An evaluation of inverse probability weighting using the propensity score for baseline covariate adjustment in smaller population randomised controlled trials with a continuous outcome 2020

Raad H, Cornelius V, Chan S, Williamson E, Cro S

This article explores the use of IPTW for baseline covariate adjustment in small sample randomised trials and subsequently provides a caution on the use of IPTW without small sample modifications to the standard error calculation.

Reference‐based multiple imputation for missing data sensitivity analyses in trial‐based cost‐effectiveness analysis. Health Economics 2020

Leurent B, Gomes M, Cro S, Wiles N, Carpenter J.R

This article introduces an accessible statistical method for conducting sensitivity analysis of cost-effectiveness data to address the impact of alternative missing data assumptions.

A randomised placebo controlled trial of anakinra for treating pustular psoriasis: statistical analysis plan for stage two of the APRICOT trial. Trials 2020

Cro, S., Patel, P., Barker, J, Burden D, Griffiths, Lachmann, H, Reynolds, N, Warron, R, Capon, F, Cornelius, V.

This paper reports the statistical analysis plan for the second stage for the APRICOT trial after the first stage adaptation has taken place.

Analysis and reporting of adverse events in randomised controlled trials: a review. BMJ Open 2019

Phillips R, Hazell L, Sauzet O, Cornelius V.

This review highlighted that the collection, reporting and analysis of AE data in clinical trials is inconsistent and RCTs as a source of safety data are underused.

The Enhanced Peri-Operative Care for High-risk patients trial: an independent discussion and commentary. BJA 2019.

Cornelius, V,. Johnston, C.

Independent invited commentary on the EPOCH trial to study the effectiveness of a national quality improvement (QI) programme to implement a care pathway to reduce mortality in patients undergoing emergency laparotomy

Comparison of Clinical Trial Changes in Primary Outcome and Reported Intervention Effect Size Between Trial Registration and Publication. JAMA Network Open 2019

Chen T, Li C, Qin R, Wang Y, Yu D, Dodd J, Cornelius V.

This review found inconsistencies between registered and published primary outcomes of clinical trials were common, and trials with primary outcome change are likely to have a larger intervention effect than those without. Compared with those without primary outcome change, trials with primary outcome change showed a 16% (pooled ROR, 0.84; 95% CI, 0.73-0.96) larger reported intervention effect size.

How to design a dose-finding study using the continual reassessment method. BMC Med Res Methodol. 2019

Wheeler GM, Mander AP, Bedding A, Brock K, Cornelius V, Grieve AP, et al.

This paper presents a structured framework for designing a dose-finding study using the continual reassessment method for phase I trials.

Information-anchored sensitivity analysis: theory and application. Journal of the Royal Statistical Society: Series A (Statistics in Society). 2019

Cro S, Carpenter JR, Kenward MG.                        

These results give a theoretical basis for the use of controlled multiple‐imputation procedures for sensitivity analysis.

January 01, 2020

Embracing model-based designs for dose-finding trials. Br J Cancer. 2017

Love, S., Brown, S., Weir, C., Cornelius, V

This paper describes the benefits of model-based designs (flexibility, superior operating characteristics, extended scope), their current uptake, and existing resources.

A small population, randomised, placebo-controlled trial to determine the efficacy of anakinra in the treatment of pustular psoriasis: study protocol for the APRICOT trial. Trials 2018.

Cornelius, V., Wilson, R., Cro, S. et al.

This paper describes an adaptive design for a small population trial  to evaluate the efficacy of anakinra for pustular psoriasis

Treatment of pustular psoriasis with anakinra: a statistical analysis plan for stage 1 of an adaptive two-staged randomised placebo-controlled trial. Trials 2018.

Cro, S., Smith, C., Wilson, Cornelius, V.

This paper describes the statistical analysis at the end or stage I of the APRICOT trial to inform the trial adaptation decisions.

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