AUTHOR=Qiu Jianjian , Ke Dongmei , Yu Yilin , Lin Hancui , Zheng Qunhao , Li Hui , Zheng Hongying , Liu Lingyun , Wang Zhiping , Wu Yahua , Liu Tianxiu , Li Jiancheng TITLE=A New Nomogram and Risk Stratification of Brain Metastasis by Clinical and Inflammatory Parameters in Stage III Small Cell Lung Cancer Without Prophylactic Cranial Irradiation JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.882744 DOI=10.3389/fonc.2022.882744 ISSN=2234-943X ABSTRACT=Background

This study was conducted to determine risk factors for developing brain metastasis (BM) and to predict brain metastasis free survival (BMFS) and overall survival (OS) by combining several clinical parameters and inflammatory indexes.

Materials and Methods

A nomogram and risk stratification were developed based on multivariate analysis results. The prognostic index (PI) predicting the high risk of BM was calculated by multiplying the weighted factor (β coefficient) with each variable.

Results

Thirty-two of one hundred patients (32.0%) developed BM. Multivariate cox regression analysis revealed that concurrent chemoradiotherapy (CCRT; hazard ratio (HR), 3.356; p = 0.020), monocyte–lymphocyte ratio (MLR; HR, 4.511; p = 0.002), neutrophil–lymphocyte ratio (NLR; HR, 4.023; p = 0.033), and prognostic-nutrition index (PNI; HR, 2.902; p = 0.018) were independent prognostic factors of BMFS. The nomogram has good accuracy in predicting BMFS, and the C-index was 0.73. The ROC curve showed that these risk factors have good discriminant ability. Similarly, tumor location (HR, 1.675; p = 0.035) and MLR (HR, 2.076; p = 0.013) were independent prognostic factors of OS. In the subgroup analysis of OS, the good group had a better prognosis than the other groups. Risk stratification by PI: the high-risk group had worse BMFS than the low-risk group, which also has certain practical significance for clinical practice in OS.

Conclusion

We developed a nomogram and corresponding risk stratification in stage III SCLC patients who developed BM. This model and risk stratification can help clinicians improve patient treatment management and better deliver personalized therapy.