Screening for Leptomeningeal Disease by High-Sensitivity Flow Cytometry in High Risk Patients with Aggressive Non-Hodgkin’s Lymphoma.
Notice bibliographique
Résumé
Abstract Background: Central nervous system (CNS) involvement by non-Hodgkin’s lymphoma (NHL) portends a very poor prognosis. There is no consensus in the literature on the “high- risk” features that predict for leptomeningeal disease, and no standardized clinical guidelines exist regarding CNS surveillance, prophylaxis or treatment for patients at increased risk. 2–4 colour flow cytometry (FCM) has been reported to be more sensitive than standard cytology in detecting occult leptomeningeal disease (Blood 2005,105:496). The current study evaluates the utility of a high-sensitivity (5-colour) flow cytometry technique for detecting occult lymphoma cells in the cerebrospinal fluid (CSF) of high-risk patients with NHL. Method: Patients with a new diagnosis of histologically aggressive B or T cell NHL were included in this study if they displayed one or more “high-risk” features for CNS involvement. Patients suspected of CNS relapse of NHL were also eligible for participation. Patients underwent routine staging investigations, with the addition of a diagnostic lumbar puncture (LP) during initial assessment. CSF was tested by standard cytology, cell count and biochemistry, and an additional 5 ml was obtained for analysis by high-sensitivity FCM on a Beckman Coulter FC500. The antibody panel (5 antibodies per tube) was customized according to the phenotype of the lymphoma. The key markers for B cell lymphoma were CD19/kappa/lambda with CD5 or CD10. CD45 was used to identify all white blood cells in the sample. Results: Seventeen patients (8M/9F) with a median age of 59 (range 36–85) have been tested. Patients displayed anywhere from 2–6 “high-risk” features for CNS involvement. These included: HIV positivity (2), primary mediastinal B-cell lymphoma (4), bone marrow (5), multifocal bone (2), paraspinal (1), nasopharyngeal (2) or orbital (1) involvement, elevated serum LDH (12), multiple extranodal sites of disease (5), poor performance status (2), high IPI (3), B-symptoms (9), stage IV disease (11), and otherwise unexplained neurological symptoms (3). 14 patients underwent CSF analysis at time of initial diagnosis, one of whom had cranial nerve palsies secondary to a nasopharyngeal mass extending to the skull base. The other 3 were tested at relapse, transformation, and suspected CNS relapse ultimately diagnosed as a stroke. Despite the presence of these features, CSF analysis was negative for lymphoma cells by both cytology and FCM in all but one of the patients tested. However this patient had very high numbers of circulating lymphoma cells in the peripheral blood (PB), and the positive result was felt to be due to PB contamination of the CSF during a “bloody tap.” One patient with vague neurological symptoms had a negative LP at diagnosis, and later developed frank CNS involvement by lymphoma, but was too unwell to undergo a repeat LP. Conclusions: Given the limited number of patients enrolled thus far and the low prevalence of patients with NHL and CNS involvement (2/17), it is difficult to fully assess the utility of high-sensitivity FCM in the diagnosis of occult leptomeningeal disease. It is of interest that CSF analysis was negative even in the patient with cranial nerve palsies and in the patient who later developed multiple CNS lesions secondary to lymphoma, suggesting that this technique may have limited sensitivity in diagnosing leptomeningeal disease. The systematic screening of high-risk patients cannot yet be recommended as standard clinical practice.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,001 | 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 ».