Predictive parameters in hypofractionated whole-breast 3D conformal radiotherapy according to the Ontario Canadian trial
Bibliographic record
Abstract
Aim: To evaluate the possible role of dosimetric parameters according Normal Tissue Complication Probability (NTCP) model as predictive of late toxicity and cosmesis in hypofractionated whole-breast three-dimensional conformal radiotherapy. Patients and methods: A retrospective analysis on 215 consecutive early breast cancer patients treated with breast conserving surgery and adjuvant hypofractionated whole-breast radiotherapy (according the Ontario Canadian trial), with a 6 years median follow-up was conducted. To assess the impact of 10%–20% dose hotspots on different percent values of planning target volume (PTV) of the breast, we retrospectively employed the NTCP model of Lyman. PTV breast (PTVbr), V110 were identified. For statistical analysis the χ 2 and paired t -test were used to find a correlation between late skin and subcutaneous toxicity and cosmetic outcome with dosimetrical parameters Multivariate analysis was performed with the aim to assess independently the impact of dosimetric and clinical parameters on late toxicity and cosmesis using Pearson’s covariance. Results: Late skin toxicity was recorded in 47/215 (22%); and G3 toxicity occurred in 11 patients (5%). Cosmesis with excellent–good score was found in 172 patients (80%) while fair–poor score was found in 43 patients (20%). In univariate χ 2 analysis the V110 >10% of the PTV breast significantly correlated with higher toxicity ( P <0.005, OR 9.60 [CI 3.89–23.72]). Cosmesis related to V110 >10% and PTV breast volume over 1,300 cc was significant at multivariate analysis ( P <0.005, OR 6.07 [CI 2.36–15.59]). Conclusion: To safely use one of the most important whole-breast hypofractionated radiotherapy schedules, we found some predictive paramaters on the basis of NTCP model by Lyman. These parameters may be useful in selection of elegible patients. Keywords: NTCP model, Ontario Canadian Trial, hypofractionated radiotherapy, whole-breast, cosmesis, toxicity, PTV breast, V110, early breast cancer
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".