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Efficacy of antibody-drug conjugates in breast cancer: A systematic review and meta-analysis of randomized clinical trials.

2023· review· en· W4379285655 on OpenAlexaff
Muhammad Ashar Ali, Wajeeha Aiman, Fatima Afzal, Hafsa Zahoor, Syeda Hafsa Kazmi, Aqsa Anwar, Ayfa Riaz Bajwa, Michael Maroules, Gunwant Guron, Hamid Shaaban

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typereview
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineTrastuzumab emtansineInternal medicineTrastuzumabOncologyBreast cancerCancerMetastatic breast cancerMeta-analysisRandomized controlled trialAntibody-drug conjugateAntibodyMonoclonal antibodyImmunology

Abstract

fetched live from OpenAlex

e13113 Background: Breast cancer (BC) is the 2nd most common cause of cancer related deaths in women. Antibody-drug conjugates are monoclonal antibodies conjugated to the cytotoxic payload and are directed towards cell surface proteins specific to tumor cells. This systematic review and meta-analysis aims to assess the efficacy of ADCs in breast cancer and comparison of different ADCs. Methods: A literature search was performed on PubMed, Embase, WOS, and clinicaltrials.gov with key words “breast neoplasms,” and “immunoconjugates” from the inception of data till 6/6/2022. Cochrane and PRISMA guidelines were followed to establish guidelines registered on Prospero (CRD42022329529). Out of 4,570 articles, seven randomized clinical trials (RCTs, N=5,302) were included. R programming language software with “meta” package was used for this meta-analysis. Results: In 7 RCTs (N=5,302), 4,834 patients had HER-2 positive disease while 468 patients were triple negative BC (TNBC). 1,486 patients had residual invasive disease while 3,816 patients had metastatic breast cancer (mBC). 3,389 patients were treated with ADC (235 with sacituzumab govitecan (saci-gov), 2,339 with trastuzumab emtansine (T-DM1) and 261 trastuzumab deruxtecan (T-der)), 2,105 patients were treated with chemotherapy regimens. In 4 RCTs on HER-2 patients (N=2,825), pooled HR of PFS and OS were 0.72 (95% CI=0.61-0.84, I2=71%) and 0.73 (95% CI=0.64-0.84, I2=20%), respectively, in favor of ADC. Risk of ORR was 1.48 (95% CI=0.84-2.60, I2=91%) in favor of ADC. In RCT on TNBC (N=468), HR of PFS and OS were 0.55 (95% CI=0.51-0.61) and 0.59 (95% CI=0.54-0.66), respectively, in favor of saci-gov (ADC). In RCT on HER-2 positive residual invasive breast cancer, HR of recurrence/death was 0.61 (95% CI=0.54-0.69) in favor of T-DM1. In an RCT by Cortes et al. (N=524) comparing two ADCs in HER-2 mBC, the HR of PFS and OS were 0.28 (95% CI= 0.22-0.37) and 0.55 (95% CI=0.36-0.86), respectively, in favor of T-der as compared to T-DM1. The RR of ORR and CR were 2.33 and 1.28, respectively, in favor of T-der. Conclusions: ADCs are significantly more effective than chemotherapy in patients with HER-2 positive mBC, HER-2 positive residually invasive BC, and metastatic TNBC in terms of improving survival and response rates. Among ADCs, T-der was significantly more effective than T-DM1 in patients with HER-2 positive mBC. More double blinded multicenter RCTs are needed to confirm these results.

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)0.043
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: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.043
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0190.038
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.654
GPT teacher head0.699
Teacher spread0.045 · 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
GenreReview

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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