Prognostic Impact of Extranodal Diffuse Large B-Cell Lymphoma in the Era of Immunochemotherapy and PET/CT Staging
Bibliographic record
Abstract
Abstract Background: Extranodal disease is common in diffuse large B-cell lymphoma (DLBCL), and involvement of more than one extranodal site is associated with a worse outcome. 18F-fluorodeoxyglucose PET/CT (PET/CT) is the current state-of-the-art for staging of DLBCL, and has shown to be much more sensitive for the detection of extranodal involvement than a stand-alone CT scan. Therefore, a re-evaluation of the clinical significance of extranodal disease among PET/CT staged DLBCL patients is warranted. Patients and Methods: We retrospectively included patients from Aalborg (2007-2012), Copenhagen (2009-2012), and British Columbia (2011-2012) in the present study. The inclusion criteria were, i) newly diagnosed DLBCL, ii) R-CHOP or R-CHOP like first-line treatment, and iii) PET/CT staging. The written PET/CT files were reviewed for disease stage and extranodal sites of involvement. The relationship between number of involved sites, extranodal locations and outcome were assessed with simple Cox regression analyses. Extranodal locations with p<0.1 in univariate analysis were entered in a multivariable Cox regression analysis together with the following International Prognostic Index (IPI) factors: age > 60 years, elevated LDH, ECOG performance score >1. Results: A total of 444 patients with a median age of 65 years (range 16-90) and a male:female ratio of 1.3 were included in the study. Of these patients 28% (n=98) had Ann Arbor stage I disease, 16% (n=72) stage II disease, 16% (n=71) stage III disease, and 46% stage IV disease (n= 203). LDH was elevated in 51% (n=224), and 17% (n=74) had ECOG performance status >1. B-symptoms were present in 37% (n=164) and 26% (n=114) had a bulky mass =/> 10 cm. With a median follow-up of 2.4 years (range 0.5-6.5) in patients still alive at the time of analysis, the 3-year OS and PFS were 73% and 69%, respectively. Extranodal disease was diagnosed in 286 (64%) of the patients. The anatomic locations of extranodal disease and their relations to outcome are shown in Table I. Figure 1A and B show the PFS and OS curves when patients are grouped according to the number of involved extranodal sites. Patients with one or two extranodal sites of involvement had similar outcome (3-year PFS 68% vs. 70%), whereas all patients with involvement of more than three extranodal sites progressed. Conclusions: Extranodal involvement is diagnosed in more than half of all newly diagnosed DLBCL patients staged with PET/CT. Bone/bone marrow involvement was the most common site and associated with a worse outcome. Thus, detection of these lesions with PET/CT is clinically important. The presence of extranodal disease is generally associated with a worse outcome, but our data suggest that the optimal cut-off for prognostication in PET/CT staged patients may be more than two sites rather than more than one site, as according to the IPI. Abstract 1630 Table1: Extranodal DLBCL and their relationship with outcome in PET/CT staged patients treated with R-CHOP. Empty boxes represent variables not included in multivariate models. Site Frequency, n (%) HR, univariate HR, multivariate PFS OS PFS OS Lung 33 (7%) 1.56, p=0.002 1.46, p=0.26 Not significant Liver 34 (8%) 2.39, p=0.001 2.43, p=0.002 Not significant Not significant Bone/bone marrow (PET/CT) 127 (29%) 2.49, p<0.001 2.53, p<0.001 1.77, p=0.007 1.66, p=0.03 Bone marrow indolent NHL (biopsy) 28 (6%) 0.86, p=0.70 0.94, p=0.87 Bone marrow DLBCL (biopsy) 43 (10%) 2.55, p<0.001 2.66, p<0.001 Not significant Not significant Gastrointestinal 35 (8%) 1.27, p=0.43 1.02, p=0.96 Kidney 13 (3%) 2.10, p=0.06 1.63, p=0.29 Not significant Soft tissue and muscle 46 (10%) 1.18, p=0.58 1.17, p=0.64 Paranasal sinus 15 (3%) 1.57, p=0.28 1.69, p=0.25 Pleural fluid 16 (4%) 2.82, p=0.005 3.23, p=0.003 2.43, p=0.02 2.53, p=0.02 Testicular 13/252 (5%) 2.42, p=0.22 1.81, p=0.41 Female genitals 10/192 (5%) 3.38, p=0.006 3.76, p=0.003 Figure 1A and B: PFS (Figure 1A) and OS (Figure 1B) in patients grouped according to the number of extranodal sites involved: zero (blue), 1 (green), 2 (grey), 3 (purple), >4 (red). Figure 1A and B:. PFS (Figure 1A) and OS (Figure 1B) in patients grouped according to the number of extranodal sites involved: zero (blue), 1 (green), 2 (grey), 3 (purple), >4 (red). 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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".