Publications
101 results found
Tull T, Cro S, Barker J, et al., 2021, Anakinra for palmoplantar pustulosis: results from a randomized, double-blind, multicentre, two staged, adaptive placebo controlled trial (APRICOT), Publisher: ELSEVIER SCIENCE INC, Pages: S157-S157, ISSN: 0022-202X
Atkinson A, Cro S, Carpenter JR, et al., 2021, Information anchored reference‐based sensitivity analysis for truncated normal data with application to survival analysis, Statistica Neerlandica, Vol: 75, Pages: 500-523, ISSN: 0039-0402
The primary analysis of time-to-event data typically makes the censoring at random assumption, that is, that—conditional on covariates in the model—the distribution of event times is the same, whether they are observed or unobserved. In such cases, we need to explore the robustness of inference to more pragmatic assumptions about patients post-censoring in sensitivity analyses. Reference-based multiple imputation, which avoids analysts explicitly specifying the parameters of the unobserved data distribution, has proved attractive to researchers. Building on results for longitudinal continuous data, we show that inference using a Tobit regression imputation model for reference-based sensitivity analysis with right censored log normal data is information anchored, meaning the proportion of information lost due to missing data under the primary analysis is held constant across the sensitivity analyses. We illustrate our theoretical results using simulation and a clinical trial case study.
Tan P-T, Cro S, Van Vogt E, et al., 2021, A review of the use of controlled multiple imputation in randomised controlled trials with missing outcome data, BMC Medical Research Methodology, Vol: 21, ISSN: 1471-2288
Background:Missing data are common in randomised controlled trials (RCTs) and can bias results if not handled appropriately. A statistically valid analysis under the primary missing-data assumptions should be conducted, followed by sensitivity analysis under alternative justified assumptions to assess the robustness of results. Controlled Multiple Imputation (MI) procedures, including delta-based and reference-based approaches, have been developed for analysis under missing-not-at-random assumptions. However, it is unclear how often these methods are used, how they are reported, and what their impact is on trial results. This review evaluates the current use and reporting of MI and controlled MI in RCTs.Methods:A targeted review of phase II-IV RCTs (non-cluster randomised) published in two leading general medical journals (The Lancet and New England Journal of Medicine) between January 2014 and December 2019 using MI. Data was extracted on imputation methods, analysis status, and reporting of results. Results of primary and sensitivity analyses for trials using controlled MI analyses were compared.Results:A total of 118 RCTs (9% of published RCTs) used some form of MI. MI under missing-at-random was used in 110 trials; this was for primary analysis in 43/118 (36%), and in sensitivity analysis for 70/118 (59%) (3 used in both). Sixteen studies performed controlled MI (1.3% of published RCTs), either with a delta-based (n = 9) or reference-based approach (n = 7). Controlled MI was mostly used in sensitivity analysis (n = 14/16). Two trials used controlled MI for primary analysis, including one reporting no sensitivity analysis whilst the other reported similar results without imputation. Of the 14 trials using controlled MI in sensitivity analysis, 12 yielded comparable results to the primary analysis whereas 2 demonstrated contradicting results. Only 5/110 (5%) trials using missing-at-random MI and 5/16 (31%) trials using con
Kelleher MM, Cro S, Van Vogt E, et al., 2021, Skincare interventions in infants for preventing eczema and food allergy: A cochrane systematic review and individual participant data meta-analysis, Clinical and Experimental Allergy, Vol: 51, Pages: 402-418, ISSN: 0954-7894
ObjectiveEczema and food allergy start in infancy and have shared genetic risk factors that affect skin barrier. We aimed to evaluate whether skincare interventions can prevent eczema or food allergy.DesignA prospectively planned individual participant data meta‐analysis was carried out within a Cochrane systematic review to determine whether skincare interventions in term infants prevent eczema or food allergy.Data sourcesCochrane Skin Specialised Register, CENTRAL, MEDLINE, Embase and trial registries to July 2020.Eligibility criteria for selected studiesIncluded studies were randomized controlled trials of infants <1 year with healthy skin comparing a skin intervention with a control, for prevention of eczema and food allergy outcomes between 1 and 3 years.ResultsOf the 33 identified trials, 17 trials (5823 participants) had relevant outcome data and 10 (5154 participants) contributed to IPD meta‐analysis. Three of seven trials contributing to primary eczema analysis were at low risk of bias, and the single trial contributing to primary food allergy analysis was at high risk of bias. Interventions were mainly emollients, applied for the first 3–12 months. Skincare interventions probably do not change risk of eczema by age 1–3 years (RR 1.03, 95% CI 0.81, 1.31; I2=41%; moderate certainty; 3075 participants, 7 trials). Sensitivity analysis found heterogeneity was explained by increased eczema in a trial of daily bathing as part of the intervention. It is unclear whether skincare interventions increase risk of food allergy by age 1–3 years (RR 2.53, 95% CI 0.99 to 6.47; very low certainty; 996 participants, 1 trial), but they probably increase risk of local skin infections (RR 1.34, 95% CI 1.02, 1.77; I2=0%; moderate certainty; 2728 participants, 6 trials).ConclusionRegular emollients during infancy probably do not prevent eczema and probably increase local skin infections.
