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AI-Assisted Acute Myeloid Leukemia Evaluation With the Leukemia End-to-End Analysis Platform (LEAP) Versus Clinician-Only Assessment

NCT07203885 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 10

Last updated 2025-10-31

No results posted yet for this study

Summary

This study will test whether artificial intelligence (AI) can help doctors diagnose a rare blood cancer called acute promyelocytic leukemia (APL) more quickly and accurately. Doctors usually examine bone marrow samples under a microscope to make this diagnosis, but it can be challenging and time-consuming.

In this study, doctors will review bone marrow samples under three different conditions:

* Unaided Review: Without AI assistance.
* AI as Double-Check: AI-generated evaluation shown after the doctor makes an initial decision.
* AI as First Look: AI-generated evaluation shown at the start of the review.

Doctors will be randomly assigned to different orders of these three conditions. This design will allow us to compare how AI support affects diagnostic accuracy, speed, and confidence.

Conditions

  • Acute Promyelocytic Leukemia (APL)
  • Acute Myeloid Leukaemia (AML)

Interventions

BEHAVIORAL

Unaided Review First, Then AI-Assisted Review

Readers first complete Block X (Unaided) on their assigned subset SX (34 slides). They then complete Block Y (AI-Assisted) on two separate subsets: SY1 (34 slides; AI as Double-Check) and SY2 (34 slides; AI as First Look). Within Block Y, the order of Y1 and Y2 is randomized. For each reader, SX, SY1, and SY2 are disjoint and stratified by APL status.

BEHAVIORAL

AI-Assisted Review First, Then Unaided Review

Readers first complete Block Y (AI-Assisted) on two assigned subsets: SY1 (up to 40 slides; AI as Double-Check) and SY2 (up to 40 slides; AI as First Look), with the order of Y1 and Y2 randomized. They then complete Block X (Unaided) on subset SX (up to 40 slides). For each reader, SX, SY1, and SY2 are disjoint and stratified by APL status.

Sponsors & Collaborators

  • National Taiwan University Hospital

    collaborator OTHER

  • Far Eastern Memorial Hospital

    collaborator OTHER

  • Taipei Veterans General Hospital, Taiwan

    collaborator OTHER_GOV

  • Brigham and Women's Hospital

    collaborator OTHER

  • Massachusetts General Hospital

    collaborator OTHER

  • Harvard Medical School (HMS and HSDM)

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
TRIPLE
Model
CROSSOVER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-09-09
Primary Completion
2025-10-10
Completion
2025-10-10

Countries

  • United States

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07203885 on ClinicalTrials.gov