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Enregistrement W4405038601 · doi:10.1182/blood-2024-198797

Handgrip Strength - Finetuning an Objective Measure of Frailty in Transplant-Eligible Patients with Multiple Myeloma

2024· article· en· W4405038601 sur OpenAlexaffabout
Steven Shih, Harjot Vohra, Anup J. Devasia, Sahar Khan, Eshetu G. Atenafu, Donna Reece, Suzanne Trudel, A. Keith Stewart, Sita Bhella, Vishal Kukreti, Chloe Yang, Rodger E. Tiedemann, Anca Prica, Eugene Leung, Christine I. Chen

Notice bibliographique

RevueBlood · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensUniversity Health NetworkWindsor Regional HospitalPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineMultiple myelomaGerontologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Background Frailty assessment has emerged as a useful tool to predict treatment toxicity and efficacy in older, transplant-ineligible patients with multiple myeloma (MM). Frailty testing might also be useful in younger patients to identify those less fit who are destined to suffer undue toxicity from transplant. However, we previously reported that current frailty tools and definitions have limited ability to discriminate amongst transplant-eligible patients, with most clustering into fit or prefrail categories (Devasia ASH 2022). Therefore, frailty-defining thresholds must be redefined and validated for this younger, fitter population. Handgrip strength is a simple objective tool that has been used to predict morbidity and mortality in various populations and in our experience, has the highest completion rate amongst the objective functional tools. Thus, we aimed to further evaluate handgrip strength and the optimal thresholds that would best identify less fit patients preparing for transplant. Method In an ongoing prospective trial at our centre, MM patients undergo a battery of objective and subjective frailty assessments prior to autologous stem cell transplant. Various handgrip strength thresholds were derived firstly by obtaining the mean and standard deviation (SD) of our cohort, a healthy US (Wang J Ortho Sports 2018), and Canadian population (Wong Stats Can 2016), stratified by gender, age, weight and height. We then constructed SD thresholds (0.5 SD, 1SD, 1SD-5kg, 1.5SD, 2SD) below the mean. These were then correlated with frailty parameters using: subjective frailty tools (Karnofsky, ECOG, Rockwood, Lawton ADL, Edmonton symptoms [ESAS], exhaustion and weight loss scores), tests of organ function (LVEF, CrCl, PFT, cell counts of marrow function), comorbidity indices (Charlson, haematopoietic cell transplant specific [HCT-CI]), and integrated myeloma-specific frailty scores (IMWG-geriatric assessment tool [IMWG-GAT], Revised Myeloma Comorbidity Index [R-MCI]). T-test was used for continuous variables; chi2 or Fisher's exact test as appropriate for categorical variables. All P values were 2 sided and statistically significant at P <0.05. Statistical analysis was performed using SAS system version 9.4. Results To date, 352 study patients have undergone frailty testing prior to transplant. Of these, 23 (7%) had incomplete data, thus 329 (93%) were included in our analysis. Overall, we found that the handgrip threshold of 1.5 SD below the mean of a healthy Canadian population stratified by gender and age, identified 76/329 (23%) of our patients and correlated with the largest number of frailty parameters (referred hereon as “weak” handgrip). When compared to all others, those patients with “weak” handgrip had lower organ function measures, including mean hemoglobin (p=0.03), albumin (p<0.01), LVEF (p=0.03), FEV1 (p=0.04), FVC (p<0.01) as well as worse subjective symptom/function scores, including higher ESAS (p<0.01), ECOG (p<0.01) , Karnofsky (p<0.01), Rockwood (p<0.01), Lawton ADL (p<0.01). Patients with “weak” handgrip also had more comorbidities as per Charlson (p<0.01) and HCT-CI (p=0.01), and rated less fit using the myeloma-specific IMWG-GAT (p<0.01). From a feasibility perspective, we reported handgrip testing had 100% completion rate, whilst up to 9.1% were unable to complete walk-based tests (6 minute walk, timed-up-and-go), mostly due to limitations from bone pain. Finally, we tested various models combining handgrip strength with “subjective” measures of patient function (ESAS, ADL, Rockwood, Karnofsky). This allowed us to further fine-tune the most unfit proportion of our cohort to 10-15%. Conclusion Handgrip strength is a quick and simple test which shows promise as a consistently feasible frailty assessment tool for transplant-eligible MM patients. Thresholds to define weak grip strength must be appropriate for each population. In this analysis, thresholds of 1.5 SD below the mean of healthy Canadian population, stratified by gender and age performed the best and correlated well with other frailty assessments. We next plan to employ this new threshold for handgrip strength in combination with subjective functional measures in our ongoing study of transplant-eligible patients and correlate with post-transplant toxicity. This may facilitate personalization of supportive care (e.g. selected antibiotic prophylaxis) and risk counseling.

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)0,002
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
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,021
Tête enseignante GPT0,274
Écart entre enseignants0,253 · 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
Publié2024
Routes d'admission2
Résumé présentoui

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