Peripheral Blood Lymphocyte Percentage May Predict Chemotolerance and Survival in Patients with Advanced Pancreatic Cancer. Association between Adaptive Immunity and Nutritional State
Bibliographic record
Abstract
Pancreatic Carcinoma (PC) cells have the ability to induce patient immunosuppression and to escape immunosurveillance. Low circulating lymphocytes are associated with an advanced stage of PC and reduced survival. Blood lymphocytes expressed as a percentage of Total White Blood Cells (L% TWBC) could predict chemotolerance (n° of tolerated cycles), survival time and Body Weight (BW) more effectively than lymphocytes expressed as an absolute value (LAB > 1500 n°/mm3) or lymphocytes >22%, which is the lowest limit of normal values in our laboratory. Forty-one patients with advanced PC, treated with chemotherapy, were selected for this observational retrospective study. Patients were evaluated at baseline (pre-chemotherapy), and at 6, 12 and 18 months, respectively, after diagnosis of PC. The study found L ≥ 29.7% to be a better predictor of survival (COX model, using age, sex, BW, serum creatinine, bilirubin and lymphocytes as covariates), chemotolerance (r = +0.50, p = 0.001) and BW (r = +0.35, p = 0.027) than LAB > 1500 or L > 22%. BW did not significantly correlate with chemotolerance or survival. The preliminary results of this study suggest that L ≥ 29.7% is more effective than LAB > 1500 or L > 22% at predicting chemotolerance, survival time and nutritional status. A possible impact of nutritional status on chemotherapy and survival seems to be lymphocyte-mediated given the association between BW and L%. This study may serve as the basis for future research to explore whether nutritional interventions can improve lymphopenia, and if so, how this may be possible.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".