Journal Logo

Research Article: Systematic Review and Meta-Analysis

Effect of antitumor treatments on triple-negative breast cancer patients

A PRISMA-compliant network meta-analysis of randomized controlled trials

Tian, Qiuhong MMa; Du, Peng MMb; Li, Sen MMb; Bai, Zhenzhu MMa; Yang, Yong MMa; Zeng, Jinsheng MMb,*

Section Editor(s): Lee., Won Sup

Author Information
doi: 10.1097/MD.0000000000008389


1 Introduction

Breast cancer is one of the most common malignant tumors in women. The World Health Organization International Cancer Research Center data from 2012 showed that there are approximately 1.2 million patients with breast cancer every year worldwide, including 540,000 new cases, and 500,000 patients die annually.[1] Currently, breast cancer treatment includes surgery, radiotherapy, chemotherapy, endocrine therapy, and targeted therapy. Breast cancer is a type of immunogenic tumor that may express a variety of tumor-associated antigens. Targeted therapy and endocrine therapy are effective treatments, particularly for hormone receptor-positive patients.

Triple-negative breast cancer (TNBC) refers to breast cancer that does not express the genes for the estrogen receptor, progesterone receptor, or receptor tyrosine-protein kinase erbB-2 (HER2/neu). TNBC accounts for approximately 10% to 20% of breast cancer patients.[2,3] The manifestation of TNBC is aggressive; it recurs and metastasizes readily and carries a worse prognosis than other types of breast cancer. Owing to the negative expression of the estrogen and progesterone receptors, hormone-related endocrine and targeted therapies are essentially futile. Furthermore, the differing therapeutic effects of neoadjuvant chemotherapy between TNBC and non-TNBC in a previous study showed that TNBC patients had a higher pathological complete response (pCR) rate but a lower survival rate.[4] Therefore, TNBC remains one of the most debated subtypes of breast cancer. Treatment guidelines for TNBC are rare, and the therapeutic strategy is also controversial.

Several meta-analyses have examined the treatment of TNBC. When associated with conventional chemotherapy, targeted therapy including Bevacizumab, Sorafenib, and Iniparib promoted gains in the progression-free survival (PFS) of TNBC patients.[5] One study indicated that these novel neoadjuvant regimens achieved significant pCR improvement in TNBC patients, particularly a Carboplatin-containing or Bevacizumab-containing regimen.[6] Platinum-based chemotherapy has been thoroughly researched and was shown to be more advantageous in TNBC patients than in non-TNBC patients.[7] Platinum-based chemotherapy yielded a higher pCR than did nonplatinum-based therapy in TNBC patients.[8,9]

All the aforementioned studies focused on the one type of chemotherapeutic drug combination that was analyzed for a TNBC treatment effect and disregarded the effect of other anti-tumor drug combinations. For example, studies of platinum-containing regimens versus nonplatinum-containing regimens disregarded the effects of other chemotherapeutic drug combinations as therapeutic regimens for TNBC treatment.[7] Therefore, the treatment strategy for TNBC requires further elucidation. In this study, a comprehensive analysis of antitumor regimens for TNBC patients was performed to guide clinical treatment.

2 Methods

This meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. Because our study was performed on the basis of previous studies, the ethical approval and informed consent were not required.

2.1 Data search strategy and selection criteria

A literature search was independently performed by 2 investigators using electronic databases including PubMed, Embase, and the Cochrane Library to identify articles published before January 2017, using the following search keywords :“triple negative breast cancer,” “TNBC,” and “random.*” The bibliographies of the obtained publications and the references of pertinent reviews were assessed to ensure that no relevant studies were unintentionally omitted. Studies were included in this meta-analysis when the following criteria were met: the study used a prospective randomized controlled trial (RCT) design; the study included TNBC patients; the study researched antitumor agents, including chemotherapy, endocrine therapy, and targeted therapy; the study clearly described the types of drugs used before and after patient randomization but not the investigators’ choice of drugs; the study groups used different types of antitumor agents; and one of the following outcomes was reported: overall response rate (ORR), PFS, and overall survival (OS). The exclusion criteria included the following: the study researched controversial antitumor drugs for suppressing tumor growth, such as ubenimex, dendritic cells, AE37 polypeptide, and zoledronic acid; the study researched different applied strategies using the same types of agents; the study included radiotherapy or radiotherapy-related trials; and the study assessed undesired outcomes. Reviews, conference abstracts, case reports, and basic research studies were also excluded.

