Nomograms predict survival of patients with lymph node-positive, luminal a breast cancer

Yilun Li,Li Ma

doi:10.1186/s12885-021-08642-6

Abstract

BackgroundTo develop nomograms for the prediction of the 1-, 3-, and 5-year overall survival (OS) and breast cancer-specific survival (BCSS) for patients with lymph node positive, luminal A breast cancer.MethodsThirty-nine thousand fifty-one patients from The Surveillance, Epidemiology, and End Results (SEER) database were included in our study and were set into a training group (n = 19,526) and a validation group (n = 19,525). Univariate analysis and Cox proportional hazards analysis were used to select variables and set up nomogram models on the basis of the training group. Kaplan-Meier curves and the log-rank test were adopted in the survival analysis and curves plotting. C-index, calibration plots and ROC curves were used to performed internal and external validation on the training group and validation group.ResultsFollowing independent factors were included in our nomograms: Age, marital status, grade, ethnic group, T stage, positive lymph nodes numbers, Metastasis, surgery, radiotherapy, chemotherapy. In both the training group and testing group, the calibration plots show that the actual and nomogram-predicted survival probabilities are consistent greatly. The C-index values of the nomograms in the training and validation cohorts were 0.782 and 0.806 for OS and 0.783 and 0.804 for BCSS, respectively. The ROC curves show that our nomograms have good discrimination.ConclusionsThe nomograms may assist clinicians predict the 1-, 3-, and 5-year OS and BCSS of patients with lymph node positive, luminal A breast cancer.

Highlights

To develop nomograms for the prediction of the 1, 3, and 5-year overall survival (OS) and breast cancer-specific survival (BCSS) for patients with lymph node positive, luminal A breast cancer
We focused on constructing nomograms which can predict the survival outcomes of patients with lymph node positive, luminal A breast cancer
The following are the inclusion criteria: (1) Female; (2) Age of diagnosis ≥18; (3) Diagnosis confirmed by positive histology instead of other methods; (4) Breast cancer was considered as the first primary cancer; (5) The subtype of breast cancer is luminal A; (6) Complete survival data and survival time was not “0”; (7) Complete information of the variables contains age of diagnosis, ethnic group, marital status, historical subtype, tumor size, location, grade, laterality, positive lymph nodes counts, histological subtype, the seventh edition of American Joint Committee on Cancer (AJCC) TNM stage, tumor grade, SEER cause-specific death, vital status, breast cancer subtype and metastasis site (8) The TNM stage is T1–4, N1-N3 and M0-M1 according to the seventh edition of AJCC TNM

Summary

Methods

Research populations We collected and screened information from January 2010 to December 2015 in SEER Registry data of 18 registries. Variables and definition The following data were extracted for each patient from the database: age at diagnosis, year diagnosed, race, marital status at diagnosis, primary site of the tumor, adjusted AJCC seventh T stage, N stage, M stage, tumor grade, histological subtype, number of positive lymph nodes, surgery, chemotherapy, radiotherapy, SEER cause-specific death, metastasis site, vital status, breast cancer subtype, and survival (months). We adopted univariate analysis and multivariate Cox regression analyses to determine the risk of each factor associated with prognosis of OS and BCSS, which were performed by SPSS software (IBM Corporation, USA, version 21). All significant factors in the univariate analysis were included in the multivariate Cox regression analyses. The significant variables in multivariate Cox regression analyses were selected for the final prognostic models in order to construct the nomograms. The C-index, ROC curves, nomogram, calibration curves and Kaplan-Meier curves were generated in R with packages “rms”, “survival”, “foreign”, “timeROC” and “regplot” respectively

Results

Background

Discussion

Conclusion