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Costa ML, Achten J, Ooms A, Png ME, Cook J, Dritsaki M, Lamb SE, Lerner R, Draper K, Campolier M, Dakin H, McGibbon A, Parsons N, Hedley H, Dias J. Moulded cast compared with K-wire fixation after manipulation of an acute dorsally displaced distal radius fracture: the DRAFFT 2 RCT. Health Technol Assess 2022; 26:1-80. [PMID: 35152940 DOI: 10.3310/rlcf6332] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Patients with a displaced fracture of the distal radius are frequently offered surgical fixation. Manipulation of the fracture and moulded plaster casting is an alternative treatment that avoids metal implants, but evidence of its effectiveness is lacking. OBJECTIVE To compare functional outcomes, quality-of-life outcomes, complications and resource use among patients with a dorsally displaced fracture of the distal radius treated with manipulation and surgical fixation with Kirschner wires (K-wires) and those treated with manipulation and moulded cast. DESIGN Pragmatic, superiority, multicentre, randomised controlled trial with a health economic evaluation. SETTING A total of 36 orthopaedic trauma centres in the UK NHS. PARTICIPANTS Patients (aged ≥ 16 years) treated for an acute dorsally displaced fracture of the distal radius were potentially eligible. Patients were excluded if their injury had occurred > 2 weeks previously, if the fracture was open, if it extended > 3 cm from the radiocarpal joint or if it required open reduction, or if the participant was unable to complete questionnaires. INTERVENTIONS Participants were randomly assigned in theatre (1 : 1) to receive a moulded cast (i.e. the cast group) or surgical fixation with K-wires (i.e. the K-wire group) after fracture manipulation. MAIN OUTCOME MEASURES The primary outcome measure was the Patient-Rated Wrist Evaluation score at 12 months, analysed on an intention-to-treat basis. Health-related quality of life was recorded using the EuroQol-5 Dimensions, five-level version, and resource use was recorded from a health and personal social care perspective. RESULTS Between January 2017 and March 2019, 500 participants (mean age 60 years, 83% women) were randomly allocated to receive a moulded cast (n = 255) or surgical fixation with K-wire (n = 245) following a manipulation of their fracture. A total of 395 (80%) participants were included in the primary analysis at 12 months. There was no difference in the Patient-Rated Wrist Evaluation score at 1 year post randomisation [cast group: n = 200, mean score 21.2 (standard deviation 23.1); K-wire group: n = 195, mean score 20.7 (standard deviation 22.3); adjusted mean difference -0.34 (95% confidence interval -4.33 to 3.66); p = 0.87]. A total of 33 (13%) participants in the cast group required surgical fixation for loss of fracture position in the first 6 weeks, compared with one participant in the K-wire group (odds ratio 0.02, 95% confidence interval 0.001 to 0.10). The base-case cost-effectiveness analysis showed that manipulation and surgical fixation with K-wires had a higher mean cost than manipulation and a moulded cast, despite similar mean effectiveness. The use of K-wires is unlikely to be cost-effective, and sensitivity analyses found this result to be robust. LIMITATIONS Because the interventions were identifiable, neither patients nor clinicians could be blind to their treatment. CONCLUSIONS Surgical fixation with K-wires was not found to be superior to moulded casting following manipulation of a dorsally displaced fracture of the distal radius, as measured by Patient-Rated Wrist Evaluation score. However, one in eight participants treated in a moulded cast required surgery for loss of fracture reduction in the first 6 weeks. After a successful closed reduction, clinicians may consider a moulded cast as a safe and cost-effective alternative to surgical fixation with K-wires. FUTURE WORK Further research should focus on optimal techniques for immobilisation and manipulation of this type of fracture, including optimal analgesia, and for rehabilitation of the patient after immobilisation. TRIAL REGISTRATION This trial is registered as ISRCTN11980540 and UKCRN Portfolio 208830. FUNDING This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 11. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Matthew L Costa
- Oxford Trauma and Emergency Care, Kadoorie Research Centre, Nuffield Department of Orthopaedic, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Juul Achten
- Oxford Trauma and Emergency Care, Kadoorie Research Centre, Nuffield Department of Orthopaedic, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Alexander Ooms
- Centre for Statistics in Medicine, Oxford Clinical Trials Research Unit, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - May Ee Png
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Jonathan Cook
- Centre for Statistics in Medicine, Oxford Clinical Trials Research Unit, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Melina Dritsaki
- Centre for Statistics in Medicine, Oxford Clinical Trials Research Unit, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Sarah E Lamb
- Oxford Trauma and Emergency Care, Kadoorie Research Centre, Nuffield Department of Orthopaedic, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.,College of Medicine and Health, St Luke's Campus, University of Exeter, Exeter, UK
| | - Robin Lerner
- Oxford Trauma and Emergency Care, Kadoorie Research Centre, Nuffield Department of Orthopaedic, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.,Blizard Institute, Queen Mary University of London, London, UK
| | - Kylea Draper
