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Post-Neoadjuvant Treatment Strategies for Patients with Early Breast Cancer.

ABSTRACT: Pre-surgical treatments in patients with early breast cancer allows a direct estimation of treatment efficacy, by comparing the tumor and the treatment. Patients who achieve a pathological complete response at surgery have a better prognosis, with lower risk of disease recurrence and death. Hence, clinical research efforts have been focusing on high-risk patients with residual disease at surgery, who may be "salvaged" through additional treatments administered in the post-neoadjuvant setting. In the present review, we aim to illustrate the development and advantages of the post-neoadjuvant setting, and to discuss the available strategies for patients with early breast cancer, either approved or under investigation. This review was written after literature search on main scientific databases (e.g., PubMed) and conference proceedings from major oncology conferences up to 1 August 2022. T-DM1 and capecitabine are currently approved as post-neoadjuvant treatments for patients with HER2-positive and triple-negative breast cancer, respectively, with residual disease at surgery. More recently, other treatment strategies have been approved for patients with high-risk early breast cancer, including the immune checkpoint inhibitor pembrolizumab, the PARP inhibitor olaparib and the CDK 4/6 inhibitor abemaciclib. Novel agents and treatment combinations are currently under investigation as promising post-neoadjuvant treatment strategies.

SUBMITTER: Agostinetto E

PROVIDER: S-EPMC9654353 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Post-Neoadjuvant Treatment Strategies for Patients with Early Breast Cancer.

Agostinetto Elisa E Jacobs Flavia F Debien Véronique V De Caluwé Alex A Pop Catalin-Florin CF Catteau Xavier X Aftimos Philippe P de Azambuja Evandro E Buisseret Laurence L

Cancers 20221107 21

Pre-surgical treatments in patients with early breast cancer allows a direct estimation of treatment efficacy, by comparing the tumor and the treatment. Patients who achieve a pathological complete response at surgery have a better prognosis, with lower risk of disease recurrence and death. Hence, clinical research efforts have been focusing on high-risk patients with residual disease at surgery, who may be "salvaged" through additional treatments administered in the post-neoadjuvant setting. In ...[more]

PMID: 36358886

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Project description:This study aimed to compare the long-term outcomes of breast-conserving surgery plus radiotherapy (BCS + RT) and mastectomy in early breast cancer (EBC) patients who received neoadjuvant systemic therapy (NST), and sought to construct and authenticate a machine learning algorithm that could assist healthcare professionals in formulating personalized treatment strategies for this patient population. We analyzed data from the Surveillance, Epidemiology, and End Results database on EBC patients undergoing BCS + RT or mastectomy post-NST (2010-2018). Employing propensity score matching (PSM) to minimize potential biases, we compared breast cancer-specific survival (BCSS) and overall survival (OS) between the two surgical groups. Additionally, we trained and validated six machine learning survival models and developed a cloud-based recommendation system for surgical treatment based on the optimal model. Among the 13,958 patients, 9028 (64.7%) underwent BCS + RT and 4930 (35.3%) underwent mastectomy. After PSM, there were 3715 patients in each group. Compared to mastectomy, BCS + RT significantly improved BCSS (p < 0.001) and OS (p < 0.001). Prognostic variables associated with BCSS were utilized to develop machine learning models. In both the training and validation cohorts, the random survival forest (RSF) model demonstrated superior predictive performance (0.847 and 0.795), not only outperforming other machine learning models, including Rpart (0.725 and 0.707), Xgboost (0.762 and 0.727), Glmboost (0.748 and 0.788), Survctree (0.764 and 0.766), and Survsvm (0.777 and 0.790), but also outperforming the classical COX model (0.749 and 0.782). Lastly, a web-based prediction tool was built to facilitate clinical application [ https://jhren.shinyapps.io/shinyapp1 ]. After adjusting other confounders, BCS + RT was associated with improved outcomes in patients with EBC after NST, compared to those who underwent mastectomy. Moreover, the RSF model, a reliable tool, can predict long-term outcomes for patients, providing valuable guidance for operative methods and postoperative follow-up.

