Nomogram predicting survival as a selection criterion for postmastectomy radiotherapy in patients with T1 to T2 breast cancer with 1 to 3 positive lymph nodes

Postmastectomy radiotherapy in patients with T1-2N1 breast cancer: a single center experience and a meta-analysis

PURPOSE

Postmastectomy radiotherapy (PMRT) in patients with T1-2N1 breast cancer is still controversial. This study was to evaluate the survival prognosis of T1-2N1 patients with or without PMRT.

PATIENTS AND METHODS

From January 2006 to May 2017, 2606 female breast cancer patients underwent mastectomy in our medical center, among whom 402 patients of T1-2N1 stage with or without PMRT were finally analyzed. The median follow-up duration was 59.5 months. The primary endpoint was overall survival (OS). The secondary endpoint was disease-free survival (DFS).

RESULTS

In the study of our center, no statistically significant difference was observed between the T1-2N1 PMRT and non-PMRT subgroups for the 5-year OS (94.4% vs 95.4%, p = 0.667) and DFS (90.1% vs. 91.1%, p = 0.798). By the date of the last follow-up, 8.96% (n = 36) of the patients experienced any recurrence. Univariate analysis revealed that PMRT was not a prognostic factor for either OS (p = 0.667) or DFS (p = 0.798) in T1-2N1 patients. We then did a meta-analysis on the current treatment patterns, in which 2606 PMRT and 4281 non-PMRT T1-2N1 breast cancer patients with mastectomy were included. The meta-analysis showed that PMRT didn't improve the OS of the patients (HR = 0.85, p = 0.11), but patients with PMRT had better DFS than those in the non-PMRT group (HR = 0.62, p < 0.001).

CONCLUSION

PMRT did not affect the survival of T1-2N1 breast cancer patients who underwent mastectomy, suggesting that radiotherapy may be safely omitted for them.

Development and validation of nomograms for predicting survival outcomes in patients with T1-2N1 breast cancer to identify those who could not benefit from postmastectomy radiotherapy

Purpose

In this study, we aimed to develop and validate nomograms for predicting the survival outcomes in patients with T1-2N1 breast cancer to identify the patients who could not benefit from postmastectomy radiotherapy (PMRT).

Methods

Data from 10191 patients with T1-2N1 breast cancer were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Of them, 6542 patients who had not received PMRT formed the training set. Concurrently, we retrospectively enrolled 419 patients from the Affiliated Hospital of North Sichuan Medical College (NSMC), and 286 patients who did not undergo PMRT formed the external validation set. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were used for selecting prognostic factors in the training set. Using the selected factors, two prognostic nomograms were constructed. The nomograms’ performance was assessed using the concordance index (C-index), calibration curves, decision curve analysis (DCA), and risk subgroup classification. The stabilized inverse probability of treatment weights (IPTWs) was used to balance the baseline characteristics of the different risk groups. Finally, the survival outcomes and effectiveness of PMRT after IPTW adjustment were evaluated using adjusted Kaplan–Meier curves and Cox regression models.

Results

The 8-year overall survival (OS) and breast cancer-specific survival (BCSS) rates for the SEER cohort were 84.3% and 90.1%, with a median follow-up time of 76 months, while those for the NSMC cohort were 84.1% and 86.9%, with a median follow-up time of 73 months. Moreover, significant differences were observed in the survival curves for the different risk subgroups (P &lt; 0.001) in both SEER and NSMC cohorts. The subgroup analysis after adjustment by IPTW revealed that PMRT was significantly associated with improved OS and BCSS in the intermediate- (hazard ratio [HR] = 0.72, 95% confidence interval [CI]: 0.59–0.88, P=0.001; HR = 0.77, 95% CI: 0.62–0.95, P = 0.015) and high- (HR=0.66, 95% CI: 0.52–0.83, P&lt;0.001; HR=0.74, 95% CI: 0.56–0.99, P=0.039) risk groups. However, PMRT had no significant effects on patients in the low-risk groups.

Conclusion

According to the prognostic nomogram, we performed risk subgroup classification and found that patients in the low-risk group did not benefit from PMRT.

Application of mammography-based radiomics signature for preoperative prediction of triple-negative breast cancer

Objective

This study is aimed to explore the value of mammography-based radiomics signature for preoperative prediction of triple-negative breast cancer (TNBC).