- Oxford Trauma and Emergency Care, Kadoorie Research Centre, Nuffield Department of Orthopaedic, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Marta Campolier
- Oxford Trauma and Emergency Care, Kadoorie Research Centre, Nuffield Department of Orthopaedic, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Helen Dakin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Alwin McGibbon
- Patient and public involvement group member, Wimbourne, UK
| | - Nicholas Parsons
- Statistics and Epidemiology Unit, Warwick Medical School, University of Warwick, Coventry, UK
| | - Helen Hedley
- Department of Orthopaedics, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK
| | - Joseph Dias
- AToMS Academic Team of Musculoskeletal Surgery, University Hospitals of Leicester NHS Trust, Leicester, UK
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Gathercole R, Bradley R, Harper E, Davies L, Pank L, Lam N, Davies A, Talbot E, Hooper E, Winson R, Scutt B, Montano VO, Nunn S, Lavelle G, Lariviere M, Hirani S, Brini S, Bateman A, Bentham P, Burns A, Dunk B, Forsyth K, Fox C, Henderson C, Knapp M, Leroi I, Newman S, O'Brien J, Poland F, Woolham J, Gray R, Howard R. Assistive technology and telecare to maintain independent living at home for people with dementia: the ATTILA RCT. Health Technol Assess 2021; 25:1-156. [PMID: 33755548 DOI: 10.3310/hta25190] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Assistive technology and telecare have been promoted to manage the risks associated with independent living for people with dementia, but there is limited evidence of their effectiveness. OBJECTIVES This trial aimed to establish whether or not assistive technology and telecare assessments and interventions extend the time that people with dementia can continue to live independently at home and whether or not they are cost-effective. Caregiver burden, the quality of life of caregivers and of people with dementia and whether or not assistive technology and telecare reduce safety risks were also investigated. DESIGN This was a pragmatic, randomised controlled trial. Blinding was not undertaken as it was not feasible to do so. All consenting participants were included in an intention-to-treat analysis. SETTING This trial was set in 12 councils in England with adult social services responsibilities. PARTICIPANTS Participants were people with dementia living in the community who had an identified need that might benefit from assistive technology and telecare. INTERVENTIONS Participants were randomly assigned to receive either assistive technology and telecare recommended by a health or social care professional to meet their assessed needs (a full assistive technology and telecare package) or a pendant alarm, non-monitored smoke and carbon monoxide detectors and a key safe (a basic assistive technology and telecare package). MAIN OUTCOME MEASURES The primary outcomes were time to admission to care and cost-effectiveness. Secondary outcomes assessed caregivers using the 10-item Center for Epidemiological Studies Depression Scale, the State-Trait Anxiety Inventory 6-item scale and the Zarit Burden Interview. RESULTS Of 495 participants, 248 were randomised to receive full assistive technology and telecare and 247 received the limited control. Comparing the assistive technology and telecare group with the control group, the hazard ratio for institutionalisation was 0.76 (95% confidence interval 0.58 to 1.01; p = 0.054). After adjusting for an imbalance in the baseline activities of daily living score between trial arms, the hazard ratio was 0.84 (95% confidence interval 0.63 to 1.12; p = 0.20). At 104 weeks, there were no significant differences between groups in health and social care resource use costs (intervention group - control group difference: mean -£909, 95% confidence interval -£5336 to £3345) or in societal costs (intervention group - control group difference: mean -£3545; 95% confidence interval -£13,914 to £6581). At 104 weeks, based on quality-adjusted life-years derived from the participant-rated EuroQol-5 Dimensions questionnaire, the intervention group had 0.105 (95% confidence interval -0.204 to -0.007) fewer quality-adjusted life-years than the control group. The number of quality-adjusted life-years derived from the proxy-rated EuroQol-5 Dimensions questionnaire did not differ between groups. Caregiver outcomes did not differ between groups over 24 weeks. LIMITATIONS Compliance with the assigned trial arm was variable, as was the quality of assistive technology and telecare needs assessments. Attrition from assessments led to data loss additional to that attributable to care home admission and censoring events. CONCLUSIONS A full package of assistive technology and telecare did not increase the length of time that participants with dementia remained in the community, and nor did it decrease caregiver burden, depression or anxiety, relative to a basic package of assistive technology and telecare. Use of the full assistive technology and telecare package did not increase participants' health and social care or societal costs. Quality-adjusted life-years based on participants' EuroQol-5 Dimensions questionnaire responses were reduced in the intervention group compared with the control group; groups did not differ in the number of quality-adjusted life-years based on the proxy-rated EuroQol-5 Dimensions questionnaire. FUTURE WORK Future work could examine whether or not improved assessment that is more personalised to an individual is beneficial. TRIAL REGISTRATION Current Controlled Trials ISRCTN86537017. FUNDING This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 19. See the NIHR Journals Library website for further project information.
