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Record W3213442100 · doi:10.1182/blood-2021-148942

Risk Stratification for Relapsed/Refractory Classical Hodgkin Lymphoma Integrating Pretransplant Deauville Score and Residual Metabolic Tumor Volume

2021· article· en· W3213442100 on OpenAlexaffabout
Ho‐Young Yhim, Yael Eshet, Ur Metser, Katherine Lajkosz, Matthew Cooper, Anca Prica, Vishal Kukreti, Sita Bhella, Noémie Lang, Wei Xu, Danielle Rodin, David Hodgson, Richard Tsang, Michael Crump, John Kuruvilla, Robert Kridel

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsWomen's College HospitalDalhousie UniversityUniversity Health NetworkUniversity of TorontoMount Sinai HospitalPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineABVDInternal medicineDacarbazineAutologous stem-cell transplantationOncologyVinblastineStandardized uptake valueSalvage therapyNuclear medicinePositron emission tomographyTransplantationVincristineChemotherapyCyclophosphamide

Abstract

fetched live from OpenAlex

Abstract Introduction Positron emission tomography (PET) positivity before autologous stem cell transplantation (ASCT) predicts poor prognosis in relapsed/refractory (rel/ref) classical Hodgkin lymphoma (cHL). However, there is limited data regarding the value of pre-ASCT residual metabolic tumor volume (rMTV) assessed by PET to predict post-ASCT outcomes. We aimed to evaluate the role of pre-ASCT Deauville score (DS) combined with rMTV in patients with rel/ref cHL who underwent salvage ASCT, and also to establish a risk model integrating pre-ASCT DS, rMTV, and other clinical risk factors. Methods This is a retrospective cohort study using clinical data of patients with rel/ref cHL identified from the lymphoma database and the ASCT database of the Princess Margaret Cancer Center, Toronto, Canada. Following criteria were required: (1) patients (≥18 yrs) with histologically confirmed rel/ref cHL between January 2014 to March 2019; (2) treatment with doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) or ABVD-equivalent regimens; (3) chemosensitive disease after salvage therapy; (4) restaging PET before ASCT clearance. Pre-ASCT PET scans were assessed using the Deauville 5-point scale, and rMTV was computed in the scans with DS 4 or 5 using the 41% maximum standardized uptake value threshold method. Receiver operating characteristics analysis was used to determine an optimal cutoff of rMTV 41% for event prediction. The primary endpoint was event-free survival (EFS), defined as time form ASCT to first documented disease progression, any new lymphoma therapy, death from any cause, or last follow-up. Results A total of 106 patients fulfilled the eligibility criteria and were included. Median age was 33.5 yrs (range, 18-70), and 72 (68%) were male. The cohort characteristics at time of progression were 55 (52%) patients with advanced stage, 28 (26%) with B symptoms, 39 (37%) with extranodal disease, and 39 (37%) with primary refractory disease, defined as achieving less than a complete response, disease progression during first-line therapy, or time to relapse (TTR) 3 months or less. All patients received gemcitabine, dexamethasone, cisplatin (GDP) regimen as salvage therapy. Based on the response to GDP therapy, 24 patients required second (N=20) or third (N=4) salvage regimens before ASCT (brentuximab vedotin [BV] alone or combination with bendamustine [N=16], pembrolizumab [N=9], and mini-BEAM [N=3]). 32 patients (30%) received planned pre- or post-ASCT involved field radiation for DS 4-5 lesions. 4 patients received post-ASCT BV consolidation. With a median follow-up of 26.2 months (interquartile range [IQR], 14.4-49.2), 2-year EFS and overall survival rates were 72.1% and 93.1%, respectively. Pre-ASCT DS was determined as 1-3 (N=63, 59%) and 4-5 (N=43, 41%). None of the patients with DS 5 had new lesions. Patients with pre-ASCT DS 1-3 had significantly better EFS than those with DS 4-5 (2-year; 80.8% vs 59.2%; P=0.002; Fig 1A). Median rMTV 41% of the 43 patients with DS 4-5 was 5.1 cm 3 (IQR, 2.0-24.7). The optimal cutoff of rMTV 41% was 4.4 cm 3. Patients with rMTV low (< 4.4cm 3, N=21) had better EFS than those with rMTV high (N=22; 2-year, 75.0% vs 45.4%; P=0.009), but had similar 2-year EFS when compared with patients with DS 1-3 (80.8%, P=0.280; Fig 1B) In the multivariable analysis for EFS, a combined assessment of pre-ASCT DS/rMTV 41% and rel/ref status at time of progression were independently associated with EFS (for DS 4-5/rMTV low, hazard ratio [HR] 1.58; for DS 4-5/rMTV high, HR 4.72; P<0.001: for primary refractory disease, HR 2.26; P=0.026). Based on these results, we stratified patients into 3 groups according to the post-ASCT outcomes: low-risk (relapsed disease [i.e., TTR > 3 months] and either pre-ASCT DS 1-3 or DS 4-5/rMTV low, N=54), intermediate-risk (refractory disease and either pre-ASCT DS 1-3 or DS 4-5/rMTV low, N=30), and high-risk (pre-ASCT DS 4-5/rMTV high irrespective of rel/ref status, N=22) groups. The risk model was significantly associated with EFS (intermediate vs low, HR 3.26, 95%CI 1.20-8.83, P=0.020; high vs low, HR 7.61, 95% CI 2.89-20.01, P<0.001; Fig 1C). Conclusion We propose a risk stratification model integrating a combination of DS and rMTV 41% on pre-ASCT PET and rel/ref status at time of progression, which allow discrimination of post-ASCT outcomes in patients with rel/ref cHL. The model may serve as a tool to facilitate risk-stratified treatment decisions. Figure 1 Figure 1. Disclosures Metser: POINT Biopharm Inc: Consultancy. Prica: Astra-Zeneca: Honoraria; Kite Gilead: Honoraria. Crump: Roche: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees; Epizyme: Research Funding; Kyte/Gilead: Membership on an entity's Board of Directors or advisory committees. Kuruvilla: Seattle Genetics: Honoraria; Amgen: Honoraria; Antengene: Honoraria; AbbVie: Honoraria; Janssen: Honoraria, Research Funding; BMS: Honoraria; Medison Ventures: Honoraria; TG Therapeutics: Honoraria; AstraZeneca: Honoraria, Research Funding; Gilead: Honoraria; Incyte: Honoraria; Karyopharm: Honoraria, Other: Data and Safety Monitoring Board; Roche: Honoraria, Research Funding; Novartis: Honoraria; Merck: Honoraria; Pfizer: Honoraria. Kridel: Gilead Sciences: 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)0.001
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.015
GPT teacher head0.247
Teacher spread0.232 · 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
Published2021
Admission routes2
Has abstractyes

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