Lymphadenopathy, malignant lymphoma Enlarged lymph nodes
Conditions
Interventions
Not applicable.
Sponsors
Prinses Máxima Centrum voor Kinderoncologie
Eligibility
Age
No minimum to 17 Years
Inclusion criteria
Inclusion criteria: Reason of referral /hospital admission: lymphadenopathy Informed consent by patient and/or parent(s)/guardian(s)
Exclusion criteria
Exclusion criteria: Gland(s) < 1 cm (exception: supraclavicular lymph nodes) Gland(s) spontaneously in regression at the time of first visit Clinical picture is consistent with lymphadenitis Swelling appears not to be a lymph node (for example, branchial cleft cyst or haemangioma)
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| The primary endpoint of this research is a machine learning diagnostic model for malignant lymphoma with a high specificity (85%+) for a minimum sensitivity (95%). The malignant lymphoma diagnosis will be confirmed by biopsy or excluded if there is an alternative diagnosis or spontaneous regression of the lymph node. | — |
Secondary
| Measure | Time frame |
|---|---|
| Additionally, we will make a separate model for a specific type of lymphoma (Nodular lymphocyte-predominant Hodgkin lymphoma). The third endpoint is a cost-effectiveness analysis. We will compare the costs and effects of the diagnostics tests using our model with standard care. | — |
Countries
Netherlands
Contacts
Public ContactA. Beishuizen
Prinses Máxima Centrum voor Kinderoncologie
Outcome results
None listed