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

NCT ID: NCT05355727

Last Updated: 2022-05-02

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

1040 participants

Study Classification

INTERVENTIONAL

Study Start Date

2022-06-30

Study Completion Date

2022-12-31

Brief Summary

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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.

Detailed Description

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I

Conditions

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Prostate Cancer

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

OTHER

Blinding Strategy

DOUBLE

Participants Outcome Assessors

Study Groups

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Arm A: Visible to MDTM

Patients going through this arm have the decision support tool outcome visible to the MDTM

Group Type OTHER

Clinical decision support tool recommended outcome

Intervention Type OTHER

The PROSAIC-DS tool will take the variables and produce a suggested outcome. It will supply supporting evidence and best practice for its recommendations

Arm B: Not-visible to MDTM

Patients going through this arm will not have the decision support tool outcome visible to the MDTM

Group Type OTHER

Clinical decision support tool recommended outcome

Intervention Type OTHER

The PROSAIC-DS tool will take the variables and produce a suggested outcome. It will supply supporting evidence and best practice for its recommendations

Interventions

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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

Intervention Type OTHER

Eligibility Criteria

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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.
Minimum Eligible Age

35 Years

Eligible Sex

MALE

Accepts Healthy Volunteers

Yes

Sponsors

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King's College Hospital NHS Trust

OTHER

Sponsor Role collaborator

King's College London

OTHER

Sponsor Role collaborator

Deontics Limited

UNKNOWN

Sponsor Role collaborator

Somerset NHS Foundation Trust

OTHER

Sponsor Role collaborator

Prostate Cancer UK

OTHER

Sponsor Role collaborator

Guy's and St Thomas' NHS Foundation Trust

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Danny Ruta, MBBS MSc

Role: PRINCIPAL_INVESTIGATOR

Guys and St Thomas NHS Foundation Trust

Locations

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Guys and St Thomas Hospitals

London, , United Kingdom

Site Status

Kings College Hospital

London, , United Kingdom

Site Status

Countries

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United Kingdom

Central Contacts

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Danny Ruta, MBBS MSc

Role: CONTACT

+44 (0)7969917016

Kate Dodgson, LLB LLM

Role: CONTACT

+447704783880

Facility Contacts

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Danny Ruta, MBBS MSc

Role: primary

+44 (0)7969917016

Jonathan Makanjuola, MBBS BSc

Role: primary

+447939512119

References

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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.

Reference Type BACKGROUND
PMID: 30028418 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 22642614 (View on PubMed)

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. No abstract available.

Reference Type BACKGROUND
PMID: 26365047 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 22295234 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 28341685 (View on PubMed)

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):e000439. doi: 10.1136/bmjopen-2011-000439. Print 2012.

Reference Type BACKGROUND
PMID: 22734113 (View on PubMed)

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. doi: 10.1038/sj.bjc.6603470. Epub 2006 Nov 21.

Reference Type BACKGROUND
PMID: 17117181 (View on PubMed)

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, Hegedus 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.

Reference Type BACKGROUND
PMID: 24246343 (View on PubMed)

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. doi: 10.1111/j.1365-2141.2005.05541.x.

Reference Type BACKGROUND
PMID: 15953000 (View on PubMed)

Tural C, Ruiz L, Holtzer C, Schapiro J, Viciana P, Gonzalez 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. doi: 10.1097/00002030-200201250-00010.

Reference Type BACKGROUND
PMID: 11807305 (View on PubMed)

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. doi: 10.1136/bmj.315.7111.791.

Reference Type BACKGROUND
PMID: 9345174 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 18806332 (View on PubMed)

Related Links

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https://www.cancerresearchuk.org/sites/default/files/full_report_meeting_patients_needs_improving_the_effectiveness_of_multidisciplinary_team_meetings_.pdf

Meeting Patients Needs: Improving the effectiveness of Multidisciplinary Team Meetings in Cancer Services. 2018

https://www.england.nhs.uk/wp-content/uploads/sites/6/2018/10/Transforming-MDTM-Martin-Gore-August-2017.pdf

Transforming Multidisciplinary Team Meetings (MDTMs): Report by Prof Martin Gore (2017) for NHS England

Other Identifiers

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304825

Identifier Type: -

Identifier Source: org_study_id

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