ReviewJournal of breast cancer2020
Comparison of Endocrine Therapies in Hormone Receptor-Positive and Human Epidermal Growth Factor Receptor 2-Negative Locally Advanced or Metastatic Breast Cancer: A Network Meta-Analysis.
Review in Journal of breast cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Pooled it
- First‑line endocrine therapy for hormone receptor positive and HER‑2 negative metastatic breast cancer: A Bayesian network meta‑analysis.Oncology letters · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We aimed to explore what kind of endocrine treatments are optimal for hormone receptor-positive and human epidermal growth factor receptor 2-negative locally advanced or metastatic breast cancer in some specific clinical situations. We searched randomized controlled trials in Embase, Medline, the Cochrane library, and PubMed from inception to April 1, 2020 and performed a network meta-analysis based on a Bayesian fixed-effects model. Progression-free survival (PFS) with hazard ratios and corresponding 95% confidence interval was defined as the primary endpoint, while overall survival (OS), objective response rate (ORR), clinical benefit rate and serious adverse events were used as secondary endpoints. A total of 35 studies involving 12,285 patients and 24 treatment options were included. In general, most co-treatment options prolonged PFS compared to single-agent therapy, of which aromatase inhibitor (AI) plus everolimus and fulvestrant plus palbociclib were probably the most effective agents, and the latter had the best safety record. However, despite the superior efficacy of fulvestrant plus capecitabine for PFS and OS, palpable toxic effects have been demonstrated for this treatment, so its application must be scrupulously considered. The results of subgroup analysis indicated that fulvestrant combined with palbociclib improved prognosis for phosphatidylinositol 3-kinase (PI3K)-mutated patients, PI3K-unmutated patients, patients with endocrine therapy resistance, and visceral metastatic patients, while no obvious improvement was detected in OS. Moreover, the efficacy of fulvestrant plus cyclin-dependent kinase 4/6 (CDK4/6) inhibitors was slightly better than that of AI plus CDK4/6 inhibitors, while AI plus everolimus was more efficacious than fulvestrant combined with everolimus in terms of PFS, OS, and ORR. In conclusion, our results provide moderate evidence that fulvestrant plus palbociclib and AI plus everolimus were the most effective treatments, while the efficacy and safety of fulvestrant plus palbociclib was obviously superior in some specific clinical situations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.