Reply to H.J adams et al: “Is <scp>FDG‐PET/CT</scp> a sensitive and specific method for the detection of extranodal involvement in diffuse large <scp>B</scp>‐cell lymphoma?”
Bibliographic record
Abstract
HR: 2.66, 95% CI: 1.63-4.34),whereas only bone marrow involvement at FDG-PET/CT was reported to be a predictor of PFS and OS in the multivariate analysis.El-Galaly et al.[1] concluded FDG-PET/CT to be highly sensitive for the detection of extranodal involvement and claim bone marrow involvement at FDG-PET/CT to be highly predictive of outcome.However, we cannot agree with El-Galaly et al.'s statement that FDG-PET/CT has high sensitivity for the detection of extranodal/bone marrow involvement, since this statement is simply not supported by their own data.Although increased bone marrow FDG uptake at PET/CT was observed much more frequently than lymphomatous involvement of the bone marrow biopsy specimen, increased FDG uptake of the bone marrow was not observed in 12/45 (26.7%) of patients with histologically proven largecell (aggressive) lymphoma, and in 18/28 (64.3%) of patients with histologically proven small-cell (indolent) lymphomatous bone marrow involvement.Note that the suboptimal sensitivity of FDG-PET/CT for the detection of bone marrow involvement has already been demonstrated by several other studies [2], and that the sensitivity of all these previous studies might even be overestimated, since they all performed a patient-based analysis rather than a local comparison between FDG-PET/CT and bone marrow biopsy findings.When a local, head-to-head comparison between FDG-PET/CT and BMB in the posterior iliac crest is performed, the sensitivity of FDG-PET for bone marrow involvement has been reported to be even lower [3].Finally, note that the bone marrow is usually the only extranodal site that is additionally biopsied in patients with histologically proven DLBCL.Due to the lack of a reference test the sensitivity of FDG-PET/CT for the detection of extranodal involvement other than the bone marrow is actually unclear.Another important issue is that El-Galaly et al. [1] reported bone marrow involvement as detected by FDG-PET/CT to be highly predictive of PFS and OS, and that it would surpass the prognostic value of BMB.However, this highly contradicts the results of previous studies on this topic [4-8], which were not correctly discussed by El-Galaly et al. [1].Of these five previous studies on the prognostic value of FDG-PET/CT-based bone marrow involvement, four studies [4,5,7,8] showed that pathological bone marrow FDG uptake has no prognostic value at all, and the only previous study that reported FDG-PET/CT-based bone marrow involvement to have any prognostic value clearly showed that bone marrow FDG-PET was prognostically inferior to BMB [6].That particular study reported bone marrow FDG-PET/CT negative patients to have 2-year PFS and OS of 84.5% and 88.5%, and bone marrow FDG-PET/CT positive patients to have 2-year PFS and OS of 62.5% and 76.1%, respectively [6].However, the 2-year PFS and OS of BMB-negative patients were 82.1% and 87.2%, and those of BMB-positive patients were 37.5% and 62.5%, respectively, which clearly shows that BMB is better at selecting patients with a worse prognosis [6].These findings suggest that increased bone marrow FDG uptake is not specific for lymphomatous bone marrow involvement.In addition, unlike El-Galaly et al.'s findings [1], it has been convincingly proven by large study cohorts that were used to develop the International Prognostic Index and its successors that bone marrow involvement detected by BMB is an independent predictor of outcome [9][10][11][12][13].Not surprisingly, the recently published National Comprehensive Cancer Network International Prognostic Index [10] for DLBCL does not incorporate imaging-based bone marrow involvement and only includes histologically confirmed bone marrow involvement as an adverse risk factor.In conclusion, both sensitivity and specificity of FDG-PET/CT for the detection of bone marrow involvement in DLBCL are suboptimal and questionable.Furthermore, the claim that bone marrow involvement as detected by FDG-PET/CT is more accurate than BMB for predicting outcome, is very doubtful.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.021 | 0.030 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".