A nomogram for predicting survival in patients with breast cancer brain metastasis

Abstract

Brain metastasis (BM) is common in patients with breast cancer. Predicting patient survival is critical for the clinical management of breast cancer brain metastasis (BCBM). The present study was designed to develop and evaluate a prognostic model for patients with newly diagnosed BCBM. Based on the clinical data of patients with BCBM treated in the Affiliated Hospital of Academy of Military Medical Sciences (Beijing, China) between 2002 and 2014, a nomogram was developed to predict survival using proportional hazards regression analysis. The model was validated internally by bootstrapping, and the concordance index (c-index) was calculated. A calibration curve and c-index were used to evaluate discriminatory and predictive ability, in order to compare the nomogram with widely used models, including recursive partitioning analysis (RPA), graded prognostic assessment (GPA) and breast-graded prognostic assessment (Breast-GPA). A total of 411 patients with BCBM were included in the development of this predictive model. The median overall survival time was 14.1 months. Statistically significant predictors for patient survival included biological subtype, Karnofsky performance score, leptomeningeal metastasis, extracranial metastasis, the number of brain metastases and disease-free survival. A nomogram for predicting 1- and 2-year overall survival rates was constructed, which exhibited good accuracy in predicting overall survival with a concordance index of 0.735. This model outperformed RPA, GPA and Breast-GPA, based on the comparisons of the c-indexes. The nomogram constructed based on a multiple factor analysis was able to more accurately predict the individual survival probability of patients with BCBM, compared with existing models.

Breast cancer patients with brain metastases or leptomeningeal disease: 10‐year results of a national cohort with validation of prognostic indexes

“…Few data are available regarding prognostic models in patients with LM carcinomatosis who in general have a very poor prognosis and are rarely included in the prognostic score or nomogram development . In our subset of seventy patients with LM, both SS‐BM and Breast‐GPA scores significantly predicted survival, but results have to be confirmed in future prospective studies.…”

<p>Breast Cancer Brain Metastasis: The Potential Role of MRI Beyond Current Clinical Applications</p>

“…Finally, DWI signal intensity, ADCs, and the disruption of white matter tracts, assessed using the DTI sequence, are positively associated with prognosis, while sharp edges of the metastases are an indication of a shorter overall survival. MRI metrics such as the above could be incorporated into prognostic models, 19,22 which are widely validated predictors of survival in brain metastasis patients. These models normally combine clinical information too, including age, status of the primary cancer, and extracranial disease.…”

Nicotine promotes brain metastasis by polarizing microglia and suppressing innate immune function

“…Approximately 170,000 patients in the United States are diagnosed with brain metastasis every year ( Ellis et al, 2012 ). Lung, breast, and skin cancers are the most common tumor types that metastasize to the brain ( Bacha et al, 2018 ; Huang et al, 2018 ; Redmer, 2018 ; Xing et al, 2018 ). Patients with metastatic lung cancer have a very poor prognosis ( Mujoomdar et al, 2007 ), and those with brain metastasis have a 1-yr survival rate of 4–20% ( Gaspar et al, 1997 ; Sperduto et al, 2008 ; Verger et al, 2005 ).…”