Induction of labour for predicted macrosomia: study protocol for the 'Big Baby' randomised controlled trial.

INTRODUCTION: Large-for-gestational age (LGA) fetuses have an increased risk of shoulder dystocia. This can lead to adverse neonatal outcomes and death. Early induction of labour in women with a fetus suspected to be macrosomic may mitigate the risk of shoulder dystocia. The Big Baby Trial aims to find if induction of labour at 38+0-38+4 weeks' gestation, in pregnancies with suspected LGA fetuses, reduces the incidence of shoulder dystocia. METHODS AND ANALYSIS: The Big Baby Trial is a multicentre, prospective, individually randomised controlled trial of induction of labour at 38+0 to 38+4 weeks' gestation vs standard care as per each hospital trust (median gestation of delivery 39+4) among women whose fetuses have an estimated fetal weight >90th customised centile according to ultrasound scan at 35+0 to 38+0 weeks' gestation. There is a parallel cohort study for women who decline randomisation because they opt for induction, expectant management or caesarean section. Up to 4000 women will be recruited and randomised to induction of labour or to standard care. The primary outcome is the incidence of shoulder dystocia; assessed by an independent expert group, blind to treatment allocation, from delivery records. Secondary outcomes include birth trauma, fractures, haemorrhage, caesarean section rate and length of inpatient stay. The main trial is ongoing, following an internal pilot study. A qualitative reporting, health economic evaluation and parallel process evaluation are included. ETHICS AND DISSEMINATION: The study received a favourable opinion from the South West-Cornwall and Plymouth Health Research Authority on 23/03/2018 (IRAS project ID 229163). Study results will be reported in the National Institute for Health Research journal library and published in an open access peer-reviewed journal. We will plan dissemination events for key stakeholders. TRIAL REGISTRATION NUMBER: ISRCTN18229892.

Development and testing of an opioid tapering self-management intervention for chronic pain: I-WOTCH.

OBJECTIVES: To describe the design, development and pilot of a multicomponent intervention aimed at supporting withdrawal of opioids for people with chronic non-malignant pain for future evaluation in the Improving the Wellbeing of people with Opioid Treated CHronic pain (I-WOTCH) randomised controlled trial. DESIGN: The I-WOTCH intervention draws on previous literature and collaboration with stakeholders (patient and public involvement). Intervention mapping and development activities of Behaviour Change Taxonomy are described. SETTING: The intervention development was conducted by a multidisciplinary team with clinical, academic and service user perspectives. The team had expertise in the development and testing of complex health behaviour interventions, opioid tapering and pain management in primary and secondary care, I.T programming, and software development-to develop an opioid tapering App. PARTICIPANTS: The I-WOTCH trial participants are adults (18 years and over) with chronic non-malignant pain using strong opioids for at least 3 months and on most days in the preceding month. OUTCOMES: A multicomponent self-management support package to help people using opioids for chronic non-malignant pain reduce opioid use. INTERVENTIONS AND RESULTS: Receiving information on the impact of long-term opioid use, and potential adverse effects were highlighted as important facilitators in making the decision to reduce opioids. Case studies of those who have successfully stopped taking opioids were also favoured as a facilitator to reduce opioid use. Barriers included the need for a 'trade-off to fill the deficit of the effect of the drug'. The final I-WOTCH intervention consists of an 8-10 week programme incorporating: education; problem-solving; motivation; group and one to one tailored planning; reflection and monitoring. A detailed facilitator manual was developed to promote consistent delivery of the intervention across the UK. CONCLUSIONS: We describe the development of an opioid reduction intervention package suitable for testing in the I-WOTCH randomised controlled trial. TRIAL REGISTRATION NUMBER: ISRCTN49470934.

Does the low prevalence affect the sample size of interventional clinical trials of rare diseases? An analysis of data from the aggregate analysis of clinicaltrials.gov.

BACKGROUND: Clinical trials are typically designed using the classical frequentist framework to constrain type I and II error rates. Sample sizes required in such designs typically range from hundreds to thousands of patients which can be challenging for rare diseases. It has been shown that rare disease trials have smaller sample sizes than non-rare disease trials. Indeed some orphan drugs were approved by the European Medicines Agency based on studies with as few as 12 patients. However, some studies supporting marketing authorisation included several hundred patients. In this work, we explore the relationship between disease prevalence and other factors and the size of interventional phase 2 and 3 rare disease trials conducted in the US and/or EU. We downloaded all clinical trials from Aggregate Analysis of ClinialTrials.gov (AACT) and identified rare disease trials by cross-referencing MeSH terms in AACT with the list from Orphadata. We examined the effects of prevalence and phase of study in a multiple linear regression model adjusting for other statistically significant trial characteristics. RESULTS: Of 186941 ClinicalTrials.gov trials only 1567 (0.8%) studied a single rare condition with prevalence information from Orphadata. There were 19 (1.2%) trials studying disease with prevalence <1/1,000,000, 126 (8.0%) trials with 1-9/1,000,000, 791 (50.5%) trials with 1-9/100,000 and 631 (40.3%) trials with 1-5/10,000. Of the 1567 trials, 1160 (74%) were phase 2 trials. The fitted mean sample size for the rarest disease (prevalence <1/1,000,000) in phase 2 trials was the lowest (mean, 15.7; 95% CI, 8.7-28.1) but were similar across all the other prevalence classes; mean, 26.2 (16.1-42.6), 33.8 (22.1-51.7) and 35.6 (23.3-54.3) for prevalence 1-9/1,000,000, 1-9/100,000 and 1-5/10,000, respectively. Fitted mean size of phase 3 trials of rarer diseases, <1/1,000,000 (19.2, 6.9-53.2) and 1-9/1,000,000 (33.1, 18.6-58.9), were similar to those in phase 2 but were statistically significant lower than the slightly less rare diseases, 1-9/100,000 (75.3, 48.2-117.6) and 1-5/10,000 (77.7, 49.6-121.8), trials. CONCLUSIONS: We found that prevalence was associated with the size of phase 3 trials with trials of rarer diseases noticeably smaller than the less rare diseases trials where phase 3 rarer disease (prevalence <1/100,000) trials were more similar in size to those for phase 2 but were larger than those for phase 2 in the less rare disease (prevalence ≥1/100,000) trials.