Infection related late mortality in survivors of childhood cancer with asplenia or radiation-induced hyposplenism: A report from the Childhood Cancer Survivor Study.
Bibliographic record
Abstract
10563 Background: Asplenia or hyposplenism can develop in survivors of childhood cancer following splenectomy or radiotherapy exposure to the left upper quadrant of the abdomen (LUQ). Knowledge regarding long-term infection related outcomes for these survivors is limited. Methods: Infection related late mortality (sepsis, meningitis or pneumonia) was evaluated in 20,805 5-year survivors (diagnosed <21 years of age from 1970-1999, median follow-up 26 years, range 5-44) using cumulative incidence and Poisson regression models to calculate adjusted relative risk (RR) and 95% confidence intervals (CI). Average LUQ radiation was calculated as a surrogate for splenic radiation. Results: Treatment included splenectomy for 1328 survivors (6%). An additional 10,295 (49%) were exposed to LUQ radiotherapy without splenectomy. The cumulative incidence of infection related late mortality was 1.4% (95%CI: 0.7%-2.2%) at 35 years after splenectomy and 0.6% (95%CI: 0.4%-0.8%) after LUQ radiotherapy, with a total of 78 deaths attributable to infectious causes (25 sepsis, 1 meningitis, 52 pneumonia). Splenectomy (RR=8.4, p<0.001) and increasing LUQ radiotherapy dose (p<0.001) were independently associated with infection related late mortality (Table). Conclusions: Splenectomy and LUQ radiotherapy increased risk for infection related late mortality. While infectious mortality increased with increasing LUQ radiation dose, even lower dose exposure (<10Gy) increased risk substantially. Accordingly, cancer survivors exposed to LUQ radiotherapy should be considered at risk for functional asplenia and managed similarly to asplenic individuals with respect to vaccinations and febrile illnesses. [Table: see text]
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".