Clinical Efficacy of Including Capecitabine in Neoadjuvant Chemotherapy for Breast Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

<div><h3>Background</h3><p>Capecitabine has proven effective as a chemotherapy for metastatic breast cancer. Though several Phase II/III studies of capecitabine as neoadjuvant chemotherapy have been conducted, the results still remain inconsistent. Therefore, we performed a meta-analysis to obtain more precise understanding of the role of capecitabine in neoadjuvant chemotherapy for breast cancer patients.</p> <h3>Methods</h3><p>The electronic database PubMed and online abstracts from ASCO and SABCS were searched to identify randomized clinical trials comparing neoadjuvant chemotherapy with or without capecitabine in early/operable breast cancer patients without distant metastasis. Risk ratios were used to estimate the association between capecitabine in neoadjuvant chemotherapy and various efficacy outcomes. Fixed- or random-effect models were adopted to pool data in RevMan 5.1.</p> <h3>Results</h3><p>Five studies were included in the meta-analysis. Neoadjuvant use of capecitabine with anthracycline and/or taxane based therapy was not associated with significant improvement in clinical outcomes including: pathologic complete response in breast (pCR; RR = 1.10, 95% CI 0.87–1.40, p = 0.43), pCR in breast tumor and nodes (tnpCR RR = 0.99, 95% CI 0.83–1.18, p = 0.90), overall response rate (ORR; RR = 1.00, 95% CI 0.94–1.07, p = 0.93), or breast-conserving surgery (BCS; RR = 0.98, 95% CI 0.93–1.04, p = 0.49).</p> <h3>Conclusions</h3><p>Neoadjuvant treatment of breast cancer involving capecitabine did not significantly improve pCR, tnpCR, BCS or ORR. Thus adding capecitabine to neoadjuvant chemotherapy regimes is unlikely to improve outcomes in breast cancer patients without distant metastasis. Further research is required to establish the condition that capecitabine may be useful in breast cancer neoadjuvant chemotherapy.</p> </div

Flow chart of study selection.

<p>Flow chart of study selection.</p

Forest plot to meta-analyze pCR outcomes for neoadjuvant therapy with or without capecitabine.

<p>Forest plot to meta-analyze pCR outcomes for neoadjuvant therapy with or without capecitabine.</p

Forest plot to meta-analyze tnpCR outcomes for neoadjuvant therapy with or without capecitabine.

<p>Forest plot to meta-analyze tnpCR outcomes for neoadjuvant therapy with or without capecitabine.</p

Additional file 1: of Breast cancer in postmenopausal women is associated with an altered gut metagenome

Table S1. Generated data of the four groups. Table S2. Distribution of the samples of the four groups in the two enterotypes. Table S3. Relative abundance of the different species between premenopausal breast cancer patients and premenopausal healthy controls. Table S4. Relative abundance of the different species between postmenopausal breast cancer patients and postmenopausal healthy controls. Table S5. PERMANOVA analysis was performed to assess effects of different phenotypes on gene profile. Table S6. The optimal species markers in the classification of postmenopausal breast cancer patients and postmenopausal healthy controls. Table S7. The abundance of Pathogen-Host Interactions (PHI) gene coding for diseases in postmenopausal breast cancer patients and postmenopausal healthy controls. Table S8. The virulence factor in samples of postmenopausal breast cancer patients and postmenopausal healthy controls. Table S9. Relative abundance of the different KEGG modules between premenopausal breast cancer patients and premenopausal healthy controls. Table S10. Relative abundance of the different KEGG modules between postmenopausal breast cancer patients and postmenopausal healthy controls. Table S11. Differentially enriched genes which annotated to butanoate metabolism pathways between postmenopausal breast cancer patients and postmenopausal healthy controls. Table S12. Relative abundance of the species of all the samples. Table S13. The species counts of all the samples. (XLS 2530 kb

Additional file 2: of Breast cancer in postmenopausal women is associated with an altered gut metagenome

Figure S1. Rarefaction for gut microbial gene in premenopausal breast cancer patients (n = 18), premenopausal healthy controls (n = 25), postmenopausal breast cancer patients (n = 44), and postmenopausal healthy controls (n = 46). Group 1 indicates premenopausal healthy controls, group 2 indicates premenopausal breast cancer patients, group 3 indicates postmenopausal healthy controls, and group 4 indicates postmenopausal breast cancer patients. Figure S2. The enterotypes of gut microbiota in breast cancer patients and healthy controls. (a) The optimal number of enterotypes was two of the four groups as indicated by Calinski-Harabasz (CH) index. The maximum CH index at two clusters (enterotypes) indicated the optimal enterotype number. (b) The gut microbiota of the four cohorts are clustered into two enterotypes at the genus level, dominated by either Bacteroides (enterotype 1) or Prevotella (enterotype 2). (c) Relative abundances of the top genera in the two enterotypes. (d) Distribution of the samples of the four groups in the two enterotypes. Figure S3. Relative abundance of the gut microbiota in the four groups at the phylum level. Figure S4. Relative abundance of the gut microbiota in the four groups at the genus level. Figure S5. Abundance distribution of the gut microbiota differed significantly between postmenopausal breast cancer patients and postmenopausal healthy controls at the genus level. Figure S6. Distribution of five trials of tenfold cross-validation error in random forest classification of postmenopausal breast cancer patients. The model was trained using the relative species abundances in patients and controls. The black line marks the average of the five trials (gray lines). The red line indicates the number of optimal species markers. Figure S7. Scatter plots for correlations between gut microbiota species and clinical indices. (DOCX 810 kb