Nomogram for Predicting the Overall Survival of Patients With Breast Cancer With Pathologic Nodal Status N3

Breast-conserving surgery versus modified radical mastectomy in T1-2N3M0 stage breast cancer: a propensity score matching analysis

PURPOSE

Breast-conserving surgery (BCS) plus radiotherapy and mastectomy exhibit highly comparable prognoses for early-stage breast cancer; however, the safety of BCS for T1-2N3M0 breast cancer remains unclear. This study compared long-term survival for BCS versus (vs.) modified radical mastectomy (MRM) among patients with T1-2N3M0 breast cancer.

METHODS

Data of patients with T1-2N3M0 breast cancer were extracted from the Surveillance, Epidemiology, and End Results database. Eligible patients were divided into 2 groups, BCS and MRM; Pearson's chi-squared test was used to estimate differences in clinicopathological features. Propensity score matching (PSM) was used to balance baseline characteristics. Univariate and multivariate analyses were performed to investigate the effects of surgical methods and other factors on breast cancer-specific survival (BCSS) and overall survival (OS).

RESULTS

In total, 2124 patients were included; after PSM, 596 patients were allocated to each group. BCS exhibited the same 5-year BCSS (77.9% vs. 77.7%; P = 0.814) and OS (76.1% vs. 74.6%; P = 0.862) as MRM in the matched cohorts. Multivariate survival analysis revealed that BCS had the same BCSS and OS as MRM (hazard ratios [HR] 0.899 [95% confidence intervals (CI) 0.697-1.160], P = 0.413 and HR 0.858 [95% CI 0.675-1.089], P = 0.208, respectively); this was also seen in most subgroups. BCS demonstrated better BCSS (HR 0.558 [95% CI 0.335-0.929]; P = 0.025) and OS (HR 0.605 [95% CI 0.377-0.972]; P = 0.038) than MRM in those with the triple-negative subtype.

CONCLUSIONS

BCS has the same long-term survival as MRM in T1-2N3M0 breast cancer and may be a better choice for triple-negative breast cancer.

Clinical value of grayscale ultrasound combined with real-time shear wave elastography nomogram in risk prediction of thyroid cancer

OBJECTIVES

This study constructed a nomogram based on grayscale ultrasound features and real-time shear wave elastography (SWE) parameters to predict thyroid cancer.

METHODS

Clinical data of 217 thyroid nodules of 201 patients who underwent grayscale ultrasound, real-time SWE, and thyroid function laboratory examination in Ma'anshan People's Hospital from January 2019 to December 2020 were retrospectively analyzed. The subjects were divided into a benign nodule group (106 nodules) and a malignant nodule group (111 nodules). The differences in grayscale ultrasound features, quantitative parameters of real-time SWE, and laboratory results of thyroid function between benign and malignant thyroid nodules were analyzed. We used a chi-square test for categorical variables and a t-test for continuous variables. Then, the independent risk factors for thyroid cancer were analyzed using multivariate logistic regression. Based on the independent risk factors, a nomogram for predicting thyroid cancer risk was constructed using the RMS package of the R software.

RESULTS

Multivariate logistic regression showed that the grayscale ultrasound features of thyroid nodules were the shape, margin, echogenicity, and echogenic foci of the nodules,the maximum Young's modulus (SWE-max) of thyroid nodules, and the ratio of thyroid nodule and peripheral gland (SWE-ratio) measured by real-time SWE were independent risk factors for thyroid cancer (all p < 0.05), and the other variables had no statistical difference (p > 0.05). Based on the shape (OR = 5.160, 95% CI: 2.252-11.825), the margin (OR = 9.647, 95% CI: 2.048-45.443), the echogenicity (OR = 6.512, 95% CI: 1.729-24.524), the echogenic foci (OR = 2.049, 95% CI: 1.118-3.756), and the maximum Young's modulus (SWE-max) (OR = 1.296, 95% CI: 1.140-1.473), the SWE-ratio (OR = 2.001, 95% CI: 1.403-2.854) of the thyroid nodule to peripheral gland was used to establish the related nomogram prediction model. The bootstrap self-sampling method was used to verify the model. The consistency index (C-index) was 0.979, ROC curve was used to analyze the nomogram scores of all patients, and the AUC of nomogram prediction of thyroid cancer was 0.976, indicating that the nomogram model had high accuracy in the risk prediction of thyroid cancer.

CONCLUSIONS

The nomogram model of grayscale ultrasound features combined with SWE parameters can accurately predict thyroid cancer.

Nomogram predicting overall prognosis for invasive micropapillary carcinoma of the breast: a SEER-based population study

OBJECTIVES

The prognosis of invasive micropapillary carcinoma (IMPC) of the breast is determined by many clinicopathological factors. This study aims to identify prognostic factors and develop reliable nomogram to predict the overall survival (OS) in patients with IMPC.

