The value of platinum-based adjuvant chemotherapy in patients with triple-negative breast cancer (TNBC) remains controversial, as does whether BRCA1 and BRCA2 (BRCA1/2) germline variants are associated with platinum treatment sensitivity. OBJECTIVE To compare 6 cycles of paclitaxel plus carboplatin (PCb) with a standard-dose regimen of 3 cycles of cyclophosphamide, epirubicin, and fluorouracil followed by 3 cycles of docetaxel (CEF-T). DESIGN, SETTING, AND PARTICIPANTS This phase 3 randomized clinical trial was conducted at 9 cancer centers and hospitals in China. Between July 1, 2011, and April 30, 2016, women aged 18 to 70 years with operable TNBC after definitive surgery (having pathologically confirmed regional node-positive disease or node-negative disease with tumor diameter >10 mm) were screened and enrolled. Exclusion criteria included having metastatic or locally advanced disease, having non-TNBC, or receiving preoperative anticancer therapy. Data were analyzed from December 1, 2019, to January 31, 2020, from the intent-to-treat population as prespecified in the protocol. INTERVENTIONS Participants were randomized to receive PCb (paclitaxel 80 mg/m 2 and carboplatin [area under the curve = 2] on days 1, 8, and 15 every 28 days for 6 cycles) or CEF-T (cyclophosphamide 500 mg/m 2 , epirubicin 100 mg/m 2 , and fluorouracil 500 mg/m 2 every 3 weeks for 3 cycles followed by docetaxel 100 mg/m 2 every 3 weeks for 3 cycles). MAIN OUTCOMES AND MEASURES The primary end point was disease-free survival (DFS). Secondary end points included overall survival, distant DFS, relapse-free survival, DFS in patients with germline variants in BRCA1/2 or homologous recombination repair (HRR)-related genes, and toxicity. RESULTS A total of 647 patients (mean [SD] age, 51 [44-57] years) with operable TNBC were randomized to receive CEF-T (n = 322) or PCb (n = 325). At a median follow-up of 62 months, DFS time was longer in those assigned to PCb compared with CEF-T (5-year DFS, 86.5% vs 80.3%, hazard ratio [HR] = 0.65; 95% CI, 0.44-0.96; P = .03). Similar outcomes were observed for distant DFS and relapse-free survival. There was no statistically significant difference in overall survival between the groups (HR = 0.71; 95% CI, 0.42-1.22, P = .22). In the exploratory and hypothesis-generating subgroup analyses of PCb vs CEF-T, the HR for DFS was 0.44 (95% CI, 0.15-1.31; P = .14) in patients with the BRCA1/2 variant and 0.39 (95% CI, 0.15-0.99; P = .04) in those with the HRR variant. Safety data were consistent with the known safety profiles of relevant drugs. CONCLUSIONS AND RELEVANCE These findings suggest that a paclitaxel-plus-carboplatin regimen is an effective alternative adjuvant chemotherapy choice for patients with operable TNBC. In the era of molecular classification, subsets of TNBC sensitive to PCb should be further investigated.
Tumor-associated macrophages (TAMs) appear to be the major component in solid tumor microenvironment, which were reported to play an important role in tumor malignant progression. Recently, TAMs were reported to be associated with drug resistance in some types of solid tumor including breast cancer. However, how TAMs regulate breast tumor resistance remains unknown. In this study, THP-1 cells were stimulated with PMA and IL-4/IL-13 to form M2-like macrophages to study the role of TAMs on chemoresistance. Our results showed that TAMs and its supernatants significantly prevent breast tumor cells from apoptosis caused by paclitaxel. We also found that the high level of IL-10 secreted by TAMS was responsible for drug resistance of breast cancer. The possible TAMs-modulated drug resistance mechanism involved may be associated with elevation of bcl-2 gene expression and up-regulation of STAT3 signaling in tumor cells. Furthermore, the blockage of TAMs-derived IL-10 by neutralizing antibody resulted in attenuation of STAT3 activation and decrease of bcl-2 mRNA expression, consequently enhanced sensitivity of breast cancer cells. Our data suggested that TAMs might induce drug resistance through IL-10/STAT3/bcl-2 signaling pathway, providing possible new targets for breast tumor therapy.
