases where a person qualifying for authorship was acknowledged rather than appearing as an author. In 31 trials, the ghost authors we identified were statisticians. It is likely that we have overlooked some ghost authors, as we had very limited information to identify the possible omission of other individuals who would have qualified as authors. CONCLUSIONS: Ghost authorship in industry-initiated trials is very common. Its prevalence could be considerably reduced, and transparency improved, if existing guidelines were followed, and if protocols were publicly available

Pain relief that matters to patients: systematic review of empirical studies assessing the minimum clinically important difference in acute pain

BACKGROUND: The minimum clinically important difference (MCID) is used to interpret the clinical relevance of results reported by trials and meta-analyses as well as to plan sample sizes in new studies. However, there is a lack of consensus about the size of MCID in acute pain, which is a core symptom affecting patients across many clinical conditions. METHODS: We identified and systematically reviewed empirical studies of MCID in acute pain. We searched PubMed, EMBASE and Cochrane Library, and included prospective studies determining MCID using a patient-reported anchor and a one-dimensional pain scale (e.g. 100 mm visual analogue scale). We summarised results and explored reasons for heterogeneity applying meta-regression, subgroup analyses and individual patient data meta-analyses. RESULTS: We included 37 studies (8479 patients). Thirty-five studies used a mean change approach, i.e. MCID was assessed as the mean difference in pain score among patients who reported a minimum degree of improvement, while seven studies used a threshold approach, i.e. MCID was assessed as the threshold in pain reduction associated with the best accuracy (sensitivity and specificity) for identifying improved patients. Meta-analyses found considerable heterogeneity between studies (absolute MCID: I(2) = 93%, relative MCID: I(2) = 75%) and results were therefore presented qualitatively, while analyses focused on exploring reasons for heterogeneity. The reported absolute MCID values ranged widely from 8 to 40 mm (standardised to a 100 mm scale) and the relative MCID values from 13% to 85%. From analyses of individual patient data (seven studies, 918 patients), we found baseline pain strongly associated with absolute, but not relative, MCID as patients with higher baseline pain needed larger pain reduction to perceive relief. Subgroup analyses showed that the definition of improved patients (one or several categories improvement or meaningful change) and the design of studies (single or multiple measurements) also influenced MCID values. CONCLUSIONS: The MCID in acute pain varied greatly between studies and was influenced by baseline pain, definitions of improved patients and study design. MCID is context-specific and potentially misguiding if determined, applied or interpreted inappropriately. Explicit and conscientious reflections on the choice of a reference value are required when using MCID to classify research results as clinically important or trivial