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Enregistrement W4389229120 · doi:10.1182/blood-2023-191009

Use of Pre-Transplant Minicog Cognitive Impairment Screening and Validation of Frailty and Functionality Assessment Prior to Allogeneic Hematopoietic Stem Cell Transplantation

2023· article· en· W4389229120 sur OpenAlexaff
Tommy Alfaro, María Queralt Salas, Eshetu G. Atenafu, Ora Bascom, Leeann Wilson, Carol Chen, Arjun Law, Armin Gerbitz, Auro Viswabandya, Fotios V. Michelis, Jeffrey H. Lipton, Wilson Lam, Igor Novitzky‐Basso, Dennis Dong Hwan Kim, Jonas Mattsson, Ivan Pašić, Rajat Kumar

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueCancer-related cognitive impairment studies
Établissements canadiensUniversity Health NetworkPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineTransplantationHematopoietic stem cell transplantationInternal medicineCohortCognitionComorbidityOncologyGerontologyPsychiatry

Résumé

récupéré en direct d'OpenAlex

Background: We demonstrated that impaired functionality and frailty have a negative impact on survival after allogeneic hematopoietic cell transplantation (HCT) (Salas et al., 2019). This impact is independent of other predictive models including HCT comorbidity index (HCT-CI) and disease risk index (DRI). Cognitive changes are frequently reported among survivors of autologous and allogeneic HCT. However, impact of the presence of cognitive impairment prior to allogeneic HCT has not been studied. We hypothesized that the presence of cognitive impairment before transplantation could have a negative effect on the outcomes of allogeneic HCT. Patients and methods: We evaluated transplant outcomes of 277 patients who underwent our updated frailty assessment including the MiniCog scale, incorporated as standard of care in April 2020. The MiniCog assessment included recalling of three unrelated words, for a total of three points and drawing of a clock with the face, number and hands indicating a specific time, for a total of 2 points. We used the cutoff score of <3 as a marker of cognitive impairment and evaluated the effect of cognitive impairment on: overall survival (OS), relapse free survival (RFS), non-relapse mortality (NRM). We further sought to validate our previously described frailty scale in prediction of transplant outcomes, including OS, RFS, and NRM, in the new cohort and compare its performance in outcome prediction to the MiniCog scale. Our frailty evaluation included the following variables: Clinical Frailty Scale (CFS), Lawton's instrumental activities of daily living (IADL), timed to get up and go test (TUGT), grip strength (GS) using a hydraulic hand dynamometer, self-rated health questionnaire (SRH), a question on number of falls in the last year (F), C-reactive protein (CRP) and serum albumin (Alb) levels at the time of the consult. The frailty scale was calculated according to the following formula: 1.5×CFS + 1×IADL +1×GS + 1.5×TUGT +1×SRH+1×F+ 1.5×Alb+2×CRP. The frailty scale score ranged from 0-10.5. With these results we stablished 3 frailty cohorts for the patients being planned for alloHCT, fit (≤1), pre-frail (<1 to ≤5.5), and frail (>5.5), based on this risk model. Results: Median age at transplantation was 59 years and 85 (31%) patients were ≥ 65 years. Of all the patients, 36 (14%) had a Karnofsky Performance Scale Index (KPS) of <90%, 206 patients had a low-intermediate risk disease risk index (DRI). Median time of follow up was 9 months. Majority of the patients (46%) underwent transplantation for acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS). Of all patients, 246 (88.8%) had a normal MiniCog score (>3). There was no difference in 2-y OS between patients with normal and low MiniCog score: 67% (95% confidence interval (CI): 59%-74%) vs 60% (95% CI: 36-78%), p=0.21. NRM at 24 months was 26% (95% CI 10-46%) for patients with an abnormal MiniCog vs 23% (95% CI 17-30%), p=0.80. There was no difference in 2-year RFS between patients with normal and low MiniCog score: 65% (95% CI 57-72%) vs 43.5% (95% CI 23-63%), p=0.09. Using the frailty scale, 144 (56%) patients were considered fit, 30 (12%) pre-frail and 81 (32%) frail. Using our original frailty scale, the 2-y OS among the fit, pre-frail and frail patients was: 78% (95% CI 65%-87%), 64% (95% CI 53%-74%) and 27% (95% CI 5.6%-55.6%) p=0.005. 2-year NRM was 19.2% (95% CI 9-31%), 23% (16-32%), and 41.6% (95% CI 11-70%) for the fit, pre-frail and frail patients respectively, p=0.12. Relapse free survival at 24 months was 72.5% (95% CI 58-83%), 60.5% (95% CI 50-70%), and 29% (95% CI 6-57%), p=0.003. Conclusions: In our cohort the sole presence of cognitive decline, based on the MiniCog assessment failed to be a predictor of outcomes after allogeneic HCT. However, ability of our preciously established frailty scale to predict transplant outcomes in this new cohort of patients further validates the results of our previous findings. The presence of frailty is an independent predictor of adverse outcomes after allogeneic HCT.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,073
Score d'incertitude au seuil0,583

Scores Codex et Gemma par catégorie

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

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 Opus0,046
Tête enseignante GPT0,311
Écart entre enseignants0,265 · 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 tête enseignante, 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

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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