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      Association of Neo-Family History Score with pathological complete response, safety, and survival outcomes in patients with breast cancer receiving neoadjuvant platinum-based chemotherapy: An exploratory analysis of two prospective trials

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          Abstract

          Background

          Homologous recombination deficiency is associated with platinum-based chemosensitivity, whereas few studies reported the predictive value of family history of cancer for breast cancer in the neoadjuvant setting. This study aimed to construct a novel family history scoring system and to explore its association with clinical outcomes for patients with breast cancer receiving neoadjuvant platinum-based chemotherapy.

          Methods

          This study included 262 patients with locally advanced breast cancer enrolled in the SHPD001 and SHPD002 trials from October 2013 to June 2018. The Neo-Family History Score (NeoFHS) was calculated according to cancer type, age at diagnosis, kinship, and number of affected relatives.

          Findings

          Clinical tumor stage (p=0·048), estrogen receptor status (p=0·001), progesterone receptor status (p=0·036), human epidermal growth factor receptor 2 status (p=0·013), and molecular subtype (p=0·016) were significantly related to NeoFHS. NeoFHS could serve as an independent predictive factor of pathological complete response (pCR) (OR=2·262, 95% CI 1·159-4·414, p=0·017) and an independent prognostic factor of relapse-free survival (adjusted HR=0·305, 95% CI 0·102-0·910, p=0·033). Alopecia (p=0·001), nausea (p=0·001), peripheral neuropathy (p=0·018), diarrhea (p=0·026), constipation (p=0·037) of any grade and leukopenia of grade 3 or greater (p=0·005) were more common in patients with higher NeoFHS.

          Interpretation

          NeoFHS is a practical and effective biomarker for predicting not only pCR and survival outcomes but also chemotherapy-induced adverse events for neoadjuvant platinum-based chemotherapy in breast cancer. It may help screen candidate responders and guide safety managements.

          Funding

          Shanghai Natural Science Foundation [grant number 19ZR1431100], Clinical Research Plan of Shanghai Hospital Development Center [grant numbers SHDC2020CR3003A, 16CR3065B, and 12016231], Shanghai “Rising Stars of Medical Talent” Youth Development Program for Youth Medical Talents - Specialist Program [grant number 2018-15], Shanghai “Rising Stars of Medical Talent” Youth Development Program for Outstanding Youth Medical Talents [grant number 2018-16], Shanghai Collaborative Innovation Center for Translational Medicine [grant number TM201908], Multidisciplinary Cross Research Foundation of Shanghai Jiao Tong University [grant numbers YG2017QN49, ZH2018QNA42, and YG2019QNA28], Nurturing Fund of Renji Hospital [grant numbers PYMDT-002, PY2018-IIC-01, PY2018-III-15, and PYIII20-09], Science and Technology Commission of Shanghai Municipality [grant numbers 20DZ2201600 and 15JC1402700], and Shanghai Municipal Key Clinical Specialty.

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          Most cited references54

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          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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            Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

            Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.
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              Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis.

              Pathological complete response has been proposed as a surrogate endpoint for prediction of long-term clinical benefit, such as disease-free survival, event-free survival (EFS), and overall survival (OS). We had four key objectives: to establish the association between pathological complete response and EFS and OS, to establish the definition of pathological complete response that correlates best with long-term outcome, to identify the breast cancer subtypes in which pathological complete response is best correlated with long-term outcome, and to assess whether an increase in frequency of pathological complete response between treatment groups predicts improved EFS and OS. We searched PubMed, Embase, and Medline for clinical trials of neoadjuvant treatment of breast cancer. To be eligible, studies had to meet three inclusion criteria: include at least 200 patients with primary breast cancer treated with preoperative chemotherapy followed by surgery; have available data for pathological complete response, EFS, and OS; and have a median follow-up of at least 3 years. We compared the three most commonly used definitions of pathological complete response--ypT0 ypN0, ypT0/is ypN0, and ypT0/is--for their association with EFS and OS in a responder analysis. We assessed the association between pathological complete response and EFS and OS in various subgroups. Finally, we did a trial-level analysis to assess whether pathological complete response could be used as a surrogate endpoint for EFS or OS. We obtained data from 12 identified international trials and 11 955 patients were included in our responder analysis. Eradication of tumour from both breast and lymph nodes (ypT0 ypN0 or ypT0/is ypN0) was better associated with improved EFS (ypT0 ypN0: hazard ratio [HR] 0·44, 95% CI 0·39-0·51; ypT0/is ypN0: 0·48, 0·43-0·54) and OS (0·36, 0·30-0·44; 0·36, 0·31-0·42) than was tumour eradication from the breast alone (ypT0/is; EFS: HR 0·60, 95% CI 0·55-0·66; OS 0·51, 0·45-0·58). We used the ypT0/is ypN0 definition for all subsequent analyses. The association between pathological complete response and long-term outcomes was strongest in patients with triple-negative breast cancer (EFS: HR 0·24, 95% CI 0·18-0·33; OS: 0·16, 0·11-0·25) and in those with HER2-positive, hormone-receptor-negative tumours who received trastuzumab (EFS: 0·15, 0·09-0·27; OS: 0·08, 0·03, 0·22). In the trial-level analysis, we recorded little association between increases in frequency of pathological complete response and EFS (R(2)=0·03, 95% CI 0·00-0·25) and OS (R(2)=0·24, 0·00-0·70). Patients who attain pathological complete response defined as ypT0 ypN0 or ypT0/is ypN0 have improved survival. The prognostic value is greatest in aggressive tumour subtypes. Our pooled analysis could not validate pathological complete response as a surrogate endpoint for improved EFS and OS. US Food and Drug Administration. Copyright © 2014 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Journal
                EClinicalMedicine
                EClinicalMedicine
                EClinicalMedicine
                Elsevier
                2589-5370
                17 July 2021
                August 2021
                17 July 2021
                : 38
                : 101031
                Affiliations
                [0001]Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, People's Republic of China
                Author notes
                [1]

                These authors contributed equally to this work.

                Article
                S2589-5370(21)00311-4 101031
                10.1016/j.eclinm.2021.101031
                8318862
                34337367
                c91cc7b7-9b62-4f32-bed9-7aeb7eef0557
                © 2021 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 28 March 2021
                : 28 June 2021
                : 30 June 2021
                Categories
                Research Paper

                breast cancer,neoadjuvant chemotherapy,pathological complete response,platinum,neo-family history score

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