ArticleBreast cancer research and treatment2021
Improved risk estimation of locoregional recurrence, secondary contralateral tumors and distant metastases in early breast cancer: the INFLUENCE 2.0 model.
Article in Breast cancer research and treatment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.
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Who cites it
22 citing papers in PubMed, 3 syntheses or guidelines pooled it, 44 citations in OpenAlex.
- Metastatic recurrence in women diagnosed with non-metastatic breast cancer: a systematic review and meta-analysis.Breast cancer research : BCR · 2024Pooled it
- The effectiveness of personalised surveillance and aftercare in breast cancer follow-up: a systematic review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Pooled it
- Comparing the outcome between multicentric/multifocal breast cancer and unifocal breast cancer: A systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- Integrated Clinicogenomic Risk Modeling for Metachronous Second Primary Cancers.medRxiv : the preprint server for health sciences · 2026Article
- Understanding Clinicians' Informational Needs for AI-Driven Clinical Decision Support Systems: Qualitative Interview Study.JMIR medical education · 2026Article
- Validation of minimal risk of recurrence classification by the Breast Cancer Index in early stage breast cancer.NPJ breast cancer · 2025Article
- Patient perceptions around the use of clinico-pathologic and genomic tools in the management of early breast cancer.Breast cancer research and treatment · 2025Article
- Predicting short- to long-term breast cancer risk from longitudinal mammographic screening history.NPJ breast cancer · 2025Article
- Predicting early stage lung cancer recurrence and survival from combined tumor motion amplitude and radiomics on free-breathing 4D-CT.Medical physics · 2025Article
- Breast cancer recurrence in relation to mode of detection: implications on personalized surveillance.Breast cancer research and treatment · 2025Article
- Adherence to guideline recommendations for follow-up in patients with DCIS at a large teaching hospital in the Netherlands.Breast cancer research and treatment · 2024Article
- Opportunities for personalised follow-up in breast cancer: the gap between daily practice and recurrence risk.Breast cancer research and treatment · 2024Article
- Article
- Method of primary breast cancer detection and the disease-free interval, adjusting for lead time.Journal of the National Cancer Institute · 2024Article
- Personalized surveillance and aftercare for non-metastasized breast cancer: the NABOR study protocol of a multiple interrupted time series design.BMC cancer · 2023Article
- The use and misuse of risk prediction tools for clinical decision-making.Breast (Edinburgh, Scotland) · 2023Article
- The underused potential of breast conserving therapy after neoadjuvant system treatment - Causes and solutions.Breast (Edinburgh, Scotland) · 2023Review
- Hormone Receptor-Positive / HER2-Negative Early Breast Cancer High-Risk Population: An Algorithm for Optimization Systemic Adjuvant Treatment Based on 2022 Updates.Breast cancer : basic and clinical research · 2023Review
- Article
- Adherence to the Dutch Breast Cancer Guidelines for Surveillance in Breast Cancer Survivors: Real-World Data from a Pooled Multicenter Analysis.The oncologist · 2022Article
Corrections and comments
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Authors and funding
11 authors at 6 institutions in 2 countries.
Funding
Abstract
purposeTo extend the functionality of the existing INFLUENCE nomogram for locoregional recurrence (LRR) of breast cancer toward the prediction of secondary primary tumors (SP) and distant metastases (DM) using updated follow-up data and the best suitable statistical approaches.
methodsData on women diagnosed with non-metastatic invasive breast cancer were derived from the Netherlands Cancer Registry (n = 13,494). To provide flexible time-dependent individual risk predictions for LRR, SP, and DM, three statistical approaches were assessed; a Cox proportional hazard approach (COX), a parametric spline approach (PAR), and a random survival forest (RSF). These approaches were evaluated on their discrimination using the Area Under the Curve (AUC) statistic and on calibration using the Integrated Calibration Index (ICI). To correct for optimism, the performance measures were assessed by drawing 200 bootstrap samples.
resultsAge, tumor grade, pT, pN, multifocality, type of surgery, hormonal receptor status, HER2-status, and adjuvant therapy were included as predictors. While all three approaches showed adequate calibration, the RSF approach offers the best optimism-corrected 5-year AUC for LRR (0.75, 95%CI: 0.74-0.76) and SP (0.67, 95%CI: 0.65-0.68). For the prediction of DM, all three approaches showed equivalent discrimination (5-year AUC: 0.77-0.78), while COX seems to have an advantage concerning calibration (ICI < 0.01). Finally, an online calculator of INFLUENCE 2.0 was created.
conclusionsINFLUENCE 2.0 is a flexible model to predict time-dependent individual risks of LRR, SP and DM at a 5-year scale; it can support clinical decision-making regarding personalized follow-up strategies for curatively treated non-metastatic breast cancer patients.
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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.