1
|
Humphreys S, von Ungern-Sternberg BS, Taverner F, Davidson A, Skowno J, Hallett B, Sommerfield D, Hauser N, Williams T, Spall S, Pham T, Atkins T, Jones M, King E, Burgoyne L, Stephens P, Vijayasekaran S, Slee N, Burns H, Franklin D, Hough J, Schibler A. High-flow nasal oxygen for children's airway surgery to reduce hypoxaemic events: a randomised controlled trial. THE LANCET. RESPIRATORY MEDICINE 2024; 12:535-543. [PMID: 38788748 DOI: 10.1016/s2213-2600(24)00115-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 03/13/2024] [Accepted: 04/03/2024] [Indexed: 05/26/2024]
Abstract
BACKGROUND Tubeless upper airway surgery in children is a complex procedure in which surgeons and anaesthetists share the same operating field. These procedures are often interrupted for rescue oxygen therapy. The efficacy of nasal high-flow oxygen to decrease the frequency of rescue interruptions in children undergoing upper airway surgery is unknown. METHODS In this multicentre randomised trial conducted in five tertiary hospitals in Australia, children aged 0-16 years who required tubeless upper airway surgery were randomised (1:1) by a web-based randomisation tool to either nasal high-flow oxygen delivery or standard oxygen therapy (oxygen flows of up to 6 L/min). Randomisation was stratified by site and age (<1 year, 1-4 years, and 5-16 years). Subsequent tubeless upper airway surgery procedures in the same child could be included if there were more than 2 weeks between the procedures, and repeat surgical procedures meeting this condition were considered to be independent events. The oxygen therapy could not be masked, but the investigators remained blinded until outcome data were locked. The primary outcome was successful anaesthesia without interruption of the surgical procedure for rescue oxygenation. A rescue oxygenation event was defined as an interruption of the surgical procedure to deliver positive pressure ventilation using either bag mask technique, insertion of an endotracheal tube, or laryngeal mask to improve oxygenation. There were ten secondary outcomes, including the proportion of procedures with a hypoxaemic event (SpO2 <90%). Analyses were done on an intention-to-treat (ITT) basis. Safety was assessed in all enrolled participants. This trial is registered in the Australian New Zealand Clinical Trials Registry, ACTRN12618000949280, and is completed. FINDINGS From Sept 4, 2018, to April 12, 2021, 581 procedures in 487 children were randomly assigned to high-flow oxygen (297 procedures) or standard care (284 procedures); after exclusions, 528 procedures (267 assigned to high-flow oxygen and 261 assigned to standard care) in 483 children (293 male and 190 female) were included in the ITT analysis. The primary outcome of successful anaesthesia without interruption for tubeless airway surgery was achieved in 236 (88%) of 267 procedures on high-flow oxygen and in 229 (88%) of 261 procedures on standard care (adjusted risk ratio [RR] 1·02, 95% CI 0·96-1·08, p=0·82). There were 51 (19%) procedures with a hypoxaemic event in the high-flow oxygen group and 57 (22%) in the standard care group (RR 0·86, 95% CI 0·58-1·24). Of the other prespecified secondary outcomes, none showed a significant difference between groups. Adverse events of epistaxis, laryngospasm, bronchospasm, hypoxaemia, bradycardia, cardiac arrest, hypotension, or death were similar in both study groups. INTERPRETATION Nasal high-flow oxygen during tubeless upper airway surgery did not reduce the proportion of interruptions of the procedures for rescue oxygenation compared with standard care. There were no differences in adverse events between the intervention groups. These results suggest that both approaches, nasal high-flow or standard oxygen, are suitable alternatives to maintain oxygenation in children undergoing upper airway surgery. FUNDING Thrasher Research Fund, the Australian and New Zealand College of Anaesthetists, the Society for Paediatric Anaesthesia in New Zealand and Australia.
