ArticleTurkish journal of medical sciences2022
Predictors of lymphovascular invasion in estrogen receptor positive/Her-2 negative breast cancer patients treated with neoadjuvant chemotherapy.
Article in Turkish journal of medical sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed, 3 citations in OpenAlex.
- Prior Clinico-Radiological Features Informed Multi-Modal MR Images Convolution Neural Network: A novel deep learning framework for prediction of lymphovascular invasion in breast cancer.Cancer medicine · 2024Trial
- Clinicopathological characteristics and prognostic analysis of multifocal/multicentric breast cancer.Scientific reports · 2025Article
- MRI Radiomics-Based Machine Learning to Predict Lymphovascular Invasion of HER2-Positive Breast Cancer.Journal of imaging informatics in medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLymphovascular invasion (LVI) is considered a high-risk factor for recurrence in early-stage breast cancer, hence examination of LVI in pathological samples is an absolute recommendation. We aim to investigate predictive factors of LVI in preneoadjuvant chemotherapy (NAC) patients with estrogen receptor positive (ER+) and human epidermal growth factor receptor 2 negative (HER2-) molecular subtypes of breast cancer.
methodsOne hundred and thirty-four patients treated with NAC were included in this study who were ER+/HER2-. The clinical characteristics of the patients, the data obtained from the core needle biopsy before NAC and the LVI status in the pathology that examined after breast surgery were collected. Univariate and multivariate analysis were performed using the logistic regression model.
resultsAn examination of the association between LVI and clinical-pathological patient characteristics showed that advanced age (>40 years old) (p = 0.021), ductal histology (p = 0.039), and presence of axillary lymph node metastasis (p = 0.005) were predictors of LVI. Independent predictors of LVI in a multivariate logistic model included advanced age (p = 0.037), and the presence of axillary lymph node metastasis prior to NAC (p = 0.006). The median RFS (Recurrence-free survival) time was 22.8 months for all patients. RFS was shorter in patients with LVI (log-rank p = 0.037). DISCUSSION: Independent predictors of LVI are advanced age and lymph node positivity at the time of diagnosis. Our study is the first study that evaluates pre-NAC predictive factors of LVI in ER+/HER2- breast cancer patients treated with NAC.
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.