The pathobiology of select adolescent young adult lymphomas
Bibliographic record
Abstract
Lymphoid cancers are among the most frequent cancers diagnosed in adolescents and young adults (AYA), ranging from approximately 30%-35% of cancer diagnoses in adolescent patients (age 10-19) to approximately 10% in patients aged 30-39 years. Moreover, the specific distribution of lymphoid cancer types varies by age with substantial shifts in the subtype distributions between pediatric, AYA, adult, and older adult patients. Currently, biology studies specific to AYA lymphomas are rare and therefore insight into age-related pathogenesis is incomplete. This review focuses on the paradigmatic epidemiology and pathogenesis of select lymphomas, occurring in the AYA patient population. With the example of posttransplant lymphoproliferative disorders, nodular lymphocyte-predominant Hodgkin lymphoma, follicular lymphoma (incl. pediatric-type follicular lymphoma), and mediastinal lymphomas (incl. classic Hodgkin lymphoma, primary mediastinal large B cell lymphoma and mediastinal gray zone lymphoma), we here illustrate the current state-of-the-art in lymphoma classification, recent molecular insights including genomics, and translational opportunities. To improve outcome and quality of life, international collaboration in consortia dedicated to AYA lymphoma is needed to overcome challenges related to siloed biospecimens and data collections as well as to develop studies designed specifically for this unique population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".