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Record W3097237398 · doi:10.1182/blood-2020-141790

Role of Allogeneic Hematopoietic Cell Transplant in Patients with Myelofibrosis in the JAK Inhibitor Era

2020· article· en· W3097237398 on OpenAlexaffabout
Dawn Maze, Murat O. Arcasoy, Ryan Henrie, Sonia Cerquozzi, Rammurti T. Kamble, Samer Al Hadidi, Abdulraheem Yacoub, Mahmoud Elsawy, Shireen Sirhan, Anurag K. Singh, Elliot Smith, C. Marcoux, Dietrich Werner, Wenda Greer, Auro Viswabandya, Andrew Daly, Hassan Sibai, Caroline McNamara, Wei Xu, Katherine Lajkosz, Lynda Foltz, Vikas Gupta

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsQueen Elizabeth II Health Sciences CentreJewish General HospitalUniversity Health NetworkUniversity of TorontoDalhousie UniversityUniversity of CalgarySt. Paul's HospitalAlberta Health ServicesUniversity of British ColumbiaPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineMyelofibrosisRuxolitinibTransplantationInternal medicineHematopoietic cellHematopoietic stem cell transplantationPediatricsHaematopoiesisBone marrowStem cell

Abstract

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Introduction Allogeneic hematopoietic cell transplantation (HCT) remains the only potentially curative therapy for myelofibrosis (MF). However, despite improvements in donor availability, most patients receive non-HCT therapy in the form of conventional drugs (e.g. hydroxyurea), or more recently, JAK inhibitor therapy (JAKi). For a proportion of patients, JAKi offers durable clinical benefit in the form of symptom improvement, reduction in splenomegaly and improved quality of life. The role of HCT in the JAKi era has not been well studied, and despite recent advances in the understanding of the pathogenesis and refinement of prognostic scoring systems,real-world decision making remains challenging. The goal of this study was to compare the outcomes of patients who received upfront JAKi vs. HCT for MF in dynamic international prognostic scoring system (DIPSS)-stratified categories. Methods This multicentre study included adult patients up to age 70 years with primary or secondary MF in chronic phase who were first seen at one of the eight participating centres in Canada and the United States between January 1, 2012 and December 31, 2017. The primary outcome was overall survival (OS) in patients with DIPSS int-1 risk or higher who received JAKi vs. HCT. To compare the planned, upfront treatment strategy, patients who received a short-course of JAKi as bridging therapy prior to HCT (< 6 months or documented plan of care) were analysed in the HCT group. Similarly, patients who were treated with JAKi, but received a HCT following JAKi failure (>12 months or documented progression) were analysed in the JAKi group. To minimize selection and lead-time bias, OS was calculated from the start of JAKi and date of transplant, respectively. Patients who were transplanted for accelerated- or blast-phase disease were not included in the analysis. OS was calculated using the Kaplan-Meier method and differences were tested using the log-rank test. Results Between 2012 and 2017, 506 patients with MF were seen at the study centres and 311 received JAKi or HCT. Of these, 174 (56%) had PMF and 137 (44%) had post-ET or post-PV MF. An upfront HCT strategy was used in 86 patients and an upfront JAKi strategy was used in 225 patients. Of those, 53 patients went on to receive HCT following JAKi failure. The median duration of follow up of survivors was 32.8 (1.2 - 99.2) months. The median OS of MF patients with DIPSS int-1 or higher was 65.3 (95% CI: 55.7 - 76.4) months for patients treated with an upfront JAKi strategy and 89.4 (95% CI: 20.4 - not reached) months for those treated with an upfront HCT strategy (p=0.018, Figure). The survival of patients with int-1 risk disease was 0.78 (95% CI: 0.69 - 0.88) in the JAKi group vs. 0.60 (95% CI: 0.43 - 0.83) in the HCT group at 36 months and 0.68 (95% CI: 0.57-0.82) in the JAKi group vs. 0.60 (95% CI: 0.43-0.83) in the HCT group at 60 months. Given the small number of patients with DIPSS high risk, these patients were combined with the int-2 cohort for analysis. The survival of patients with int-2/high risk disease was 0.58 (95% CI: 0.49 - 0.69) in the JAKi group vs. 0.49 (95% CI: 0.36 - 0.65) in the HCT group at 36 months and 0.37 (95% CI: 0.24-0.55) in the JAKi group vs. 0.45 (95% CI: 0.32-0.62) in the HCT group at 60 months (Table). Conclusions Previous studies, which included many patients treated in the era before widespread availability of JAKi, supported an upfront HCT strategy in patients with higher risk MF. While these agents have not demonstrated consistent disease-modifying effects, many patients do experience durable clinical benefit in the form of symptom improvement and reduction in spleen size. In our study, there was no clear benefit of upfront HCT. The median OS of patients who received HCT upfront was longer than that of patients who were treated with upfront JAKi, but upfront HCT was associated with early mortality and the OS benefit was not apparent until after 5 years. An inherent limitation of this study is a lack of data on potentially important comorbid conditions which may have contributed to selection bias. However, to our knowledge this is the largest study to compare upfront HCT and JAKi strategies in patients with higher risk MF, making these findings relevant to modern clinical practice in the JAKi era. A delayed transplant approach may be appropriate for selected patients who are deriving clinical benefit from JAKi. Defining the optimal timing for HCT in higher risk MF remains a question for future research. Disclosures Maze: Pfizer: Consultancy; Novartis: Honoraria; Takeda: Research Funding. Arcasoy:CTI Biopharma: Research Funding; Samus Therapeutics: Research Funding; Gilead: Research Funding; Incyte: Research Funding; Janssen: Research Funding. Yacoub:Dynavax: Current equity holder in publicly-traded company; Ardelyx: Current equity holder in publicly-traded company; Cara Therapeutics: Current equity holder in publicly-traded company; Hylapharm: Current equity holder in private company; Incyte: Speakers Bureau; Agios: Honoraria, Speakers Bureau; Novartis: Speakers Bureau; Roche: Other: Support of parent study and funding of editorial support. McNamara:Novartis: Honoraria. Foltz:Celgene: Membership on an entity's Board of Directors or advisory committees; Constellation: Research Funding; Incyte: Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. Gupta:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol MyersSquibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sierra Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy; Incyte: Honoraria, Research Funding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.192
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2020
Admission routes2
Has abstractyes

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