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Optimal Methods of Disease Detection in Children and Young Adults With Acute Lymphoblastic Leukemia in the Pediatric Oncology Branch

Retrospective Study of Optimal Methods of Disease Detection in Children and Young Adults With Acute Lymphoblastic Leukemia in the Pediatric Oncology Branch

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03627208
Enrollment
150
Registered
2018-08-13
Start date
2018-08-02
Completion date
2022-04-14
Last updated
2022-06-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

ALL, Childhood, Leukemia, Lymphoblastic, Acute

Keywords

LYMPHOBLASTIC LYMPHOMA, Minimal Residual Disease, Childhood All, B-Cell Malignancies, Natural History

Brief summary

Background: Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. It occurs when a bone marrow cell develops errors in its DNA. Certain tests are used to help detect the disease. But the results of these tests often disagree. Researchers want to review the results of tests of bone marrow and cerebrospinal fluid (CSF) from people with ALL. They want to try to find the best ways to detect the disease. Objective: To compare results of certain bone marrow and CSF tests for detecting ALL, in order to see how much and how often the results disagreed. Eligibility: Children and young adults with ALL or lymphoblastic lymphoma who were enrolled in certain previous studies and consented for their data to be used. Design: Investigators will review participants medical records. They will collect data like the participant s gender, age, and when their tests were done. They will also collect results from tests like: Bone marrow tests Flow cytometry tests Imaging CSF cell count All of the stored data will be labeled by a code that only the study team at the research site can link to the participant. Data will be stored in password protected computers. ...

Detailed description

Minimal residual disease detection in the bone marrow is highly prognostic for disease relapse in patients with acute lymphoblastic leukemia (ALL) and is determined based on a single bone marrow aspirate sample. Our anecdotal experience over the past decade in the Pediatric Oncology Branch (POB) has led us to believe that a bone marrow aspirate as the only metric for disease detection may not be adequate, but a systematic review detailing our experience and reporting on instances where we have identified discrepancies in disease status has not been performed to confirm our hypothesis. Additionally, patients with ALL also may have CNS involvement by disease. Current standard of care assessment of disease in the central nervous system (CNS) consists of cerebrospinal (CSF) fluid sampling and evaluation for blasts by cytology only, which may not identify occult levels of CNS disease. Flow cytometry-based CSF testing is highly dependent on the media used for CNS specimens and the expertise of the center performing these studies. NCI Flow cytometry has established expertise in CNS disease evaluation. In evaluation of patients with ALL for POB treatment protocols, we have observed cases where there is a discrepancy between cytopathology and flow cytometry results. Recent literature in ALL indicates that subclinical CNS disease may be relevant to patient outcomes. With a primary goal of identifying the optimal methods for disease detection in ALL, this protocol is a retrospective chart review of bone marrow evaluations and cerebrospinal fluid results in patients with ALL or lymphoblastic lymphoma (LBL) who underwent treatment or evaluation in the Pediatric Oncology Branch of the National Cancer Institute. This study will not involve the use of specimens or participant contact. All data that is needed has already been collected and is available in CRIS records. Data will only be collected on patients with ALL or LBL where routine PET scans to follow EM disease, bone marrow and/or CSF evaluations were done as standard of care or on study and will largely be from trials where Dr. Nirali Shah is or has served as the PI (e.g., 12-C-0112, 15-C-0029.)

Interventions

None listed

Sponsors

National Cancer Institute (NCI)
Lead SponsorNIH

Study design

Observational model
COHORT
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
2 Years to 40 Years
Healthy volunteers
No

Inclusion criteria

* INCLUSION CRITERIA: Subjects with ALL or LBL enrolled in any of the source protocols: -98-C-0037, 08-C-0123, 10-C-0220, 11-C-0073, 12-C-0112, 14-C-0175, 15-C-0029, 18-C-0059

Exclusion criteria

Patients who opted out of storage of specimens/data for future use on prior studies will be excluded from this study.

Design outcomes

Primary

MeasureTime frameDescription
To identify the frequency and degree of disease discrepancies in identification of bone marrow involvement by ALL when comparing bone marrow biopsy to bone marrow aspirate to flow cytometric disease detection.1 yearTo identify the frequency and degree of disease discrepancies in identification of bone marrow involvement by ALL when comparing bone marrow biopsy to bone marrow aspirate to flow cytometric disease detection.
To identify the frequency of discrepancies in identification of CNS involvement by leukemia when comparing flow cytometry to cytopathology.1 yearTo identify the frequency of discrepancies in identification of CNS involvement by leukemia when comparing flow cytometry to cytopathology.
To identify and characterize immunophenotypic changes in leukemic cells over time and in response to targeted therapy.1 yearTo identify and characterize immunophenotypic changes in leukemic cells over time and in response to targeted therapy.
To comprehensively characterize EM disease including incidence, presentation, risk factors for and radiographic presentation of disease.1 yearTo comprehensively characterize EM disease including incidence, presentation, risk factors for and radiographic presentation of disease.

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026