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Enregistrement W2553445886 · doi:10.1182/blood.v118.21.2091.2091

Comparison of Comorbidity Scores and the Impact of Comorbidities on Length of Stay and Survival in Patients with Non−Hodgkin's Lymphoma Treated with Autologous Stem Cell Transplant

2011· article· en· W2553445886 sur OpenAlexaff
Kylie Lepic, A. Benger, Ronan Foley, Graeme Fraser, Deborah Marcellus, Michelle Saunders-Roy, Michael Trus, Anita Adams, Kari Kolm, Jennifer Wiernikowski, C. Tom Kouroukis

Notice bibliographique

RevueBlood · 2011
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensMcMaster UniversityHamilton Health SciencesJuravinski Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineComorbidityInternal medicineInternational Prognostic IndexAutologous stem-cell transplantationOncologyTransplantationDiffuse large B-cell lymphomaProportional hazards modelMelphalanPerformance statusPopulationSurgeryLymphomaCancer

Résumé

récupéré en direct d'OpenAlex

Abstract Abstract 2091 Autologous stem cell transplant (ASCT) is the treatment of choice for relapsed aggressive histology Non-Hodgkin's lymphoma (NHL) and is part of first line therapy for mantle cell lymphoma (MCL). Although treatment related morbidity and mortality from ASCT is considerably less than for allogeneic transplant, it is not without risk and can be affected by comorbid conditions. Two comorbidity scores have been used for stem cell transplant patients to assess risk, the Charlson Comorbidity Index (CCI) (Biol Blood Marrow Transplant 2008;14:840-6) and the Hematopoietic Stem Cell Transplantation Comorbidity Index (HCT-CI) (Blood 2005;106:2912-19). The Cumulative Illness Rating- Geriatric Severity Index (CIRS-G SI) has also been used in patients with cancer (J Clin Oncol 1998;16:1582-7). This project compares these comorbidity scores and examines the effect of comorbid conditions on outcomes post transplant. A retrospective chart review was performed on 101 patients with NHL receiving ASCT from 2003 to 2010 at our institution. Patients were conditioned using BEAM chemotherapy (BCNU, etoposide, cytarabine, melphalan). Variables collected included age, gender, diagnosis, international prognostic index (IPI), comorbidity scores, length of stay (LOS) and overall survival. The length of stay was calculated as the extra LOS (ELOS) beyond day 14 to account for some patients who were able to be discharged early for proximity reasons. Correlations were calculated using the Pearson Correlation Coefficient. Linear and Cox regression were used in the analysis. The median age of the patient population was 57 years (range 26–68 years) and 38% were female. The majority of patients had diffuse large B cell lymphoma (DLBCL) 57%, other histological subtypes included MCL 10%, follicular lymphoma (FL) 10%, transformed FL 7% and others 16%. The median follow-up time was 17.2 months (0.5–96 months) for the entire group, and 28 months (0.5–83) for the DLBCL group. For the DLBCL group, the international prognostic index (IPI) at diagnosis was 0–1 in 67% and 2–5 in 33%. The IPI at relapse was 0–1 in 55% and 2–5 in 45%. The median number of reinfused stem cells was 4.9 × 106 CD34+/ kg (range 1.7–27). The median score on the CCI was 2 (range 2–5), 73% of patients had CCI score of 2 or less, 23% had score of 3 and 4% had a score 4 or greater. The median score on the CIRS-G SI was 3 (range 1.6 – 4). The median score on the HCT-CI was 0 (range 0–5), 66% had a score of 0, 27% had a score of 1 or 2, and 7% had a score of at least 3. The Pearson correlation between the CCI and HCT-CI was 0.8 (p<0.001), between HCT-CI and CIRS-G was 0.3 (p=0.001) and between CCI and CIRS-G was 0.2 (p=0.03). The median survival for the entire group and the for the DLBCL patients was not reached. Survival estimates were 75% for the entire group at 24 months, and 75% for the DLBCL group at 36 months. There was no statistically significant relationship between any of the comorbidity scores and overall survival using Cox regression for either the entire group or the DLBCL group. On univariate analysis, for the entire group of patients, CCI was significantly related to ELOS (p=0.011) but the other comorbidity scores were not. For the DLBCL group, univariate analysis showed that ELOS was associated with CCI (p=0.037) and trended towards significance with HCT-CI (p=0.098). We also performed a multivariable analysis on the entire group looking for predictive factors for ELOS using age, gender, albumin and CCI and found that CCI and gender were significant (p=0.001 for both). In the DLBCL group the same multivariable analysis was done with the addition of IPI at relapse and we found that CCI (p=0.007) and gender (p=0.014) were significant, IPI at relapse, age and albumin were not. In conclusion, the CCI and HCT-CI comorbidity scores are highly correlated for this group of ASCT patients. The CIRS-G SI did not correlate as well with the other comorbidity scores. In this group of patients we could not detect any influence of comorbidity score on survival, however there seems to be a statistically significant relationship between the CCI score and length of stay. The HCT-CI and CIRS-G SI did not affect LOS in this study. There also seems to be a relationship between gender and length of stay, as male patients had a shorter duration of hospitalization. The results of this study will need to be investigated further with a larger sample size. 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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,023
Tête enseignante GPT0,249
Écart entre enseignants0,227 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2011
Routes d'admission1
Résumé présentoui

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