Navigating breast cancer brain metastasis:Risk factors,prognostic indicators,and treatment perspectives

In this editorial,we comment on the article by Chen et al.We specifically focus on the risk factors,prognostic factors,and management of brain metastasis(BM)in breast cancer(BC).BC is the second most common cancer to have BM after lung cancer.Independent risk factors for BM in BC are:HER-2 positive BC,triplenegative BC,and germline BRCA mutation.Other factors associated with BM are lung metastasis,age less than 40 years,and African and American ancestry.Even though risk factors associated with BM in BC are elucidated,there is a lack of data on predictive models for BM in BC.Few studies have been made to formulate predictive models or nomograms to address this issue,where age,grade of tumor,HER-2 receptor status,and number of metastatic sites(1 vs>1)were predictive of BM in metastatic BC.However,none have been used in clinical practice.National Comprehensive Cancer Network recommends screening of BM in advanced BC only when the patient is symptomatic or suspicious of central nervous system symptoms;routine screening for BM in BC is not recommended in the guidelines.BM decreases the quality of life and will have a significant psychological impact.Further studies are required for designing validated nomograms or predictive models for BM in BC;these models can be used in the future to develop treatment approaches to prevent BM,which improves the quality of life and overall survival.

Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy

BACKGROUND Colorectal cancer is a common digestive cancer worldwide.As a comprehensive treatment for locally advanced rectal cancer(LARC),neoadjuvant therapy(NT)has been increasingly used as the standard treatment for clinical stage II/III rectal cancer.However,few patients achieve a complete pathological response,and most patients require surgical resection and adjuvant therapy.Therefore,identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance.AIM To establish effective prognostic nomograms and risk score prediction models to predict overall survival(OS)and disease-free survival(DFS)for LARC treated with NT.METHODS Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017.The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors,which were validated by the Cox regression method.Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves,and that of the two nomograms was conducted by calculating the concordance index(C-index)and calibration curves.The results were validated in a cohort of 65 patients from 2015 to 2017.RESULTS Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model:Vascular_tumors_bolt,cancer nodules,yN,body mass index,matchmouth distance from the edge,nerve aggression and postoperative carcinoembryonic antigen.The nomogram showed good predictive value for OS,with a C-index of 0.91(95%CI:0.85,0.97)and good calibration.In the validation cohort,the C-index was 0.69(95%CI:0.53,0.84).The risk factor prediction model showed good predictive value.The areas under the curve for 3-and 5-year survival were 0.811 and 0.782.The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77(95%CI:0.69,0.85).In the validation cohort,the C-index was 0.71(95%CI:0.61,0.81).The prediction model for DFS also had good predictive value,with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754.CONCLUSION We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.