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Affiliation(s)
| | - Rosie Bradley
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Emma Harper
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Lucy Davies
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Lynn Pank
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Natalie Lam
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Anna Davies
- School of Health Sciences, City, University of London, London, UK.,Population Health Sciences, University of Bristol, Bristol, UK
| | - Emma Talbot
- Norfolk and Suffolk NHS Foundation Trust, Stowmarket, UK
| | - Emma Hooper
- Lancashire Care NHS Foundation Trust, Preston, UK.,Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Rachel Winson
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Bethany Scutt
- Department of Old Age Psychiatry, King's College London, London, UK
| | | | - Samantha Nunn
- Cambridgeshire Community Services NHS Trust, Cambridge, UK
| | - Grace Lavelle
- Department of Old Age Psychiatry, King's College London, London, UK
| | - Matthew Lariviere
- Centre for International Research on Care, Labour and Equalities, University of Sheffield, Sheffield, UK
| | | | - Stefano Brini
- School of Health Sciences, City, University of London, London, UK
| | - Andrew Bateman
- School of Health and Social Care, University of Essex, Colchester, UK
| | - Peter Bentham
- Birmingham and Solihull Mental Health NHS Foundation Trust, Birmingham, UK
| | - Alistair Burns
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Barbara Dunk
- South London and Maudsley NHS Foundation Trust, London, UK
| | - Kirsty Forsyth
- School of Health Sciences, Queen Margaret University, Edinburgh, UK
| | - Chris Fox
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Catherine Henderson
- Care Policy and Evaluation Centre, London School of Economics and Political Science, London, UK
| | - Martin Knapp
- Care Policy and Evaluation Centre, London School of Economics and Political Science, London, UK
| | - Iracema Leroi
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Stanton Newman
- School of Health Sciences, City, University of London, London, UK
| | - John O'Brien
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Fiona Poland
- School of Health Sciences, University of East Anglia, Norwich, UK
| | - John Woolham
- National Institute for Health Research (NIHR) Health & Social Care Workforce Research Unit, King's College London, London, UK
| | - Richard Gray
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
| | - Robert Howard
- Division of Psychiatry, University College London, London, UK
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Taylor SA, Mallett S, Bhatnagar G, Morris S, Quinn L, Tomini F, Miles A, Baldwin-Cleland R, Bloom S, Gupta A, Hamlin PJ, Hart AL, Higginson A, Jacobs I, McCartney S, Murray CD, Plumb AA, Pollok RC, Rodriguez-Justo M, Shabir Z, Slater A, Tolan D, Travis S, Windsor A, Wylie P, Zealley I, Halligan S. Magnetic resonance enterography compared with ultrasonography in newly diagnosed and relapsing Crohn's disease patients: the METRIC diagnostic accuracy study. Health Technol Assess 2020; 23:1-162. [PMID: 31432777 DOI: 10.3310/hta23420] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Magnetic resonance enterography and enteric ultrasonography are used to image Crohn's disease patients. Their diagnostic accuracy for presence, extent and activity of enteric Crohn's disease was compared. OBJECTIVE To compare diagnostic accuracy, observer variability, acceptability, diagnostic impact and cost-effectiveness of magnetic resonance enterography and ultrasonography in newly diagnosed or relapsing Crohn's disease. DESIGN Prospective multicentre cohort study. SETTING Eight NHS hospitals. PARTICIPANTS Consecutive participants aged ≥ 16 years, newly diagnosed with Crohn's disease or with established Crohn's disease and suspected relapse. INTERVENTIONS Magnetic resonance enterography and ultrasonography. MAIN OUTCOME MEASURES The primary outcome was per-participant sensitivity difference between magnetic resonance enterography and ultrasonography for small bowel Crohn's disease extent. Secondary outcomes included sensitivity and specificity for small bowel Crohn's disease and colonic Crohn's disease extent, and sensitivity and specificity for small bowel Crohn's disease and colonic Crohn's disease presence; identification of active disease; interobserver variation; participant acceptability; diagnostic impact; and cost-effectiveness. RESULTS Out of the 518 participants assessed, 335 entered the trial, with 51 excluded, giving a final cohort of 284 (133 and 151 in new diagnosis and suspected relapse cohorts, respectively). Across the whole cohort, for small bowel Crohn's disease extent, magnetic resonance enterography sensitivity [80%, 95% confidence interval (CI) 72% to 86%] was significantly greater than ultrasonography sensitivity (70%, 95% CI 62% to 78%), with a 10% difference (95% CI 1% to 18%; p = 0.027). For small bowel Crohn's disease