2.2 Data extraction and quality assessment

Two investigators independently extracted the following information from each eligible study: name of the first author, publication year, register ID, sample size, patient age, clinical stage, intervention treatment, control treatment, ratio of allocation, and follow-up. We assessed the methodological quality of the included trials using the Cochrane Collaboration tool. Studies were graded as having a “low risk,” “high risk,” or “unclear risk” of bias across the 7 specified domains.[10]

We analyzed all the intervention-related antitumor agents applied before and after randomization, including combined agents that might affect patient outcomes. The 3 main outcomes were ORR, PFS, and OS. The major indicator of ORR was an objective response rate for patients with metastasis and a pCR for patients without metastasis (nonmetastatic patients). The objective response rate followed the Response Evaluation Criteria In Solid Tumors (RECIST) standard, which includes a complete response and partial response. A pCR was defined as the absence of invasive tumor in the final surgical breast tissue sample (stage yT0/ypTis) as recorded by the primary pathologist, irrespective of the nodal status (ypN0), according to the included study. Additionally, because of the different follow-up periods, we mainly analyzed the 5-year or median PFS or OS as reference indicators.

2.3 Statistical analysis

We performed a traditional paired meta-analysis using a random-effects model. All the outcome measures were dichotomous, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to determine the effect sizes. ORs are suitable for all designs with control groups with superior mathematical properties for complex statistical analysis. We also performed subgroup analyses according to the patients’ pathological stage. For research on treatment strategies, we used a random-effects network meta-analysis for mixed multiple antitumor treatment comparisons, which adopted a frequentist framework, and a contrast-based model to evaluate multiarm trials.[11] The random-effects model fully preserves the within-trial randomized treatment comparison of each trial. The random-effects model allows the existence of other sources of variation in addition to sampling errors with greater robustness. Inconsistency between direct and indirect sources of evidence was assessed globally by comparison of the fit and parsimony of consistency and inconsistency models and locally by calculation of the difference between direct and indirect estimates in all closed loops in the network. To rank the treatment strategy for each outcome, we used the Surface Under the Cumulative Ranking (SUCRA) probabilities. Comparison-adjust funnel plots were used to determine whether small-study effects were present in our analysis. For the antitumor drug research, we attempted to use the multilevel mixed-effects logistic regression model for each antitumor drug [11]; the components of different therapeutic strategies were evaluated as fixed-effects, whereas different studies were considered using random-effects. We performed the analysis in STATA (version 14.0) with the “metan” and “melogit” commands and the “network” command set.

3 Results

3.1 Literature search

In our study, 605 articles were identified after the duplicates were removed. A total of 514 articles were excluded after the titles and abstracts were screened. The full texts of the remaining 91 articles were assessed, and the following types of studies were removed: studies with a nonprospective RCT design (11), studies that did not analyze TNBC patients separately (10), studies that did not report the analyzed outcomes (10), studies in which the types of drugs used were unclear (10), duplicates (5), studies that did not investigate anti-tumor agents (4), studies in which the groups used the same type of drug with different strategies (3), radiotherapy-related studies (2), and basic research (1) (Fig. 1). Ultimately, 35 articles assessing a total of 8476 TNBC patients were included in our systematic review[12–46] (Table 1).

Figure 1
Figure 1:
PRISMA flowchart illustrating the selection of studies included in the present analysis. The illustration shows the number of documents obtained from the database, the simple screening process, and the final number of studies included in the analysis.
Table 1
Table 1:
Characteristics of subjects in eligible studies.

The included studies were published between the years 2010 and 2016. Few studies were published before 2010 because of a lack of understanding of TNBC. Several studies did not assess TNBC patients independently; they evaluated a subgroup of breast cancer patients and reported the outcome of individual TNBC patients. None of the included studies restricted the age of the studied populations; however, all patients were older than 18 years. The included studies confirmed the type of disease using pathological examinations. The clinical stage of the patients was grouped into 2 types: metastasis and nonmetastasis. The follow-up period was conducted immediately at the end of the studies and lasted for up to 15 years depending on the purpose of the study. Sixteen trials used a neoadjuvant approach for the nonmetastasis group, and the median follow-up in the neoadjuvant trials was approximately 1 month.

The antitumor agents analyzed in the meta-analysis, in alphabetical order, included Bevacizumab, Capecitabine, Carboplatin, Cetuximab, Cisplatinum, Cyclophosphamide, Docetaxel, Doxorubicin, EndoTAG-1, Epirubicin, Eribulin, Everolimus, 5-Fluorouracil, Gefitinib, Gemcitabine, Iniparib, Ixabepilone, Methotrexate, Onartuzumab, Paclitaxel, Ramucirumab, Tamoxifen, Tigatuzumab, Veliparib, Vinorelbine, and YH16. To decrease disputes, controversial antitumor drugs for clearing or suppressing tumor growth, such as ubenimex, dendritic cells, AE37 polypeptide, and zoledronic acid, were not analyzed. However, some of those drugs may be confirmed to have antitumor effects in the future. All included studies had a prospective RCT design, few studies used a blind method, and most randomizations were not rigorous (Figure S1, Supplemental digital content 1, However, the assessed outcomes were relatively objective; thus, the overall quality of the included studies was not ideal but was acceptable.

