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Record W3214525102 · doi:10.1182/blood-2021-145870

A Retrospective Cohort Study of Treatment Outcomes of Adult Patients with Relapsed or Refractory Low-Grade Follicular Lymphoma (ReCORD-FL)

2021· article· en· W3214525102 on OpenAlexaff
Gilles Salles, Stephen J. Schuster, Luca Fischer, John Kuruvilla, Piers Patten, Bastian von Tresckow, Sonali M. Smith, Ana Isabel Jiminez Ubieto, Keith L. Davis, Saurabh Nagar, Jie Zhang, Vamsi Bollu, Etienne Jousseaume, Roberto Ramos, Yucai Wang, Brian K. Link

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineInternal medicineFollicular lymphomaRetrospective cohort studyCohortSalvage therapyPopulationOncologyProgression-free survivalRituximabChemotherapy regimenHazard ratioClinical trialSurgeryLymphomaChemotherapyConfidence interval

Abstract

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Abstract Background: Novel therapies for multiply relapsed follicular lymphoma (FL) are often evaluated in single arm trials with no comparative data on patients receiving usual care. This study (ReCORD-FL) therefore sought to construct a historical control cohort to augment current and future single arm trials in relapsed/refractory (r/r) FL. The analytic aims were to document patient characteristics, treatment patterns and clinical outcomes in a r/r FL population treated with standard therapies in routine practice. Methods: This was a retrospective cohort study via medical record review in 10 oncology centers across North America and Europe. Adult patients were required to meet several criteria defining multiply r/r FL (i.e., r/r after ≥2 lines of therapy, or relapsed during or within 6 months after completion of anti-CD20 antibody maintenance, or relapsed after autologous HSCT). Patients were also required to have ≥1 line of systemic therapy (i.e., first qualifying salvage therapy) after first meeting the r/r FL criteria; the date of first qualifying salvage therapy defined the study index date. At index, patients were required to have grade 1-3A FL, Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1, and no evidence of prior histological transformation. Outcomes were observed from the index date and from the start of each therapy line until the earliest of death, last follow-up, or December 31, 2020 (data cutoff). Endpoints were complete response (CR) rate, overall response rate (ORR), time to next treatment (TTNT), progression-free survival (PFS), and overall survival (OS). In a subgroup analysis, endpoints were examined by double refractoriness (r/r to both an anti-CD20 mAb and an alkylator) and POD24 status at index (best response of stable/progressive disease or relapsed within 24 months of front-line anti-CD20 mAb-containing therapy). Time to event outcomes were analyzed using the Kaplan-Meier method. Results: A total of 187 patients were identified for inclusion (Table 1). Most patients' (80.2%) first qualifying salvage (index) therapy occurred in third line (3L) (range: 3L - 6L). Anti-CD20 mAb plus chemotherapy (including alkylating and/or non-alkylating agents) was the most common index regimen (64.2% of patients); 8% received anti-CD20 mAb monotherapy, 11.2% received alkylator-based chemotherapy alone (i.e., an alkylator-containing regimen without anti-CD20 mAb), and 16.6% received other therapies (i.e., other regimens containing neither anti-CD20 mAb nor alkylator). Median follow-up from FL diagnosis was 9 years (range: 1 - 21 years), over which a median of 5 (range: 3 - 11) lines of therapy were observed per patient. CR rate and ORR to the index treatment were 39.0% and 70.6%, respectively (Table 2). Median (95% confidence interval [CI]) TTNT and PFS from index were 14.4 (11.8 - 18.6) and 14.6 (11.0 - 18.0) months, respectively; median OS from index was 128 months (10.6 years). Compared with non-double refractory, those with double refractory disease at index had numerically lower CR (34.3% vs. 45.1%) and ORR (67.6% vs. 74.4%) and substantially shorter median (95% CI) TTNT (11.8 [9.0 - 15.2] vs. 20.9 [14.4 - 26.2] months), PFS (10.7 [7.7 - 14.5] vs. 20.1 [14.4 - 25.4] months), and OS (78.1 [45.8 - 146.7] vs. [Not Reached] months). Outcomes were similarly less favorable for patients who were POD24 at index. All outcomes steadily worsened across successive treatment lines (Table 2, Figures 1a-c). ORR, for