DESIGN

Log-rank test and Cox proportional hazards analysis were used to identify variables and construct a nomogram based on the training cohort. C-index and calibration curves were performed to evaluate the performance of the model in the training cohort and validation cohorts.

SETTING

We collected the patient data from the Surveillance, Epidemiology and End Results (SEER) database. This database holds data related to the cancer incidence from 18 population-based cancer registries in the USA.

PARTICIPANTS

The SEER database was used to screen 754 eligible patients as the study cohort. The whole cohort was randomly divided into a training cohort (n=377) and a validation cohort (n=377).

RESULTS

Age at diagnosis, hormone receptors, number of positive regional lymph nodes and clinical stage were independent prognostic factors for patients with IMPC. The calibration curves presented excellent consistency between the actual and nomogram-predict survival probabilities in the training and validation cohorts. The C-index values of the nomogram were 0.794 and 0.774 for OS in the training and validation cohorts, respectively.

CONCLUSIONS

The novel nomogram provides new insights of the risk of each prognostic factor and can assist doctors in predicting the 1-year, 3-year and 5-year OS in patients with IMPC.

Survival Nomogram for Patients With Locally Advanced Breast Cancer Undergoing Immediate Breast Reconstruction: A SEER Population-Based Study

INTRODUCTION/BACKGROUND

This study aimed to construct a nomogram to provide prognostic references for patients with locally advanced breast cancer (LABC) to receive immediate breast reconstruction (IBR).

MATERIALS AND METHODS

All data were obtained from the Surveillance, Epidemiology and End Results (SEER) database. Univariate Cox regression, least absolute shrinkage and selection operator (LASSO) and best subset regression (BSR), separately followed by backward stepwise multivariable Cox, were used to construct the nomogram. Risk stratification was established after validation.

RESULTS

A total of 6,285 patients were enrolled to generate the training group (n = 3,466) and the test group (n = 2,819) by geographical split. Age, marital status, grade, T staging, N staging, radiotherapy, chemotherapy, estrogen receptor status (ER), progesterone receptor status (PR) and human epidermal growth factor receptor type 2 status (HER2) were used to fit the nomogram. The overall Harrell's concordance index (C-index) was 0.772 in the training group and 0.762 in the test group. The area under the receiver operator characteristic curves (AUC) at 3-year and 5-year were respectively 0.824 and 0.720 in the training group, 0.792 and 0.733 in the test group. The calibration curves showed great consistency in both groups. A dynamic nomogram (https://dcpanfromsh.shinyapps.io/NomforLABCafterIBR/) was developed.

CONCLUSION

A nomogram was developed and validated that predicts prognosis more accurately than the AJCC 7th stage and can be used as a reference for decision-making in LABC patients receiving IBR.

Nontherapeutic Risk Factors of Different Grouped Stage IIIC Breast Cancer Patients’ Mortality: A Study of the US Surveillance, Epidemiology, and End Results Database

Objectives

Stage IIIC breast cancer, as a local advanced breast cancer, has a poor prognosis compared with that of early breast cancer. We further investigated the risk factors of mortality in stage IIIC primary breast cancer patients and their predictive value.

Methods

We extracted data from the US Surveillance, Epidemiology, and End Results (SEER) database of female patients with stage IIIC primary breast cancer (n = 1673) from January 2011 to December 2015.

Results

Hormone receptor negativity (P ≤ 0.001 and P ≤ 0.001, respectively), aggressive molecular typing (P ≤ 0.001 and P ≤ 0.001, respectively), high T stage (P ≤ 0.001 and P ≤ 0.001, respectively), a high number of positive lymph nodes (≥14) (P=0.005 and P=0.001, respectively), and lymph node ratio (≥0.8148) (P ≤ 0.001 and P ≤ 0.001, respectively) were associated with poor disease-specific survival. The indicators of disease-specific survival included estrogen receptor status, progesterone receptor status, molecular typing, T stage, number of positive lymph nodes, and lymph node ratio (P ≤ 0.001,P ≤ 0.001,P ≤ 0.001,P ≤ 0.001, P=0.002, and P ≤ 0.001, respectively).

Conclusion

Hormone receptor negativity, aggressive molecular typing, high T stage, high number of positive lymph nodes, and lymph node ratio are poor prognostic factors patients with stage IIIC primary breast cancer. The efficient indicators of disease-specific survival include estrogen receptor status, progesterone receptor status, molecular typing, T stage, number of positive lymph nodes, and lymph node ratio.

