Outcome of Bone Marrow Biopsy in Patients with Diffuse Large B-Cell Lymphoma Patients Staged by Combined 18 FGD-PET/CT Scan
Bibliographic record
Abstract
Abstract DLBCL represents 1/3 of non-Hodgkin lymphoma, in 60% of the cases the disease presented in advanced stage (III-IV). Extranodal organs are involved in 40% of cases; BM involvement in 11% to 27% of cases. BMB is an invasive procedure, & it also could represent false negative result in patients with patchy pattern of involvement or if involvement else where the routine biopsy site. Study included 102 patients, above the age of 18 years, confirmed to have newly diagnosed DLBCL with no any other malignancy. Every patient had a baseline PET-Ct, bone marrow biopsy. PET-CT detected BM infiltration in 23 patients, i.e 22.5%. BMB were positive in 20 patients, while PET-CT showed BM involvement in 23 patients.- 94 patients had concordant negative ( 75 patients ) or positive ( 19 patients), PET-CT & BMB results. One patient had positive BMB and negative PET-CT. All patients with stage I & II had concordant PET-CT & BMB results One patient graded stage III by PET-CT showed 1-2% BM infiltration & upstaged to stage IV. Of the 49 patients graded stage IV by PET-CT, 3 had positive BM involvement PET-CT and negative BMB. the sensitivity of PET-CT was 95%, the specificity of PET-CT was 96.2%. the PPV was 86.4% & the NPV was 98.7%. PET-CT showed 95.9% accuracy. Our results suggest PET-CT as a powerful tool to evaluate BM infiltration in patients with DLBCL, with overall concordance exceeding 94% (100%for stage I & II ). For patients with advanced stage IV disease, PET-CT was able to retrieve patients with BM involvement & false negative BMB. Disclosures No relevant conflicts of interest to declare.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".