AUTHOR=He Shanshan , Chen Qingjinan , Li Gang , Ding Bowen , Wang Shu , Han Chunyong , Sun Jingyan , Huang Qingfeng , Yin Jian 

TITLE=Novel nomograms for predicting survival for immediate breast reconstruction patients diagnosed with invasive breast cancer—a single-center 15-year experience

JOURNAL=Frontiers in Oncology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1202650

DOI=10.3389/fonc.2023.1202650

ISSN=2234-943X

ABSTRACT=Background: Immediate breast reconstruction is widely accepted following oncologic mastectomy. This study aimed to build a novel nomogram predicting the survival outcome for Chinese patients undergoing immediate reconstruction following mastectomy for invasive breast cancer. 

Methods: A retrospective review of all patients undergoing immediate reconstruction following treatment for invasive breast cancer was performed from May 2001 to March 2016. Patients eligible were assigned to a training and validating set. Univariate and multivariate cox proportional hazard regression model were used to select associate variables. Two nomograms were developed based on the training cohort for breast cancer-specific survival (BCSS)  and disease-free survival (DFS). Internal and external validations were performed, and the C-index and calibration plots were generated to evaluate the performance (discrimination and accuracy) of the models.

Results: The 10-year estimated BCSS and DFS were 90.80% (95%CI: 87.30%-94.40%) and 78.40% (95%CI: 72.50%-84.70%), respectively, in the training cohort. In the validating cohort, they were and 85.60% ( 95%CI, 75.90%-96.50%) and 84.10% (95%CI, 77.80%-90.90%), respectively.  Ten independent factors were used to build nomogram for prediction of 1-, 5- and 10-year BCSS, while 9 were used for DFS. The C-index were 0.841 for BCSS and 0.737 for DFS in internal validation, and the C-index were 0.782 for BCSS and 0.700 for DFS in external validation. The calibration curve for both BCSS and DFS demonstrated acceptable agreement between the predicted and actual observation in the training and the validating cohorts. 

Conclusions: The nomograms provided valuable visualization of factors predicting BCSS and DFS in invasive breast cancer patients with immediate breast reconstruction. The nomograms may have tremendous potential in guiding individualized decision-making for physicians and patients in choosing the optimized treatment methods.