21-Gene Recurrence Score Assay Could Not Predict Benefit of Post-mastectomy Radiotherapy in T1-2 N1mic ER-Positive HER2-Negative Breast Cancer

21-gene recurrence score predictive of the benefit of postoperative radiotherapy after breast-conserving surgery for elderly patients with T1N0 and luminal breast cancer

PURPOSE

To assess the predictive value of the 21-gene recurrence score (RS) on the survival outcomes of postoperative radiotherapy (PORT) in elderly patients with T1N0 luminal breast cancer after breast-conserving surgery.

METHODS

We retrospectively included patients aged ≥ 70 years and diagnosed with T1N0 luminal BC between 2004 and 2015 using the data from the Surveillance, Epidemiology, and End Results. The RS groups were categorized using the TAILORx criteria as follows: low risk (RS < 11) (LR), intermediate risk (RS 11-25) (IR), and high risk (RS > 25) (HR). Kaplan-Meier analysis, propensity score matching (PSM), and Cox proportional hazards analysis were used for statistical analysis.

RESULTS

We included 5901 patients in the analysis. Of the patients, 4492 (76.1%) underwent PORT, while 1409 (23.9%) did not receive PORT. There were 1588 (26.9%), 3613 (61.2%), and 700 (12.0%) patients classified as LR, IR, and HR, respectively. There were 1182 (74.4%), 2773 (76.8%), and 537 (76.7%) patients in the LR, IR, and HR groups receiving PORT, respectively (P = 0.182). A total of 1353 pairs of patients were completely matched using PSM. PORT was independently associated with better overall survival (OS) (P < 0.001) and breast cancer-specific survival (BCSS) (P = 0.015) in the entire cohort. The sensitivity analyses showed that the receipt of PORT was not associated with OS (P = 0.887) and BCSS (P = 0.861) in the LR group. However, the receipt of PORT was associated with OS (P < 0.001) and BCSS in the IRHR group (P = 0.026).

CONCLUSION

Our study highlights the possible role of the 21-gene RS in predicting the survival outcomes of PORT following BCS in elderly patients with T1N0 luminal breast cancer.

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.

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.

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.

Personalization in Modern Radiation Oncology: Methods, Results and Pitfalls. Personalized Interventions and Breast Cancer

Breast cancer, the most frequent malignancy in women worldwide, is a heterogeneous group of diseases, characterized by distinct molecular aberrations. In precision medicine, radiation oncology for breast cancer aims at tailoring treatment according to tumor biology and each patient’s clinical features and genetics. Although systemic therapies are personalized according to molecular sub-type [i.e. endocrine therapy for receptor-positive disease and anti-human epidermal growth factor receptor 2 (HER2) therapy for HER2-positive disease] and multi-gene assays, personalized radiation therapy has yet to be adopted in the clinical setting. Currently, attempts are being made to identify prognostic and/or predictive factors, biomarkers, signatures that could lead to personalized treatment in order to select appropriate patients who might, or might not, benefit from radiation therapy or whose radiation therapy might be escalated or de-escalated in dosages and volumes. This overview focuses on what has been achieved to date in personalized post-operative radiation therapy and individual patient radiosensitivity assessments by means of tumor sub-types and genetics.

Prognostic and Predictive Value of the American Joint Committee on Cancer Pathological Prognostic Staging System in Nodal Micrometastatic Breast Cancer

Introduction

To investigate the prognostic and predictive effect of the American Joint Committee on Cancer (AJCC) 8^th edition pathological prognostic staging system in patients with T1-2N1micM0 breast cancer who underwent mastectomy.

Methods

Data from T1-2N1micM0 breast cancer patients who underwent mastectomy from 2010–2014 were obtained from the Surveillance, Epidemiology, and End Results program. The chi-square test, binomial logistics regression, receiver-operating characteristics curve, competing-risk regression model, Cox proportional hazards regression model, and proportional hazard assumption were used for statistical analyses.