Kelleher MM, Cro S, Cornelius V, et al., 2021, Skin care interventions in infants for preventing eczema and food allergy., Cochrane Database of Systematic Reviews, Vol: 2021, Pages: 1-165, ISSN: 1469-493X
BACKGROUND: Eczema and food allergy are common health conditions that usually begin in early childhood and often occur together in the same people. They can be associated with an impaired skin barrier in early infancy. It is unclear whether trying to prevent or reverse an impaired skin barrier soon after birth is effective in preventing eczema or food allergy. OBJECTIVES: Primary objective To assess effects of skin care interventions, such as emollients, for primary prevention of eczema and food allergy in infants Secondary objective To identify features of study populations such as age, hereditary risk, and adherence to interventions that are associated with the greatest treatment benefit or harm for both eczema and food allergy. SEARCH METHODS: We searched the following databases up to July 2020: Cochrane Skin Specialised Register, CENTRAL, MEDLINE, and Embase. We searched two trials registers and checked reference lists of included studies and relevant systematic reviews for further references to relevant randomised controlled trials (RCTs). We contacted field experts to identify planned trials and to seek information about unpublished or incomplete trials. SELECTION CRITERIA: RCTs of skin care interventions that could potentially enhance skin barrier function, reduce dryness, or reduce subclinical inflammation in healthy term (> 37 weeks) infants (0 to 12 months) without pre-existing diagnosis of eczema, food allergy, or other skin condition were included. Comparison was standard care in the locality or no treatment. Types of skin care interventions included moisturisers/emollients; bathing products; advice regarding reducing soap exposure and bathing frequency; and use of water softeners. No minimum follow-up was required. DATA COLLECTION AND ANALYSIS: This is a prospective individual participant data (IPD) meta-analysis. We used standard Cochrane methodological procedures, and primary ana
Cornelius V, Cro S, Phillips R, 2020, Advantages of visualisations to evaluate and communicate adverse event information in randomised controlled trials, Trials, Vol: 21, ISSN: 1745-6215
BackgroundRandomised controlled trials (RCTs) provide valuable information and inform the development of harm profiles of new treatments. Harms are typically assessed through the collection of adverse events (AEs). Despite AEs being routine outcomes collected in trials, analysis and reporting of AEs in journal articles are continually shown to be suboptimal. One key challenge is the large volume of AEs, which can make evaluation and communication problematic. Prominent practice is to report frequency tables of AEs by arm. Visual displays offer an effective solution to assess and communicate complex information; however, they are rarely used and there is a lack of practical guidance on what and how to visually display complex AE data.MethodsIn this article, we demonstrate the use of two plots identified to be beneficial for wide use in RCTs, since both can display multiple AEs and are suitable to display point estimates for binary, count, or time-to-event AE data: the volcano and dot plots. We compare and contrast the use of data visualisations against traditional frequency table reporting, using published AE information in two placebo-controlled trials, of remdesivir for COVID-19 and GDNF for Parkinson disease. We introduce statistical programmes for implementation in Stata.Results/case studyVisualisations of AEs in the COVID-19 trial communicated a risk profile for remdesivir which differed from the main message in the published authors’ conclusion. In the Parkinson’s disease trial of GDNF, the visualisation provided immediate communication of harm signals, which had otherwise been contained within lengthy descriptive text and tables. Asymmetry in the volcano plot helped flag extreme events that were less obvious from review of the frequency table and dot plot. The dot plot allowed a more comprehensive representation by means of a more detailed summary.ConclusionsVisualisations can better support investigators to assimilate large volumes of data and ena
Kahan BC, Ahmad T, Forbes G, et al., 2020, Public availability and adherence to pre-specified statistical analysis approaches was low in published randomised trials., Journal of Clinical Epidemiology, Vol: 128, Pages: 29-34, ISSN: 0895-4356
OBJECTIVE: Pre-specification of statistical methods in clinical trial protocols and Statistical Analysis Plans (SAPs) can help to deter bias from p-hacking, but is only effective if the pre-specified approach is made available. STUDY DESIGN AND SETTING: For 100 randomised trials published in 2018 and indexed in PubMed we evaluated how often a pre-specified statistical analysis approach for the trial's primary outcome was publicly available. For each trial with an available pre-specified analysis, we compared this to the trial publication to identify whether there were unexplained discrepancies. RESULTS: Only 11 of 100 trials (11%) had a publicly available pre-specified analysis approach for their primary outcome; this document was dated before recruitment began for only one trial. Of the 11 trials with an available pre-specified analysis approach, 10 (91%) had one or more unexplained discrepancies. Only 4/100 trials (4%) stated that the statistician was blinded until the SAP was signed off and only 10/100 (10%) stated the statistician was blinded until the database was locked. CONCLUSION: For most published trials, there is insufficient information available to determine whether results may be subject to p-hacking. Where information was available, there were often unexplained discrepancies between the pre-specified and final analysis methods.