Collapse
Affiliation(s)
- Susan Humphreys
- Department of Anaesthesia, Queensland Children's Hospital, Brisbane, QLD, Australia; The University of Queensland, Brisbane, QLD, Australia
| | - Britta S von Ungern-Sternberg
- Division of Emergency Medicine, Anaesthesia, and Pain Medicine, Perth Children's Hospital, Perth, WA, Australia; University of Western Australia, Perth, WA, Australia
| | - Fiona Taverner
- Department of Children's Anaesthesia, Women's and Children's Hospital, Adelaide, SA, Australia; University of Adelaide, Adelaide, SA, Australia
| | - Andrew Davidson
- Department of Anaesthesia, Royal Children's Hospital, Melbourne, VIC, Australia; Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Justin Skowno
- Department of Anaesthesia, The Children's Hospital at Westmead, Sydney, NSW, Australia; School of Child and Adolescent Health, University of Sydney, Sydney, NSW, Australia
| | - Ben Hallett
- Department of Anaesthesia, Royal Children's Hospital, Melbourne, VIC, Australia; Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - David Sommerfield
- Division of Emergency Medicine, Anaesthesia, and Pain Medicine, Perth Children's Hospital, Perth, WA, Australia; University of Western Australia, Perth, WA, Australia
| | - Neil Hauser
- Division of Emergency Medicine, Anaesthesia, and Pain Medicine, Perth Children's Hospital, Perth, WA, Australia; University of Western Australia, Perth, WA, Australia
| | - Tara Williams
- Department of Anaesthesia, Queensland Children's Hospital, Brisbane, QLD, Australia; The University of Queensland, Brisbane, QLD, Australia
| | - Susan Spall
- Department of Anaesthesia, Queensland Children's Hospital, Brisbane, QLD, Australia
| | - Trang Pham
- Department of Anaesthesia, Queensland Children's Hospital, Brisbane, QLD, Australia
| | - Tiffany Atkins
- Institute for Evidence-Based Healthcare, Bond University, Robina, QLD, Australia
| | - Mark Jones
- Institute for Evidence-Based Healthcare, Bond University, Robina, QLD, Australia
| | - Emma King
- Department of Children's Anaesthesia, Women's and Children's Hospital, Adelaide, SA, Australia
| | - Laura Burgoyne
- Department of Children's Anaesthesia, Women's and Children's Hospital, Adelaide, SA, Australia; University of Adelaide, Adelaide, SA, Australia
| | - Philip Stephens
- Department of Anaesthesia, Queensland Children's Hospital, Brisbane, QLD, Australia
| | - Shyan Vijayasekaran
- Division of Emergency Medicine, Anaesthesia, and Pain Medicine, Perth Children's Hospital, Perth, WA, Australia; University of Western Australia, Perth, WA, Australia
| | - Nicola Slee
- Department of Ear, Nose, and Throat Surgery, Queensland Children's Hospital, Brisbane, QLD, Australia
| | - Hannah Burns
- Department of Ear, Nose, and Throat Surgery, Queensland Children's Hospital, Brisbane, QLD, Australia; The University of Queensland, Brisbane, QLD, Australia
| | - Donna Franklin
- The University of Queensland, Brisbane, QLD, Australia; Children's Critical Care Research Collaborative Group, Griffith University, Gold Coast University Hospital, Southport, QLD, Australia; Wesley Research Institute, Brisbane, QLD, Australia; Menzies Health Institute Queensland, Southport, QLD, Australia
| | - Judith Hough
- Australia Catholic University, Department of Physiotherapy, Brisbane, QLD, Australia
| | - Andreas Schibler
- Critical Care Research Group, St Andrew's War Memorial Hospital, Wesley Research Institute, Brisbane, QLD, Australia; College of Medicine & Dentistry, James Cook University, Townsville, QLD, Australia.
