Immunophenotype Study in Children with Leukemia and Its Relationship with Relapse in Ahvaz Shafa Hospital from 2013 to 2018
Bibliographic record
Abstract
Introduction: Acute lymphoblastic leukemia (ALL) is one of the most common cancers in children. Since the identification of patients immunophenotypes is effective for disease diagnose and prognosis, and due to very few studies in Iran, especially Khuzestan province, the aim of this study was to investigate the immunophenotype of children with leukemia and its association with recurrence in Ahvaz Shafa Hospital from 2013 to 2019. Methods: This is a retrospective study that was conducted in patients referring to Ahvaz Shafa Hospital during the years 2013 to 2019. Demographic data including age, gender, height, weight, leukocyte count, flow cytometry and other laboratory findings were collected and analyzed by version 22 SPSS statistical software. Results: The mean age of the patients was 7.59 ± 3.94 years and the sex of 51 (52%) were female. Immunophenotype of 81 patients (82.7%) was Pre B cell, 4 patients (4.1%) was Pro-B Cell, 5 patients (5.1%) was Pro-T Cell, and 8 patients (8.2%) was T Cells. 87 patients (88.8%) recovered and 11 patients (11.2%) had recurrence. Only 11 patients with Pre B cell (13.6%) had recurrence, but in other immunophenotypes, 100% of patients had remission, but this difference was not statistically significant (p = 0.46). There was no statistically significant difference between the prevalence of phenotypes in female and male sexes (p = 0.76). The incidence of recurrence was 9.8% in female patients and 12.8% in male patients, which was not statistically significant (p = 0.64). Conclusion: The results of this study showed that preB cell immunophenotypes with the prevalence of 82.7% had the highest frequency in acute lymphoblastic leukemia, and the incidence of recurrence in patients was 11.2%. Also, patients with other immunophenotypes did not recurrence, so his finding may have been because of insufficent patients to study and compare.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".