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Design and Validation of a Generative AI and Propensity Score Matching Model for the VEN-DEC Phase II Study in Elderly AML Eligible for Allo-SCT; Evaluation of an Exploratory Approach Respect to a Randomized Phase III Trial

Design and Validation of a Generative AI and Propensity Score Matching Model for the VEN-DEC Phase II Study in Elderly AML Eligible for Allo-SCT; Evaluation of an Exploratory Approach Respect to a Randomized Phase III Trial

Recruiting
18-75 years
All
Phase N/A
  • Technical (Original)
  • Simplified (AI rewritten)

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Overview

To better delineate the contribution of VEN-DEC to the treatment of AML patients aged between ≥ 60 and \< 75 years and deemed fit for Allo-HSCT, real-world data on a patient-level basis will be collected and utilized to generate a matched control cohort of same AML patients treated with intensive chemotherapy.

In addittion, to further validate the efficacy of the VEN-DEC treatment approach in elderly AML patients, an advanced generative AI model will be constructed and trained using the historical cohort data. The AI model aims to simulate outcomes based on the standard

Eligibility

Inclusion Criteria:

  • Patients with AML treated with cht (historical cohort) or VenDec (experimental cohort)

Exclusion Criteria:

\-

Study details
    Acute Myeloid Leukemia

NCT07420790

Azienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia

13 May 2026

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