PROSAIC-DS Study (PROState AI in Cancer - Decision Support)

Prostate Cancer Clinical Trial

— PROSAIC-DS  

Official title:

PROSAIC-DS (PROState AI in Cancer - Decision Support): Evaluation of the Deontics AI Platform for Evidence-based Treatment Planning in Multidisciplinary Cancer Care: Increasing Compliance and Streamlining MDTs in Prostate Cancer

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05355727
• Other study ID #: 304825
• Status: Not yet recruiting
• Phase: N/A
• Start date: June 2022
• Est. completion date: December 2022

Study information

• Verified date: April 2022
• Source: Guy's and St Thomas' NHS Foundation Trust
• Contact: Danny Ruta, MBBS MSc
• Phone: +44 (0)7969917016
• Email: Danny.Ruta[@]gstt.nhs.uk
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Around 375,000 cancers are diagnosed in the UK annually, with this figure expected to reach 500,000 by 2035. As the number of different cancer treatment options and our scientific understanding continue to grow rapidly, it can be difficult for clinicians to keep up-to-date with best practice, causing unjustified variations in the quality of care and clinical outcomes for patients.

Currently, when a patient has been referred to and seen by a clinician, their treatment is then discussed in a Multi-Disciplinary Team Meeting (MDTM). MDTM is a meeting of medical experts, including Surgeons, Oncologists, Nurses, and specialists in cancer, imaging and diagnosis. This is the case even if a treatment decision is straightforward.

A nationwide review published by CRUK in 2017 highlighted the demands on cancer teams and the MDTM process:

• Increased caseloads are causing dramatic increases in the time spent by clinicians in MDTMs, leading to an unsustainable rise in costs: the cost in England has increased from £88m to £159m in 4 years;

• There is not enough time in the MDTM to discuss complex cases;

• There is a failure to involve patients in the decision-making process: around 75% of patients feel their views are unrepresented in MDTMs; In our study we are looking at the potential of technology - particularly Clinical Decision Support Systems (CDSS) - to improve MDTM decision making.

Deontics has a CE marked AI-based CDSS that integrates individual patient data and preferences with evidence-based clinical guidelines. This dynamically and transparently generates best-practice, individualised treatment recommendations which can help determine treatment. Deontics' AI tool has already been shown to provide personalised recommendations concordant with UK best practice while incorporating patient values, and can be used to safely triage less complex patients straight to treatment with minimal clinical oversight. Our project partners with Deontics to develop PROSAIC-DS - A CDSS for prostate cancer.

Description:

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Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 1040
• Est. completion date: December 2022
• Est. primary completion date: December 2022
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Male
• Age group: 35 Years and older

Eligibility

Inclusion Criteria:

• All patients referred to the GSTT and KCH Prostate MDT meetings where sufficient information is available for the MDT to make a treatment decision (approximately 40-50 per week) will be eligible for the study.

Exclusion Criteria:

• If data available for patients is not adequate to make any treatment decisions they will be excluded. Non-consenting patients will be excluded.

Related Conditions & MeSH terms

• Prostate Cancer
• Prostatic Neoplasms

Intervention

Other:
• Clinical decision support tool recommended outcome
The PROSAIC-DS tool will take the variables and produce a suggested outcome. It will supply supporting evidence and best practice for its recommendations

Locations

Country	Name	City	State
United Kingdom	Guys and St Thomas Hospitals	London
United Kingdom	Kings College Hospital	London

Sponsors (6)

Lead Sponsor	Collaborator
Guy's and St Thomas' NHS Foundation Trust	Deontics Limited, King's College Hospital NHS Trust, King's College London, Prostate Cancer UK, Somerset NHS Foundation Trust

Country where clinical trial is conducted

United Kingdom, 

References & Publications (12)

Bury J, Hurt C, Roy A, Cheesman L, Bradburn M, Cross S, Fox J, Saha V. LISA: a web-based decision-support system for trial management of childhood acute lymphoblastic leukaemia. Br J Haematol. 2005 Jun;129(6):746-54. — View Citation

Knight SR, Cao KN, South M, Hayward N, Hunter JP, Fox J. Development of a Clinical Decision Support System for Living Kidney Donor Assessment Based on National Guidelines. Transplantation. 2018 Oct;102(10):e447-e453. doi: 10.1097/TP.0000000000002374. — View Citation

Miles A, Chronakis I, Fox J, Mayer A. Use of a computerised decision aid (DA) to inform the decision process on adjuvant chemotherapy in patients with stage II colorectal cancer: development and preliminary evaluation. BMJ Open. 2017 Mar 24;7(3):e012935. doi: 10.1136/bmjopen-2016-012935. — View Citation