example, decreased from 69.5% in 3L (n = 187) to 45.8% in 5L (n = 96) and 41.2% in ≥8L (n = 51), while median (95% CI) PFS decreased from 11.8 (10.1 - 16.6) months in 3L to 9.4 (6.8 - 13.1) months in 5L and 4.4 (1.7 - 5.9) months in ≥8L; median (95% CI) OS had a similar trend: 133.7 (78.1 - 232.4), 46.3 (31.7 - 76.5), and 11.4 (5.9 - 21.2) months in 3L, 5L, and ≥8L, respectively. Conclusions: Our findings further demonstrate the poor outcomes and limited survival in FL patients with multiply r/r, double refractory, or POD24 disease. In assessing response rates and PFS, it is important to consider that response assessment criteria and schedules were more heterogenous in the routine practice settings of ReCORD-FL than in clinical trials. Based on comparability of results with another similar study (SCHOLAR-5), the robustness of data collected, and continued low likelihood of randomized trials in this area, ReCORD-FL provides valuable historical control data for new r/r FL therapies in development. Figure 1 Figure 1. Disclosures Salles: Beigene, BMS/Celgene, Debiopharm, Genentech/Roche, Genmab, Incyte, Ipsen, anssen, Novartis. Kite/Gilead, Loxo, Miltneiy, Rapt, TAKEDA, Velosbio, Allogene: Consultancy; Abbvie, Epizyme, Morphosys, Regeneron: Consultancy, Honoraria; Bayer: Honoraria. Schuster: Abbvie: Consultancy, Research Funding; Acerta Pharma/AstraZeneca: Consultancy; Alimera Sciences: Consultancy; BeiGene: Consultancy; Juno Theraputics: Consultancy, Research Funding; Loxo Oncology: Consultancy; Tessa Theraputics: Consultancy; Genentech/Roche: Consultancy, Research Funding; Merck: Research Funding; Pharmacyclics: Research Funding; Adaptive Biotechnologies: Research Funding; Incyte: Research Funding; TG Theraputics: Research Funding; Novartis: Consultancy, Honoraria, Patents & Royalties, Research Funding; Nordic Nanovector: Consultancy; Celgene: Consultancy, Honoraria, Research Funding. Kuruvilla: Seattle Genetics: Honoraria; Merck: Honoraria; Novartis: Honoraria; Gilead: Honoraria; BMS: Honoraria; Antengene: Honoraria; Amgen: Honoraria; AbbVie: Honoraria; Karyopharm: Honoraria, Other: Data and Safety Monitoring Board; Janssen: Honoraria, Research Funding; Incyte: Honoraria; Medison Ventures: Honoraria; Roche: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Pfizer: Honoraria; TG Therapeutics: Honoraria. Patten: GILEAD SCIENCES: Honoraria, Research Funding; ROCHE: Research Funding; ASTRA ZENECA: Honoraria; NOVARTIS: Honoraria; JANSSEN: Honoraria; ABBVIE: Honoraria. von Tresckow: Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Other, Research Funding; Pentixafarm: Consultancy, Honoraria; AbbVie: Other: congress and travel support; BMS-Celgene: Consultancy, Honoraria, Other: congress and travel support; AstraZeneca: Honoraria, Other: congress and travel support; Pfizer: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Kite-Gilead: Consultancy, Honoraria; MSD: Consultancy, Honoraria, Other: congress and travel support, Research Funding; Novartis: Consultancy, Honoraria, Other: congress and travel support, Research Funding. Smith: Alexion, AstraZeneca Rare Disease: Other: Study investigator; Celgene, Genetech, AbbVie: Consultancy. Davis: Novartis, Vertex Pharmaceuticals, Pfizer, Eisai, Eli Lilly, AstraZeneca: Research Funding. Nagar: Novartis, AstraZeneca, Eisai: Research Funding. Zhang: Novartis: Current Employment, Current equity holder in publicly-traded company. Bollu: Novartis: Current Employment, Current equity holder in publicly-traded company. Jousseaume: Novartis: Current Employment, Current equity holder in publicly-traded company. Ramos: Novartis: Current Employment, Current equity holder in publicly-traded company. Wang: Eli Lilly: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; MorphoSys: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; InnoCare: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding. Link: Genentech/Roche: Consultancy, Research Funding; MEI: Consultancy; Novartis, Jannsen: 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)0.002
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.008
GPT teacher head0.240
Teacher spread0.231 · 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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Citations4
Published2021
Admission routes1
Has abstractyes

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