A Link Between Hypercholesterolemia and Chronic Lymphocytic Leukemia
Notice bibliographique
Résumé
Abstract Background Dyslipidemia and metabolic syndrome are risk factors for cancer, and clinically aggressive CLL cells are believed to rely on lipid metabolism. Statins promote apoptosis and inhibit CLL cell growth in pre-clinical models, and statin use during salvage therapy for CLL may confer a survival advantage. Methods To investigate the prevalence of hyperlipidemia and the effect of statin therapy, lipid profiling was performed on 238 consecutive patients presenting to a specialized CLL clinic between January 2012 and February 2014. Demographics, timing of diagnosis and initiation of chemoimmunotherapy was ascertained from clinical records. Prognostic information was obtained from pathology or flow cytometeric reports. The first lipid profile following CLL diagnosis was recorded. RAI stage was determined from blood counts and radiology or clinical examination at the time of lipid profiling. Patients were grouped according to statin therapy (yes/no) and hyperlipidemia. Results Of 281 patients reviewed, 238 were evaluable with a lipid profile. 110 patients (46.2%) were either taking statins at the time of their CLL diagnosis (27.3%) or prescribed a statin during the study period (18.5%) and an additional 11 (4.2%) had a diagnosis of dyslipidemia not on therapy. Of the remaining 117 patients, 18 had LDL ³ 3.5mmol/L, giving a total of 139 patients (58.4%) with abnormal lipid profiles. The statin-exposed group was significantly older (median age 69.5 vs 65, p=0.03) and there were a larger proportion of males (68.6% vs. 53.9%, p=0.02). There were no significant differences in RAI staging, cytogenetics, beta-2-microglobulin levels, or CD38 expression between groups. (Table 1) 59.7% of all patients were treatment-free by the end of the study period and there were no differences between statin/no-statin groups. Of those requiring treatment, median time to first treatment (TFT) was 48 (IQR, 24-85.3) months. TFT was significantly longer with statins (57.5 (IQR, 32-77) vs. 36 (IQR, 11-100) months, p<0.02. Initiation of statins following diagnosis of CLL was associated with further prolongation of TFT compared to those on statins at diagnosis (74 (IQR, 62-96) vs. 45 (IQR, 30-64) months, p<0.02). Two cases of spontaneous remission were noted with statin initiation. (Figure 1) Conclusions There is an increased prevalence of hyperlipidemia in CLL patients (58.4%) compared to the general population (35-39%). Statin therapy is associated with a prolonged TFT despite a significantly older population and a higher proportion of male patients in this group. CLL patients should be screened for hyperlipidemia and statin therapy may be an adjunct to CLL treatment. Patient Characteristics by Lipid Abnormalities Abstract 5630. Table 1.Time to First Treatment (TFT) by Statin UseTotal N (%)No statin N (%)Statin Use/Dyslipidemia N (%)p -valueTotal238117121Male146 (61.3)63 (53.9)83 (68.6)0.02Median age (Q1, Q3)67 (60, 74)65 (58, 73)69 (63, 76)0.01RAI Stage0.64N1178 (74.8%)78 (66.7%)99 (81.8%)MBL73407135361341618232102232081241477Lipid profile (Mean ± Std Dev)HDL (mM)1.23 ± 0.471.33 ± 0.491.14 ± 0.420.001LDL (mM)2.55 ± 1.032.69 ± 0.872.42 ± 1.160.05TC/HDL3.92 ± 1.433.80 ± 1.254.03 ± 1.570.21Non HDL-C (mM)3.22 ± 1.143.29 ± 0.993.14 ± 1.270.29B2M (N = 0.6-2.3 m g/ml)0.52Mean ± Std Dev3.20 ± 2.143.19 ± 2.363.21 ± 1.92CD38 status0.86Unknown74 (31.1%)37 (31.6%)37 (30.6%)CD38+331419CD38-1226260Partial945Cytogenetics20.32Unknown125 (52.5%)61 (52.1%)63 (52.1%)13q-62283511q-1367+122081217p-1275normal24159>1 abnormality201010 1stage determined from those untreated at time of lipid profiling 2counted in all pertinent groups if more than one abnormality Abstract 5630. Table 2. Time to First Treatment (TFT) by Statin Initiation Total (N=238) No statin (N=128) Statin Use (N=110) P-value W&W1 (%) 142 (59.7) 74 (58.8) 68 (61.8) 0.53 Available TFT data/Total Treated2 89/96 51/54 38/42 Median TFT (IQR) (mo) 48 (24, 83) 36 (11, 100) 57.5 (32, 77) 0.02 1watch & wait 2could not determine TFT for some patients. Abstract 5630. Table 3. No statin (N=128) Statin Started (N=43) Statin Previous (N=67) P-value W&W1 (%) 74 (58.8) 29 (67.4) 39 (58.2) 0.55 Available TFT data/Total Treated2 51/54 13/14 25/28 Median TFT (IQR) (mo) 36 (11, 100) 74 (62, 96) 45 (30, 64) 0.04 1watch & wait 2could not determine TFT for some Figure 1 Figure 1. [1]Spaner DE, Lee E, Shi Y, Wen F, Li Y et al. Leukemia 2013; 27:1090-1099. [2]Chae YK, Trinh L, Jain P, Wang X, Rozovski U et al. Blood 2014; 123: 1424-1426. Disclosures No relevant conflicts of interest to declare.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,003 | 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 ».