Materials and methods

Initially, the clinical and X-ray data of patients (n = 319, age of 54 ± 14) with breast cancer (triple-negative—65, non-triple-negative—254) from the First Affiliated Hospital of Soochow University (n = 211, as a training set) and Suzhou Municipal Hospital (n = 108, as a verification set) from January 2018 to February 2021 are retrospectively analyzed. Comparing the mediolateral oblique (MLO) and cranial cauda (CC) mammography images, the mammography images with larger lesion areas are selected, and the image segmentation and radiomics feature extraction are then performed by the MaZda software. Further, the Fisher coefficients (Fisher), classification error probability combined average correlation coefficients (POE + ACC), and mutual information (MI) are used to select three sets of feature subsets. Moreover, the score of each patient’s radiomics signature (Radscore) is calculated. Finally, the receiver operating characteristic curve (ROC) is analyzed to calculate the AUC, accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of TNBC.

Results

A significant difference in the mammography manifestation between the triple-negative and the non-triple-negative groups (P < 0.001) is observed. The (POE + ACC)-NDA method showed the highest accuracy of 88.39%. The Radscore of triple-negative and non-triple-negative groups in the training set includes − 0.678 (− 1.292, 0.088) and − 2.536 (− 3.496, − 1.324), respectively, with a statistically significant difference (Z = − 6.314, P < 0.001). In contrast, the Radscore in the validation set includes − 0.750 (− 1.332, − 0.054) and − 2.223 (− 2.963, − 1.256), with a statistically significant difference (Z = − 4.669, P < 0.001). In the training set, the AUC, accuracy, sensitivity, specificity, positive predictive value and negative predictive value of TNBC include 0.821 (95% confidence interval 0.752–0.890), 74.4%, 82.5%, 72.5%, 41.2%, and 94.6%, respectively. In the validation set, the AUC, accuracy, sensitivity, specificity, positive predictive value and negative predictive value of TNBC are of 0.809 (95% confidence interval 0.711–0.907), 80.6%, 72.0%, 80.7%, 55.5%, and 93.1%, respectively.

Conclusion

In summary, we firmly believe that this mammography-based radiomics signature could be useful in the preoperative prediction of TNBC due to its high value.

Influence of age as a continuous variable on the prognosis of patients with pT1-2N1 breast cancer

PURPOSE

To assess the influence of age as a continuous variable on the prognosis of pT1-2N1 breast cancer and examine its decision-making value for postmastectomy radiotherapy (PMRT).

METHODS

We retrospectively evaluated 5438 patients with pT1-2N1 breast cancer after mastectomy in 11 hospitals. A multivariable Cox proportional hazards regression model with penalized splines was used to examine the relationship between age and oncologic outcomes.

RESULTS

The median follow-up was 67.0 months. After adjustments for confounding characteristics, nonsignificant downward trend in locoregional recurrence (LRR) risk was observed with increasing age (P-non-linear association = 0.640; P-linear association = 0.078). A significant non-linear association was found between age and disease-free survival (DFS) and overall survival (OS) (P-non-linear association <0.05; P-linear association >0.05, respectively). The DFS and OS exhibited U-shaped relationships, with the hazard ratios (HRs), reaching a nadir at 50 years old. A decreased risk of LRR with PMRT vs. no PMRT (HR = 0.304, 95% CI: 0.204-0.454) was maintained in all ages. The HR of PMRT vs. no PMRT for DFS and OS gradually increased with age. In patients ≤50 years old, PMRT was independently associated with favorable LRR, DFS, and OS, all P < 0.05). In patients >50 years old, PMRT was independently associated with reduced LRR (P = 0.004), but had no effect on DFS or OS.

CONCLUSIONS

Age was an independent prognostic factor for pT1-2N1 breast cancer; PMRT provided survival benefits for patients ≤50 years old, but not for patients >50 years old.

Practical Model to Optimize the Strategy of Adjuvant Postmastectomy Radiotherapy in T1-2N1 Breast Cancer With Modern Systemic Therapy

Purpose

The effect of adjuvant irradiation after mastectomy in early-stage breast cancer patients remains controversial. The present study aims to explore the clinical benefit obtained from adjuvant radiotherapy among post-mastectomy pT1-2N1 breast cancer patients who received adjuvant modern systemic therapy.

Methods

Medical records of consecutive patients with pT1-2N1 breast cancer who received mastectomy in our institution between January 2009 and December 2016 were retrospectively reviewed. High-risk features consist of patient age, number of positive lymph nodes, T stage, and Ki67 index, which were developed previously at our institution using early-stage breast cancer patients after mastectomy without adjuvant radiotherapy. Differences of survival and local recurrence were compared between no-postmastectomy radiotherapy (PMRT) and PMRT group according to number of risk factors. The time-to-event curves were calculated by the Kaplan–Meier methods and compared by the log-rank test. Propensity score matching (PSM) was performed to reduce the imbalances in patient characteristics.