Nomograms predict survival of patients with lymph node-positive, luminal a breast cancer

Background

To develop nomograms for the prediction of the 1-, 3-, and 5-year overall survival (OS) and breast cancer-specific survival (BCSS) for patients with lymph node positive, luminal A breast cancer.

Methods

Thirty-nine thousand fifty-one patients from The Surveillance, Epidemiology, and End Results (SEER) database were included in our study and were set into a training group (n = 19,526) and a validation group (n = 19,525). Univariate analysis and Cox proportional hazards analysis were used to select variables and set up nomogram models on the basis of the training group. Kaplan-Meier curves and the log-rank test were adopted in the survival analysis and curves plotting. C-index, calibration plots and ROC curves were used to performed internal and external validation on the training group and validation group.

Results

Following independent factors were included in our nomograms: Age, marital status, grade, ethnic group, T stage, positive lymph nodes numbers, Metastasis, surgery, radiotherapy, chemotherapy. In both the training group and testing group, the calibration plots show that the actual and nomogram-predicted survival probabilities are consistent greatly. The C-index values of the nomograms in the training and validation cohorts were 0.782 and 0.806 for OS and 0.783 and 0.804 for BCSS, respectively. The ROC curves show that our nomograms have good discrimination.

Conclusions

The nomograms may assist clinicians predict the 1-, 3-, and 5-year OS and BCSS of patients with lymph node positive, luminal A breast cancer.

Risk Factors, Prognostic Factors, and Nomogram for Distant Metastasis in Breast Cancer Patients Without Lymph Node Metastasis

BACKGROUND

Lymph node negative (N0) breast cancer can be found coexisting with distant metastasis (DM), which might consequently make clinicians underestimate the risk of relapse and insufficient treatment for this subpopulation.

METHODS

The clinicopathological characteristics of N0 breast cancer patients from the Surveillance, Epidemiology, and End Results (SEER) database between January 2010 and December 2015 were retrospectively reviewed. Multivariate logistic and Cox analyses were used to identify independent risk factors in promoting DM and the 1-, 3-, and 5- year cancer-specific survival (CSS) in this subpopulation.

RESULT

Seven factors including age (<40 years), tumor size (>10 mm), race (Black), location (central), grade (poor differentiation), histology (invasive lobular carcinoma), and subtype (luminal B and Her-2 enriched) were associated with DM, and the area under curve (AUC) was 0.776 (95% CI: 0.763-0.790). Moreover, T1-3N0M1 patients with age >60 years at diagnosis, Black race, triple-negative breast cancer subtype, no surgery performed, and multiple DMs presented a worse 1-, 3-, and 5-year CSS. The areas under the ROC for 1-, 3-, and 5- year CSS in the training cohort were 0.772, 0.741, and 0.762, respectively, and 0.725, 0.695, and 0.699 in the validation cohort.

CONCLUSION

The clinicopathological characteristics associated with the risk of DM and the prognosis of female breast cancer patients without lymph node metastasis but with DM are determined. A novel nomogram for predicting 1-, 3-, 5- year CSS in T1-3N0M1 patients is also well established and validated, which could help clinicians better stratify patients who are at a high-risk level for receiving relatively aggressive management.

Cancer-Specific Survival Outcome in Early-Stage Young Breast Cancer: Evidence From the SEER Database Analysis

BACKGROUND

Young women with breast cancer are determined to present poorer survival compare with elderly patients. Therefore, identifying the clinical prognostic factors in young women with early-stage (T_1-2N_0-1M₀) breast cancer is pivotal for surgeons to make better postoperative management.

METHODS

The clinicopathological characteristics of female patients with early-stage breast cancer from the Surveillance, Epidemiology, and End Results program between Jan 2010 and Dec 2015 were retrospectively reviewed and analyzed. Univariate and multivariate Cox regression analyses were used to determine the potential risk factors of cancer-specific survival in young women with early-stage breast cancer. The nomogram was constructed and further evaluated by an internal validation cohort. The Kaplan-Meier survival curves were used to estimate cancer-specific survival probability and the cumulative incidence.

RESULTS

Six variables including race, tumor location, grade, regional lymph node status, tumor subtype, and size were identified to be significantly associated with the prognosis of young women with early-stage breast cancer during the postoperative follow-up. A nomogram for predicting the 3-, 5- year cancer-specific survival probability in this subpopulation group was established with a favorable concordance index of 0.783, supported by an internal validation cohort with the AUC of 0.722 and 0.696 in 3-, 5- year cancer-specific survival probability, respectively.

CONCLUSIONS

The first predictive nomogram containing favorable discrimination is successfully established and validated for predicting the 3-, 5- year cancer-specific survival probability in young women with early-stage breast cancer during the postoperative follow-up. This model would help clinicians to make accurate treatment decisions in different clinical risk population.