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Record W3212166614 · doi:10.1182/blood-2021-153045

Propensity Score Matching Analysis Comparing Extracorporeal Photopheresis (ECP) Vs Best Available Therapy in Third Line or Later Treatment of Chronic Graft-Versus-Host Disease (cGVHD)

2021· article· en· W3212166614 on OpenAlexaff
Swe Mar Linn, Igor Novitzky‐Basso, Elizabeth Shin, Christopher J. Patriquin, Ivan Pašić, Wilson Lam, Arjun Law, Fotios V. Michelis, Armin Gerbitz, Auro Viswabandya, Jeffrey H. Lipton, Rajat Kumar, Jonas Mattsson, David Barth, Dennis Dong Hwan Kim

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicinePrednisoneExtracorporeal PhotopheresisPropensity score matchingRituximabPhotopheresisInternal medicineGraft-versus-host diseaseRandomized controlled trialMaintenance therapyCohortRetrospective cohort studySurgeryTransplantationChemotherapyDiseaseLymphoma

Abstract

fetched live from OpenAlex

Abstract *DB and DK contributed to the work equally Background Prospective randomized controlled data comparing extracorporeal photopheresis (ECP) to other treatments for chronic graft vs host disease (cGvHD) as third-line or later therapy are limited, despite its clinical benefit observed in patients (pts) who failed ≥ 2 lines of previous therapy. Our single-center experience has reported promising results, including 68.3% failure-free survival (FFS) and 85.9% overall survival (OS) at 12 months in 75 heavily pre-treated cGvHD pts treated with ECP (ASH 2021 Abstract ID 152640). The present study compared outcomes, using propensity-score matching (PSM), between ECP ("ECP group", n=74) and a historical cohort treated with best available therapy (BAT) as third-line or later treatment from 2007 to 2021 ("BAT group", n=132). Statistical endpoints such as FFS and OS, as well as steroid dose reduction were evaluated instead of overall response due to limited response assessment data available from retrospective chart review. Patients and methods The BAT group received MMF (n=71, 53.8%), prednisone (n=37, 28.0%), prednisone/cyclosporine (n=7, 5.3%), rituximab (n=7, 5.3%), and others (n=10, 7.6%). There was an imbalance in characteristics between the two groups, as expected; the ECP group had more pts with severe cGVHD (91.1% vs 20.5%; p<0.001), fewer with a previous history of acute GVHD (aGvHD: 60.8% vs 78.0%; p=0.008), and fewer on a prednisone dose ≥0.5mg/kg/day (37.8% vs. 90.5%; p<0.001). PSM analysis was applied to adjust risk factors imbalanced between groups, including cGVHD grade (mild/moderate vs severe), aGVHD history, and baseline prednisone dose (<0.5 vs. ≥ 0.5 mg/kg/day). A total of 54 pts (27 case-control pairs) were selected via PSM within 0.2 of a calliper difference, resulting in the balancing of risk factors between groups: cGVHD severity (p=0.941), aGVHD history (p=0.75) and prednisone dose ≥ 0.5 mg/kg/day (p=0.788). FFS and OS were calculated from the day of starting ECP or BAT, and were compared using Cox's hazard model. Daily prednisone dose at months 0, 3 and 6 were calculated divided by body weight (kg), and the proportions of pts on prednisone ≤ 0, 0.1, 0.2 and 0.5mg/kg/day were compared. Results In the overall cohort (n=206), with a median 29 months of follow-up, 114 treatment failures (55.3%) occurred. While the non-relapse mortality (NRM) was similar in both groups, the ECP group showed a lower rate of resistance requiring therapy switch. Failure was noted in 27 ECP pts (36.4%) due to causes including resistance/intolerance requiring a switch to other therapy (n=15; 20.3%), NRM (n=11, 14.8%), and relapse (n=1; 1.4%), while 87 failures (65.9%) were noted in BAT pts due to resistance requiring a switch to other therapy (n=63; 47.7%), NRM (n=7; 5.3%), and relapse (n=17; 12.9%). In the overall cohort, the 12-month FFS was 68.3% and 32.0% in ECP and BAT groups (p<0.0001; Fig 1A), while OS was 86.2% and 82.2% in ECP and BAT groups, respectively (p=0.333; Fig 1B). In the PSM cohort (n=54), the ECP group showed a survival benefit at 12 months: FFS was 65.8% in the ECP group vs. 30.5% in the BAT group (p=0.00226; Fig 2A), and OS was 76.6% in the ECP group vs. 67.1% in the BAT group (p=0.0977; Fig 2B). Multivariate analysis in the PSM cohort confirmed that ECP was superior to BAT for FFS (p=0.024, HR 0.317 [0.117-0.859]) when adjusted for other risk factors including cGVHD severity, aGvHD history, age, HCT-CI score and prednisone dose ≤0.5mg/kg/day. Prednisone doses were gradually reduced over time; the median doses of prednisone at months 0, 3, and 6 were 0.35, 0.22 and 0.11 mg/kg/day, respectively, in the ECP group vs. 0.96, 0.24 and 0.19mg/kg/day in the BAT group. ECP also showed better kinetics of steroid dose reduction over time; the proportions of pts who discontinued prednisone at months 0, 3 and 6 were 16.2, 17.6% and 32.4% in ECP group vs. 0.8%, 0% and 2.5% in BAT group (Fig 3). The differences in the proportion of pts (delta) who discontinued prednisone in the ECP vs. BAT groups were 15.4%, 17.6% and 29.9% at 0, 3, and 6 months, respectively. Conclusion In the current study using PSM analysis, use of ECP was associated with a superior FFS to BAT when used as third-line or later therapy in cGVHD patients who failed at least 2 lines of previous therapy. Use of ECP also allowed for better steroid tapering in comparison to BAT. Figure 1 Figure 1. Disclosures Patriquin: Alexion: Consultancy, Honoraria, Speakers Bureau; BioCryst Pharmaceuticals: Honoraria; AstraZeneca: Consultancy, Honoraria, Speakers Bureau; Apellis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria. Law: Novartis: Consultancy; Actinium Pharmaceuticals: Research Funding. Lipton: Bristol Myers Squibb, Ariad, Pfizer, Novartis: Consultancy, Research Funding. Mattsson: MattssonAB medical: Current Employment, Current holder of individual stocks in a privately-held company. Kim: Novartis: Consultancy, Honoraria, Research Funding; Paladin: Consultancy, Honoraria, Research Funding; Bristol-Meier Squibb: Research Funding; Pfizer: 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)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.081
GPT teacher head0.291
Teacher spread0.210 · 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 designNon-randomized trial
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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Citations1
Published2021
Admission routes1
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