Influence of chemotherapy combined with radiotherapy on the time-to-development of radiation-induced sarcomas: A multicenter, retrospective analysis.
Bibliographic record
Abstract
11046 Background: An increasing number and proportion of cancer patients with apparently localised disease are treated with chemotherapy and radiation therapy in contemporary oncology practice. In a pilot study of radiation-induced sarcoma (RIS) patients, we demonstrated that chemotherapy was associated with a reduced time to development of RIS. We now present an international multi-centre collaborative study to validate this association. Methods: This was a retrospective cohort study of RIS cases across five large international sarcoma centres between the 1st January, 2000 to 31st December, 2014. The primary endpoint was time to development of RIS, defined as the date of diagnosis of the first malignancy to date of the RIS diagnosis. We also assessed the relationship between chemotherapy, patient and cancer characteristics, and time to RIS. Results: We identified 419 patients with RIS, who were predominantly diagnosed with their first malignancy at adulthood. The median interval from the index cancer to development of RIS for the entire cohort was 11 years (range 1-64). Chemotherapy for the first malignancy was associated with a shorter time to RIS development (HR 1·37; 95% CI: 1·08-1·72; P = 0·009). In the multi-variable model, older age (HR 2·11; CI 1·83-2·43; P < 0·001) and chemotherapy for the first malignancy (HR 1·61; CI 1·26-2·05; P < 0·001) were independently associated with a shorter time to RIS. Anthracyclines and alkylating agents significantly contribute to the effect. Conclusions: This study confirms an association between chemotherapy given for the first malignancy and a shorter time to development of a RIS. Our data highlights the importance of vigilance in surveillance for RIS after chemotherapy and radiation therapy, particularly in younger patients who also have a longer potential time to develop a second malignancy.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".