The traditional meta-analysis compared the anti-tumor regimens of each direct comparison in the included studies with ORR outcomes without pooling (Fig. 2). In the patients without metastasis, Paclitaxel combined with Carboplatin had a greater effect than Epirubicin (OR, 3.88; 95% CI, 1.35–11.15; P = .012). The regimen that included Paclitaxel, Doxorubicin, and Cyclophosphamide was more effective when combined with Bevacizumab (OR, 3.65; 95% CI, 1.32–10.11; P = .013). The regimen of Paclitaxel, Bevacizumab, and Carboplatin was superior to that of Paclitaxel alone (OR, 0.48; 95% CI, 0.28–0.82; P = .008) and superior to the combination of Paclitaxel and Bevacizumab (OR, 0.58; 95% CI, 0.34–0.99; P = .047). The regimen of Paclitaxel, Doxorubicin, and Bevacizumab was superior when combined with Carboplatin (OR, 1.94; 95% CI, 1.24–3.04; P = .004). The regimen of Paclitaxel, Cyclophosphamide, Epirubicin, and 5-Fluorouracil was also superior when combined with Carboplatin (OR, 4.60; 95% CI, 1.72–12.27; P = .002). The combination of Epirubicin, Cyclophosphamide, Docetaxel, and Bevacizumab was superior to that without Bevacizumab (OR, 1.67; 95% CI, 1.21–2.31; P = .002). However, the regimen including Docetaxel, Doxorubicin, and Cyclophosphamide was inferior when combined with Vinorelbine and Capecitabine (OR, 0.36; 95% CI, 0.23–0.56; P < .001). Notably, we only analyzed individuals who did not respond to initial treatment with Docetaxel, Doxorubicin, and Cyclophosphamide. The responders did not undergo changes to their treatment strategy after randomization.[45] Simultaneously, the ORR results displayed several significant differences between regimens in the patients with metastasis (Figure 2) regarding PFS (Figure S2, Supplemental digital content 1, and OS (Figure S3, Supplemental digital content 1, outcomes. However, the included regimens were too complex and scattered to pool, and pairwise comparisons were not possible because of the lack of robustness and reliability.

Figure 2
Figure 2:
Traditional meta-analysis of overall response rate (ORR) among regimens. The forest plot shows a traditional meta-analysis for ORR results. The results were not pooled because of the various types of intervention and control regimens.

For the network meta-analysis of ORR outcomes, we analyzed 12 antitumor regimens (Fig. 3A). Other regimens were not included because we could not directly compare the included regimens. No significant differences were observed among regimens in the network pairwise comparisons (Table S1, The results of the inconsistency analysis showed no local or global inconsistency. In terms of SUCRA rank, Bevacizumab, Carboplatin, and Paclitaxel (78.2%) were the most likely to improve the ORR in TNBC patients, followed by EndoTAG-1 and Paclitaxel (69.7%), Carboplatin and Paclitaxel (65.0%), and Bevacizumab and Paclitaxel (61.8%). Six regimens were analyzed in the patients without metastasis (Figure 3B). No significant differences were found in the network pairwise comparisons (Table S2, In terms of SUCRA rank, the combination of Bevacizumab, Carboplatin, and Paclitaxel (74.9%) remained the most likely to improve the ORR, followed by Carboplatin and Paclitaxel (59.6%), Bevacizumab and Paclitaxel (50.7%), and Iniparib and Paclitaxel (42.7%). The comparison-adjusted funnel plot used to assess publication bias and to determine the presence of small-study effects did not suggest any publication bias. Despite the results of the metastasis and outcomes of PFS and OS, we were unable to draw comprehensive and accurate conclusions because <4 regimens formed the network.

Figure 3
Figure 3:
Network of comparisons for overall response rate included in the analyses. (A) All TNBC patients; (B) TNBC patients without metastasis. In the network plot, the connection of two interventions indicates a direct comparison. The nodes are weighted according to the number of studies and the edges according to the precision of the direct estimate for each pairwise comparison. B1 = Bevacizumab, C1 = Capecitabine, C2 = Carboplatin, E1 = EndoTAG-1, E2 = Epirubicin, I1 = Iniparib, O = Onartuzumab, P = Paclitaxel, T2 = Tigatuzumab, TNBC = triple-negative breast cancer.

