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Assessment of lymphoma involvement in bone marrow by a novel cell-based liquid biopsy platform from blood sampling

Recruiting
Conditions
ewly diagnosed lymphoma of any subtypes aged greater than 18 years.
Newly diagnosed lymphoma of any subtypes and participants with normal white blood cell (WBC) counts and normal differential WBC counts from the last CBC result (within 1 year)
Registration Number
TCTR20220921002
Lead Sponsor
Siriraj Hospital Mahidol University
Brief Summary

Not available

Detailed Description

Not available

Recruitment & Eligibility

Status
Recruiting
Sex
All
Target Recruitment
176
Inclusion Criteria

1. Newly diagnosed lymphoma of any subtypes
2. Aged greater than 18 years
3. Participants with normal white blood cell (WBC) counts and normal differential WBC counts from the last CBC result (within 1 year)

Exclusion Criteria

1. Participants with known underlying diseases of hemolytic anemia
2. Participants with known underlying diseases of hematologic malignancy besides lymphoma
3. Participants with known underlying disease of neoplasms involving bone marrow
4. Participants with lymphocytosis (absolute lymphocyte count > 4,000/mcL)
5. Participants with a history of recently receiving blood transfusion within 4 weeks
6. Participants with a history of receiving chemotherapy within 4 weeks
7. Participants with a history of blood donation or recent blood loss greater than 250 mL within 4 weeks
8. Participants who receiving erythropoietin
9. Participants with GI mucosal involvement of lymphoma

Study & Design

Study Type
Observational
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
To evaluate the correlation between circulating erythroblast event elevation and abnormality and confirmed BMI in lymphoma patients by BM study First clinic visit Result between circulating erythroblast event elevation and abnormality confirmed BMI per normal
Secondary Outcome Measures
NameTimeMethod
To identify BMD specificity cut-off value to correctly predict BMI. within one year after end of study identify the optimal cut-off for highest test performance the classical receiver operator characteristic (ROC) curve analysis
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