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Multi-omics Approach of Risk Stratification for Patients With de Novo Acute Myeloid Leukemia

NCT05983172 · Status: ENROLLING_BY_INVITATION · Type: OBSERVATIONAL · Enrollment: 1500

Last updated 2023-08-14

No results posted yet for this study

Summary

The investigators will use machine learning to identify features on bone marrow smears and select features that are related to gene mutations, gene expression, or prognosis. The investigators will then use genome-wide transcriptomic profiling to investigate gene expression that is associated with patients' outcomes. The investigators will design a next-generation sequencing panel with unique molecular index and assess its feasibility and robustness in detecting measurable residual disease and optimize the panel/platform/bioinformatic pipeline. Finally, The investigators will use machine learning to integrate bone marrow smear features, gene mutations, gene expression, and measurable residual disease to construct a comprehensive risk assessment system that is based on multi-omics data. The investigators believe that such a platform will help physicians to design the most appropriate treatment strategies for individual patients, not only advancing the concept of precision medicine but also improving patients' prognoses.

Conditions

Sponsors & Collaborators

  • National Taiwan University Hospital

    lead OTHER

Principal Investigators

  • Xavier Cheng-Hong Tsai, MD, MSc, PhD · National Taiwan University Hospital

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-08-31
Primary Completion
2024-07-31
Completion
2026-07-31

Countries

  • Taiwan

Study Locations

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Entities

Diseases

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 NCT05983172 on ClinicalTrials.gov