extent, magnetic resonance enterography specificity (95%, 95% CI 85% to 98%) was significantly greater than ultrasonography specificity (81%, 95% CI 64% to 91%), with a 14% difference (95% CI 1% to 27%). For small bowel Crohn's disease presence, magnetic resonance enterography sensitivity (97%, 95% CI 91% to 99%) was significantly greater than ultrasonography sensitivity (92%, 95% CI 84% to 96%), with a 5% difference (95% CI 1% to 9%). For small bowel Crohn's disease presence, magnetic resonance enterography specificity was 96% (95% CI 86% to 99%) and ultrasonography specificity was 84% (95% CI 65% to 94%), with a 12% difference (95% CI 0% to 25%). Test sensitivities for small bowel Crohn's disease presence and extent were similar in the two cohorts. For colonic Crohn's disease presence in newly diagnosed participants, ultrasonography sensitivity (67%, 95% CI 49% to 81%) was significantly greater than magnetic resonance enterography sensitivity (47%, 95% CI 31% to 64%), with a 20% difference (95% CI 1% to 39%). For active small bowel Crohn's disease, magnetic resonance enterography sensitivity (96%, 95% CI 92% to 99%) was significantly greater than ultrasonography sensitivity (90%, 95% CI 82% to 95%), with a 6% difference (95% CI 2% to 11%). There was some disagreement between readers for both tests. A total of 88% of participants rated magnetic resonance enterography as very or fairly acceptable, which is significantly lower than the percentage (99%) of participants who did so for ultrasonography. Therapeutic decisions based on magnetic resonance enterography alone and ultrasonography alone agreed with the final decision in 122 out of 158 (77%) cases and 124 out of 158 (78%) cases, respectively. There were no differences in costs or quality-adjusted life-years between tests. LIMITATIONS Magnetic resonance enterography and ultrasonography scans were interpreted by practitioners blinded to clinical data (but not participant cohort), which does not reflect use in clinical practice. CONCLUSIONS Magnetic resonance enterography has higher accuracy for detecting the presence, extent and activity of small bowel Crohn's disease than ultrasonography does. Both tests have variable interobserver agreement and are broadly acceptable to participants, although ultrasonography produces less participant burden. Diagnostic impact and cost-effectiveness are similar. Recommendations for future work include investigation of the comparative utility of magnetic resonance enterography and ultrasonography for treatment response assessment and investigation of non-specific abdominal symptoms to confirm or refute Crohn's disease. TRIAL REGISTRATION Current Controlled Trials ISRCTN03982913. FUNDING This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 23, No. 42. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Stuart A Taylor
- Centre for Medical Imaging, University College London, London, UK
| | - Sue Mallett
- Institute of Applied Health Research, National Institute for Health Research Birmingham Biomedical Research Centre, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | | | - Stephen Morris
- Applied Health Research, University College London, London, UK
| | - Laura Quinn
- Institute of Applied Health Research, National Institute for Health Research Birmingham Biomedical Research Centre, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Florian Tomini
- Applied Health Research, University College London, London, UK
| | - Anne Miles
- Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - Rachel Baldwin-Cleland
- Intestinal Imaging Centre, St Mark's Hospital, London North West University Healthcare NHS Trust, Harrow, UK
| | - Stuart Bloom
- Department of Gastroenterology, University College Hospital, London, UK
| | - Arun Gupta
- Intestinal Imaging Centre, St Mark's Hospital, London North West University Healthcare NHS Trust, Harrow, UK
| | - Peter John Hamlin
- Department of Gastroenterology, St James's University Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Ailsa L Hart
- Inflammatory Bowel Disease Unit, St Mark's Hospital, London North West University Healthcare NHS Trust, Harrow, UK
| | - Antony Higginson
- Department of Radiology, Portsmouth Hospitals NHS Trust, Portsmouth, UK
| | - Ilan Jacobs
- Independent patient representative, c/o Centre for Medical Imaging, University College London, London, UK
| | - Sara McCartney
- Department of Gastroenterology, University College Hospital, London, UK
| | - Charles D Murray
- Department of Gastroenterology and Endoscopy, Royal Free London NHS Foundation Trust, London, UK
| | - Andrew Ao Plumb
- Centre for Medical Imaging, University College London, London, UK
| | - Richard C Pollok
- Department of Gastroenterology, St George's Hospital, London, UK
| | | | - Zainib Shabir
- Comprehensive Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK
| | - Andrew Slater
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Damian Tolan
- Department of Radiology, St James's University Hospital, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Simon Travis