Muller P, Skene SS, Chowdhury K, et al., 2020, A randomised, multi-centre trial of total ankle replacement versus ankle arthrodesis in the treatment of patients with end stage ankle osteoarthritis (TARVA): statistical analysis plan, Trials, Vol: 21, Pages: 1-9, ISSN: 1745-6215
BackgroundThe total ankle replacement versus ankle arthrodesis (TARVA) trial aims to determine which surgical procedure confers the greatest improvement in pain-free function for patients with end-stage ankle osteoarthritis. Both procedures are effective but there has not yet been a direct comparison to establish which is superior. This article describes the statistical analysis plan for this trial as an update to the published protocol. It is written prior to the end of patient follow-up, while the outcome of the trial is still unknown.Design and methodsTARVA is a randomised, un-blinded, parallel group trial of total ankle replacement versus ankle arthrodesis. The primary outcome is the Manchester-Oxford Foot Questionnaire walking/standing domain score at 52 weeks post-surgery. Secondary outcomes include measures of pain, social interaction, physical function, quality of life, and range of motion. We describe in detail the statistical aspects of TARVA: the outcome measures, the sample size calculation, general analysis principles including treatment of missing data, the planned descriptive statistics and statistical models, and planned subgroup and sensitivity analyses.DiscussionThe TARVA statistical analysis will provide comprehensive and precise information on the relative effectiveness of the two treatments. The plan will be implemented in January 2020 when follow-up for the trial is completed.
Benzian-Olsson N, Dand N, Chaloner C, et al., 2020, Association of clinical and demographic factors with the severity of Palmoplantar Pustulosis, JAMA Dermatology, Vol: 156, Pages: 1216-1222, ISSN: 2168-6068
Importance Although palmoplantar pustulosis (PPP) can significantly impact quality of life, the factors underlying disease severity have not been studied.Objective To examine the factors associated with PPP severity.Design, Setting, and Participants An observational, cross-sectional study of 2 cohorts was conducted. A UK data set including 203 patients was obtained through the Anakinra in Pustular Psoriasis, Response in a Controlled Trial (2016-2019) and its sister research study Pustular Psoriasis, Elucidating Underlying Mechanisms (2016-2020). A Northern European cohort including 193 patients was independently ascertained by the European Rare and Severe Psoriasis Expert Network (2014-2017). Patients had been recruited in secondary or tertiary dermatology referral centers. All patients were of European descent. The PPP diagnosis was established by dermatologists, based on clinical examination and/or published consensus criteria. The present study was conducted from October 1, 2014, to March 15, 2020.Main Outcomes and Measures Demographic characteristics, comorbidities, smoking status, Palmoplantar Pustulosis Psoriasis Area Severity Index (PPPASI), measuring severity from 0 (no sign of disease) to 72 (very severe disease), or Physician Global Assessment (PGA), measuring severity as 0 (clear), 1 (almost clear), 2 (mild), 3 (moderate), and 4 (severe).Results Among the 203 UK patients (43 men [21%], 160 women [79%]; median age at onset, 48 [interquartile range (IQR), 38-59] years), the PPPASI was inversely correlated with age of onset (r = −0.18, P = .01). Similarly, in the 159 Northern European patients who were eligible for inclusion in this analysis (25 men [16%], 134 women [84%]; median age at onset, 45 [IQR, 34-53.3] years), the median age at onset was lower in individuals with a moderate to severe PGA score (41 years [IQR, 30.5-52 years]) compared with those with a clear to mild PGA score (46.5 years [IQR, 35-55 years]) (P&t
Kahan B, Morris TP, White IR, et al., 2020, Treatment estimands in clinical trials of patients hospitalised for COVID-19: ensuring trials ask the right questions, BMC Medicine, Vol: 18, ISSN: 1741-7015
When designing a clinical trial, explicitly defining the treatment estimands of interest (that which is to be estimated) can help to clarify trial objectives and ensure the questions being addressed by the trial are clinically meaningful. There are several challenges when defining estimands. Here, we discuss a number of these in the context of trials of treatments for patients hospitalised with COVID-19 and make suggestions for how estimands should be defined for key outcomes. We suggest that treatment effects should usually be measured as differences in proportions (or risk or odds ratios) for outcomes such as death and requirement for ventilation, and differences in means for outcomes such as the number of days ventilated. We further recommend that truncation due to death should be handled differently depending on whether a patient- or resource-focused perspective is taken; for the former, a composite approach should be used, while for the latter, a while-alive approach is preferred. Finally, we suggest that discontinuation of randomised treatment should be handled from a treatment policy perspective, where non-adherence is ignored in the analysis (i.e. intention to treat).
