Po‐Poster ‐ 29: Radiation‐induced apoptosis of lymphocytes to predict late toxicity from radiotherapy
Bibliographic record
Abstract
An important challenge arises in radiotherapy when certain individuals present with abnormal radiosensitivities. Radiosensitive individuals may not tolerate normal therapy and encounter complications whereas radioresistant patients may not respond adequately to standard treatments regimes because of intrinsic cellular resistance. It has been shown (Crompton et al. IJROBP 2003; 45:707–714 and IJROBP 2001; 49:547–554) that late normal tissue toxicity was correlated to low level apoptosis in CD4 and CD8 lymphocytes. The assay developed by this group used a simple flow cytometry based assay. Our group has researched the sensitivity of alternative apoptosis assays (DiOC6, Caspase‐3, Annexin‐V, PI, 7AAD and Comet), and have shown that both the Annexin V‐FITC and the DiOC6 assay have the greatest suitability in clinical use with respect to speed, simplicity and sensitivity. In our present study, 80 prostate cancer patients will be tested for radiosensitivity using lymphocyte apoptosis assays. These patients were formerly enrolled in a randomized dose‐escalation study (Sathya et al. JCO 2005; 45:1192–1199). Toxicity was recorded prospectively. The aim of this study is to determine a correlation between the proportion of T‐lymphocytes undergoing apoptosis when irradiated (2, 4 and 8Gy) and the occurrence of late toxicity (Grade II and above). We will present our current results showing a large inter‐individual variation within our patient cohort. Data obtained using the Annexin Assay measuring CD4 lymphocyte apoptosis receiving 8Gy show a wide range of responses (mean = 34% apoptosis, σ = 8.2) with z‐scores ranging from −1.5 to 2.4.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".