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Side Effects and Supportive Care in Relapsed or Refractory Classical Hodgkin Lymphoma Patients Treated in Later Lines of Therapy: A Pilot Analysis Conducted in 4 Countries

2017· article· en· W3153841548 on OpenAlexaboutno aff
Clara Chen, Katherine Byrne, Pam Hallworth, Christopher A. Yasenchak

Bibliographic record

VenueBlood · 2017
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsBrentuximab vedotinMedicineNivolumabInternal medicineRefractory (planetary science)PembrolizumabChemotherapy regimenOncologyLymphomaChemotherapyHodgkin lymphomaCancerImmunotherapy

Abstract

fetched live from OpenAlex

Abstract Introduction: Most patients with classical Hodgkin lymphoma (cHL) can be cured with first-line multiagent chemotherapy. However, up to 20% require second-line (2L) therapy, including autologous hematopoietic cell transplantation (auto-HCT); 50% of those will develop relapsed/refractory cHL (R/R HL) after 2L therapy. The introduction of brentuximab vedotin (BV) in 2011 has changed the management of patients with R/R HL. The European Medicines Agency approved programmed death-1 (PD-1) inhibitor nivolumab (nivo) in 2016 for the treatment of patients with R/R HL who failed auto-HCT and BV and pembrolizumab (pembro) in 2017 for the treatment of R/R HL patients who failed auto-HCT and BV or who are transplant-ineligible and have failed BV. Both agents have improved clinical outcomes for indicated patients. As a pilot analysis, we assessed side effects and supportive care to manage side effects in patients with R/R HL who were treated with BV, nivo, or pembro in third- (3L) or later lines of therapy in real-world practice. Methods: The study was designed as a multicenter, cross-sectional survey of R/R HL patients receiving 3L or later-line systemic drug treatment, and was administered between June and September 2016 in Canada and 3 European countries (France, Germany, and UK). The study consisted of 2 components, a physician survey and a medical chart review; data captured included demographics and patient characteristics, treatment and disease management, clinical outcomes, and resource utilization. Side effects and supportive care were assessed during treatment. Summary statistics were reported and difference between treatment cohorts assessed using t -tests and Kruskal-Wallis tests for continuous variables and chi-square/Fisher exact tests for categorical variables. P value Results: A total of 116 physicians (Canada, 16; France, 31; Germany, 44; UK, 25) provided information on 955 patients with R/R HL who were treated in 3L or later-line therapy. Among these, 452 patients received exclusively BV, nivo, or pembro in 3L or later lines (median age 52 years; 58% male) and there was no overlap in utilization of the 3 agents. The 452 patients were divided into 3 treatment cohorts: 336 (74%) on BV, 90 (20%) on nivo, and 26 (6%) on pembro; these were mutually exclusive. Patients in the 3 cohorts were similar in terms of age, sex, most recent cancer stage, and performance status at study enrollment (Table). There was no statistically significant difference between cohorts in proportion of patients with bulky disease. Compared with those on BV, patients on nivo or pembro were more likely to be tested for Epstein-Barr virus (EBV)-specific antibodies (p=0.0003); among those tested, the proportions of patients with positive results were similar across cohorts (Table). The data suggest that nivo may generally result in fewer side effects than pembro and BV (Table). Pairwise comparisons between nivo and pembro show that nivo was associated with lower incidence of anemia (3.3% vs 15.4%, p=0.0438), diarrhea (2.2% vs 23.1%, p=0.0015), fatigue (3.3% vs 15.4%, p=0.0438), nausea (4.4% vs 26.9%, p=0.0024), vomiting (1.1% vs 26.9%, p Conclusions: The sample size of patients receiving nivo or pembro in this analysis is small, but preliminary analysis indicates that patients treated with nivo may have fewer side effects and require less supportive care than those receiving BV or pembro. Further analysis may be necessary to validate these findings. Study support: Bristol-Myers Squibb. Download : Download high-res image (226KB) Download : Download full-size image Disclosures Chen: Bristol-Myers Squibb: Employment. Byrne: Adelphi Real World: Employment. Hallworth: Adelphi Real World: Employment. Yasenchak: Bristol-Myers Squibb: Consultancy; Seattle Genetics: Consultancy.

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)0.003
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 score0.085
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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
Published2017
Admission routes1
Has abstractyes

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