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Efficacy and safety of lenvatinib in the real-world treatment of hepatocellular carcinoma: Results from a Canadian multicenter database (HCC CHORD).

2021· article· en· W3123141270 on OpenAlexaffabout
Carla Pires Amaro, Michael J. Allen, Jennifer J. Knox, Erica S. Tsang, Howard J. Lim, Richard M. Lee‐Ying, Jessica Qian, Brandon M. Meyers, Alia Thawer, Sulaiman Mohammed Saif Al-Saadi, Tina Hsu, Ravi Ramjeesingh, Hatim Karachiwala, Tasnima Abedin, Vincent C. Tam

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsBaker Hughes (Canada)Ottawa Regional Cancer FoundationSunnybrook Health Science CentreJuravinski Cancer CentreNova Scotia Cancer CentreOttawa HospitalPrincess Margaret Cancer CentreDalhousie UniversityUniversity Health NetworkUniversity of Calgary
Fundersnot available
KeywordsMedicineLenvatinibHepatocellular carcinomaSorafenibInternal medicineHepatitis CLiver cancerOncologySurgeryGastroenterology

Abstract

fetched live from OpenAlex

275 Background: The REFLECT trial establishedlenvatinib (LEN) as a first-line treatment option for hepatocellular carcinoma (HCC). Compared to sorafenib (S), LEN has a higher objective response rate (ORR) and progression-free survival (PFS) with a slightly different toxicity profile. The aim of this study was to gather data regarding the efficacy and safety of LEN when used in the real-world treatment of HCC. To our knowledge, this is the first study to examine LEN use in HCC patients treated outside of Asia. Methods: HCC patients treated with LEN from 10 cancer centers in the Canadian provinces of British Columbia, Alberta, Ontario and Nova Scotia between July 2018 to July 2020 were included. Overall survival (OS), PFS, disease control rate (DCR) and ORR were retrospectively analyzed and compared across first- and second-to-fourth line use of LEN. ORR was determined radiographically according to the treating physician´s opinion in clinical notes and not RECIST 1.1 or mRECIST. Toxicities were also examined. Results: A total of 220 patients were included in this analysis. Median age was 67 years, 80% were men and 25.5% East Asian. The most frequent causes of liver disease were hepatitis C (37%) and B (26%). 62% of patients received any localized treatment before LEN, of those 26% had TACE, 15% TARE and 7.7% had liver transplant. Before starting LEN 29% of patients were ECOG 0 and 59% were ECOG 1. Most patients were Child-Pugh A (81%) and BCLC stage C (75.5%). Main portal vein invasion was present in 14% of the patients. Median follow-up was 4.5 months. A total of 173 patients (79%) received LEN as first line therapy and 47 patients (21%) were treated in second-to-fourth line. Of patients receiving LEN in first line, 22 (13%) started treatment with S, but switched to LEN before progression due to poor tolerance of S. ORR, DCR, PFS and OS are shown in the table. Toxicities occurred in 86% of patients and led to dose reductions in 76 (35%) patients and drug discontinuation in 53 (24%) patients. The most common side effects were fatigue (59%), hypertension (41%), decreased appetite (25%) and diarrhea (22%). Conclusions: Outcomes of HCC patients treated in Canada with LEN in the first line are comparable to those demonstrated in the REFLECT trial, despite the inclusion of Child-Pugh B and ECOG >1 patients. LEN use in second or later lines also showed similar outcomes, although more conclusions are difficult to draw due to the small numbers. LEN appears to be effective and safe in real world practice outside of Asia in first- and second-to-fourth line treatment of HCC. [Table: see text]

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)0.002
metaresearch head score (Gemma)0.004
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 score0.182
Threshold uncertainty score0.366

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0010.000
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 head0.196
GPT teacher head0.400
Teacher spread0.204 · 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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Citations3
Published2021
Admission routes2
Has abstractyes

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