Results

We identified 4,729 patients, including 1,062 patients were received postmastectomy radiotherapy (PMRT). Stage change occurred in 88.2% of the patients, of which 84.4% were downstaged and 3.7% were upstaged. Patients with higher pathological prognostic stages were independently predicted to receive PMRT. The 5-year breast cancer-specific survival (BCSS) was 97.5, 93.7, 90.1, 86.0, and 73.5% in disease stages IA, IB, IIA, IIB, and IIIA, respectively, according to the 8^th edition criteria (P < 0.001). The AJCC 8^th edition demonstrated moderate discriminative ability, and it had a significantly better ability to predict the BCSS than the AJCC 7^th edition criteria (P < 0.001). The multivariate prognostic analysis showed that the new pathological prognostic staging was an independent prognostic factor affecting the BCSS. The BCSS worsened with an increase in the stage. The PMRT did not affect the BCSS regardless of the pathological prognostic stage. Similar trends were found using the competing-risks regression model.

Conclusions

The 8^th AJCC breast cancer pathological prognostic staging system downstaged 84.4% of patients with T1-2N1micM0 disease and the survival outcome prediction with this staging system was more accurate than the AJCC 7^th edition system. Our study does not support using the prognostic stage as a guideline to escalate of PMRT.

Association between the 21-gene recurrence score and isolated locoregional recurrence in stage I-II, hormone receptor-positive breast cancer

Background

Although the 21-gene recurrence score (RS) assay is widely used to predict distant recurrence risk and benefit from adjuvant chemotherapy among women with hormone receptor-positive (HR+) breast cancer, the relationship between the RS and isolated locoregional recurrence (iLRR) remains poorly understood. Therefore, we examined the association between the RS and risk of iLRR for women with stage I-II, HR+ breast cancer.

Methods

We identified 1758 women captured in the national prospective Breast Cancer-Collaborative Outcomes Research Database who were diagnosed with stage I-II, HR+ breast cancer from 2006 to 2012, treated with mastectomy or breast-conserving surgery, and received RS testing. Women who received neoadjuvant therapy were excluded. The association between the RS and risk of iLRR was examined using competing risks regression.

Results

Overall, 19% of the cohort (n = 329) had a RS ≥25. At median follow-up of 29 months, only 22 iLRR events were observed. Having a RS ≥25 was not associated with a significantly higher risk of iLRR compared to a RS < 25 (hazard ratio 1.14, 95% confidence interval 0.39–3.36, P = 0.81). When limited to women who received adjuvant endocrine therapy without chemotherapy (n = 1199; 68% of the cohort), having a RS ≥25 (n = 74) was significantly associated with a higher risk of iLRR compared to a RS < 25 (hazard ratio 3.66, 95% confidence interval 1.07–12.5, P = 0.04). In this group, increasing RS was associated with greater risk of iLRR (compared to RS < 18, hazard ratio of 1.66, 3.59, and 7.06, respectively, for RS 18–24, 25–30, and ≥ 31; P_trend = 0.02).

Conclusions

The RS was significantly associated with risk of iLRR in patients who did not receive adjuvant chemotherapy. The utility of the RS in identifying patients who have a low risk of iLRR should be further studied.

Commercially Available Gene Expression Assays as Predictive Tools for Adjuvant Radiotherapy? A Critical Review

Background

Gene expression assays are increasingly used for decision-making regarding adjuvant chemotherapy in patients with hormone receptor-positive, HER2-negative breast cancer. There are some clinical situations in which there is also a need for better prognostic and predictive markers to better estimate the amount of benefit from adjuvant radiotherapy. The rising availability of gene expression analyses prompts the question whether their results can also be used to guide clinical decisions regarding adjuvant radiation.

Summary

Multiple studies suggest a correlation between results from gene expression assays and locoregional recurrence rates. Only few publications addressed the predictive value of results from gene expression analysis for the role of adjuvant radiotherapy in different settings.

Key Messages

To date, the available evidence on the possible predictive value of gene expression assays for radiotherapy does not support their inclusion into the decision-making process for adjuvant radiation. This is due to methodological weaknesses and limitations regarding patient selection, the nonrandomized design of all studies in terms of radiotherapy use, and limited availability of tissue from prospective trials. Thus, utilization of the present knowledge for clinical indication of radiotherapy should be very cautious.