Kahan B, Forbes G, Cro S, 2020, How to design a pre-specified statistical analysis approach to limit p-hacking in clinical trials: the Pre-SPEC framework, BMC Medicine, Vol: 18, ISSN: 1741-7015
Results from clinical trials can be susceptible to bias if investigators choose their analysis approach after seeing trial data, as this can allow them to perform multiple analyses and then choose the method that provides the most favourable result (commonly referred to as ‘p-hacking’). Pre-specification of the planned analysis approach is essential to help reduce such bias, as it ensures analytical methods are chosen in advance of seeing the trial data. For this reason, guidelines such as SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) and ICH-E9 (International Conference for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use) require the statistical methods for a trial’s primary outcome be pre-specified in the trial protocol. However, pre-specification is only effective if done in a way that does not allow p-hacking. For example, investigators may pre-specify a certain statistical method such as multiple imputation, but give little detail on how it will be implemented. Because there are many different ways to perform multiple imputation, this approach to pre-specification is ineffective, as it still allows investigators to analyse the data in different ways before deciding on a final approach. In this article we describe a five-point framework (the Pre-SPEC framework) for designing a pre-specified analysis approach that does not allow p-hacking. This framework was designed based on the principles in the SPIRIT and ICH-E9 guidelines, and is intended to be used in conjunction with these guidelines to help investigators design the statistical analysis strategy for the trial’s primary outcome in the trial protocol.
Cro S, Morris TP, Kahan BC, et al., 2020, A four-step strategy for handling missing outcome data in randomised trials affected by a pandemic, BMC Medical Research Methodology, Vol: 20, ISSN: 1471-2288
BackgroundThe coronavirus pandemic (Covid-19) presents a variety of challenges for ongoing clinical trials, including an inevitably higher rate of missing outcome data, with new and non-standard reasons for missingness. International drug trial guidelines recommend trialists review plans for handling missing data in the conduct and statistical analysis, but clear recommendations are lacking.MethodsWe present a four-step strategy for handling missing outcome data in the analysis of randomised trials that are ongoing during a pandemic. We consider handling missing data arising due to (i) participant infection, (ii) treatment disruptions and (iii) loss to follow-up. We consider both settings where treatment effects for a ‘pandemic-free world’ and ‘world including a pandemic’ are of interest.ResultsIn any trial, investigators should; (1) Clarify the treatment estimand of interest with respect to the occurrence of the pandemic; (2) Establish what data are missing for the chosen estimand; (3) Perform primary analysis under the most plausible missing data assumptions followed by; (4) Sensitivity analysis under alternative plausible assumptions. To obtain an estimate of the treatment effect in a ‘pandemic-free world’, participant data that are clinically affected by the pandemic (directly due to infection or indirectly via treatment disruptions) are not relevant and can be set to missing. For primary analysis, a missing-at-random assumption that conditions on all observed data that are expected to be associated with both the outcome and missingness may be most plausible. For the treatment effect in the ‘world including a pandemic’, all participant data is relevant and should be included in the analysis. For primary analysis, a missing-at-random assumption – potentially incorporating a pandemic time-period indicator and participant infection status – or a missing-not-at-random assumption with a poorer response may b
Cro S, Morris TP, Kenward MG, et al., 2020, Sensitivity analysis for clinical trials with missing continuous outcome data using controlled multiple imputation: a practical guide, Statistics in Medicine, Vol: 39, Pages: 2815-2842, ISSN: 0277-6715
Missing data due to loss to follow‐up or intercurrent events are unintended, but unfortunately inevitable in clinical trials. Since the true values of missing data are never known, it is necessary to assess the impact of untestable and unavoidable assumptions about any unobserved data in sensitivity analysis. This tutorial provides an overview of controlled multiple imputation (MI) techniques and a practical guide to their use for sensitivity analysis of trials with missing continuous outcome data. These include δ ‐ and reference‐based MI procedures. In δ ‐based imputation, an offset term, δ , is typically added to the expected value of the missing data to assess the impact of unobserved participants having a worse or better response than those observed. Reference‐based imputation draws imputed values with some reference to observed data in other groups of the trial, typically in other treatment arms. We illustrate the accessibility of these methods using data from a pediatric eczema trial and a chronic headache trial and provide Stata code to facilitate adoption. We discuss issues surrounding the choice of δ in δ ‐based sensitivity analysis. We also review the debate on variance estimation within reference‐based analysis and justify the use of Rubin's variance estimator in this setting, since as we further elaborate on within, it provides information anchored inference.
