Chemotherapy with radiotherapy influences time-to-development of radiation-induced sarcomas: a multicenter study
Bibliographic record
Abstract
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 a 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 1 January 2000 to 31 December 2014. The primary endpoint was time to development of RIS. RESULTS: We identified 419 patients with RIS. 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; 95% CI 1.83-2.43; P<0.001) and chemotherapy for the first malignancy (HR 1.61; 95% 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 RIS.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".