Munro AJ. Multidisciplinary Team Meetings in Cancer Care: An Idea Whose Time has Gone? Clin Oncol (R Coll Radiol). 2015 Dec;27(12):728-31. doi: 10.1016/j.clon.2015.08.008. Epub 2015 Sep 11. — View Citation

Patkar V, Acosta D, Davidson T, Jones A, Fox J, Keshtgar M. Cancer multidisciplinary team meetings: evidence, challenges, and the role of clinical decision support technology. Int J Breast Cancer. 2011;2011:831605. doi: 10.4061/2011/831605. Epub 2011 Jul 17. — View Citation

Patkar V, Acosta D, Davidson T, Jones A, Fox J, Keshtgar M. Using computerised decision support to improve compliance of cancer multidisciplinary meetings with evidence-based guidance. BMJ Open. 2012 Jun 25;2(3). pii: e000439. doi: 10.1136/bmjopen-2011-000439. Print 2012. — View Citation

Patkar V, Fox J. Clinical guidelines and care pathways: a case study applying PROforma decision support technology to the breast cancer care pathway. Stud Health Technol Inform. 2008;139:233-42. — View Citation

Patkar V, Hurt C, Steele R, Love S, Purushotham A, Williams M, Thomson R, Fox J. Evidence-based guidelines and decision support services: A discussion and evaluation in triple assessment of suspected breast cancer. Br J Cancer. 2006 Dec 4;95(11):1490-6. Epub 2006 Nov 21. — View Citation

Peleg M, Fox J, Patkar V, Glasspool D, Chronakis I, South M, Nassar S, Gaglia JL, Gharib H, Papini E, Paschke R, Duick DS, Valcavi R, Hegedüs L, Garber JR. A Computer-Interpretable Version of the AACE, AME, ETA Medical Guidelines for Clinical Practice for the Diagnosis and Management of Thyroid Nodules. Endocr Pract. 2014 Apr;20(4):352-9. doi: 10.4158/EP13271.OR. — View Citation

Taylor C, Atkins L, Richardson A, Tarrant R, Ramirez AJ. Measuring the quality of MDT working: an observational approach. BMC Cancer. 2012 May 29;12:202. doi: 10.1186/1471-2407-12-202. — View Citation

Tural C, Ruiz L, Holtzer C, Schapiro J, Viciana P, González J, Domingo P, Boucher C, Rey-Joly C, Clotet B; Havana Study Group. Clinical utility of HIV-1 genotyping and expert advice: the Havana trial. AIDS. 2002 Jan 25;16(2):209-18. — View Citation

Walton RT, Gierl C, Yudkin P, Mistry H, Vessey MP, Fox J. Evaluation of computer support for prescribing (CAPSULE) using simulated cases. BMJ. 1997 Sep 27;315(7111):791-5. — View Citation

* Note: There are 12 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	PROSAIC-DS as a triage tool	The % of patients the PROSAIC-DS tool can appropriately triage away non-complex Prostate Cancer cases from the MDTM with appropriate treatment plans as directed by approved guidelines (EAU, BAUS, NICE, AUA).	6-9 months
Primary	PROSAIC-DS influence on MDTM concordance with approved guidelines	Evaluation of PROSAIC-DS as a member of the MDTM via the impact of live PROSAIC-DS recommendations on MDTM decision concordance with approved guidelines (EAU, BAUS, NICE, AUA) on randomised patients discussed in the MDTM. This is measured through the difference in level of concordance between the MDTM with PROSAIC-DS switched off and the MDTM with PROSAIC-DS on when less complex cases (ones triaged away) are excluded.	6-9 months
Secondary	Cost effectiveness of PROSAIC-DS	Estimate the financial savings that PROSAIC-DS brings by triaging non-complex cases away from the MDTM.	6-9 months - duration of data collection
Secondary	Qualitative Analysis: Patient acceptability	We will use qualitative methods, and data capture methods including self-administered questionnaires, focus groups, semi-structured interviews and video analysis, to explore patient and staff views about, including concerns and satisfaction with, the use of AI technology to support clinical decisions in prostate cancer, both prior to their engagement with PROSAIC-DS, during and after deployment of the tool of the technology to patients.	12 months

External Links

•   Meeting Patients Needs: Improving the effectiveness of Multidisciplinary Team Meetings in Cancer Services. 2018
•   NHS England : Streamlining Multi-Disciplinary Team Meetings
•   Transforming Multidisciplinary Team Meetings (MDTMs): Report by Prof Martin Gore (2017) for NHS England