PURPOSE Standard adjuvant chemotherapy for triple-negative breast cancer (TNBC) includes a taxane and an anthracycline. Concomitant capecitabine may be beneficial, but robust data to support this are lacking. The efficacy and safety of the addition of capecitabine into the TNBC adjuvant treatment regimen was evaluated. PATIENTS AND METHODS This randomized, open-label, phase III trial was conducted in China. Eligible female patients with early TNBC after definitive surgery were randomly assigned (1:1) to either capecitabine (3 cycles of capecitabine and docetaxel followed by 3 cycles of capecitabine, epirubicin, and cyclophosphamide) or control treatment (3 cycles of docetaxel followed by 3 cycles of fluorouracil, epirubicin, and cyclophosphamide). Randomization was centralized without stratification. The primary end point was disease-free survival (DFS). RESULTS Between June 2012 and December 2013, 636 patients with TNBC were screened, and 585 were randomly assigned to treatment (control, 288; capecitabine, 297). Median follow-up was 67 months. The 5-year DFS rate was higher for capecitabine than for control treatment (86.3% v 80.4%; hazard ratio, 0.66; 95% CI, 0.44 to 0.99; P = .044). Five-year overall survival rates were numerically higher but not significantly improved (capecitabine, 93.3%; control, 90.7%). Overall, 39.1% of patients had capecitabine dose reductions, and 8.4% reported grade ≥ 3 hand-foot syndrome. The most common grade ≥ 3 hematologic toxicities were neutropenia (capecitabine, 136 [45.8%]; control, 118 [41.0%]) and febrile neutropenia (capecitabine, 50 [16.8%]; control, 46 [16.0%]). Safety data were similar to the known capecitabine safety profile and generally comparable between arms. CONCLUSION Capecitabine when added to 3 cycles of docetaxel followed by 3 cycles of a 3-drug anthracycline combination containing capecitabine instead of fluorouracil significantly improved DFS in TNBC without new safety concerns.
Clinical Named Entity Recognition (CNER) aims to identify and classify clinical terms such as diseases, symptoms, treatments, exams, and body parts in electronic health records, which is a fundamental and crucial task for clinical and translational research. In recent years, deep neural networks have achieved significant success in named entity recognition and many other Natural Language Processing (NLP) tasks. Most of these algorithms are trained end to end, and can automatically learn features from large scale labeled datasets. However, these data-driven methods typically lack the capability of processing rare or unseen entities. Previous statistical methods and feature engineering practice have demonstrated that human knowledge can provide valuable information for handling rare and unseen cases. In this paper, we address the problem by incorporating dictionaries into deep neural networks for the Chinese CNER task. Two different architectures that extend the Bi-directional Long Short-Term Memory (Bi-LSTM) neural network and five different feature representation schemes are proposed to handle the task. Computational results on the CCKS-2017 Task 2 benchmark dataset show that the proposed method achieves the highly competitive performance compared with the state-of-the-art deep learning methods.
BackgroundEnvironmental exposure to cadmium causes renal dysfunction and bone damage. Cadmium contamination in food is regarded as the main environmental source of non-occupational exposure. The aim of this study was to assess the contribution of dietary cadmium exposure in environmental cadmium exposure and its health risk among adults in Shanghai, China.MethodsA cross-sectional survey about food consumption was conducted in 2008 among 207 citizens aged over 40 years in Shanghai, China. The food frequency questionnaire was combined with food, tobacco and water cadmium exposure to estimate the daily environmental cadmium exposure in both point and probabilistic estimations. Urine and blood samples of the participants were analyzed for internal exposure to total cadmium. Correlation analysis was conducted between the internal cadmium exposure and environmental cadmium exposure.ResultsAccording to the point estimation, average daily environmental cadmium exposure of the participants was 16.7 μg/day and approached 33.8% of the provisional tolerable daily intake (PTDI). Dietary and tobacco cadmium exposure approached 25.8% and 7.9% of the PTDI, respectively. Males had higher levels of dietary cadmium exposure than females (p?=?0.002). The probabilistic model showed that 93.4% of the population did not have any health risks from dietary cadmium exposure. By sensitivity analysis, tobacco consumption, tobacco cadmium level, cadmium in vegetables and cadmium in rice accounted for 27.5%, 24.9%, 20.2% and 14.6% of the total cadmium exposure, respectively. The mean values of urinary and blood cadmium among the study population were 0.5 μg/L and 1.9 μg/L, respectively. Positive correlations were observed between environmental cadmium exposure and blood cadmium (R?=?0.52, P<0.01), tobacco cadmium intake and blood cadmium excluding non-smokers (R?=?0.26, P?=?0.049<0.05), and urine cadmium and age (R?=?0.15, P?=?0.037).ConclusionsIt has been suggested that there is no increased health risk among adult residents in Shanghai, China because of recent total cadmium exposure. Vegetables and rice were the main sources of dietary cadmium intake. Tobacco cadmium exposure, which accounted for approximately 25% of the total dietary cadmium exposure, was another important source of non-occupational cadmium exposure.
Entity and relation extraction is the necessary step in structuring medical text. However, the feature extraction ability of the bidirectional long short term memory network in the existing model does not achieve the best effect. At the same time, the language model has achieved excellent results in more and more natural language processing tasks. In this paper, we present a focused attention model for the joint entity and relation extraction task. Our model integrates well-known BERT language model into joint learning through dynamic range attention mechanism, thus improving the feature representation ability of shared parameter layer. Experimental results on coronary angiography texts collected from Shuguang Hospital show that the F1-scores of named entity recognition and relation classification tasks reach 96.89% and 88.51%, which outperform state-of-the-art methods by 1.65% and 1.22%, respectively.
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