ArticleFrontiers in oncology2024
An intraoperative nomogram for predicting secondary margin positivity in breast conserving surgery utilizing frozen section analysis.
Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Breast conserving surgery (BCS) is a standard treatment for breast cancer. Intraoperative frozen section analysis (FSA) is widely used for margin assessment in BCS. In addition, FSA-assisted excisional biopsy is still commonly practiced in many developing countries. The aim of this study is to develop a predictive model applicable to BCS with FSA-assisted excisional biopsy and margin assessment, with a focus on predicting the risk of secondary margin positivity in re-excision procedures following positive initial margins. This may reduce surgical complications and healthcare costs associated with multiple re-excisions and FSAs for recurrent positive margins. Methods: Patients were selected, divided into training and testing sets, and their data were collected. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to identify significant variables from the training set for model building. Model performance was evaluated using Receiver Operating Characteristic (ROC) curves, calibration curves, and Decision Curve Analyses (DCAs). An optimal threshold identified by the Youden index was validated using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Results: The study included 348 patients (256 in the training set, 92 in the testing set). No significant statistical differences were found between the sets. LASSO identified six variables to construct the model and corresponding nomogram. The model showed good discrimination (mean area under the curve (AUC) values of 0.79 in the training set and 0.83 in the testing set), calibration (Hosmer-Lemeshow test results ( Conclusions: This study successfully developed a novel predictive model for secondary margin positivity applicable to BCS with FSA-assisted excisional biopsy and margin assessment. It demonstrates good discriminative ability, calibration, and clinical utility.
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.