Technetium‐99m‐sestamethoxyisobutylisonitrile scan as a predictor of chemotherapy response in malignant lymphomas compared with P‐glycoprotein expression, multidrug resistance‐related protein expression and other prognosis factors
Bibliographic record
Abstract
The purpose of the present study was to predict the response of malignant lymphomas (MLs) to chemotherapy using technetium-99m methoxyisobutylisonitrile (Tc-MIBI) scan and to compare it with the predictive ability of P-glycoprotein (P-gp) expression, multidrug resistance-related protein (MRP) expression and other prognosis factors. Twenty-five ML patients were enrolled in this study prior to initiation of chemotherapy. Images were obtained 10 min after intravenous injection of Tc-MIBI, interpreted visually and the tumour-to-background (T/B) ratios calculated. Immunohistochemical analyses were performed on sections of the biopsy specimens to determine P-gp and MRP expression. Chemotherapy response was evaluated in the first 1-2 years after completion of chemotherapy. The mean T/B ratio of the 15 patients with a good response (3.3 +/- 0.6) was significantly higher than that of the 10 patients with a poor response (1.2 +/- 0.1). All 15 patients with a good chemotherapy response had positive Tc-MIBI scan results and negative P-gp and MRP expression. All 10 patients with a poor response had negative Tc-MIBI scan results and either positive P-gp or MRP expression. Other prognosis factors showed no significant difference in the incidence of good and poor responses. Tc-MIBI scan results represent P-gp or MRP expression more accurately than other prognosis factors and predict the chemotherapy response in ML 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".