[A survival of 103 cases of T-cell non-Hodgkin lymphoma].
Bibliographic record
Abstract
OBJECTIVE: T-cell non-Hodgkin lymphoma was heterogeneous and relatively high incident in our country. It's response and prognosis were poor. This study was to analyze clinical feature and survival of T-NHL. METHODS: Records of 103 cases with T-NHL, treated from Dec 1998 to Dec 2004 in Cancer Center of Sun Yat-sen University, were retrospectively analyzed. All the patients were classified according to WHO 2001 Classification Criteria. RESULTS: Median age of the whole group was 35 (ranged 2-78) years-old. Of the 103 cases, 68 were male, 35 were female; 25 (24.3%) received chemoradiotherapy, 70 (68.0%) received chemotherapy alone, 3 received radiotherapy and 5 received stem cell transplantation after complete remission. Median survival was 24.1 (ranged 0.8-84) months. 5-year survival rate was 24.3%. Kaplan-Meier analysis discovered that age > 60 years, advanced stage (stage II, IV), extranodal involvement, bulky disease, B symptom, performance status (PS) > or = 2, LDH elevated, hypoalbumin, median-high IPI (IPI > or = 2) were bad to prognosis, but Cox regression found that age > or = 60 years, performance status (PS) > or = 2S, hypoalbumin were the independent bad factors to prognosis. CONCLUSION: This study proved that age, albumin, PS were the independent factors to prognosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".