Project description:ObjectiveTo develop and validate a radiomics nomogram based on pre-treatment, early treatment ultrasound (US) radiomics features combined with clinical characteristics for early prediction of response to neoadjuvant chemotherapy (NAC) in breast cancer.MethodA total of 217 patients with histological results of breast cancer receiving four to eight cycles of NAC before surgery from January 2018 to December 2020 were enrolled. Patients from the study population were randomly separated into a training set (n = 152) and a validation set (n = 65) at a ratio of 7:3. A total of 788 radiomics features were extracted from each region of interest in the US image at pre-treatment baseline (radiomic signature, RS1), early treatment (after completion of two cycles of NAC, RS2) and delta radiomics (calculated between the pre-treatment and post-treatment features, Delta RS). The Max-Relevance and Min-Redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) regression were applied for feature selection. The predictive nomogram was built based on the radiomics signature combined with clinicopathological risk factors. Discrimination, calibration, and prediction performance were further evaluated in the validation set.ResultsOf the 217 breast masses, 127 (58.5%) were responsive to NAC and 90 (41.5%) were non-responsive. Following feature selection, nine features in RS1, 11 features in RS2, and eight features in Delta RS remained. With multivariate analysis, the RS1, RS2, Delta RS, and Ki-67 expression were independently associated with breast NAC response. However, the performance of the Delta RS (AUC Delta RS = 0.743) was not higher than RS1 (AUC RS1 = 0.722, PDelta vs RS1 = 0.086) and RS2 (AUC RS2 = 0.811, PDelta vs RS2 = 0.173) with the Delong test. The nomogram incorporating RS1, RS2, and Ki-67 expression showed better predictive ability for NAC response with an area under the curve (AUC) of 0.866 in validation cohorts than either the single RS1 (AUC 0.725) or RS2 (AUC 0.793) or Ki-67 (AUC 0.643).ConclusionThe nomogram incorporating pre-treatment and early-treatment US radiomics features and Ki-67 expression showed good performance in terms of NAC response in breast cancer, thereby providing valuable information for individual treatment and timely adjustment of chemotherapy regimens.

Project description:BackgroundNeoadjuvant endocrine therapy presents an important downstaging option with lower toxicity than neoadjuvant chemotherapy in oestrogen receptor (ER)-positive early breast cancer. Meta-analysis of the effects of neoadjuvant endocrine therapy on surgical outcomes across randomized clinical trials (RCTs) and cohort studies has not previously been performed.MethodsA systematic review and meta-analysis was performed to evaluate the effect of neoadjuvant endocrine therapy on surgical outcomes (PROSPERO (international prospective register of systematic reviews, 2020)) compared with surgery followed by adjuvant endocrine therapy. PubMed and EMBASE were searched to identify RCT and cohort studies between 1946 and 27 March 2024. Two independent reviewers manually screened the identified records and extracted the data. Risk of bias was assessed using the Cochrane Collaboration tools and random-effects meta-analysis was done with ReviewManager.ResultsThe search identified 2390 articles eligible for screening. The review included 20 studies (12 cohort and 8 RCTs); 19 were included in the meta-analysis with a total of 6382 patients. Overall, neoadjuvant endocrine therapy was associated with a lower mastectomy rate compared with surgery first (risk ratio (RR) 0.53, 95% c.i. 0.44 to 0.64). Subgroup analysis showed similar improvement in the mastectomy rate in the neoadjuvant endocrine therapy group versus control group irrespective of study type (RCT: RR 0.58, 95% c.i. 0.50 to 0.66; cohorts: RR 0.48, 95% c.i. 0.33 to 0.70). There was no difference in the mastectomy rate by duration of neoadjuvant endocrine therapy (more than 4 months: RR 0.57, 95% c.i. 0.42 to 0.78; 4 months or less than 4 months: RR 0.52, 95% c.i. 0.43 to 0.64). Most of the studies were characterized by moderate-quality evidence with significant heterogeneity.ConclusionNeoadjuvant endocrine therapy is associated with a reduction in mastectomy rate. Given the moderate methodological quality of previous studies, further RCTs are required.Registration idCRD42020209257.