- Translational Gastroenterology Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | | | - Peter Wylie
- Department of Radiology, Royal Free London NHS Foundation Trust, London, UK
| | - Ian Zealley
- Department of Radiology, Ninewells Hospital, Dundee, UK
| | - Steve Halligan
- Centre for Medical Imaging, University College London, London, UK
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Hernández Alava M, Wailoo A, Pudney S, Gray L, Manca A. Mapping clinical outcomes to generic preference-based outcome measures: development and comparison of methods. Health Technol Assess 2020; 24:1-68. [PMID: 32613941 DOI: 10.3310/hta24340] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Cost-effectiveness analysis using quality-adjusted life-years as the measure of health benefit is commonly used to aid decision-makers. Clinical studies often do not include preference-based measures that allow the calculation of quality-adjusted life-years, or the data are insufficient. 'Mapping' can bridge this evidence gap; it entails estimating the relationship between outcomes measured in clinical studies and the required preference-based measures using a different data set. However, many methods for mapping yield biased results, distorting cost-effectiveness estimates. OBJECTIVES Develop existing and new methods for mapping; test their performance in case studies spanning different preference-based measures; and develop methods for mapping between preference-based measures. DATA SOURCES Fifteen data sets for mapping from non-preference-based measures to preference-based measures for patients with head injury, breast cancer, asthma, heart disease, knee surgery and varicose veins were used. Four preference-based measures were covered: the EuroQoL-5 Dimensions, three-level version (n = 11), EuroQoL-5 Dimensions, five-level version (n = 2), Short Form questionnaire-6 Dimensions (n = 1) and Health Utility Index Mark 3 (n = 1). Sample sizes ranged from 852 to 136,327. For mapping between generic preference-based measures, data from FORWARD, the National Databank for Rheumatic Diseases (which includes the EuroQoL-5 Dimensions, three-level version, and EuroQoL-5 Dimensions, five-level version, in its 2011 wave), were used. MAIN METHODS DEVELOPED Mixture-model-based approaches for direct mapping, in which the dependent variable is the health utility value, including adaptations of methods developed to model the EuroQoL-5 Dimensions, three-level version, and beta regression mixtures, were developed, as were indirect methods, in which responses to the descriptive systems are modelled, for consistent multidirectional mapping between preference-based measures. A highly flexible approach was designed, using copulas to specify the bivariate distribution of each pair of EuroQoL-5 Dimensions, three-level version, and EuroQoL-5 Dimensions, five-level version, responses. RESULTS A range of criteria for assessing model performance is proposed. Theoretically, linear regression is inappropriate for mapping. Case studies confirm this. Flexible, direct mapping methods, based on different variants of mixture models with appropriate underlying distributions, perform very well for all preference-based measures. The precise form is important. Case studies show that a minimum of three components are required. Covariates representing disease severity are required as predictors of component membership. Beta-based mixtures perform similarly to the bespoke mixture approaches but necessitate detailed consideration of the number and location of probability masses. The flexible, bi-directional indirect approach performs well for testing differences between preference-based measures. LIMITATIONS Case studies drew heavily on EuroQoL-5 Dimensions. Indirect methods could not be undertaken for several case studies because of a lack of coverage. These methods will often be unfeasible for preference-based measures with complex descriptive systems. CONCLUSIONS Mapping requires appropriate methods to yield reliable results. Evidence shows that widely used methods such as linear regression are inappropriate. More flexible methods developed specifically for mapping show that close-fitting results can be achieved. Approaches based on mixture models are appropriate for all preference-based measures. Some features are universally required (such as the minimum number of components) but others must be assessed on a case-by-case basis (such as the location and number of probability mass points). FUTURE RESEARCH PRIORITIES Further research is recommended on (1) the use of the monotonicity concept, (2) the mismatch of trial and mapping distributions and measurement error and (3) the development of indirect methods drawing on methods developed for mapping between preference-based measures. FUNDING This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 34. See the NIHR Journals Library website for further project information. This project was also funded by a Medical Research Council grant (MR/L022575/1).
