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Enregistrement W2989272704 · doi:10.1182/blood.v128.22.1184.1184

Cost Analysis of Stored Autologous Peripheral Blood Stem Cells for a Second Autologous Transplantation in Multiple Myeloma Patients: A Markov Model

2016· article· en· W2989272704 sur OpenAlexaffabout
Anca Prica, Vinita Dhir, Nuchanan Areethamsirikul, Christine Chen, Donna Reece, Suzanne Trudel, Rodger E. Tiedemann, Vishal Kukreti

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineMultiple myelomaAutologous stem-cell transplantationLenalidomideTransplantationCohortSurgeryStem cellOncologyInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Autologous stem cell transplantation (ASCT) is a standard part of first-line therapy for pts <70 years of age with multiple myeloma. If remission length is ≥ 2 years, our policy is to offer a salvage transplant upon relapse if the patient is eligible. Many centers, including ours, collect adequate CD34+ cells for two transplantations, as there is concern for poor mobilization post-therapy, including lenalidomide. However, no good data truly quantifies this rate, given plerixafor availability. The advent of novel therapies has reduced the use of second salvage ASCT (ASCT2), and the prolonged storage of cryopreserved stem cells imposes a significant economic burden. We performed a cost analysis to compare the cost of mobilizing and storing stem cells for ASCT2 in all patients versus remobilizing and collecting for ASCT2 upon relapse in eligible patients. Methods: We developed a Markov decision-analytic model to compare the two strategies in a hypothetical cohort of 60 year old patients newly-diagnosed with multiple myeloma. The model simulates the clinical course of 10,000 patients over a 10 year time horizon, with the end point of costs per patient per strategy. Baseline probabilities were derived from published studies as well as analysis of multiple myeloma patients who underwent ASCT1 at Princess Margaret Cancer Centre between January 2003 and December 2012. Key health states include probability of progression (pPD) and death in the 1st 2 years post-ASCT1, pPD >2 years post-transplantation, probability of having an ASCT2 upon relapse vs. a non-ASCT approach. Direct costs were collected from a Canadian public health payer's perspective. Costs were obtained from hospital and provincial databases, as well as the literature and presented in 2016 Canadian dollars. Key costs collected were the cost of mobilization for 2 transplants vs. 1, the cost of remobilization and the cost of stem cell storage. Costs were discounted at 3%. All patients were assumed ASCT2 eligible at relapse. In the re-mobilization arm, all patients were successfully remobilized, with an assumed >50% rate of plerixafor use. Results: 938 patients underwent ASCT1 at Princess Margaret Cancer Centre during this time period, with stem cells stored for a salvage transplant. The mean age of transplanted patients at ASCT1 was 58.4 yrs. The mean number of aphaeresis days required to collect enough cells for 2 stem cell transplants was 1.53 days. The calculated mean aphaeresis days required to collect for 1 transplant was 1.15 days. The median number of bags processed for 2 ASCT was 4, as such, after ASCT1, the median number of bags stored per person was 2. 74 patients (7.9%) underwent ASCT2 over the 10 year period. Most (73%) occurred early, 2-5 yrs post-ASCT1, with only 27% beyond this time period. Over the 10 yr horizon, the total mobilization and storage cost of the stored stem cells strategy was C$9702, versus C$7229 for the re-mobilization strategy, thus storing stem cells for a potential ASCT2 costs an extra C$2473 per patient. Our centre collects such stem cells in >100 pts/yr, at a cost of approximately $250,000. The model was robust to one-way sensitivity analyses of all variables. Storing stem cells only becomes the less costly strategy if the storage costs are less than C$125/6mo or C$10/bag/month (figure 1). Conclusions: The use of salvage ASCT for patients who sustain at least a 2 yr remission with their first is low (less than 10%), and it is associated with significant costs to the system unless the costs of stem cell storage are minimal. With the availability of plerixafor, the cost savings would justify a re-mobilization approach for the minority of patients that are eligible for a salvage ASCT. Figure 1 Figure 1. Disclosures Prica: Janssen: Honoraria; Celgene: Honoraria. Chen:Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Takeda: Research Funding. Reece:Janssen: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Merck: Research Funding; Novartis: Honoraria, Research Funding; Otsuka: Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; BMS: Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding. Trudel:Glaxo Smith Kline: Honoraria, Research Funding; Celgene: Honoraria; Novartis: Honoraria; Oncoethix: Research Funding. Tiedemann:Takeda Oncology: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Novartis: Honoraria; Amgen: Honoraria; BMS Canada: Honoraria. Kukreti:Celgene: Honoraria; Lundbeck: Honoraria; Amgen: Honoraria.

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)0,004
score de la tête « metaresearch » (Gemma)0,009
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,079
Score d'incertitude au seuil0,158

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,009
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0030,001
Intégrité de la recherche0,0030,003
Charge utile insuffisante (le modèle a refusé de juger)0,0100,000

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 Opus0,027
Tête enseignante GPT0,276
Écart entre enseignants0,250 · 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'étudeSimulation ou modélisation
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
Publié2016
Routes d'admission2
Résumé présentoui

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