For the multilevel mixed-effects logistic regression analysis, the analysis of ORR outcomes showed that Cisplatinum (OR, 5.41; 95% CI, 3.11–9.42; P < .001), Paclitaxel (OR, 4.44; 95% CI, 2.83–6.97; P < .001), Ixabepilone (OR, 4.32; 95% CI, 2.21–8.44; P < .001), Docetaxel (OR, 2.53; 95% CI, 1.47–4.37; P = .001), Gemcitabine (OR, 2.47; 95% CI, 1.34–4.53; P = .004), EndoTAG-1 (OR, 2.36; 95% CI, 1.13–4.93; P = .022), Carboplatin (OR, 2.07; 95% CI, 1.62–2.64; P < .001), and Bevacizumab (OR, 1.71; 95% CI, 1.43–2.05; P < .001) yielded a higher ORR for TNBC patients (Fig. 4). Vinorelbine (OR, 0.24; 95% CI, 0.12–0.46; P < .001) reduced patients’ ORR (Fig. 4). Additionally, we analyzed patients with and without metastasis separately. Patients without metastasis who received Paclitaxel (OR, 5.48; 95% CI, 1.96–15.33; P = .001), Ixabepilone (OR, 4.8; 95% CI, 1.48–15.51; P = .009), Capecitabine (OR, 2.22; 95% CI, 1.11–4.44; P = .024), Carboplatin (OR, 1.93; 95% CI, 1.49–2.51; P < .001), and Bevacizumab (OR, 1.63; 95% CI, 1.36–1.96; P < .001) had a significantly higher ORR. Vinorelbine (OR, 0.15; 95% CI, 0.07–0.34; P < .001) reduced the ORR. For patients with metastasis, the application of Ixabepilone (OR, 4.82; 95% CI, 1.99–11.72; P = .001), Docetaxel (OR, 4.56; 95% CI, 2.19–9.57; P < .001), Gemcitabine (OR, 3.89; 95% CI, 2.49–6.07; P < .001), Bevacizumab (OR, 3.4; 95% CI, 2.08–5.53; P < .001), Paclitaxel (OR, 2.98; 95% CI, 1.44–6.16; P = .003), EndoTAG-1 (OR, 2.9; 95% CI, 1.5–5.61; P = .002), and Cisplatinum (OR, 2.87; 95% CI, 1.33–6.2; P = .007) yielded a significantly higher ORR.

Figure 4
Figure 4:
Forest plot of antitumor agents for overall response rate (ORR) by multilevel mixed-effects logistic regression. The components of different therapeutic strategies were analyzed to assess the relationship to the ORR of patients by logistic regression.

Regarding PFS outcomes, the application of Carboplatin (OR, 4.85; 95% CI, 1.94–12.11; P = .001), Epirubicin (OR, 3.1; 95% CI, 1.56–6.14; P = .001), or Cisplatinum (OR, 2.84; 95% CI, 1.09–7.39; P = .033) significantly increased the number of patients who experienced PFS during follow-up (Fig. 5). Although Gemcitabine (OR, 0.04; 95% CI, 0.01–0.22; P < .001) reduced PFS, it had a large standard error (Fig. 5). In patients without metastasis, Doxorubicin (OR, 8.99; 95% CI, 2.34–34.59; P = .001), Carboplatin (OR, 4.3; 95% CI, 1.5–12.28; P = .007), and Methotrexate (OR, 4.0; 95% CI, 2.2–7.29; P < .001) significantly increased the PFS rate during follow-up. However, Doxorubicin (OR, 8.99; 95% CI, 2.34–34.59; P = .001), Carboplatin (OR, 4.3; 95% CI, 1.5–12.28; P = .007), and Methotrexate (OR, 4.0; 95% CI, 2.2–7.29; P < .001) had opposite effects. For metastatic TNBC patients, Cisplatinum (OR, 4.03; 95% CI, 1.49–10.88; P = .006), Eribulin (OR, 3.6; 95% CI, 1.01–12.79; P = .047), and Paclitaxel (OR, 2.72; 95% CI, 1.28–5.76; P = .009) significantly increased the PFS rate, and Gemcitabine (OR, 0.11; 95% CI, 0.02–0.57; P = .008) decreased the PFS rate. However, the aforementioned results exhibited large standard errors.

Figure 5
Figure 5:
Forest plot of antitumor agents for progression-free survival (PFS) by multilevel mixed-effects logistic regression. The components of different therapeutic strategies were analyzed to assess the relationship to the PFS of patients by logistic regression.