Beaney T, Schutte AE, Stergiou GS, et al., 2020, May Measurement Month 2019 The Global Blood Pressure Screening Campaign of the International Society of Hypertension, Hypertension, Vol: 76, Pages: 333-341, ISSN: 0194-911X
Elevated blood pressure remains the single biggest risk factor contributing to the global burden of disease and mortality. May Measurement Month is an annual global screening campaign aiming to improve awareness of blood pressure at the individual and population level. Adults (≥18 years) recruited through opportunistic sampling were screened at sites in 92 countries during May 2019. Ideally, 3 blood pressure readings were measured for each participant, and data on lifestyle factors and comorbidities were collected. Hypertension was defined as a systolic blood pressure ≥140 mm Hg, or a diastolic blood pressure ≥90 mm Hg (mean of the second and third readings) or taking antihypertensive medication. When necessary, multiple imputation was used to estimate participants’ mean blood pressure. Mixed-effects models were used to evaluate associations between blood pressure and participant characteristics. Of 1 508 130 screenees 482 273 (32.0%) had never had a blood pressure measurement before and 513 337 (34.0%) had hypertension, of whom 58.7% were aware, and 54.7% were on antihypertensive medication. Of those on medication, 57.8% were controlled to <140/90 mm Hg, and 28.9% to <130/80 mm Hg. Of all those with hypertension, 31.7% were controlled to <140/90 mm Hg, and 350 825 (23.3%) participants had untreated or inadequately treated hypertension. Of those taking antihypertensive medication, half were taking only a single drug, and 25% reported using aspirin inappropriately. This survey is the largest ever synchronized and standardized contemporary compilation of global blood pressure data. This campaign is needed as a temporary substitute for systematic blood pressure screening in many countries worldwide.
Chis Ster AM, Cornelius V, Cro S, 2020, Current approaches to handling rescue medication in asthma and eczema randomized controlled trials are inadequate: a systematic review., Journal of Clinical Epidemiology, Vol: 125, Pages: 148-157, ISSN: 0895-4356
OBJECTIVES: The objective of this study was to examine how rescue medication is defined, reported, and accounted for in randomized controlled trials (RCTs) in eczema and asthma populations. STUDY DESIGN AND SETTING: This is a systematic review of phase II/III RCTs evaluating monoclonal antibodies for treating chronic eczema or asthma. A search of EMBASE, MEDLINE, and the Cochrane Central Register of Controlled Trials was conducted to identify eligible RCTs. RESULTS: Sixty published RCTs were identified, of which 60 (100%) allowed use of rescue medication but only 28 (47%) reported its use. Twenty-seven (45%) articles summarized rescue use by arm, with an average of 25% (95% CI (17%, 36%)) greater use in the placebo arm. Nine (15%) trials undertook an analysis that adjusted the primary treatment effect estimate for rescue medication use, but 8 of these used a suboptimal approach using single imputation, including 4 which used "last observation carried forward" after setting postrescue data to missing. CONCLUSION: Rescue medication use in eczema and asthma trials evaluating monoclonal antibodies is often permitted, but not routinely reported. There is evidence of imbalance in rescue use between arms, but few articles attempted to estimate a rescue-adjusted treatment effect. In trials that did, the methods used were suboptimal which could introduce bias.