Project description:ImportanceThe neoadjuvant treatment options for ERBB2-positive (also known as HER2-positive) breast cancer are associated with different rates of pathologic complete response (pCR). The KATHERINE trial showed that adjuvant trastuzumab emtansine (T-DM1) can reduce recurrence in patients with residual disease compared with patients treated with trastuzumab; however, T-DM1 and other ERBB2-targeted agents are costly, and understanding the costs and health consequences of various combinations of neoadjuvant followed by adjuvant treatments in the United States is needed.ObjectiveTo examine the costs and disease outcomes associated with selection of various neoadjuvant followed by adjuvant treatment strategies for patients with ERBB2-positive breast cancer.Design, setting, and participantsIn this economic evaluation, a decision-analytic model was developed to evaluate various neoadjuvant followed by adjuvant treatment strategies for women with ERBB2-positive breast cancer from a health care payer perspective in the United States. The model was informed by the KATHERINE trial, other clinical trials with different regimens from the KATHERINE trial, the Flatiron Health Database, McKesson Corporation data, and other evidence in the published literature. Starting trial median age for KATHERINE patients was 49 years (range, 24-79 years in T-DM1 arm and 23-80 years in trastuzumab arm). The model simulated patients receiving 5 different neoadjuvant followed by adjuvant treatment strategies. Data analyses were performed from March 2019 to August 2020.ExposureThere were 4 neoadjuvant regimens: (1) HP: trastuzumab (H) plus pertuzumab (P), (2) THP: paclitaxel (T) plus H plus P, (3) DDAC-THP: dose-dense anthracycline/cyclophosphamide (DDAC) plus THP, (4) TCHP: docetaxel (T) plus carboplatin (C) plus HP. All patients with pCR, regardless of neoadjuvant regimen, received adjuvant H. Patients with residual disease received different adjuvant therapies depending on the neoadjuvant regimen according to the 5 following strategies: (1) neoadjuvant DDAC-THP followed by adjuvant H, (2) neoadjuvant DDAC-THP followed by adjuvant T-DM1, (3) neoadjuvant THP followed by adjuvant DDAC plus T-DM1, (4) neoadjuvant HP followed by adjuvant DDAC/THP plus T-DM1, or (5) neoadjuvant TCHP followed by adjuvant T-DM1.Main outcomes and measuresLifetime costs in 2020 US dollars and quality-adjusted life-years (QALYs) were estimated for each treatment strategy, and incremental cost-effectiveness ratios were estimated. A strategy was classified as dominated if it was associated with fewer QALYs at higher costs than the alternative.ResultsIn the base-case analysis, costs ranged from $415 833 (strategy 3) to $518 859 (strategy 4), and QALYs ranged from 9.67 (strategy 1) to 10.73 (strategy 3). Strategy 3 was associated with the highest health benefits (10.73 QALYs) and lowest costs ($415 833) and dominated all other strategies. Probabilistic analysis confirmed that this strategy had the highest probability of cost-effectiveness (>70% at willingness-to-pay thresholds of $0-200,000/QALY) and was associated with the highest net benefit.Conclusions and relevanceThese results suggest that neoadjuvant THP followed by adjuvant H for patients with pCR or followed by adjuvant DDAC plus T-DM1 for patients with residual disease was associated with the highest health benefits and lowest costs for women with ERBB2-positive breast cancer compared with other treatment strategies considered.

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Post-Neoadjuvant Treatment Strategies for Patients with Early Breast Cancer.

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Post-Neoadjuvant Treatment Strategies for Patients with Early Breast Cancer.

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