| |
Collapse
|
2
|
Ramakrishnan S, Jeffers H, Langford-Wiley B, Davies J, Thulborn SJ, Mahdi M, A'Court C, Binnian I, Bright S, Cartwright S, Glover V, Law A, Fox R, Jones A, Davies C, Copping D, Russell RE, Bafadhel M. Blood eosinophil-guided oral prednisolone for COPD exacerbations in primary care in the UK (STARR2): a non-inferiority, multicentre, double-blind, placebo-controlled, randomised controlled trial. THE LANCET. RESPIRATORY MEDICINE 2024; 12:67-77. [PMID: 37924830 DOI: 10.1016/s2213-2600(23)00298-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/04/2023] [Accepted: 08/07/2023] [Indexed: 11/06/2023]
Abstract
BACKGROUND Systemic glucocorticoids are recommended for use in chronic obstructive pulmonary disease (COPD) exacerbations; however, there is increased harm associated with their use. We hypothesised that the use of eosinophil biomarker-directed oral prednisolone therapy at the time of an exacerbation of COPD was effective at reducing prednisolone use without affecting adverse outcomes. METHODS The studying acute exacerbations and response (STARR2) study was a multicentre, randomised, double-blind, placebo-controlled trial conducted in 14 primary care practices in the UK. We included adults (aged ≥40 years), who were current or former smokers (with at least a 10 pack year smoking history) with a diagnosis of COPD, defined as a post-bronchodilator FEV1/forced vital capacity ratio of less than 0·7 previously recorded by the primary care physician, and a history of at least one exacerbation in the previous 12 months requiring systemic corticosteroids with or without antibiotics. All study staff and participants were masked to study group allocation and to treatment allocation. Participants were randomly assigned (1:1) to blood eosinophil-directed treatment (BET; to receive oral prednisolone 30 mg once daily if eosinophil count was high [≥2%] or placebo if eosinophil count was low [<2%]) or to standard care treatment (ST; to receive prednisolone 30 mg once daily irrespective of the point-of-care eosinophil result). Treatment was prescribed for 14 days and all patients also received antibiotics. The primary outcome was the rate of treatment failure, defined as any need for re-treatment with antibiotics or steroids, hospitalisation for any cause, or death, assessed at 30 days after exacerbation in the modified intention-to-treat population. Participants were eligible for re-randomisation at further exacerbations (with a maximum of four exacerbations per participant). A safety analysis was conducted on all randomly assigned participants. Although designed as a superiority trial, after identification of an error in the randomisation code before data lock the study converted to show non-inferiority. An upper margin of 1·105 for the 95% CI was defined as the non-inferiority margin. This study was registered with EudraCT, 2017-001586-24, and is complete. FINDINGS Between Nov 6, 2017, and April 30, 2020, 308 participants were recruited from 14 general practices. 144 exacerbations (73 in the BET group and 71 in the ST group) from 93 participants (mean age 70 years [range 46-84] and mean percent predicted FEV1 60·9% [SD 19·4]; 52 [56%] male and 41 [44%] female; ethnicity data was not collected]) were included in the modified intention-to-treat analysis. There were 14 (19%) treatment failures at 30 days post-exacerbation in the BET group and 23 (32%) in the ST group; we found a large non-significant estimated effect between BET and ST (RR 0·60 [95% CI 0·33-1·04]; p=0·070) in reducing treatment failures after a COPD exacerbation. The non-inferiority analysis supported that BET was non-inferior to ST. Frequency of adverse events were similar between the study groups; glycosuria (2/102 [2%] in BET group and 1/101 [1%] in the ST group) and hospital admission for COPD exacerbation (2/102 [2%] in BET group and 1/101 [1%] in the ST group) were the two most common adverse events in both groups. No deaths occurred in the study. INTERPRETATION Blood eosinophil-directed prednisolone therapy at the time of an acute exacerbation of COPD is non-inferior to standard care and can be used to safely reduce systemic glucocorticoid use in clinical practice. FUNDING National Institute for Health and Care Research.