Results

A total of 548 patients were enrolled (no-PMRT: 259 and PMRT: 289). After a median follow-up of 69 months, the 5-year rate of DFS, BCSS, and LRR in the overall cohort was 90.2%, 97.4%, and 3.6%, respectively. PMRT did not significantly improve DFS, BCSS, and LRRFS in the whole cohort. Patients were divided into low-risk (with no or one risk factor) and high-risk (with two or more risk factors) groups. According to the univariable and multivariable analysis, high-risk group (HR = 1.81, 95% CI 1.11–2.98, p = 0.02) was demonstrated as an independent risk factor for DFS. For the high-risk group, PMRT significantly improved DFS from 81.4% to 91.9% and BCSS from 95.5% to 98.6% and decreased the 5-year rate of LRR from 5.6% to 1.4%, respectively (p < 0.01, p = 0.05, and p = 0.06). However, no survival benefit from PMRT was observed in the low-risk group in terms of DFS, BCSS, and LRR (p = 0.45, p = 0.51, and p = 0.99, respectively). In multivariate analysis, PMRT remained an independent prognostic factor for DFS (HR = 0.50, 95% CI 0.24–1.00, p = 0.05) in the high-risk group. After PSM analysis, the survival benefit of PMRT was sustained in high-risk patients.

Conclusion

PMRT significantly improved DFS in high-risk pT1-2N1 breast cancer patients, but not in low-risk patients. Independent validation of our scoring system is recommended.

Institutionally validated nomogram predicting prognosis for older patients with nonmetastatic nasopharyngeal carcinoma

Aim: Older adult patients with nonmetastatic nasopharyngeal carcinoma (NPC) have poor outcomes relative to younger patients. The authors' group established a nomogram to predict the overall survival of older adults with NPC and inform patient management. Methods: Cases with NPC (n = 782) were enrolled in this study; clinical data in the Surveillance, Epidemiology, and End Results database from 2010 to 2015 served as the training cohort (n = 657), and patients from Jiangxi Cancer Hospital (n = 125) served as the external validation cohort. Results: Training and external validation cohort C-index, receiver operator characteristics curves and calibration curves showed that our nomogram has great predictive ability. Conclusions: Compared with tumor-node-metastasis staging, this nomogram can help clinicians better predict the prognosis of older adults with nonmetastatic NPC.

Debate: Postmastectomy Radiation Therapy in T1/2N1 Disease

Although postmastectomy radiation therapy is known to reduce local recurrence in patients with T1/2N1 breast cancer, some have postulated that not all patients require this treatment. In this era of genomic analyses and personalized therapy, clinicians have debated whether the toxicity of post-mastectomy radiation therapy (PMRT) can be avoided for some subsets of patients. However, the data in this regard remain controversial, particularly as surgeons de-escalate the surgical management of the axilla. Several ongoing clinical trials may provide a glimpse into optimal management in this scenario. However, the "right" answer to this debate currently remains unclear.

A Prognostic Risk Stratification Model to Identify Potential Population Benefiting From Postmastectomy Radiotherapy in T1-2 Breast Cancer With 1-3 Positive Axillary Lymph Nodes

Background and Objectives

To establish a prognostic stratification nomogram for T1–2 breast cancer with 1–3 positive lymph nodes to determine which patients can benefit from postmastectomy radiotherapy (PMRT).

Methods

A population-based study was conducted utilizing data collected from the Surveillance, Epidemiology, and End Results database. Chi-square test or Fisher exact test was used to compare the distribution of characteristics. Cox analysis identified significant prognostic factors for survival. A prognostic stratification model was constructed by R software. Propensity score matching was applied to balance characteristics between PMRT cohort and control cohort. Kaplan-Meier method was performed to evaluate the performance of stratification and the benefits of PMRT in the total population and three risk groups.

Results

The overall performance of the nomogram was good (3-year, 5-year, 10-year AUC were 0.75, 0.72 and 0.67, respectively). The nomogram was performed to excellently distinguish low-risk, moderate-risk, and high-risk groups with 10-year overall survival (OS) of 86.9%, 73.7%, and 62.7%, respectively (P<0.001). In the high-risk group, PMRT can significantly better OS with 10-year all-cause mortality reduced by 6.7% (P = 0.027). However, there was no significant survival difference between PMRT cohort and control cohort in low-risk (P=0.49) and moderate-risk groups (P = 0.35).

Conclusion

The current study developed the first prognostic stratification nomogram for T1–2 breast cancer with 1–3 positive axillary lymph nodes and found that patients in the high-risk group may be easier to benefit from PMRT.