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Affiliation(s)
| | - Allan Wailoo
- School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
| | - Stephen Pudney
- School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
| | - Laura Gray
- School of Health and Related Research (ScHARR), University of Sheffield, Sheffield, UK
| | - Andrea Manca
- Centre for Health Economics, University of York, York, UK
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5
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Taylor SA, Mallett S, Miles A, Morris S, Quinn L, Clarke CS, Beare S, Bridgewater J, Goh V, Janes S, Koh DM, Morton A, Navani N, Oliver A, Padhani A, Punwani S, Rockall A, Halligan S. Whole-body MRI compared with standard pathways for staging metastatic disease in lung and colorectal cancer: the Streamline diagnostic accuracy studies. Health Technol Assess 2019; 23:1-270. [PMID: 31855148 PMCID: PMC6936168 DOI: 10.3310/hta23660] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Whole-body magnetic resonance imaging is advocated as an alternative to standard pathways for staging cancer. OBJECTIVES The objectives were to compare diagnostic accuracy, efficiency, patient acceptability, observer variability and cost-effectiveness of whole-body magnetic resonance imaging and standard pathways in staging newly diagnosed non-small-cell lung cancer (Streamline L) and colorectal cancer (Streamline C). DESIGN The design was a prospective multicentre cohort study. SETTING The setting was 16 NHS hospitals. PARTICIPANTS Consecutive patients aged ≥ 18 years with histologically proven or suspected colorectal (Streamline C) or non-small-cell lung cancer (Streamline L). INTERVENTIONS Whole-body magnetic resonance imaging. Standard staging investigations (e.g. computed tomography and positron emission tomography-computed tomography). REFERENCE STANDARD Consensus panel decision using 12-month follow-up data. MAIN OUTCOME MEASURES The primary outcome was per-patient sensitivity difference between whole-body magnetic resonance imaging and standard staging pathways for metastasis. Secondary outcomes included differences in specificity, the nature of the first major treatment decision, time and number of tests to complete staging, patient experience and cost-effectiveness. RESULTS Streamline C - 299 participants were included. Per-patient sensitivity for metastatic disease was 67% (95% confidence interval 56% to 78%) and 63% (95% confidence interval 51% to 74%) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference in sensitivity of 4% (95% confidence interval -5% to 13%; p = 0.51). Specificity was 95% (95% confidence interval 92% to 97%) and 93% (95% confidence interval 90% to 96%) respectively, a difference of 2% (95% confidence interval -2% to 6%). Pathway treatment decisions agreed with the multidisciplinary team treatment decision in 96% and 95% of cases, respectively, a difference of 1% (95% confidence interval -2% to 4%). Time for staging was 8 days (95% confidence interval 6 to 9 days) and 13 days (95% confidence interval 11 to 15 days) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference of 5 days (95% confidence interval 3 to 7 days). The whole-body magnetic resonance imaging pathway was cheaper than the standard staging pathway: £216 (95% confidence interval £211 to £221) versus £285 (95% confidence interval £260 to £310). Streamline L - 187 participants were included. Per-patient sensitivity for metastatic disease was 50% (95% confidence interval 37% to 63%) and 54% (95% confidence interval 41% to 67%) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference in sensitivity of 4% (95% confidence interval -7% to 15%; p = 0.73). Specificity was 93% (95% confidence interval 88% to 96%) and 95% (95% confidence interval 91% to 98%), respectively, a difference of 2% (95% confidence interval -2% to 7%). Pathway treatment decisions agreed with the multidisciplinary team treatment decision in 98% and 99% of cases, respectively, a difference of 1% (95% confidence interval -2% to 4%). Time for staging was 13 days (95% confidence interval 12 to 14 days) and 19 days (95% confidence interval 17 to 21 days) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference of 6 days (95% confidence interval 4 to 8 days). The whole-body magnetic resonance imaging pathway was cheaper than the standard staging pathway: £317 (95% confidence interval £273 to £361) versus £620 (95% confidence interval £574 to £666). Participants generally found whole-body magnetic resonance imaging more burdensome than standard imaging but most participants preferred the whole-body magnetic resonance imaging staging pathway if it reduced time to staging and/or number of tests. LIMITATIONS Whole-body magnetic resonance imaging was interpreted by practitioners blinded to other clinical data, which may not fully reflect how it is used in clinical practice. CONCLUSIONS In colorectal and non-small-cell lung cancer, the whole-body magnetic resonance imaging staging pathway has similar accuracy to standard staging pathways, is generally preferred by patients, improves staging efficiency and has lower staging costs. Future work should address the utility of whole-body magnetic resonance imaging for treatment response assessment. TRIAL REGISTRATION Current Controlled Trials ISRCTN43958015 and ISRCTN50436483. FUNDING This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 23, No. 66. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Stuart A Taylor
