Preferred Reporting Items for Systematic Reviews and Meta-Analyses - Artificial Intelligence Extension

NCT05382455 | Unknown

• 1 other identifier: UP-22-00370
• Study Type: observational
• Target: 150
• Locations: 1 country
• Sites: 1

Brief Summary

The investigators aim to develop the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Artificial Intelligence Extension (PRISMA-AI) guideline as a stand-alone extension of the PRISMA statement, modified to reflect the particular requirements for the reporting of AI and its related topics (namely machine learning, deep learning, neuronal networking) in systematic reviews.

Conditions

Consensus Development

Outcome Measures

Primary Outcomes (1)

• Degree of consensus

  The level of agreement for all statements achieving consensus from the expert panel; consensus is predefined as ≥ 80% of the panel rating a given statement

  3 months

Study Arms (1)

Delphi Panel

A team of experts in the use AI technology in medicine together with experts in PRISMA, STARD-AI, CONSORT-AI, SPIRIT-AI, TRIPOD-AI, PROBAST-AI, CLAIM-AI and DECIDE-AI will evaluate the PRISMA-AI extension reporting guidelines

Other: Delphi Questionnaire

Interventions

Delphi Questionnaire OTHER

An invitation email, including a link to the survey, will be sent to the panel of experts in Ai in healthcare. The Delphi questionnaire will be administered via Welphi.com. In the first survey, panel members will outline the AI reporting standards in systematic reviews and objectively identify critical aspects of reporting methodology and results. In subsequent surveys, the expert panel will evaluate the modified criteria using a 1 to 5-point Likert scale with space provided for suggested edits and comments. Multiple rounds will be conducted until consensus is reached. After each round of Likert responses, the study team will calculate the agreement and distribution of responses. Likert responses will be dichotomized with positive values indicating agreement and neutral or negative values indicating disagreement. For the questions that do not reach a consensus of more than 80% in the first round or need further explanation, additional rounds of the survey may be performed.

Delphi Panel

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

A team of experts in the use AI technology in medicine together with experts in PRISMA, STARD-AI, CONSORT-AI, SPIRIT-AI, TRIPOD-AI, PROBAST-AI, CLAIM-AI and DECIDE-AI will evaluate the PRISMA-AI extension reporting guidelines.

You may qualify if:

• experts in the use AI technology in medicine
• experts in PRISMA
• leading authors of STARD-AI, CONSORT-AI, SPIRIT-AI, TRIPOD-AI, PROBAST-AI, CLAIM-AI and DECIDE-AI

You may not qualify if:

• Panelists who were not able to commit to all rounds of the modified Delphi process will be excluded

Sponsors & Collaborators

• University of Southern California: lead

Study Sites (1)

University of Southern California

Los Angeles, California, 90005, United States

Location

Related Publications (5)

• Ibrahim H, Liu X, Rivera SC, Moher D, Chan AW, Sydes MR, Calvert MJ, Denniston AK. Reporting guidelines for clinical trials of artificial intelligence interventions: the SPIRIT-AI and CONSORT-AI guidelines. Trials. 2021 Jan 6;22(1):11. doi: 10.1186/s13063-020-04951-6.

  PMID: 33407780 BACKGROUND

• Cruz Rivera S, Liu X, Chan AW, Denniston AK, Calvert MJ; SPIRIT-AI and CONSORT-AI Working Group. Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension. Lancet Digit Health. 2020 Oct;2(10):e549-e560. doi: 10.1016/S2589-7500(20)30219-3. Epub 2020 Sep 9.

  PMID: 33328049 BACKGROUND

• Sounderajah V, Ashrafian H, Aggarwal R, De Fauw J, Denniston AK, Greaves F, Karthikesalingam A, King D, Liu X, Markar SR, McInnes MDF, Panch T, Pearson-Stuttard J, Ting DSW, Golub RM, Moher D, Bossuyt PM, Darzi A. Developing specific reporting guidelines for diagnostic accuracy studies assessing AI interventions: The STARD-AI Steering Group. Nat Med. 2020 Jun;26(6):807-808. doi: 10.1038/s41591-020-0941-1. No abstract available.

  PMID: 32514173 BACKGROUND

• Collins GS, Dhiman P, Andaur Navarro CL, Ma J, Hooft L, Reitsma JB, Logullo P, Beam AL, Peng L, Van Calster B, van Smeden M, Riley RD, Moons KG. Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence. BMJ Open. 2021 Jul 9;11(7):e048008. doi: 10.1136/bmjopen-2020-048008.

  PMID: 34244270 BACKGROUND

• Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, Chou R, Glanville J, Grimshaw JM, Hrobjartsson A, Lalu MM, Li T, Loder EW, Mayo-Wilson E, McDonald S, McGuinness LA, Stewart LA, Thomas J, Tricco AC, Welch VA, Whiting P, Moher D. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021 Mar 29;372:n71. doi: 10.1136/bmj.n71.

  PMID: 33782057 RESULT

Study Officials

• Giovanni Cacciamani, MD

  University of Southern California

  STUDY CHAIR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assistant Professor of Research Urology and Radiology

Study Record Dates

• First Submitted: May 2, 2022
• First Posted: May 19, 2022
• Study Start: June 15, 2022
• Primary Completion: June 30, 2022
• Study Completion: July 15, 2022
• Last Updated: May 19, 2022

Record last verified: 2022-05

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)