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?”
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,002 | 0,004 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,021 | 0,030 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,004 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».