Abstract A027 Investigations on association of month of birth and seasonality with chromosomal abnormalities of prognostic significance and disease incidences in pediatric acute lymphoblastic leukemia in Saudi Arabia
Bibliographic record
Abstract
Abstract Introduction: Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. It is associated with many environmental factors. The correlation between month of birth, seasonality, genetic abnormalities and ALL has been studied with conflicting results and this issue remains controversial. The principal aim of this study was to assess the association of ALL and month/season of birth and its association. with cytogenetic abnormalities. Methods This was a retrospective cohort study that took place at Department of pediatric hematology, King Abdulaziz Medical City, Riyadh, Saudi Arabia. Inclusion criteria was any patient diagnosed with ALL until the age of 14 years. Patients with a family history of ALL were excluded. Data was retrived from electronic medical records and analyzed using SPSS version 27. Results: A total of 192 patients were analyzed. More than half (60.9%) of the patients were male. With regard to ALL’s subtype, B-cell was found in 84.9% of the patients. In addition, B-ALL was the highest incidence in both genders accounting for 82.05% and 89.3% in males and females, respectively. January was the month with the highest incidence of ALL (12%), while February and September were the lowest (6.3%). Season-wise, spring season had the highest number of ALL patients (26.6%), and Summer had the lowest incidence (24%). We found trisomy of chromosome 12 in patients with ALL is significantly higher in 1-3 years age group (P-value= 0.039). Patients who had trisomy of chromosome 12 accounted for 13.7% in 1-3 age group compared to 3.8% in 7-14, 1.5% in 3-7, and none in up to 1 year of age. Moreover, AML gene abnormality in ALL patients was also found to be significantly associated with age group, where it was found that majority of patients were aged from 3-7 years (27.7%) (P-value= 0.014). the lowest was in 1-3 age group accounting for 7.8%. TCRgamma mutation was also found to be significantly increased (14.3%) in ALL patients aged up to 1 year (P-value= 0.025), and only 2% in 1-3 age group. Furthermore, we divided them into seasons (summer, winter, autumn, and spring) and their chromosomal abnormalities. Autumn was found to have a significant increase (31.9%) in trisomy 17 (P-value= 0.004). Furthermore, in winter, spring, and summer, it accounted for 8.30%, 9.80%, and 13.00%, respectively. We also noted an increase in trisomy 21 in Spring season in 23.5% of the patients (P-value= 0.039). in winter, summer, and autumn, it was 4.20%, 23.50%, 10.90%, 14.90%, respectively. Lastly, tetrasomy of chromosome 21 had a significant increase in Autumn season (23.4%) (P-value= 0.032) compared to 10.40% in winter, 9.80% in spring, and 4.30% in autumn. Conclusion: We found that age at the time of diagnosis was significantly associated with the season of birth. We conclude that prognostically important genetic abnormalities have a significant association with seasonality and age groups in pediatric ALL patients. Further studies in this regard can help understand important bearing of seasonality on biology and genetics of pediatric ALL. Citation Format: Khalid Aljamaan, Sarah AlMukhaylid, Zafar Iqbal. Investigations on association of month of birth and seasonality with chromosomal abnormalities of prognostic significance and disease incidences in pediatric acute lymphoblastic leukemia in Saudi Arabia [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A027.
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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) | 0.002 | 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".