For OS outcomes in metastatic and non-metastatic TNBC patients, the applications of Epirubicin (OR, 2.42; 95% CI, 1.14–5.11; P = .021), Cyclophosphamide (OR, 1.93; 95% CI, 1.12–3.32; P = .018), and Iniparib (OR, 1.51; 95% CI, 1.11–2.07; P = .009) significantly increased the TNBC patients’ OS during follow-up (Fig. 6). In patients without metastasis, Carboplatin (OR, 10.48; 95% CI, 2.53–43.48; P = .001), Epirubicin (OR, 5.1; 95% CI, 1.95–13.3; P = .001), and Cyclophosphamide (OR, 1.81; 95% CI, 1.03–3.17; P = .037) significantly increased the OS. In patients with metastasis, only Iniparib (OR, 1.53; 95% CI, 1.12–2.09; P = .008) significantly increased the OS. However, to eliminate collateral influence and minimize the false-positive rate, we calculated the tested level of significance as approximately 0.0023 for each individual drug in accord with the 0.05 general level of significance. Thus, we recommend P = .002 as a reference for significant differences in the multilevel mixed-effects logistic regression.

Figure 6
Figure 6:
Forest plot of anti-tumor agents for overall survival (OS) by multilevel mixed-effects logistic regression. The components of different therapeutic strategies were analyzed to assess the relationship to the OS of patients by logistic regression.

4 Discussion

In the present study, we comprehensively analyzed antitumor treatments for TNBC patients. The assessment index included ORR, PFS, and OS. We considered all antitumor agents applied before and after randomization. A network meta-analysis and multilevel mixed-effects logistic regression were used to analyze the regimens and agents, respectively. In the network analysis, the regimen of Bevacizumab, Carboplatin, and Paclitaxel was the most likely to improve the ORR in TNBC patients and in metastatic TNBC patients. Other antitumor agents could not be analyzed by less direct comparisons. The multilevel logistic regression analysis showed that the application of Cisplatinum, Paclitaxel, Ixabepilone, Docetaxel, Carboplatin, and Bevacizumab had advantages in improving patients’ ORRs. Carboplatin and Epirubicin were beneficial for patients’ PFS. Additionally, we found unexpected results for Paclitaxel, Cyclophosphamide, and Docetaxel in PFS outcomes, which did not significantly reduce patients’ PFS. In regimens without Paclitaxel, the application of the more effective agent Epirubicin might bias the results. In regimens without Cyclophosphamide, the application of Epirubicin and Carboplatin might also bias the results.

Several drugs are involved in the chemotherapy strategy used to treat neoplasms. The research protocols for a meta-analysis analyzing this type of treatment included a comparison of combinations of drugs and different types of chemotherapy. These analyses might have ignored the effects from other accompanying treatments and the different strategies in the control group, such as previous analyses of platinum-based chemotherapy versus nonplatinum-based therapy.[6] With several widely researched strategies, a network meta-analysis could be used for direct and indirect comparisons. However, when strategies are controversial and scattered, a network meta-analysis has low feasibility because of the less direct comparisons among strategies. For example, in our network analysis, many chemotherapy regimens did not connect in the network.

To ensure that all the agents used in the chemotherapy period were included in the analysis, our research first collected all antitumor agents before and after randomization. A multilevel mixed-effects logistic regression was used to analyze the therapeutic effect of each antitumor drug. However, this method had limitations in that it did not consider the combined effect among drugs. For example, if an ineffective drug is combined with an effective drug, the results will show a positive effect associated with that ineffective drug. In that case, this method had relatively higher false positive rates and low accuracy. Similar to other meta-analyses, the small sample size might have produced a larger standard error and reduced the accuracy of the analysis. Additionally, because all the antitumor agents were considered, the probability of a type I error (false-positive error) was increased.

Furthermore, a difference between ORR and PFS persisted in our results. Although the difference might have been caused by sampling error, we also cannot exclude possible inference because of the lack of a necessary connection between the patients’ ORR and OS. Thus, the large standard error in PFS and OS results may also have reduced robustness and induced the difference between ORR and PFS. Therefore, increased sample sizes are necessary to further confirm the effects of antitumor agents.

Design bias and publication bias also affected the results. In most studies, ORR was used as a primary outcome, with PFS and OS as secondary outcomes. Positive ORR results are more easily accepted by institutions or journals, whereas negative results are not. However, negative results for PFS and OS have a greater chance of publication. Notably, only 1 article used PFS as a primary outcome with neoadjuvant treatment. The PFS results reported for the comparison were not significant (P = .17).[41] Other neoadjuvant trials only reported the pCR results. Thus, the conclusion regarding PFS and OS was mainly based on nonneoadjuvant trials. Design bias may be present because most of the included studies did not adopt a blinded approach. Therefore, subjective factors may have affected the results. Thus, we concluded that the reliability of the pCR outcome was inferior to that of PFS and OS. Further studies are necessary in the future, particularly studies on the results of PFS and OS. The details of all patients who withdrew were described in each of the included studies. The main reasons for loss to follow-up were disease progression and adverse events, whereas others included death, other disease onset, and patient/physician decisions. Among the major reasons, the number of patients who withdrew because of disease progression was included in the PFS outcomes. The adverse event-related outcomes were described in each of the included studies in detail but were outside the scope of our study. Notably, however, the withdrawal of patients due to adverse events may have led to bias in the results of this study.

