An Exploratory Study of Cytokine Markers of Cancer-Related Cognitive Impairment in Hematological Malignancy
Notice bibliographique
Résumé
Abstract Introduction. Cancer-related cognitive impairment is a distressing symptom that affects numerous patients after cancer therapy, including those treated for hematological malignancy. The lack of effective interventions has driven interest in determining underlying mechanisms. Accumulating evidence in the context of solid tumours suggests inflammatory processes are involved in the development of cognitive symptoms. The objective of this study was to explore whether changes in serum markers of inflammation underlie differences in cognitive functioning among patients treated for hematological malignancies. Methods. The sample comprised participants treated for lymphoma or multiple myeloma who were participating in a feasibility study of a computerized cognitive training program. Prior to the intervention, a battery of neuropsychological tests were administered to assess cognitive function in the following domains: Learning Efficiency and Memory; Information Processing and Psychomotor Efficiency; and Executive Functioning and Working Memory. Composite T-scores for each domain were computed as the mean of demographically adjusted T-scores from constituent tests. Blood was drawn concurrently from consenting participants. Soluble proteins were quantified from serum using a multiplex sandwich elisa assay of 27 arrayed cytokine and chemokine analytes. Pearson's correlations between composite T-scores and cytokine concentrations were calculated. T-tests assessed differences in cytokine concentrations between participants who met the criteria for impairment (composite T-score<40) compared to those who did not. Results. Eleven participants (Non-Hodgkin Lymphoma: n=5; Hodgkin Lymphoma: n=3; Multiple Myeloma: n=3; Mean age = 52 years; 6 males/5 females) were included in this analysis. Six of the participants were treated with autologous stem cell transplant for either lymphoma or multiple myeloma; five with primary chemotherapy treatment for lymphoma. Participants were a median 59 days (range 28-265 days) from completion of treatment. Proportion of patients impaired in each domain were: Leaning Efficiency and Memory (5/11); Information Processing and Psychomotor Efficiency (5/11); and Executive Functioning and Working Memory (3/11). Serum concentration of Chemokine Ligand 4 (CCL4, also known as Macrophage Inflammatory Protein 1β) was positively correlated with performance in Information Processing and Psychomotor Efficiency, such that increased CCL4 was associated with better cognitive performance (r=0.62, p=0.0418). Participants who met the criteria for impairment in the domain of Information Processing and Psychomotor Efficiency had a significantly lower concentration of CCL4 compared to those who did not (impaired: 8.14 pg/ml; non-impaired: 14.88 pg/ml; p= 0.0072). Participants who met the criteria for impairment in the domain of Information Processing and Psychomotor Efficiency also had a lower concentration of Granulocyte Colony Stimulating Factor (GCSF) compared to those who did not (impaired: 14.40 pg/ml; non-impaired: 22.47 pg/ml; p=0.0467). We did not detect any other significant relationships between cytokine concentration and cognitive performance. Conclusions. The findings from this exploratory study suggest that there may be a role for macrophage recruitment in modulating the pathogenesis of cancer-related cognitive impairment in hematological malignancies, particularly in the area of information processing and psychomotor speed. Larger studies are needed to validate this finding and clarify the role of CCL4 in the context of cell signalling pathways involved in cognitive functioning. Disclosures Kuruvilla: Janssen: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Leukemia and Lymphoma Society Canada: Research Funding; Abbvie: Consultancy; Celgene: Honoraria; Amgen: Honoraria; Gilead: Consultancy, Honoraria; Princess Margaret Cancer Foundation: Research Funding; Seattle Genetics: Consultancy, Honoraria; Karyopharm: Honoraria; Lundbeck: Honoraria; Roche: Consultancy, Honoraria, Research Funding.
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 | 0,002 |
| 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 | 0,001 | 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 ».