Both Discordant and Concordant Bone Marrow (BM) Involvement Predict for a Poorer Outcome Independent of the IPI in Patients with Diffuse Large B-Cell Lymphoma (DLBCL) Treated with R-CHOP.
Bibliographic record
Abstract
Abstract Recently, it has been suggested that concordant but not discordant BM involvement is a negative predictor of outcome in DLBCL patients treated with CHOP (Chung et al, Blood 2007). The significance of BM involvement in pts treated in the current era of therapy including rituximab has not been fully examined. We evaluated the prognostic impact of BM involvement in DLBCL patients treated with the current standard of care, R-CHOP. Patients: We identified 282 patients with biopsy proven de novo DLBCL treated in British Columbia (BC) with an R-CHOP regimen between 01/01/2001 and 01/01/2005 with complete clinical information and staging bone marrows available for review. Cases were identified using the Lymphoid Cancer Database of the BC Cancer Agency. Median follow-up is 44 mos (range 1–77). Results: 234/282 (83%) had a negative staging BM, 27 pts (10%) had a positive BM with concordant histology (Con-BM) and 21 (7%) had a positive BM with discordant histology (Dis-BM) with predominantly small B-cells present. Clinical characteristics for the entire cohort were as follows: median age 64 y (range 18–88); 66% male; 65% stage III/IV; 39% PS>1; 51% elevated LDH; 31% >1 extranodal site. IPI risk factors: 10% 0; 42% 1–2; 48% 3–5. In addition to higher stage and greater extranodal involvement, pts with a positive BM were more likely to have a higher LDH and a poorer PS than pts with a negative BM. Compared to pts with Con-BM, pts with Dis-BM were more likely to be elderly, but otherwise exhibited a similar distribution of clinical prognostic factors. The Kaplan-Meier 4-year PFS was significantly worse for pts with both Dis-BM (32%) and Con-BM (46%) involvement compared to pts with a negative BM (75%) (p<0.0001) (see Figure). Similarly, 4-year overall survival was significantly worse for pts with Dis-BM and Con-BM involvement (53% and 54%) compared to pts with a negative BM (74%) (p=0.005). All patients with Dis-BM involvement who developed progressive or relapsed disease were believed to have progression of their aggressive lymphoma based on clinical behavior or biopsy proof. In a multivariate analysis controlling for the IPI, BM involvement (Dis-BM and Con-BM) remained an independent predictor of PFS (p=0.03). Conclusions: In DLBCL pts treated with R-CHOP, both discordant and concordant BM involvement predict for a poorer outcome independent of the IPI. It is possible that pts with DLBCL and discordant BM involvement represent a subset of pts with transformed disease which is inherently less treatment-sensitive. Figure Figure
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".