The results of our study were based on RCT studies. However, the National Comprehensive Cancer Network (NCCN) guideline was based not only on RCTs but also on retrospective and case–control studies with more comprehensive conclusions. Therefore, our study may only serve as a supplement to the NCCN guideline. The recommended regimen for HER-2 negative breast cancer including Doxorubicin, Cyclophosphamide, and Paclitaxel was not included in the network meta-analysis. In traditional meta-analysis, the aforementioned regimen was inferior to that same regimen plus Bevacizumab.[46] Therefore, we considered that the recommended regimen might be combined with Bevacizumab to increase the therapeutic effect. However, the results are derived from single studies and remain lacking in robustness.

The network meta-analysis lacked critical comparisons to analyze all the included regimens. In the 12 included regimens, Paclitaxel-containing regimens, particularly the combined Paclitaxel, Bevacizumab, and Carboplatin regimen, showed superior ORR improvement. Thus, it may be used clinically when acceptable. Additional critical comparison RCTs, such as Paclitaxel- and Paclitaxel plus Bevacizumab-related comparisons were needed to conduct a more comprehensive network meta-analysis. For single chemotherapeutic drug application, no new evidence emerged to supplement the NCCN guideline.

5 Limitations

Our study had several limitations. First, the present analysis was performed at the study level, not at an individual level. Second, tumor heterogeneity among the TNBC patients affected the outcomes. Thus, the formulation of individualized treatments according to the characteristics of each tumor is crucial. Third, a network meta-analysis cannot include all related regimens. Fourth, factors such as the agents’ dosages and the duration of application were not considered in our research.

In conclusion, a regimen including Bevacizumab, Carboplatin, and Paclitaxel was the most likely to improve the ORR in TNBC patients and in advanced metastatic TNBC patients. The application of Bevacizumab and Carboplatin provided greater benefit for improving patients’ ORR.


