Effect of adding chemotherapy or hyperthermia to radiotherapy in patients with uterine cervical cancer
Bibliographic record
Abstract
was relatively long. Furthermore, a Canadian study shows no benefit from adding cisplatin to radiotherapy. A detailed study of the different trials might provide us with a better understanding about the effect of concomitant cisplatin, and about which patient groups may benefit. Indeed, a meta-analysis of individual patient data would be required. A point of concern about standard application of cisplatin concurrently with radiotherapy is that late toxic effects might increase, as has been seen in experimental and clinical studies, even though cisplatin by itself causes no adverse effects in the organs involved. Workers in all studies of cervical cancer report an increase in acute toxic effects, and animal and human studies have provided evidence for a relation between acute and late intestinal radiation sequelae. In part of the Netherlands, patients with advanced cervical cancer are treated with combined radiotherapy and hyperthermia, after a randomised study showed substantial benefit from additional hyperthermia to patients, of whom 80% had a stage IIIb or IVa tumour. 3 Although the study populations in the various trials are not comparable, the effects of adding either hyperthermia or cisplatin can be compared for odds ratios for pelvic-tumour control and hazard ratios for death, and seem similar (table). In the hyperthermia study, acute or late radiation toxic effects were not increased. In view of the reasons listed above, we find that, to date, no definite conclusions can be drawn about adding cisplatin to standard, state of the art, radiation treatment for all patients with advanced stage cervical carcinoma, and have decided to continue with combined radiotherapy and hyperthermia in this group of patients.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.014 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".