Statistical analysis plan for the ARtificially Intelligent image fusion system versus standard treatment to guide endovascular Aortic aneurysm repair (ARIA): a multi-centre randomised controlled trial
Abstract Background Aortic aneurysms, a significant cause of mortality, particularly in individuals aged 55 years and older, have witnessed a transformative shift in treatment strategies with the advent of endovascular surgery. Cydar-EV is an innovative image fusion technology that can augment preop...
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2025-04-01
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| Online Access: | https://doi.org/10.1186/s13063-025-08770-5 |
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| author | Hatem A. Wafa James Budge Tom Carrell Medeah Yaqub Matt Waltham Izabela Pilecka Joanna Kelly Caroline Murphy Stephen Palmer Rachel E. Clough Yanzhong Wang |
| author_facet | Hatem A. Wafa James Budge Tom Carrell Medeah Yaqub Matt Waltham Izabela Pilecka Joanna Kelly Caroline Murphy Stephen Palmer Rachel E. Clough Yanzhong Wang |
| author_sort | Hatem A. Wafa |
| collection | DOAJ |
| description | Abstract Background Aortic aneurysms, a significant cause of mortality, particularly in individuals aged 55 years and older, have witnessed a transformative shift in treatment strategies with the advent of endovascular surgery. Cydar-EV is an innovative image fusion technology that can augment preoperative planning and surgical guidance of endovascular aneurysm repair (EVAR). The ARIA trial aims to evaluate the efficacy of using Cydar-EV with EVAR procedures to reduce operating time while enhancing procedural precision, patient outcomes, and cost-effectiveness. This paper describes the statistical analysis plan for the study. Methods/design The ARIA trial, a phase III, multi-centre, open-label, two-armed, parallel groups randomised controlled surgical trial, seeks to recruit 340 patients diagnosed with abdominal or thoraco-abdominal aortic aneurysms. Participants are randomly assigned to receive either standard endovascular repair or an endovascular repair assisted by Cydar-EV for planning and surgical guidance. Primary and secondary outcomes are assessed at baseline, 4–12 weeks, and 52 weeks. The primary outcome measure is procedure duration at baseline, while additional secondary outcomes are recorded at various time points and include indicators for technical effectiveness, patient outcomes, procedure efficiency, and cost-effectiveness. We plan to analyse the patient outcome data according to the treatment they received regardless of initial allocation. The statistical analysis plan outlines methods for handling missing data, covariates for adjusted analyses, and planned sensitivity analyses to ensure robust evaluation of treatment effects. Trial registration The trial was registered with the ISRCTN register on 03/12/2021, number ISRCTN13832085. |
| format | Article |
| id | doaj-art-72b3f08ceaf8451eaa9fc7dceb21162a |
| institution | DOAJ |
| issn | 1745-6215 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Trials |
| spelling | doaj-art-72b3f08ceaf8451eaa9fc7dceb21162a2025-08-20T02:55:39ZengBMCTrials1745-62152025-04-012611810.1186/s13063-025-08770-5Statistical analysis plan for the ARtificially Intelligent image fusion system versus standard treatment to guide endovascular Aortic aneurysm repair (ARIA): a multi-centre randomised controlled trialHatem A. Wafa0James Budge1Tom Carrell2Medeah Yaqub3Matt Waltham4Izabela Pilecka5Joanna Kelly6Caroline Murphy7Stephen Palmer8Rachel E. Clough9Yanzhong Wang10School of Biomedical Engineering and Imaging Science, King’s College LondonSchool of Biomedical Engineering and Imaging Science, King’s College LondonCydar Medical LimitedKing’s Clinical Trial Unit, King’s College LondonCydar Medical LimitedKing’s Clinical Trial Unit, King’s College LondonKing’s Clinical Trial Unit, King’s College LondonKing’s Clinical Trial Unit, King’s College LondonCentre for Health Economics, University of YorkSchool of Biomedical Engineering and Imaging Science, King’s College LondonSchool of Life Course and Population Sciences, King’s College LondonAbstract Background Aortic aneurysms, a significant cause of mortality, particularly in individuals aged 55 years and older, have witnessed a transformative shift in treatment strategies with the advent of endovascular surgery. Cydar-EV is an innovative image fusion technology that can augment preoperative planning and surgical guidance of endovascular aneurysm repair (EVAR). The ARIA trial aims to evaluate the efficacy of using Cydar-EV with EVAR procedures to reduce operating time while enhancing procedural precision, patient outcomes, and cost-effectiveness. This paper describes the statistical analysis plan for the study. Methods/design The ARIA trial, a phase III, multi-centre, open-label, two-armed, parallel groups randomised controlled surgical trial, seeks to recruit 340 patients diagnosed with abdominal or thoraco-abdominal aortic aneurysms. Participants are randomly assigned to receive either standard endovascular repair or an endovascular repair assisted by Cydar-EV for planning and surgical guidance. Primary and secondary outcomes are assessed at baseline, 4–12 weeks, and 52 weeks. The primary outcome measure is procedure duration at baseline, while additional secondary outcomes are recorded at various time points and include indicators for technical effectiveness, patient outcomes, procedure efficiency, and cost-effectiveness. We plan to analyse the patient outcome data according to the treatment they received regardless of initial allocation. The statistical analysis plan outlines methods for handling missing data, covariates for adjusted analyses, and planned sensitivity analyses to ensure robust evaluation of treatment effects. Trial registration The trial was registered with the ISRCTN register on 03/12/2021, number ISRCTN13832085.https://doi.org/10.1186/s13063-025-08770-5 |
| spellingShingle | Hatem A. Wafa James Budge Tom Carrell Medeah Yaqub Matt Waltham Izabela Pilecka Joanna Kelly Caroline Murphy Stephen Palmer Rachel E. Clough Yanzhong Wang Statistical analysis plan for the ARtificially Intelligent image fusion system versus standard treatment to guide endovascular Aortic aneurysm repair (ARIA): a multi-centre randomised controlled trial Trials |
| title | Statistical analysis plan for the ARtificially Intelligent image fusion system versus standard treatment to guide endovascular Aortic aneurysm repair (ARIA): a multi-centre randomised controlled trial |
| title_full | Statistical analysis plan for the ARtificially Intelligent image fusion system versus standard treatment to guide endovascular Aortic aneurysm repair (ARIA): a multi-centre randomised controlled trial |
| title_fullStr | Statistical analysis plan for the ARtificially Intelligent image fusion system versus standard treatment to guide endovascular Aortic aneurysm repair (ARIA): a multi-centre randomised controlled trial |
| title_full_unstemmed | Statistical analysis plan for the ARtificially Intelligent image fusion system versus standard treatment to guide endovascular Aortic aneurysm repair (ARIA): a multi-centre randomised controlled trial |
| title_short | Statistical analysis plan for the ARtificially Intelligent image fusion system versus standard treatment to guide endovascular Aortic aneurysm repair (ARIA): a multi-centre randomised controlled trial |
| title_sort | statistical analysis plan for the artificially intelligent image fusion system versus standard treatment to guide endovascular aortic aneurysm repair aria a multi centre randomised controlled trial |
| url | https://doi.org/10.1186/s13063-025-08770-5 |
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