Analysis of Prognostic Factors and Construction of Prognostic Models for Invasive Micropapillary Carcinoma of the Breast

Abstract

Objective. To compare and analyze the clinical characteristics of invasive micropapillary carcinoma (IMPC) of the breast (IMPC-B) and invasive ductal carcinoma (IDC) of the breast (IDC-B) and establish a prognostic model of IMPC-B. Methods. We retrospectively analyzed data for patients diagnosed with breast cancer in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2018 and screened 581 patients with IMPC and 1325 patients with IDC. We compared age, race, laterality, tumor site, histological grade, type of surgery, radiation, chemotherapy, whether the first primary tumor, T stage, N stage, M stage, and molecular type between IMPC-B and IDC-B and draw survival curves of IMPC-B and IDC-B. The relationship between clinical factors and prognosis was investigated by univariate analysis using the Log-rank test and multivariate analysis of the Cox proportional hazards regression model. A risk scoring model was constructed based on independent risk factors to distinguish high-risk and low-risk patients; in addition, a nomogram was created to predict patient survival. Results. There were differences between the two groups in the age of onset, race, tumor site, histological grade, type of surgery, N stage, and molecular type ( p < 0.05 ). Overall survival was decreased in IMPC-B compared with IDC-B ( p < 0.05 ). The prognosis of IMPC-B was significantly correlated with histological grade, whether the first primary tumor, type of surgery, radiotherapy, chemotherapy, T stage, and N stage. Based on the relationship between the above factors and overall survival prognosis, the risk score model we constructed can effectively distinguish high-risk and low-risk patients ( p < 0.05 ). The established nomogram had better performance in predicting survival in patients with IMPC-B ( C − index = 0.78 ). Conclusion. IMPC-B has a worse prognosis than IDC-B, with earlier age of onset, higher histological grade, and later N stage, and luminal breast cancer is the main type. The nomogram can well predict the prognosis of patients with IMPC-B, which has a high clinical reference value and provides a scientific basis for clinical treatment.

Advances in invasive micropapillary carcinoma of the breast research: A review

“…Notably, fewer IMPC components within a tumor can become a significant predictor of LNM. Both Wang [8] and Cemal [11] emphasized that the mere presence of IMPC components, irrespective of their size or proportion, was significantly correlated with increased lymphatic infiltration rate, LNM, recurrence, and distant metastasis rates.…”

“…This observation was supported by Chen [ 7 ] and Fu, [ 4 ] who reported that IMPC patients often display increased tumor dimensions and LNM rates. Another study by Wang [ 8 ] indicated that IMPC patients were younger, exhibited tumors more commonly in the central and upper quadrants, and had higher LNM rates than IDC patients. Hence, a significant proportion of IMPC cases are classified as Grade III in comparison to IDC when examined histopathologically.…”

“…Notably, fewer IMPC components within a tumor can become a significant predictor of LNM. Both Wang [ 8 ] and Cemal [ 11 ] emphasized that the mere presence of IMPC components, irrespective of their size or proportion, was significantly correlated with increased lymphatic infiltration rate, LNM, recurrence, and distant metastasis rates. Another study by Wang [ 12 ] compared the clinicopathological features of pure and mixed IMPC and noted that pure IMPC displays more aggressive characteristics and a higher Luminal B subtype ratio, while mixed IMPC was predominantly of the Luminal A subtype.…”

The cell death‐related genes machine learning model for precise therapy and clinical drug selection in hepatocellular carcinoma

“…Since tumours are extremely heterogeneous, patients with identical tumour stage undergoing the same course of treatment are expected to have distinct prognoses, with significant implications for patient outcomes. As a result, therapy regimens should be tailored based on the particular genetic and molecular characteristics that differ between tumours 7,8 . Given the heterogeneity of HCC tumours and the variation in treatment response among patients, there is a pressing need to explore new therapeutic modalities and develop personalized treatment regimens.…”

“…As a result, therapy regimens should be tailored based on the particular genetic and molecular characteristics that differ between tumours. 7 , 8 Given the heterogeneity of HCC tumours and the variation in treatment response among patients, there is a pressing need to explore new therapeutic modalities and develop personalized treatment regimens. This requires understanding the underlying genetic and molecular alterations driving tumour growth and progression, as well as identifying biomarkers that can predict treatment response and guide treatment decisions.…”