Precursor B-cell Lymphoblastic Lymphoma in Children: Hacettepe Experience
Bibliographic record
Abstract
The purpose of the study was to review the clinical and pathologic characteristics and treatment results of children with precursor B-cell lymphoblastic lymphoma. Of 530 children diagnosed with non-Hodgkin lymphomas between 2000 and 2021, 39 (7.4%) were identified as having precursor B-cell lymphoblastic lymphoma. Clinical characteristics, pathologic, radiologic, laboratory data, treatments, responses, and overall outcomes were recorded from hospital files and analyzed. The median age of 39 patients (males/females, 23/16) was 8.3 years (range 1.3 to 16.1). The most common sites of involvement were the lymph nodes. At a median follow-up of 55.8 months, 14 patients (35%) had a recurrence of disease (11 stage IV, 3 stage III); 4 were in complete remission with salvage therapies, 9 died of progressive disease and one died due to febrile neutropenia. Five-year event-free survival and overall survival rates were 65.4% and 78.3% for all cases, respectively. Survival rates were higher in patients with a complete remission at the end of induction therapies. The survival rates were lower in our study compared with other studies, which could be explained by the high relapse rate and higher incidence of advanced-stage disease due to bone marrow involvement. We demonstrated a prognostic impact of treatment response at the end of the induction phase. Cases with a disease relapse have poor prognosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".