[1]. Torre LA, Bray F, Siegel RL, et al. Global cancer statistics, 2012. CA Cancer J Clin 2015;65:87–108.
[2]. Foulkes WD, Smith IE, Reis-Filho JS. Triple-negative breast cancer. N Engl J Med 2010;363:1938–48.
[3]. Duffy MJ, McGowan PM, Crown J. Targeted therapy for triple-negative breast cancer: where are we? Int J Cancer 2012;131:2471–7.
[4]. Tian M, Zhong Y, Zhou F, et al. Effect of neoadjuvant chemotherapy in patients with triple-negative breast cancer: A meta-analysis. Oncol Lett 2015;9:2825–32.
[5]. Clark O, Botrel TE, Paladini L, et al. Targeted therapy in triple-negative metastatic breast cancer: a systematic review and meta-analysis. Core Evid 2014;9:1.
[6]. Chen XS, Yuan Y, Garfield DH, et al. Both carboplatin and bevacizumab improve pathological complete remission rate in neoadjuvant treatment of triple negative breast cancer: a meta-analysis. PLoS One 2014;9:e108405.
[7]. Liu M, Mo QG, Wei CY, et al. Platinum-based chemotherapy in triple-negative breast cancer: A meta-analysis. Oncol Lett 2013;5:983–91.
[8]. Petrelli F, Coinu A, Borgonovo K, et al. The value of platinum agents as neoadjuvant chemotherapy in triple-negative breast cancers: a systematic review and meta-analysis. Breast Cancer Res Treat 2014;144:223–32.
[9]. Guan X, Ma F, Fan Y, et al. Platinum-based chemotherapy in triple-negative breast cancer: a systematic review and meta-analysis of randomized-controlled trials. Anticancer Drugs 2015;26:894–901.
[10]. Higgins JP, Altman DG, Gotzsche PC, et al. The Cochrane Collaboration's tool for assessing risk of bias in randomised trials. BMJ 2011;343:d5928.
[11]. Vermunt JK. Mixed-Effects Logistic Regression Models for Indirectly Observed Discrete Outcome Variables. Multivariate Behav Res 2005;40:281–301.
[12]. Yue Z, Jin-Feng LI, Chu GW. Neoadjuvant chemotherapy regimens for patients with triple-negative breast cancer:TE versus TC. J Rheumatol 2014;29:576–9.
[13]. Ying LU, Huang H. Clinical Study of the Combination of Endostar and GP Regimen in the Treatment of Metastatic TNBC[J]. Chin J Clin Oncol 2012;39:1946–8.
[14]. Yardley DA, Reeves J, Dees EC, et al. Ramucirumab with eribulin versus eribulin in locally recurrent or metastatic breast cancer previously treated with anthracycline and taxane therapy: a multicenter, randomized, phase II study. Clin Breast Cancer 2016;16:471-9 e1.
[15]. Zhang P, Yin Y, Mo H, et al. Better pathologic complete response and relapse-free survival after carboplatin plus paclitaxel compared with epirubicin plus paclitaxel as neoadjuvant chemotherapy for locally advanced triple-negative breast cancer: a randomized phase 2 trial. Oncotarget 2016;7:60647–56.
[16]. Twelves C, Awada A, Cortes J, et al. Subgroup analyses from a phase 3, open-label, randomized study of eribulin mesylate versus capecitabine in pretreated patients with advanced or metastatic breast cancer. Breast Cancer (Auckl) 2016;10:77–84.
[17]. Nahleh ZA, Barlow WE, Hayes DF, et al. SWOG S0800 (NCI CDR0000636131): addition of bevacizumab to neoadjuvant nab-paclitaxel with dose-dense doxorubicin and cyclophosphamide improves pathologic complete response (pCR) rates in inflammatory or locally advanced breast cancer. Breast Cancer Res Treat 2016;158:485–95.
[18]. Kummar S, Wade JL, Oza AM, et al. Randomized phase II trial of cyclophosphamide and the oral poly (ADP-ribose) polymerase inhibitor veliparib in patients with recurrent, advanced triple-negative breast cancer. Invest New Drugs 2016;34:355–63.
[19]. Hilborn E, Gacic J, Fornander T, et al. Androgen receptor expression predicts beneficial tamoxifen response in oestrogen receptor-alpha-negative breast cancer. Br J Cancer 2016;114:248–55.
[20]. Llombart-Cussac A, Bermejo B, Villanueva C, et al. SOLTI NeoPARP: a phase II randomized study of two schedules of iniparib plus paclitaxel versus paclitaxel alone as neoadjuvant therapy in patients with triple-negative breast cancer. Breast Cancer Res Treat 2015;154:351–7.
[21]. Dieras V, Campone M, Yardley DA, et al. Randomized, phase II, placebo-controlled trial of onartuzumab and/or bevacizumab in combination with weekly paclitaxel in patients with metastatic triple-negative breast cancer. Ann Oncol 2015;26:1904–10.
[22]. Sparano JA, Zhao F, Martino S, et al. Long-term follow-up of the E1199 phase III trial evaluating the role of taxane and schedule in operable breast cancer. J Clin Oncol 2015;33:2353–60.
[23]. Hu XC, Zhang J, Xu BH, et al. Cisplatin plus gemcitabine versus paclitaxel plus gemcitabine as first-line therapy for metastatic triple-negative breast cancer (CBCSG006): a randomised, open-label, multicentre, phase 3 trial. Lancet Oncol 2015;16:436–46.
[24]. Forero-Torres A, Varley KE, Abramson VG, et al. TBCRC 019: a phase II trial of nanoparticle albumin-bound paclitaxel with or without the anti-death receptor 5 monoclonal antibody tigatuzumab in patients with triple-negative breast cancer. Clin Cancer Res 2015;21:2722–9.
[25]. O'Shaughnessy J, Schwartzberg L, Danso MA, et al. Phase III study of iniparib plus gemcitabine and carboplatin versus gemcitabine and carboplatin in patients with metastatic triple-negative breast cancer. J Clin Oncol 2014;32:3840–7.