Cro S, Forbes G, Johnson NA, et al., 2020, Evidence of unexplained discrepancies between planned and conducted statistical analyses: a review of randomized trials, BMC Medicine, Vol: 18, ISSN: 1741-7015
Evidence of unexplained discrepancies between planned and conducted statistical analyses: a review of randomised trials
Raad H, Cornelius V, Chan S, et al., 2020, An evaluation of inverse probability weighting using the propensity score for baseline covariate adjustment in smaller population randomised controlled trials with a continuous outcome, BMC Medical Research Methodology, Vol: 20, Pages: 1-12, ISSN: 1471-2288
BackgroundIt is important to estimate the treatment effect of interest accurately and precisely within the analysis of randomised controlled trials. One way to increase precision in the estimate and thus improve the power for randomised trials with continuous outcomes is through adjustment for pre-specified prognostic baseline covariates. Typically covariate adjustment is conducted using regression analysis, however recently, Inverse Probability of Treatment Weighting (IPTW) using the propensity score has been proposed as an alternative method. For a continuous outcome it has been shown that the IPTW estimator has the same large sample statistical properties as that obtained via analysis of covariance. However the performance of IPTW has not been explored for smaller population trials (< 100 participants), where precise estimation of the treatment effect has potential for greater impact than in larger samples.MethodsIn this paper we explore the performance of the baseline adjusted treatment effect estimated using IPTW in smaller population trial settings. To do so we present a simulation study including a number of different trial scenarios with sample sizes ranging from 40 to 200 and adjustment for up to 6 covariates. We also re-analyse a paediatric eczema trial that includes 60 children.ResultsIn the simulation study the performance of the IPTW variance estimator was sub-optimal with smaller sample sizes. The coverage of 95% CI’s was marginally below 95% for sample sizes < 150 and ≥ 100. For sample sizes < 100 the coverage of 95% CI’s was always significantly below 95% for all covariate settings. The minimum coverage obtained with IPTW was 89% with n = 40. In comparison, regression adjustment always resulted in 95% coverage. The analysis of the eczema trial confirmed discrepancies between the IPTW and regression estimators in a real life small population setting.ConclusionsThe IPTW variance e
Raglan M, Machin JT, Cro S, et al., 2020, Total ankle replacement: comparison of the outcomes of STAR and Mobility, Acta orthopaedica Belgica, Vol: 86, Pages: 109-114, ISSN: 0001-6462
Total Ankle Replacement is a recognised treatmentfor end-stage ankle arthritis and an alternative toarthrodesis. This study reviews a single centre seriesof prospectively collected outcome measures todetermine whether the Mobility performs better thanthe Scandinavian ankle replacement. The primaryoutcome measure was the survivorship. Secondaryoutcome measures consisted of complications andinternational scoring systems.147 Scandinavian and 162 Mobility ankle replacementswere reviewed at a mean follow up of 12.4 and 7.7years respectively. The revision rate, which includedliner exchange, component exchange or removal ofimplant was at 7 years 12.3% (18) for Scandinavianand 5.2% (8) for Mobility. The complication rate was16.5% (22) for Scandinavian compared to 9.9 % (15)for Mobility.The results of our unit compare favourably withprevious published studies. In this study the Mobilityhas been shown to have more favourable results at 7years compared to the Scandinavian.
Kelleher MM, Cro S, Cornelius V, et al., 2020, Skincare interventions in infants for preventing eczema and food allergy, Cochrane Database of Systematic Reviews, Vol: 2020
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:. Primary objective. To assess the effects of skincare interventions, such as emollients, for prevention of eczema and food allergy in infants. Secondary objectives. To ascertain whether active skincare interventions, commenced in early infancy, influence risk of developing eczema or food allergy To identify features of the study populations such as age, hereditary risk and adherence to the interventions, which are associated with the greatest treatment benefit or harm for both eczema and food allergy.
