Impact of Concordant and Discordant Bone Marrow Involvement on Outcome in Diffuse Large B-Cell Lymphoma Treated With R-CHOP
Bibliographic record
Abstract
PURPOSE: In diffuse large B-cell lymphoma (DLBCL), prior studies suggest that concordant bone marrow involvement with DLBCL portends a poorer prognosis, whereas discordant bone marrow involvement with small B-cell lymphoma does not. We examined the significance of bone marrow involvement in patients treated in the current era of therapy including rituximab. PATIENTS AND METHODS: We performed a retrospective analysis of the prognostic impact of bone marrow involvement in an unselected population of patients with newly diagnosed DLBCL treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone in British Columbia and Auckland, New Zealand, with complete clinical information and evaluable staging bone marrow biopsies. RESULTS: In total, 795 patients were identified. Six hundred seventy (84.3%) of 795 had a negative bone marrow, 67 patients (8.4%) had concordant and 58 (7.3%) had discordant involvement. Median follow-up was 41 months (range, 1 to 115). Progression-free survival (PFS) was inferior in those with concordant (P < .001) and discordant (P = .019) involvement while overall survival (OS) was inferior in those with concordant involvement (P < .001) only. In a multivariate analysis controlling for the International Prognostic Index (IPI) score, concordant involvement remained an independent predictor of PFS (P < .001) and OS (P = .007). Discordant involvement was associated with older age, elevated lactate dehydrogenase, advanced stage, and increased number of extranodal sites and was not a negative prognostic factor independent of the IPI score. CONCLUSION: The negative prognostic impact of discordant involvement is adequately represented by the IPI score, while the risk with concordant involvement is greater than that encompassed by this predictor. The results emphasize the need for accurate staging assessment of bone marrow involvement in DLBCL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".