Vascularization Predicts Overall Survival (OS) & Risk of Transformation (RT) in Uniformly Treated Patients with Follicular Lymphoma (FL).
Notice bibliographique
Résumé
Abstract Introduction: FL is an indolent disease with heterogeneous survival. Transformation is asscoiated with short survival. In solid tumors, tumor angiogenesis is required for tumor growth/metastasis and microvessel density (MVD) has, in some tumor types, shown correlation with poor OS. In FL, the impact of MVD on prognosis is controversial. Recent studies have highlighted the effect of the microenvironment on FL prognosis including ours which showed that high numbers of lymphoma-associated-macrophages (LAM) are associated with adverse outcome. Because LAM have been shown to promote angiogenesis and neoplastic growth, we used a quantitative tumor mapping approach to determine whether the degree of vascularization in FL correlated with adverse outcome. Method: Between 1987 and 1993, 126 pts were enrolled on a phase II study of BP-VACOP with involved region radiotherapy. All pts were treatment naïve, < 61y and had advanced-stage FL. Paraffin blocks of the diagnostic biopsies were available for 105 pts. Images of whole sections stained for CD34 were captured using a cooled CCD camera, a motorized stage, and customized NIH-Image software. The motorized stage allowed for tiling of adjacent microscope fields of view, thereby allowing reassembly of the entire tumor section at high-resolution. The distance from each point in the tissue to the nearest CD34+ pixel was measured and the tumor to vessel distance that encompassed 90% of the tumor (TVD90) calculated. A TMA was immunostained with S100A8/Calgranulin A-specific antibody, a M2-like macrophage marker, to determine a subset of LAM. Univariate & multivariate analyses were used to determine OS and RT. Results: There were 84 evaluable cases. The median follow-up of the living patients was 14.3 y and the estimated 10-y OS and RT were 65% and 20%, respectively. The IPI was predictive of OS (RR =3.4, 95% CI =1.8–6.3, p < 0.001) and RT (RR =3.3, 95% CI =1.3–7.9, p = 0.01). Histologic grade included 66 grade 1, 14 grade 2 and 4 grade 3a. Cases revealed TVD90 of 50.3 to 144 microns (median 78.4) and were divided into quartiles. A subset of 14 cases showed high density of S100A8+ cells (> 5 per high power field). In univariate analysis the quartile (21 cases) with low TVD90 (i.e. high MVD) showed inferior OS (p < 0.001) and high RT (p = 0.012). Cases with high density of S100A8+ LAM also had inferior OS (p = 0.04), but the high density did not predict RT (p = 0.4). A Cox multivariate model with IPI, S100A8+ score and TVD90 showed only IPI and TVD90 to be independent predictors of OS (RR = 2.9, 95% CI = 1.6–5.6, P = 0.001; RR = 2.4, 95% CI = 1.3–4.7, p = 0.009, respectively), but only TVD90 predicted RT (RR = 3.1, 95% CI = 1.2–7.6, p = 0.017). Interestingly, low TVD90 (i.e. high MVD) correlated with increased content of S100A8+ cells (χ2, p < 0.001). Conclusion: These results show that in FL, increased vascularization is independently associated with an adverse clinical outcome and, most importantly, predicts for increased RT. These findings may provide a rationale for trials of antiangiogenic therapy in “aggressive” FLs. Tumor to Vessel Distance (TVD) and Follicular Lymphoma Overall Survival & Risk of Transformation Tumor to Vessel Distance (TVD) and Follicular Lymphoma Overall Survival & Risk of Transformation
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».