- Centre for Medical Imaging, University College London, London, UK
| | - Susan Mallett
- Institute of Applied Health Research, NIHR Birmingham Biomedical Research Centre, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Anne Miles
- Department of Psychological Sciences, Birkbeck, University of London, London, UK
| | - Stephen Morris
- Applied Health Research, University College London, London, UK
| | - Laura Quinn
- Institute of Applied Health Research, NIHR Birmingham Biomedical Research Centre, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Caroline S Clarke
- Research Department of Primary Care and Population Health, and Priment Clinical Trials Unit, University College London, London, UK
| | - Sandy Beare
- Cancer Research UK & UCL Cancer Trials Centre, University College London, London, UK
| | | | - Vicky Goh
- Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Sam Janes
- Lungs for Living Research Centre, UCL Respiratory, University College London, London, UK
| | - Dow-Mu Koh
- Department of Radiology, The Royal Marsden Hospital, Sutton, UK
| | - Alison Morton
- c/o Centre for Medical Imaging, University College London, London, UK
| | - Neal Navani
- Lungs for Living Research Centre, UCL Respiratory, University College London, London, UK
| | - Alfred Oliver
- c/o Centre for Medical Imaging, University College London, London, UK
| | - Anwar Padhani
- Mount Vernon Centre for Cancer Treatment, Mount Vernon Hospital, Northwood, UK
| | - Shonit Punwani
- Centre for Medical Imaging, University College London, London, UK
| | - Andrea Rockall
- Imaging Department, Imperial College Healthcare NHS Trust, London, UK
| | - Steve Halligan
- Centre for Medical Imaging, University College London, London, UK
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Swinnen TW, Milosevic M, Van Huffel S, Dankaerts W, Westhovens R, de Vlam K. Instrumented BASFI (iBASFI) Shows Promising Reliability and Validity in the Assessment of Activity Limitations in Axial Spondyloarthritis. J Rheumatol 2016; 43:1532-40. [PMID: 27307537 DOI: 10.3899/jrheum.150439] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/19/2016] [Indexed: 11/22/2022]
Abstract
OBJECTIVE The Bath Ankylosing Spondylitis Functional Index (BASFI) is the most popular method to assess activity capacity in axial spondyloarthritis (axSpA), to our knowledge. It is endorsed by the Assessment of Spondyloarthritis international Society. But it may have recall bias or aberrant self-judgments in individual patients. Therefore, we aimed to (1) develop the instrumented BASFI (iBASFI) by adding a body-worn accelerometer with automated algorithms to performance-based measurements (PBM), (2) study the iBASFI's core psychometric properties, and (3) reduce the number of iBASFI items. METHODS Twenty-eight patients with axSpA wore a 2-axial accelerometer while completing 12 PBM derived from the BASFI. A chronometer and both manual and "automated algorithm-based" acceleration segmentation identified movement time. Test-retest trials and methods (algorithm vs manual segmentation/chronometer/BASFI) were compared with ICC, standard error of measurement [percentage of movement time (SEM%)], and Spearman ρ correlation coefficients. Linear regression identified the optimal set of reliable iBASFI PBM. RESULTS Good to excellent test-retest reliability was found for 8/12 iBASFI items (ICC range 0.812-0.997, SEM range 0.4-30.4%), typically with repeated and fast movements. Automated algorithms excellently mimicked manual segmentation (ICC range 0.900-0.998) and the chronometer (ICC range 0.878-0.998) for 10/12 iBASFI items. Construct validity compared with the BASFI was confirmed for 7/12 iBASFI items (δ range 0.504-0.755). Together, sit-to-stand speed test (stBeta 0.483), cervical rotation (stBeta -0.392), and height (stBeta -0.375) explained 59% of the variance in the BASFI (p < 0.01). CONCLUSION The proof-of-concept iBASFI showed promising reliability and validity in measuring activity capacity. The number of the iBASFI's PBM may be minimized, but further validation in larger axSpA cohorts is needed before its clinical use.
