ArticleFrontiers in surgery2022
Nomogram for predicting overall survival in patients with invasive micropapillary carcinoma after breast-conserving surgery: A population-based analysis.
Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Applications and challenges of biomarker-based predictive models in proactive health management.Frontiers in public health · 2025Pooled it
- Prognostic nomogram for overall survival in breast invasive micropapillary carcinoma integrating LODDS and treatment factors: A SEER-based study.Biomolecules & biomedicine · 2026Article
- Association of molecular subtypes and treatment with survival in invasive micropapillary breast cancer: an analysis of the Surveillance, Epidemiology, and End Results database.Breast cancer (Tokyo, Japan) · 2024Article
- A web-based novel model for predicting prognostic value in patients with invasive micropapillary carcinoma in breast cancer: a real-world data retrospective cohort study.Updates in surgery · 2023Article
- Nomogram predicting overall prognosis for invasive micropapillary carcinoma of the breast: a SEER-based population study.BMJ open · 2023Article
- Nomogram for predicting overall survival in patients with invasive micropapillary carcinoma after breast-conserving surgery: A population-based analysis.Frontiers in surgery · 2022Article
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Due to the loss of prediction of overall survival (OS) for patients with invasive micropapillary carcinoma (IMPC) after breast-conserving surgery (BCS), this study aimed to construct a nomogram for predicting OS in IMPC patients after BCS. Methods: In total, 481 eligible cases staged 0-III IMPC from 2000 to 2016 were retrieved from the SEER database. A nomogram was built based on the variables selected by LASSO regression to predict the 3-year and 5-year probabilities of OS. Results: A total of 336 patients were randomly assigned to the training cohort and 145 cases in the validation cohort. The LASSO regression revealed that six variables (age at diagnosis, AJCC stage, marital status, ER status, PR status, and chemotherapy) were predictive variables of OS, and then a nomogram model and an easy-to-use online tool were constructed. The C-indices 0.771 in the training cohort and 0.715 in the validation cohort suggested the robustness of the model. The AUC values for 3-year and 5-year OS in the training cohort were 0.782, 0.790, and 0.674, and 0.682 in the validation cohort, respectively. Based on the cutoff values of 147.23 and 222.44 scores calculated by X-tile analysis, participants in the low-risk group (≤147.23 scores) had a more favorable OS in comparison with those in the medium (>147.23, but <222.44 scores)- and high-risk groups (≥222.44 scores). Conclusions: By risk stratification, this model is expected to provide a precise and personalized prediction of the cumulative risk and guide treatment decision-making in improving OS strategies for IMPC patients.
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