[26]. Brodowicz T, Lang I, Kahan Z, et al. Selecting first-line bevacizumab-containing therapy for advanced breast cancer: TURANDOT risk factor analyses. Br J Cancer 2014;111:2051–7.
[27]. Tredan O, Campone M, Jassem J, et al. Ixabepilone alone or with cetuximab as first-line treatment for advanced/metastatic triple-negative breast cancer. Clin Breast Cancer 2015;15:8–15.
[28]. Sikov WM, Berry DA, Perou CM, et al. Impact of the addition of carboplatin and/or bevacizumab to neoadjuvant once-per-week paclitaxel followed by dose-dense doxorubicin and cyclophosphamide on pathologic complete response rates in stage II to III triple-negative breast cancer: CALGB 40603 (Alliance). J Clin Oncol 2015;33:13–21.
[29]. von Minckwitz G, Schneeweiss A, Loibl S, et al. Neoadjuvant carboplatin in patients with triple-negative and HER2-positive early breast cancer (GeparSixto; GBG 66): a randomised phase 2 trial. Lancet Oncol 2014;15:747–56.
[30]. Ando M, Yamauchi H, Aogi K, et al. Randomized phase II study of weekly paclitaxel with and without carboplatin followed by cyclophosphamide/epirubicin/5-fluorouracil as neoadjuvant chemotherapy for stage II/IIIA breast cancer without HER2 overexpression. Breast Cancer Res Treat 2014;145:401–9.
[31]. Gonzalez-Angulo AM, Akcakanat A, Liu S, et al. Open-label randomized clinical trial of standard neoadjuvant chemotherapy with paclitaxel followed by FEC versus the combination of paclitaxel and everolimus followed by FEC in women with triple receptor-negative breast cancerdagger. Ann Oncol 2014;25:1122–7.
[32]. Awada A, Bondarenko IN, Bonneterre J, et al. A randomized controlled phase II trial of a novel composition of paclitaxel embedded into neutral and cationic lipids targeting tumor endothelial cells in advanced triple-negative breast cancer (TNBC). Ann Oncol 2014;25:824–31.
[33]. Rocca A, Bravaccini S, Scarpi E, et al. Benefit from anthracyclines in relation to biological profiles in early breast cancer. Breast Cancer Res Treat 2014;144:307–18.
[34]. Steger GG, Greil R, Lang A, et al. Epirubicin and docetaxel with or without capecitabine as neoadjuvant treatment for early breast cancer: final results of a randomized phase III study (ABCSG-24). Ann Oncol 2014;25:366–71.
[35]. Gerber B, Loibl S, Eidtmann H, et al. Neoadjuvant bevacizumab and anthracycline-taxane-based chemotherapy in 678 triple-negative primary breast cancers; results from the geparquinto study (GBG 44). Ann Oncol 2013;24:2978–84.
[36]. Saura C, Tseng LM, Chan S, et al. Neoadjuvant doxorubicin/cyclophosphamide followed by ixabepilone or paclitaxel in early stage breast cancer and evaluation of betaIII-tubulin expression as a predictive marker. Oncologist 2013;18:787–94.
[37]. Baselga J, Gomez P, Greil R, et al. Randomized phase II study of the anti-epidermal growth factor receptor monoclonal antibody cetuximab with cisplatin versus cisplatin alone in patients with metastatic triple-negative breast cancer. J Clin Oncol 2013;31:2586–92.
[38]. Fan Y, Xu BH, Yuan P, et al. Docetaxel-cisplatin might be superior to docetaxel-capecitabine in the first-line treatment of metastatic triple-negative breast cancer. Ann Oncol 2013;24:1219–25.
[39]. Carey LA, Rugo HS, Marcom PK, et al. TBCRC 001: randomized randomized phase II study of cetuximab in combination with carboplatin in stage IV triple-negative breast cancer. J Clin Oncol 2012;30:2615–23.
[40]. von Minckwitz G, Eidtmann H, Rezai M, et al. Neoadjuvant chemotherapy and bevacizumab for HER2-negative breast cancer. N Engl J Med 2012;366:299–309.
[41]. Bonnefoi H, Piccart M, Bogaerts J, et al. TP53 status for prediction of sensitivity to taxane versus non-taxane neoadjuvant chemotherapy in breast cancer (EORTC 10994/BIG 1-00): a randomised phase 3 trial. Lancet Oncol 2011;12:527–39.
[42]. Martin M, Romero A, Cheang MC, et al. Genomic predictors of response to doxorubicin versus docetaxel in primary breast cancer. Breast Cancer Res Treat 2011;128:127–36.
[43]. Bernsdorf M, Ingvar C, Jorgensen L, et al. Effect of adding gefitinib to neoadjuvant chemotherapy in estrogen receptor negative early breast cancer in a randomized phase II trial. Breast Cancer Res Treat 2011;126:463–70.
[44]. O'Shaughnessy J, Osborne C, Pippen JE, et al. Iniparib plus chemotherapy in metastatic triple-negative breast cancer. N Engl J Med 2011;364:205–14.
[45]. Huober J, von Minckwitz G, Denkert C, et al. Effect of neoadjuvant anthracycline-taxane-based chemotherapy in different biological breast cancer phenotypes: overall results from the GeparTrio study. Breast Cancer Res Treat 2010;124:133–40.
[46]. Colleoni M, Cole BF, Viale G, et al. Classical cyclophosphamide, methotrexate, and fluorouracil chemotherapy is more effective in triple-negative, node-negative breast cancer: results from two randomized trials of adjuvant chemoendocrine therapy for node-negative breast cancer. J Clin Oncol 2010;28:2966–73.

chemotherapy; endocrine therapy; meta-analysis; targeted therapy; triple-negative breast cancer

Supplemental Digital Content

Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.