Cro S, Patel P, Barker J, et al., 2020, A randomised placebo controlled trial of anakinra for treating pustular psoriasis: statistical analysis plan for stage two of the APRICOT trial, Trials, Vol: 21, ISSN: 1745-6215
Background:Current treatment options for Palmoplantar Pustulosis (PPP), a debilitating chronic skin disease which affects the hands and feet, are limited. The Anakinra for Pustular psoriasis: Response in a Controlled Trial (APRICOT) aims to determine the efficacy of anakinra in the treatment of PPP. This article describes the statistical analysis plan for the final analysis of this two-staged trial, which was determined prior to unblinding and database lock. This is an update to the published protocol and stage one analysis plan.Methods:APRICOT is a randomised, double-blind, placebo-controlled trial of anakinra versus placebo, with two stages and an adaptive element. Stage one compared treatment arms to ensure proof-of-concept and determined the primary outcome for stage two of the trial. The primary outcome was selected to be the change in Palmoplantar Pustulosis Psoriasis Area and Severity Index (PPPASI) at 8 weeks. Secondary outcomes include other investigator-assessed efficacy measures of disease severity, participant-reported measures of efficacy and safety measures. This manuscript describes in detail the outcomes, sample size, general analysis principles, the pre-specified statistical analysis plan for each of the outcomes, the handling of missing outcome data and the planned sensitivity and supplementary analyses for the second stage of the APRICOT trial.Discussion:This statistical analysis plan was developed in compliance with international trial guidelines and is published to increase transparency of the trial analysis. The results of the trial analysis will indicate whether anakinra has a role in the treatment of PPP.Trial registration:ISCRTN, ISCRTN13127147. Registered on 1 August 2016. EudraCT Number 2015-003600-23. Registered on 1 April 2016.
Leurent B, Gomes M, Cro S, et al., 2020, Reference-based multiple imputation for missing data sensitivity analyses in trial-based cost-effectiveness analysis, Health Economics, Vol: 29, Pages: 171-184, ISSN: 1057-9230
Missing data are a common issue in cost‐effectiveness analysis (CEA) alongside randomised trials and are often addressed assuming the data are ‘missing at random’. However, this assumption is often questionable, and sensitivity analyses are required to assess the implications of departures from missing at random. Reference‐based multiple imputation provides an attractive approach for conducting such sensitivity analyses, because missing data assumptions are framed in an intuitive way by making reference to other trial arms. For example, a plausible not at random mechanism in a placebo‐controlled trial would be to assume that participants in the experimental arm who dropped out stop taking their treatment and have similar outcomes to those in the placebo arm.Drawing on the increasing use of this approach in other areas, this paper aims to extend and illustrate the reference‐based multiple imputation approach in CEA. It introduces the principles of reference‐based imputation and proposes an extension to the CEA context. The method is illustrated in the CEA of the CoBalT trial evaluating cognitive behavioural therapy for treatment‐resistant depression. Stata code is provided. We find that reference‐based multiple imputation provides a relevant and accessible framework for assessing the robustness of CEA conclusions to different missing data assumptions.
Chan S, Cornelius V, Cro S, et al., 2020, Treatment effect of omalizumab on severe pediatric atopic dermatitis: The ADAPT randomized clinical trial, JAMA Pediatrics, Vol: 174, Pages: 29-37, ISSN: 2168-6203
Importance: Systemic treatments for severe childhood atopic dermatitis have limited evidence and/or are unlicensed. Despite the efficacy of anti-IgE medication (omalizumab) in the treatment of atopy, no large randomized studies in childhood atopic dermatitis have been published. Objective: To determine the effectiveness of omalizumab in treating severe atopic dermatitis in children. Design, Setting, and Participants: The Atopic Dermatitis Anti-IgE Pediatric Trial (ADAPT) was a 24-week single-center, double-blind, placebo-controlled randomized clinical trial with a 24-week follow-up. Conducted from November 20, 2014, to August 31, 2017, at Guy's and St Thomas' Hospital NHS Foundation Trust and King's College London in the United Kingdom, this trial recruited participants after a screening visit. Eligible participants (n = 62) were aged 4 to 19 years and had severe eczema (with objective Scoring Atopic Dermatitis [SCORAD] index >40) that was unresponsive to optimum therapy. Statistical analysis was conducted using the intention-to-treat principle. Interventions: Subcutaneous omalizumab or placebo for 24 weeks. The drug manufacturer's dosing tables were used to determine the dosage based on total IgE (30-1500 IU/mL) and body weight (in kilograms) at randomization. Main Outcomes and Measures: Objective SCORAD index after 24 weeks of treatment. Results: In total, 62 children (mean [SD] age, 10.3 [4.2] years; 32 (52%) were male) were randomized to either omalizumab (n = 30) or placebo (n = 32). Five participants withdrew from treatment (4 [13%] from the placebo group, and 1 [3%] from the omalizumab group). Follow-up attendance was 97% at week 24 and 98% at week 48. After adjustment for baseline objective SCORAD index, age, and IgE level, the mean difference in objective SCORAD index improvement between groups at week 24 was -6.9 (95% CI, -12.2 to -1.5; P = .01), significantly favoring omalizumab therapy and reflec
