Does adjuvant alpha-interferon improve outcome when combined with total skin irradiation for mycosis fungoides?
Bibliographic record
Abstract
BACKGROUND: Patients with mycosis fungoides (MF) experience frequent disease recurrences following total skin electron irradiation (TSEI) and may benefit from adjuvant therapy. OBJECTIVES: To review the McGill experience with adjuvant alpha-interferon (IFN) in the treatment of MF. METHODS: From 1990 to 2000, 50 patients with MF were treated with TSEI: 31 with TSEI alone and 19 with TSEI + IFN. Median TSEI dose was 35 Gy. In the TSEI + IFN group, IFN was given subcutaneously at 3 x 10(6) units three times per week starting 2 weeks prior to start of TSEI, continued concurrently with the radiation and for an additional 12 months following TSEI. The TSEI alone group included 16 men and 15 women with a median age of 61 years (range 31-84). The TSEI + IFN group included 14 men and five women with a median age of 51 years (range 24-83). Clinical stage was IA, IB, IIA, IIB, III and IVA in 2, 9, 4, 8, 1 and 7 patients of the TSEI group and 0, 3, 3, 7, 4 and 2 patients of the TSEI + IFN group. RESULTS: Median follow up for living patients was 70 months. All patients responded to treatment. Complete response (CR) rate was 65% following TSEI and 58% following TSEI + IFN (P = 0.6). Median overall survival (OS) was 61 months following TSEI and 38 months following TSEI + IFN (P = 0.4). Acute grade II-III dermatitis was seen in all patients. Fever, chills or myalgia were seen in 32% of patients treated with TSEI + IFN. CONCLUSIONS: Concurrent IFN and TSEI is feasible, with acceptable toxicity. Even when controlling for disease stage, the addition of IFN did not appear to increase CR rate, disease-free survival or OS.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".