MétaCan
Menu
← Back to cohort

Propensity Score Matching Analysis Comparing Reduced Intensity Versus Myeloablative Conditioning in AML/MDS Patients Transplanted with Fludarabine-Busulfan-Low Dose Total Body Irradiation Based Regimen

2014· article· en· W2979363781 on OpenAlexaff
Hassan Sibai, Fotios V. Michelis, Nada Hamad, Jieun Uhm, Vikas Gupta, John Kuruvilla, Jeffrey H. Lipton, Hans A. Messner, Matthew D. Seftel, Dennis Dong Hwan Kim

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsBusulfanFludarabineMedicineTotal body irradiationInternal medicinePropensity score matchingRegimenTransplantationHematopoietic stem cell transplantationOncologySurgeryChemotherapyCyclophosphamide

Abstract

fetched live from OpenAlex

Abstract Background: Allogeneic hematopoietic cell transplantation (HCT) is an effective therapy in Acute Myeloid Leukemia and Myelodysplastic Syndrome (AML/MDS). There is controversy over whether reduced intensity conditioning (RIC) results in similar outcomes to myeloablative conditioning (MAC), especially regarding relapse risk. It is difficult to identify the specific cause of the transplant failure rate in RIC patients amongst the multiple possible factors including relapse risk due to disease characteristics of older pts with AML/MDS, or multiple comorbidities in the population receiving RIC, resulting in higher morbidity and mortality, versus expected lower risk of regimen-related toxicity. In order to overcome this, we used a propensity score matching analysis in this study. Methods: A total of 248 patients transplanted for AML or MDS at the Princess Margret Cancer Center between 2009 and 2013 were included in this analysis. Inclusion was restricted to patients receiving Fludarabine/Busulfan plus low dose total body irradiation (TBI) with either RIC conditioning (Fludarabine 30mg/m2/day for 4 days, Busulfan 3.2mg/kg/day for 2 days and TBI 200 cGy n=121) or MAC conditioning (Fludarabine 50mg/m2/day for 4 days, Busulfan 3.2mg/kg/day for 4 days and TBI 400 cGy; n=127). The RIC and MAC groups were compared for overall survival (OS), non-relapse mortality (NRM) and relapse. Propensity score matching (PSM) analysis is used to adjust for the risk factors which affect the choice of treatment between different treatment options. Using PSM analysis, we performed a case-control study with well-balanced pairs of RIC and MAC patients. Pre-transplant variables included in the PSM were age at HCT, HCT-Comorbidity Index (HCT-CI), complete remission status (CR) at HCT, diagnosis (AML vs MDS), cytogenetic risk group (high-risk vs others), donor type (related vs unrelated) and period effect (transplant year). A total of 39 case-control pairs were selected within 0.2 of a difference in propensity score. Paired analysis was adopted throughout the PSM analysis for survival. RESULTS: With a median follow-up of 18 months among survivors in the overall population (n=248), the 2-year OS, NRM and relapse incidence rates were 48.0±3.6%, 34.6±3.6% and 24.8±3.5% respectively There was no difference between the 2 groups in OS (45.2±5.0% in RIC vs 51.7±5.2% in MAC at 2 years; p=0.541) or NRM (32.9±5.2% in RIC vs 35.7±4.9% in MAC at 2 years; p=0.504). However, there was a higher incidence of relapse in the RIC group (31.5±5.1% in RIC vs 18.2±4.8% in MAC at 2 years; p=0.033) Demographic and transplant characteristics were imbalanced between the 2 groups within the overall population, including older age (P=<0.001), higher HCT-CI score (p=0.002) and more related donors in the RIC group (p=0.02). However, no differences were observed in CR status at HCT (p=0.110), subtype of diagnosis (AML vs MDS, p=0.174), or cytogenetic risk group (p=0.278). To overcome baseline imbalances we used a PSM analysis, and 39 case-control pairs (n=78) were selected. All pre-transplant variables became well balanced after propensity score matching, i.e. there were no differences in age (p=0.537), HCT-CI (p=0.931), CR status at HCT (p=0.655), diagnosis (p=0.774), cytogenetic risk group (p=0.784), donor type (p=0.496) or period effect (p=0.984). In the propensity score matched patients, there were no differences in OS (58.0±8.8% in RIC vs 50.9±8.1% in MAC at 2 years; p=0.554), NRM (28.0±8.2% in RIC vs 32.8±7.8% in MAC at 2 years; p=0.688), or relapse (17.8±6.7% in RIC vs 18.0±6.8% in MAC at 2 years; p=0.635). Conclusion: These results suggest, based on a propensity score matching analysis, that the outcomes of a Fludarabine/Busulfan plus low dose TBI based‎ RIC HCT for AML/MDS are equivalent to a Fludarabine/Busulfan plus low dose TBI based MAC with regards to the risk of relapse, NRM, and OS. Disclosures No relevant conflicts of interest to declare.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.259
Teacher spread0.235 · 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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueBlood→Same topicAcute Myeloid Leukemia Research→French-language works237,207→