[Survival outcomes of T-cell non-Hodgkin's lymphoma: a report of 111 cases].
Bibliographic record
Abstract
BACKGROUND & OBJECTIVE: T-cell non-Hodgkin's lymphoma (NHL) is a group of heterogeneous malignancies with poor prognosis, and without ideal therapeutic regimen. This study was to summarize clinical and pathologic features of T-cell NHL. METHODS: Records of 111 patients with T-cell NHL, treated from Jan. 1994 to Dec. 2001 in Cancer Center of Sun Yat-sen University, were retrospectively analyzed. All the patients were classified according to WHO classification criteria. RESULTS: Median age of the whole group was 37 years (ranged 7-77 years). Of the 111 patients, 82 were men, 29 were women;45 (40.5%) were treated with chemoradiotherapy, 62 (55.8%) were treated with chemotherapy alone, and 4 (3.6%) were treated with radiotherapy alone. The 3-year survival rate of the whole group was 45% with a median follow-up of 28 months. The 3-year survival rates of chemoradiotherapy, chemotherapy, and radiotherapy groups were 56%, 38%, and 25%, respectively. Among all histological type subgroups, the prognosis of NK/T-cell lymphoma was the worst with the 3-year survival rate of only 25%u the 3-year survival rate was 40% in unspecified peripheral T-cell lymphoma group,and 85% in angioimmunoblast T-cell lymphoma group. International prognostic index was a significant factor for predicting overall survival. The 3-year survival rates of low risk,low-intermediate risk,intermediate-high risk, and high risk groups were 60%, 30%, 10%, and 0%, respectively. CONCLUSIONS: Present treatment modalities for T-cell NHL patients, especially the high risk patients, can't achieve satisfactory outcomes. New treatment modality for these patients needs to be explored.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".