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Abstract P4-07-02: Toxicity profile of single agent trastuzumab deruxtecan in solid tumors: A meta-analysis

2023· article· en· W4322769668 on OpenAlexaff
Faris Tamimi, Abhenil Mittal, Consolacion Molto Valiente, Massimo Di Iorio, Laith Al-Showbaki, Michelle B. Nadler, Eitan Amir

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineToxicityInternal medicineClinical trialNeutropeniaAnemiaTrastuzumabOncologyOdds ratioConfidence intervalPhases of clinical researchBreast cancerGastroenterologyCancer

Abstract

fetched live from OpenAlex

Abstract Background: Trastuzumab deruxtecan (T-DXd) has been evaluated in numerous solid tumors and has been approved for metastatic HER2-positive breast and gastric/gastroesophageal cancers. We aimed to provide a precise estimate of toxicity of T-DXd observed in clinical trials. Methods: A systematic literature search was performed in PubMed and supplemented by review of abstracts from ASCO and ESMO. Eligible studies were clinical trials (dose-expansion phase 1, phase 2, and phase 3) investigating single agent T-DXd. The search was performed in June 2022. For single-arm trials, meta-analysis comprised one-sample proportions to obtain the random effects estimates of toxicity and respective 95% confidence intervals (CI) for T-DXd, while for randomized trials, the Mantel-Haenszel odds ratio method was utilized. Results: Fifteen trials comprising 1566 participants were evaluable for toxicity. ECOG Performance Status (PS) was reported in 11 studies and was ≥ 2 in only a single patient. The median age at enrollment was reported for 13 studies and was 57.5 years. Seven trials comprising 1023 (65.3%) participants evaluated T-DXd for breast cancer. From available data, 1209/1440 (84%)of participants were female and 735/1551 (47%) were from East Asia. The median follow-up time was 11.1 months (13 studies) and median previous lines of treatment were 3 (12 studies). All-grade toxicity rate of ≥10% was reported for most toxicities; however, grade ≥3 toxicity rate of ≥10% was reported only for neutropenia and anemia; 17.4% (95%CI 12-22.8) and 14.8% (95%CI 8.6-21), respectively (Table 1). Interstitial lung disease/pneumonitis (ILD) was reported in 203 (12.4%) patients, including 160 (9.41%) grade 1-2, and 23 (1.1%) grade 3-4. Treatment-related death was reported in 20 (1%) patients, and all were due to grade 5 ILD. No significant difference in ILD was identified in subgroup analysis of trials conducted in east Asia vs. the rest of the world, breast vs. other solid tumors, 5.4mg/kg vs. other doses, median follow-up < 12 months vs. ≥12 months or median previous lines ≥3 vs. < 3. In the three randomized clinical trials, grade ≥3 toxicity was significantly higher for nausea (OR: 9.32, 95%CI: 2.53-34.32), ILD (OR: 5.35, 95%CI: 0.97, 29.48), fatigue (OR:2.5, 95%CI: 1.11-5.66), and anemia (OR:1.77 95%CI: 1.14-2.74). Conclusions: T-DXd was associated with infrequent grade ≥3 toxicities across clinical trials. Grade 1-2 ILD was more common; however, grade 3-4 ILD occurred in 1.1%. This may be related to active monitoring of this toxicity in clinical trials and discontinuation of treatment in participants with G2 ILD. There is lack of evidence for the safety of T-DXd in patients with ECOG PS ≥ 2. Citation Format: Faris Tamimi, Abhenil Mittal, Consolacion Molto Valiente, Massimo Di Iorio, Laith Al-Showbaki, Michelle Nadler, Eitan Amir. Toxicity profile of single agent trastuzumab deruxtecan in solid tumors: A meta-analysis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-07-02.

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)0.022
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.032
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0160.078
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.170
GPT teacher head0.426
Teacher spread0.255 · 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 designMeta-analysis
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
Published2023
Admission routes1
Has abstractyes

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