MétaCan
Menu
Back to cohort
Record W4296167489 · doi:10.3389/fphar.2022.960323

Efficacy and safety of PD-1 and PD-L1 inhibitors combined with chemotherapy in randomized clinical trials among triple-negative breast cancer

2022· review· en· W4296167489 on OpenAlexfundno aff
Yihang Qi, Wenxiang Zhang, Ray Jiang, Olivia Xu, Xiangyi Kong, Lin Zhang, Yi Fang, Jingping Wang, Jing Wang

Bibliographic record

VenueFrontiers in Pharmacology · 2022
Typereview
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
FundersNYU Grossman School of MedicinePeking Union Medical CollegeChinese Academy of Medical SciencesNational Natural Science Foundation of ChinaYork UniversityCancer Foundation of ChinaBeijing Xisike Clinical Oncology Research FoundationChina International Medical FoundationMassachusetts General Hospital
KeywordsMedicineTriple-negative breast cancerBreast cancerOncologyChemotherapyInternal medicineClinical trialCancerTriple negativeRandomized controlled trialPharmacology

Abstract

fetched live from OpenAlex

Background: The combination of immune checkpoint inhibitors (ICIs) and chemotherapy (CT) is a new strategy to explore cancer treatment in recent years, and it is also practiced in triple-negative breast cancer (TNBC). However, several published randomized controlled trials (RCTs) reported heterogeneous results. We conducted this meta-analysis to yield insights into the efficacy and safety of the combination of ICIs and CT for TNBC patients in both the adjuvant and neoadjuvant settings. Method: EMBASE, PUBMED, Cochrane, and www.clinicaltrials.gov databases were searched to determine potential eligible studies from the inception to 20 May 2022. Published RCTs on PD-1/PD-L1 ICIs combined with CT for TNBC patients were included. Result: This meta-analysis included six double-blind RCTs comprising 4,081 TNBC patients treated with PD-1 or PD-L1 ICIs plus CT or placebo plus CT. The combination strategy benefited a better pathologic complete response (pCR) by 29% (RR = 1.29; 95% CI: 1.17–1.41; I2 = 0%) and a better progression-free survival (PFS) (HR = 0.82; 95% CI: 0.74–0.90; I2 = 0%) in the neoadjuvant and the adjuvant settings, respectively, especially in PD-L1-positive population (HR = 0.71; 95% CI: 0.62–0.81; I2 = 13%). The safety profiles were generally tolerable in both settings but the combination treatment will increase the risk of severe adverse events in the adjuvant setting (RR = 1.33; 95% CI 1.08–1.62, I2 = 0%). Additionally, the combination will increase the risk of any-grade hypothyroidism, hyperthyroidism, pneumonia, and rash in the adjuvant setting, and the risk of any-grade hypothyroidism, hyperthyroidism, infusion-related reactions, and severe cutaneous reactions in the neoadjuvant setting. Conclusion: This meta-analysis demonstrated a significant pCR benefit and confirms the PFS benefit with PD-1/PD-L1 ICIs plus CT in TNBC patients with tolerable safety events in both neoadjuvant and adjuvant settings.

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)0.034
metaresearch head score (Gemma)0.060
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.034
Threshold uncertainty score0.182

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.060
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0150.036
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0030.003
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 head0.050
GPT teacher head0.419
Teacher spread0.369 · 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 designSystematic review
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".

Quick stats

Citations16
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in PharmacologySame topicCancer Immunotherapy and BiomarkersFrench-language works237,207