Abstract Introduction: The management of senile breast cancer is still controversial, especially chemotherapy. Therefore, we conduct an analysis of the impact of chemotherapy and establish prediction models of prognosis in elderly early TNBC by using machine learning. Methods: We enrolled 4,696 patients from SEER database according to the following criteria: female; year of diagnosis from 2010 to 2016; age of diagnosis ≥ 70 years; invasive ductal carcinoma as the only primary malignant cancer; stage I-III; TNBC subtype. The PSM method was utilized to reduce covariable imbalance. Univariable and multivariable analyses were used to compare BCSS and OS. KNN, CatBoost, decision tree, random forest, Gradient Boost, LightGBM, neural network models, SVM, XGBoost and logistic regression models were developed to predict the 5-year OS and BCSS for patients in the chemotherapy group. Results: Compared to matched patients with no-chemotherapy, multivariate analysis showed a better survival in matched patients with chemotherapy(BCSS:HR = 0.594,95%CI = 0.479-0.737,p < 0.001; OS:HR = 0.532,95%CI = 0.446-0.635,p < 0.001). Stratified analyses by age and stage was also conducted to discriminate the patients benefited from chemotherapy. Chemotherapy didn’t lowered the risk of cancer-specific mortality and all-cause mortality in stage I cohort (70-79 years, BCSS, HR=1.058, 95% CI=0.609-1.838, p=0.841; OS HR=0.721, 95% CI=0.478-1.086, p=0.117; 80+ years, BCSS, HR=0.210, 95% CI=0.005-8.920, p=0.414; OS HR=0.458, 95% CI=0.048-3.918, p=0.458). But patients diagnosed with stage II can benefit from chemotherapy (70-79 years, BCSS, HR=0.628, 95% CI=0.424-0.932, p=0.021; OS HR=0.538, 95% CI=0.386-0.749, p<0.001; 80+ years, BCSS, HR=0.413, 95% CI=0.230-0.744, p=0.003; OS HR=0.416, 95% CI=0.260-0.667, p<0.001). We observed similar phenomena in the stage III cohort. We further investigated the effects of tumor and nodal status in stage II cases between the two groups. We found that chemotherapy was a better prognostic indicator for patients with T2N0M0 and stage IIb (T2N0M0, BCSS, HR=0.420, 95% CI=0.261-0.675, p<0.001; OS HR=0.0.361, 95% CI=0.243-0.536, p<0.001; stage IIb, BCSS, HR=0.752, 95% CI=0.454-1.246, p=0.269; OS HR=0.640, 95% CI=0419-0.978, p=0.039), but not for T1N1M0 (BCSS, HR=0.778, 95% CI=0.249-2.432, p=0.666; OS HR=1.072, 95% CI=0.458-2.508, p=0.872). For patients with grade I and II, no statistical survival differences were identified between chemotherapy and no-chemotherapy patients(BCSS, HR=0.781, 95% CI=0.445-1.368, p=0.387; OS HR=0.802, 95% CI=0.512-1.256, p=0.335). While for patients with grade III, the chemotherapy patients demonstrated a better prognosis than no-chemotherapy patients (BCSS, HR=0.558, 95% CI=0.440-0.707, p<0.001; OS, HR=0.492, 95% CI=0.405-0.599, p<0.001). Ten models mentioned above were conducted to predict the 5-year OS and BCSS for patients in the chemotherapy group. On average, the accuracy was 0.885 on 5-year BCSS and 0.858 on 5-year OS. The average precision of the examined ten algorithms was 0.880 on 5-year BCSS and 0.862 on 5-year OS. Similarly, the average sensitivity was 0.981 on 5-year BCSS and 0.971 on 5-year OS. There was average F1 score of 0.932 on 5-year BCSS and 0.913 on 5-year OS. In terms of the AUC, the highest AUC was observed for the LightGBM. Considering all the parameters above, the LightGBM outperformed all other algorithms. Conclusion: For stage I, T1N1M0, grade I and grade II elderly early triple negative invasive ductal carcinoma patients, chemotherapy could not improve OS and BCSS. Therefore, de-escalation therapy might be appropriate for selected patients. The LightGBM is practical and trustful to predict the 5-year OS and BCSS for patients in the chemotherapy group. Citation Format: KaiYan Huang, Jie Zhang, YuShuai Yu, YuXiang Lin, ChuanGui Song. The impact of chemotherapy in elderly early triple negative breast cancer: A population based study from the SEER database [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-12-04.
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