Collapse
Affiliation(s)
- Sanjay Ramakrishnan
- Respiratory Medicine Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Helen Jeffers
- Respiratory Medicine Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Beverly Langford-Wiley
- Respiratory Medicine Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Joanne Davies
- Respiratory Medicine Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Samantha J Thulborn
- Respiratory Medicine Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Mahdi Mahdi
- Respiratory Medicine Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | | | | | | | | | | | - Alison Law
- White Horse Medical Practice, Faringdon, UK; Montgomery House Surgery, Bicester, UK
| | - Robin Fox
- Bicester Health Centre, Bicester, UK
| | | | | | | | - Richard Ek Russell
- Respiratory Medicine Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK; King's Centre of Lung Health, School of Immunology and Microbial Sciences, Faculty of Life Sciences and Medicine, King's College London, UK
| | - Mona Bafadhel
- Respiratory Medicine Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; King's Centre of Lung Health, School of Immunology and Microbial Sciences, Faculty of Life Sciences and Medicine, King's College London, UK.
| |
Collapse
|
4
|
Goulao B, Duncan A, Innes K, Ramsay CR, Kahan BC. Using re-randomisation designs to increase the efficiency and applicability of retention studies within trials: a case study. Trials 2023; 24:299. [PMID: 37118802 PMCID: PMC10148456 DOI: 10.1186/s13063-023-07323-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 04/22/2023] [Indexed: 04/30/2023] Open
Abstract
BACKGROUND Poor retention in randomised trials can lead to serious consequences to their validity. Studies within trials (SWATs) are used to identify the most effective interventions to increase retention. Many interventions could be applied at any follow-up time point, but SWATs commonly assess interventions at a single time point, which can reduce efficiency. METHODS The re-randomisation design allows participants to be re-enrolled and re-randomised whenever a new retention opportunity occurs (i.e. a new follow-up time point where the intervention could be applied). The main advantages are as follows: (a) it allows the estimation of an average effect across time points, thus increasing generalisability; (b) it can be more efficient than a parallel arm trial due to increased sample size; and (c) it allows subgroup analyses to estimate effectiveness at different time points. We present a case study where the re-randomisation design is used in a SWAT. RESULTS In our case study, the host trial is a dental trial with two available follow-up points. The Sticker SWAT tests whether adding the trial logo's sticker to the questionnaire's envelope will result in a higher response rate compared with not adding the sticker. The primary outcome is the response rate to postal questionnaires. The re-randomisation design could double the available sample size compared to a parallel arm trial, resulting in the ability to detect an effect size around 28% smaller. CONCLUSION The re-randomisation design can increase the efficiency and generalisability of SWATs for trials with multiple follow-up time points.
Collapse
Affiliation(s)
- Beatriz Goulao
- Health Services Research Unit, University of Aberdeen, Aberdeen, Scotland.
| | - Anne Duncan
- Health Services Research Unit, University of Aberdeen, Aberdeen, Scotland
| | - Karen Innes
- Health Services Research Unit, University of Aberdeen, Aberdeen, Scotland
| | - Craig R Ramsay
- Health Services Research Unit, University of Aberdeen, Aberdeen, Scotland
| | | |
Collapse
|
5
|
Lange KM, Kasza J, Sullivan TR, Yelland LN. Partially clustered designs for clinical trials: Unifying existing designs using consistent terminology. Clin Trials 2023; 20:99-110. [PMID: 36628406 PMCID: PMC10021130 DOI: 10.1177/17407745221146987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
INTRODUCTION Clinical trial designs based on the assumption of independent observations are well established. Clustered clinical trial designs, where all observational units belong to a cluster and outcomes within clusters are expected to be correlated, have also received considerable attention. However, many clinical trials involve partially clustered data, where only some observational units belong to a cluster. Examples of such trials occur in neonatology, where participants include infants from both singleton and multiple births, and ophthalmology, where one or two eyes per participant may need treatment. Partial clustering can also arise in trials of group-based treatments (e.g. group education or counselling sessions) or treatments administered individually by a discrete number of health care professionals (e.g. surgeons or physical therapists), when this is compared to an unclustered control arm. Trials involving partially clustered data have received limited attention in the literature and the current lack of standardised