Phillips R, Cornelius V, Cro S, et al., 2019, The use of visual analytics for clinical trial safety outcomes: a methodological review, 5th International Clinical Trials Methodology Conference, Publisher: BMC
Kahan B, Forbes G, Ahmad T, et al., 2019, Statistical transparency in clinical trials: an evaluation of unexplained discrepancies between planned and conducted analyses, Publisher: BMC
Cro S, Chan S, Cornelius V, 2019, Controlled multiple imputation: an accessible flexible tool for estimating hypothetical estimands in clinical trials, Publisher: BMC
Cornelius V, Cro S, 2019, Designing trials for small populations, Publisher: BMC
Ster AMC, Cornelius V, Cro S, 2019, Statistical approaches to adjust for the use of rescue medication in randomised controlled trials, Publisher: BMC
Leurent B, Gomes M, Cro S, et al., 2019, Reference-based multiple imputation for data missing not-at-random in cost-effectiveness analysis, Publisher: BMC
Beaney T, Burrell LM, Castillo RR, et al., 2019, May Measurement Month 2018: a pragmatic global screening campaign to raise awareness of blood pressure by the International Society of Hypertension, European Heart Journal, Vol: 40, Pages: 2006-2017, ISSN: 1522-9645
AIMS: Raised blood pressure (BP) is the biggest contributor to mortality and disease burden worldwide and fewer than half of those with hypertension are aware of it. May Measurement Month (MMM) is a global campaign set up in 2017, to raise awareness of high BP and as a pragmatic solution to a lack of formal screening worldwide. The 2018 campaign was expanded, aiming to include more participants and countries. METHODS AND RESULTS: Eighty-nine countries participated in MMM 2018. Volunteers (≥18 years) were recruited through opportunistic sampling at a variety of screening sites. Each participant had three BP measurements and completed a questionnaire on demographic, lifestyle, and environmental factors. Hypertension was defined as a systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg, or taking antihypertensive medication. In total, 74.9% of screenees provided three BP readings. Multiple imputation using chained equations was used to impute missing readings. 1 504 963 individuals (mean age 45.3 years; 52.4% female) were screened. After multiple imputation, 502 079 (33.4%) individuals had hypertension, of whom 59.5% were aware of their diagnosis and 55.3% were taking antihypertensive medication. Of those on medication, 60.0% were controlled and of all hypertensives, 33.2% were controlled. We detected 224 285 individuals with untreated hypertension and 111 214 individuals with inadequately treated (systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg) hypertension. CONCLUSION: May Measurement Month expanded significantly compared with 2017, including more participants in more countries. The campaign identified over 335 000 adults with untreated or inadequately treated hypertension. In the absence of systematic screening programmes, MMM was effective at raising awareness at least among these individuals at risk.
Cro S, Carpenter JR, Kenward MG, 2019, Information-anchored sensitivity analysis: theory and application, The Authors Journal of the Royal Statistical Society: Series A (Statistics in Society)
Analysis of longitudinal randomised controlled trials is frequently complicated because patients deviate from the protocol. Where such deviations are relevant for the estimand, we are typically required to make an untestable assumption about post-deviation behaviour in order to perform our primary analysis and estimate the treatment effect. In such settings, it is now widely recognised that we should follow this with sensitivity analyses to explore the robustness of our inferences to alternative assumptions about post-deviation behaviour. Although there has been a lot of work on how to conduct such sensitivity analyses, little attention has been given to the appropriate loss of information due to missing data within sensitivity analysis. We argue more attention needs to be given to this issue, showing it is quite possible for sensitivity analysis to decrease and increase the information about the treatment effect. To address this critical issue, we introduce the concept of information-anchored sensitivity analysis. By this we mean sensitivity analysis in which the proportion of information about the treatment estimate lost due to missing data is the same as the proportion of information about the treatment estimate lost due to missing data in the primary analysis. We argue this forms a transparent, practical starting point for interpretation of sensitivity analysis. We then derive results showing that, for longitudinal continuous data, a broad class of controlled and reference-based sensitivity analyses performed by multiple imputation are information-anchored. We illustrate the theory with simulations and an analysis of a peer review trial, then discuss our work in the context of other recent work in this area. Our results give a theoretical basis for the use of controlled multiple imputation procedures for sensitivity analysis.
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