Body Composition Predicts Survival in Allogeneic Hematopoietic Stem Cell Transplantation (HSCT) Recipients
Notice bibliographique
Résumé
Abstract Background: Innovative means to risk-stratify HSCT patients are needed. Previous studies in cancer patients suggest association between body composition and survival. However, this has not been previously described is allogeneic HSCT recipients. Furthermore, the correlation of body composition with pre- and post-HSCT physical activity in cancer patients remains undefined. We postulated that body composition prior to HSCT is associated with post-HSCT outcomes. Methods: Patients who had completed pre-HSCT physical function assessment as part of ongoing prospective clinical trial were identified. Analysis of self-reported and measured physical activity and their association with outcomes after transplantation is currently ongoing. Regional CT at the 4th thoracic vertebra (T4) was obtained for post-hoc analysis of body composition within this cohort. Using Slice-O-Matic software V4.3 (Tomovision, Magog, Quebec, Canada), both adipose and muscle tissue were quantified to obtain the respective cross sectional area (cm2). Fat and skeletal muscle were identified and quantified within the following CT Hounsfield unit thresholds: -29 to +150 for skeletal muscle and -190 to -30 for adipose tissue. Tissue boundaries were manually corrected as necessary. Cross sectional areas were subsequently normalized for stature (height2) to obtain a tissue index for both fat and muscle (cm2/m2). For this analysis, fat index (FI) and muscle index (MI) were divided into quartiles (group 0: ≤25%, group 1: 26-50%, group 2: 51=75%, group 3: ≥75%). Statistical significance was defined as p < 0.05 and all analyses were done on SAS 9.3. Results: All patients (n=50) enrolled on the pre-HSCT functionality trial between 02/2014 and 02/2015 were identified for this analysis. 3 patients were excluded for analysis: 2 subjects ultimately did not proceed to HSCT and 1 subject had a CT scan that was not evaluable. Thus, 47 subjects had evaluable data; baseline characteristics are summarized (Table 1). Median follow-up for survivors is 298 days (interquartile range (IQR): 272-368 days). Overall survival (OS) significantly differs between FI strata (log rank p value =0.0013) (Figure 1). MI is not associated with OS (p=NS). FI is inversely correlated with distance walked during 6-minute walk test pre-HSCT (r = -0.33, p = 0.027). FI and MI are not significantly associated with self-reported physical activity using the International Physical Activity Questionnaire (IPAQ) post-HSCT (day 1, 30, 90), or patient-reported quality of life (QOL). Conclusions: These data provide the first evidence supporting an association between CT-defined cross sectional adipose tissue index and survival following HSCT. This non-invasive, routinely employed imaging modality may provide a new avenue for enhanced risk-assessment for HSCT patients. Subsequent studies will examine this effect in larger populations, with specific attention to other established prognostic variables. Table 1. Baseline Characteristics Variables N (%) Age, yrs (median, range) 60 (24-75) Gender, male 30 (63.8%) KPS ≥90 42 (89.3%) HCT-CI≥3 29 (61.7) Diagnosis § AML § ALL § CLL § CML § MDS § HD § MM § MPS § NHL 12 (25.5%) 5 (10.6%) 3 (6.4%) 2 (4.3%) 9 (19.1%) 2 (4.3%) 3 (6.4%) 2 (4.3%) 9 (19.1%) Conditioning Intensity, Myeloablative 24 (51.1%) Armand Disease Risk at HSCT § Low § Intermediate § High/Very High 2 (4.3%) 26 (55.3%) 19 (40.4%) Donor Type § Matched Related Donor § Matched Unrelated Donor § Mismatched Unrelated Donor § Double Umbilical Cord Blood 13 (27.7%) 27 (57.4%) 6 (12.8%) 1 (2.1%) Disclosures No relevant conflicts of interest to declare.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 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 | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».