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Record W3096392740 · doi:10.1182/blood-2020-139736

ATG and Post-Transplant Cyclophosphamide Do Not Abrogate the Inferior Outcome Risk Conferred By HLA-Α and HLA-B Mismatched Unrelated Donors

2020· article· en· W3096392740 on OpenAlexaffabout
Igor Novitzky‐Basso, Carol Chen, Ivan Pašić, Zeyad Al‐Shaibani, Wilson Lam, Arjun Law, Armin Gerbitz, Auro Viswabandya, Jeffrey H. Lipton, Dennis Dong Hwan Kim, Rajat Kumar, Fotios V. Michelis, Jonas Mattsson

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsCumulative incidenceMedicineInternal medicineCyclophosphamideRetrospective cohort studyProportional hazards modelLog-rank testTransplantationIncidence (geometry)CohortOncologyImmunologyGastroenterologyChemotherapy

Abstract

fetched live from OpenAlex

Background Donor selection for allogeneic stem cell transplant is a complex process, where several factors are considered for potential impact on transplant outcome. Several publications have suggested that 9/10 mismatched unrelated donors (MMUD) may be equivalent to 10/10 MUDs. However, there is debate as to whether all 9/10 mismatches (MM) are equivalent. We sought to examine this in a single centre retrospective study using ATG followed by post transplant cyclophosphamide (ATG PTCy) as standard GvHD prophylaxis and correlated outcomes in terms of donor MM, donor age and CMV serostatus. Patients and methods A total of 414 patients who received HCT from unrelated donors between Jan 2015 and Dec 2019, at Princess Margaret Cancer Centre, Canada, were enrolled in the retrospective study. Patients and disease characteristics, and outcomes are detailed in Tables 1-3. The probability of overall survival (OS) was calculated using the Kaplan Meier product limit method and heterogeneity of time to event distribution functions was compared by the log rank test. The cumulative incidences of chronic and acute GvHD, relapse, and transplant related mortality (TRM) were estimated using the cumulative incidence method considering competing risk, and groups were compared using Gray's test. Death was considered a competing event for relapse, acute and cGvHD, and relapse was considered a competing event for NRM, acute and cGvHD. GvHD outcomes shown in Table 4. Results Median OS at 5y for the whole cohort (n=414) was 45.8% (38.2-53.0), and relapse free survival was 40.2% (32.9-47.4), with TRM at 1y 23.7% (19.6-28.0), Table 5. Compared to the whole cohort (median OS 38.8mo [21.6-NA]), patients who received grafts from MMUD (n=86) had median OS 9.2mo (6.0-17.3), p<0.001, in particular median OS for HLA-A MM was 8.1mo (5.3-18.4), HLA-B MM 5.9 (2.7-11.8) compared to other 9/10 MMUD (n=32) 18.8mo (5.7-NA), p<0.001. This was due to higher TRM at 1y, MMUD 39.1% (24.0-49.4) vs MUD (n=327) 19.2% (15.0-23.8) p<0.001 primarily due to HLA-A MM 39.6% (24.0-54.9) and HLA-B MM 35.7% (11.7-61.1), p=0.001. GVHD-Free Relapse free Survival (GRFS) at 5y for the whole cohort was 36.8% (29.7-43.9). GRFS At 2y for 9/10 MMUD was 25.2% (16.1-35.4), HLA-A MM 21.6% (9.9-36.2) HLA-B MM 15.4% (2.5-38.8) vs MUD 51.4% (45.3-57.2), p<0.001. Median OS for patients who received ATG PTCY (n=298) was 49.2mo (49.2-NA), for 9/10 (n=58) 10.2mo (6.1-19.6), with HLA-A MMUD (n=26) 9.6 mo (5.8-27.4), HLA-B MMUD (n=9) 4.6mo (1-11.8) (p<0.001), Figure. A number of donor factors significant by univariate analysis (incl. donor age, recipient/donor CMV, CD34 dose, presence of HLA MM, type of MM, female donor to male recipient), were selected to determine correlates with all mortality by multivariable analysis (MVA). The only significant factor was 9/10 MMUD HR 2.27 (1.65-3.14), p<0.0001, specifically HLA-A MM HR 2.69 (1.77-4.08), p<0.00001, HLA-B MM HR 3.14 (1.71-5.78) p=0.0002, Table 6. The same donor factors significant by univariate analysis were examined for correlation with TRM and significance was found for HLA MM HR 2.36 (1.57-3.55) p=0.00004, specifically HLA-A MM HR 2.44 (1.42-4.17), p=0.0012, HLA-B MM HR 2.39 (1.03-5.57) p=0.0034. Graft failure (GF) occurred in 4.6% of patients. Significant donor factors for GF were CD34 dose <4.0x106/kg, HR 5.28 (1.11-24.98) p=0.038; and HLA MM 2.78 (1.27-6.05) p=0.01. Of 414 patients, 395 patients (95.4%) received fresh stem cells and 19 (4.6%) received cryopreserved stem cells. Cryopreserved MUD grafts were associated with GF on MVA, HR 5.56 (1.75-17.4, p=0.0034), which may be due to several possible factors including the travel time prior to cryopreservation. Among AML patients, CMV negative patients in receipt of grafts from CMV negative donors (CMV-/-) (n=64) had worse survival (HR 2.05, 1.03-4.09, p=0.04) compared to recipient/donor pairs where any were CMV positive. There was a significantly higher relapse rate in the CMV-/- (15/64, 23.4%), compared to CMV positive (30/236, 12.2%, any combination), p=0.01 by Chi-squared test. Conclusions These data suggest that HLA-A and HLA-B mismatched donors confer a significantly inferior outcome despite the use of ATG PTCy. Cryopreserved stem cells from unrelated donors were associated with graft failure, and CMV-/- were associated with higher incidence of relapse. Further work is required to develop novel conditioning regimens and GvHD prophylaxis to mitigate these risks. Disclosures Lipton: BMS: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Ariad: Consultancy, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Takeda: Consultancy, Honoraria, Research Funding. Mattsson:Gilead: Honoraria; ITB: Honoraria; Takeda: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Honoraria; Mallinkrodt: Honoraria.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.013
GPT teacher head0.239
Teacher spread0.226 · 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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Citations0
Published2020
Admission routes2
Has abstractyes

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