terminology may be hampering the development and dissemination of methods for designing and analysing these trials. METHODS AND EXAMPLES In this article, we present an overarching definition of partially clustered trials, bringing together several existing trial designs including those for group-based treatments, clustering due to facilitator effects and the re-randomisation design. We define and describe four types of partially clustered trial designs, characterised by whether the clustering occurs pre-randomisation or post-randomisation and, in the case of pre-randomisation clustering, by the method of randomisation that is used for the clustered observations (individual randomisation, cluster randomisation or balanced randomisation within clusters). Real life examples are provided to highlight the occurrence of partially clustered trials across a variety of fields. To assess how partially clustered trials are currently reported, we review published reports of partially clustered trials. DISCUSSION Our findings demonstrate that the description of these trials is often incomplete and the terminology used to describe the trial designs is inconsistent, restricting the ability to identify these trials in the literature. By adopting the definitions and terminology presented in this article, the reporting of partially clustered trials can be substantially improved, and we present several recommendations for reporting these trial designs in practice. Greater awareness of partially clustered trials will facilitate more methodological research into their design and analysis, ultimately improving the quality of these trials.
Collapse
Affiliation(s)
- Kylie M Lange
- School of Public Health, The University of Adelaide, Adelaide, SA, Australia.,Women and Kids Theme, South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Jessica Kasza
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Thomas R Sullivan
- School of Public Health, The University of Adelaide, Adelaide, SA, Australia.,Women and Kids Theme, South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| | - Lisa N Yelland
- School of Public Health, The University of Adelaide, Adelaide, SA, Australia.,Women and Kids Theme, South Australian Health and Medical Research Institute, Adelaide, SA, Australia
| |
Collapse
|
6
|
Kahan BC, Li F, Copas AJ, Harhay MO. Estimands in cluster-randomized trials: choosing analyses that answer the right question. Int J Epidemiol 2023; 52:107-118. [PMID: 35834775 PMCID: PMC9908044 DOI: 10.1093/ije/dyac131] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 06/07/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Cluster-randomized trials (CRTs) involve randomizing groups of individuals (e.g. hospitals, schools or villages) to different interventions. Various approaches exist for analysing CRTs but there has been little discussion around the treatment effects (estimands) targeted by each. METHODS We describe the different estimands that can be addressed through CRTs and demonstrate how choices between different analytic approaches can impact the interpretation of results by fundamentally changing the question being asked, or, equivalently, the target estimand. RESULTS CRTs can address either the participant-average treatment effect (the average treatment effect across participants) or the cluster-average treatment effect (the average treatment effect across clusters). These two estimands can differ when participant outcomes or the treatment effect depends on the cluster size (referred to as 'informative cluster size'), which can occur for reasons such as differences in staffing levels or types of participants between small and large clusters. Furthermore, common estimators, such as mixed-effects models or generalized estimating equations with an exchangeable working correlation structure, can produce biased estimates for both the participant-average and cluster-average treatment effects when cluster size is informative. We describe alternative estimators (independence estimating equations and cluster-level analyses) that are unbiased for CRTs even when informative cluster size is present. CONCLUSION We conclude that careful specification of the estimand at the outset can ensure that the study question being addressed is clear and relevant, and, in turn, that the selected estimator provides an unbiased estimate of the desired quantity.
Collapse
Affiliation(s)
- Brennan C Kahan
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Fan Li
- Department of Biostatistics, Yale University School of Public Health, New Haven, CT, USA
- Center for Methods in Implementation and Prevention Science, Yale University School of Public Health, New Haven, CT, USA
| | - Andrew J Copas
- MRC Clinical Trials Unit at UCL, Institute of Clinical Trials and Methodology, London, UK
| | - Michael O Harhay
- Clinical Trials Methods and Outcomes Lab, PAIR (Palliative and Advanced Illness Research) Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| |
Collapse
|