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Affiliation(s)
- Thijs Willem Swinnen
- From the Division of Rheumatology, University Hospitals Leuven; Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven; iMinds, Medical Information Technology, KU Leuven, Leuven, Belgium.T.W. Swinnen, PT, MSc, Doctoral Research Fellow, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven, and Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; M. Milosevic, MSc Eng, Doctoral Research Fellow, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; S. Van Huffel, MSc Eng, PhD, Full Professor Biomedical Data Processing, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; W. Dankaerts, PT, PhD, Professor Rehabilitation Sciences, Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; R. Westhovens, MD, PhD, Full Professor Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; K. de Vlam, MD, PhD, Principal Investigator Clinical Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven
| | - Milica Milosevic
- From the Division of Rheumatology, University Hospitals Leuven; Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven; iMinds, Medical Information Technology, KU Leuven, Leuven, Belgium.T.W. Swinnen, PT, MSc, Doctoral Research Fellow, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven, and Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; M. Milosevic, MSc Eng, Doctoral Research Fellow, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; S. Van Huffel, MSc Eng, PhD, Full Professor Biomedical Data Processing, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; W. Dankaerts, PT, PhD, Professor Rehabilitation Sciences, Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; R. Westhovens, MD, PhD, Full Professor Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; K. de Vlam, MD, PhD, Principal Investigator Clinical Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven
| | - Sabine Van Huffel
- From the Division of Rheumatology, University Hospitals Leuven; Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven; iMinds, Medical Information Technology, KU Leuven, Leuven, Belgium.T.W. Swinnen, PT, MSc, Doctoral Research Fellow, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven, and Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; M. Milosevic, MSc Eng, Doctoral Research Fellow, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; S. Van Huffel, MSc Eng, PhD, Full Professor Biomedical Data Processing, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; W. Dankaerts, PT, PhD, Professor Rehabilitation Sciences, Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; R. Westhovens, MD, PhD, Full Professor Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; K. de Vlam, MD, PhD, Principal Investigator Clinical Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven
| | - Wim Dankaerts
- From the Division of Rheumatology, University Hospitals Leuven; Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven; iMinds, Medical Information Technology, KU Leuven, Leuven, Belgium.T.W. Swinnen, PT, MSc, Doctoral Research Fellow, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven, and Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; M. Milosevic, MSc Eng, Doctoral Research Fellow, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; S. Van Huffel, MSc Eng, PhD, Full Professor Biomedical Data Processing, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; W. Dankaerts, PT, PhD, Professor Rehabilitation Sciences, Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; R. Westhovens, MD, PhD, Full Professor Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; K. de Vlam, MD, PhD, Principal Investigator Clinical Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven
| | - Rene Westhovens
- From the Division of Rheumatology, University Hospitals Leuven; Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven; iMinds, Medical Information Technology, KU Leuven, Leuven, Belgium.T.W. Swinnen, PT, MSc, Doctoral Research Fellow, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven, and Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; M. Milosevic, MSc Eng, Doctoral Research Fellow, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; S. Van Huffel, MSc Eng, PhD, Full Professor Biomedical Data Processing, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; W. Dankaerts, PT, PhD, Professor Rehabilitation Sciences, Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; R. Westhovens, MD, PhD, Full Professor Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; K. de Vlam, MD, PhD, Principal Investigator Clinical Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven
| | - Kurt de Vlam
- From the Division of Rheumatology, University Hospitals Leuven; Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven; iMinds, Medical Information Technology, KU Leuven, Leuven, Belgium.T.W. Swinnen, PT, MSc, Doctoral Research Fellow, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven, and Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; M. Milosevic, MSc Eng, Doctoral Research Fellow, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; S. Van Huffel, MSc Eng, PhD, Full Professor Biomedical Data Processing, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering, KU Leuven, and iMinds, Medical Information Technology, KU Leuven; W. Dankaerts, PT, PhD, Professor Rehabilitation Sciences, Musculoskeletal Rehabilitation Research Unit, Department of Rehabilitation Sciences, KU Leuven; R. Westhovens, MD, PhD, Full Professor Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven; K. de Vlam, MD, PhD, Principal Investigator Clinical Rheumatology, Division of Rheumatology, University Hospitals Leuven, and Skeletal Biology and Engineering Research Center, Department of Development and Regeneration, KU Leuven.
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