A retrospective safety and efficacy analysis of the first patients treated with eribulin for metastatic breast cancer in Stockholm, Sweden

<div><p></p><p><b>Backgrounds.</b> Eribulin is a non-taxane, microtubule dynamics inhibitor approved for the treatment of patients with metastatic breast cancer (MBC) in Europe in March 2011.</p><p><b>Material and methods.</b> For the purpose of an internal quality control, all patients with MBC treated with eribulin at Karolinska University Hospital were registered in a database. Clinical data were collected retrospectively for patients that were registered by August 2012 and safety and efficacy of eribulin were evaluated. Treatment toxicity including fatigue, neurotoxicity and infection was graded according to CTCAE v4.0. Objective response to treatment was investigated using routinely performed radiological assessments. When only clinical assessments were made, the evaluation of the treating physician was used. Furthermore, the efficacy of eribulin was investigated in different tumor subtypes.</p><p><b>Results.</b> Forty-eight patients who received at least one cycle of eribulin were identified. Most patients were heavily pretreated with a median of 3 (range 1–7) previous chemotherapy lines prior to eribulin. Median patient age was 56 years (range 35–74). At the end of the analysis, 23 patients were alive and two were still treated with eribulin. No hypersensitivity reactions and no toxic deaths were seen. Fatigue grade 3–4 was observed in three patients (6.3%). One patient experienced grade 4 neurotoxicity. Grade 3–4 neutropenia was documented in 18.8%, and three patients were treated for a grade 3 infection. Interestingly, three individuals developed Herpes zoster reactivation. One patient responded to treatment with complete remission, while 33.3% had a partial response. 48% of all patients had a clinical benefit (objective response or stable disease for more than six months).</p><p><b>Conclusions.</b> Eribulin administered outside of a clinical trial in patients with advanced breast cancer was safe and well tolerated. A clinical benefit was seen in half of the cases. No statistically significant differences in objective response or survival were observed between histopathological subgroups.</p></div

Additional file 5: Table S2. of A polymorphism in the base excision repair gene PARP2 is associated with differential prognosis by chemotherapy among postmenopausal breast cancer patients

Associations between SNP and breast cancer-specific mortality by radiotherapy for interactions showing p <0.1 (LRT)$ in the MARIE study and results of replication in BCAC studies. (DOCX 20 kb

Additional file 3: Figure S2. of A polymorphism in the base excision repair gene PARP2 is associated with differential prognosis by chemotherapy among postmenopausal breast cancer patients

Meta-analysis across BCAC studies of PARP2 and breast cancer prognosis. Forest plot of the combined hazard ratios and 95 % confidence intervals for PARP2 rs878156 in the discovery MARIE study and the replication studies in Breast Cancer Association Consortium (BCAC) using fixed effect models, according to treatment, i.e. no chemotherapy (A), any type of chemotherapy (B), and anthracycline-based chemotherapy (C). The combined effects for the BCAC studies were also based on fixed effect models. (DOCX 996 kb

Additional file 1: Table S1. of Reproductive profiles and risk of breast cancer subtypes: a multi-center case-only study

Definitions of breast cancer subtypes that have been applied in previous BCAC manuscripts. Table S2 Number of breast cancer patients with reproductive risk factor data in the 34 BCAC studies assessed in this study. Table S3 Number of breast cancer case patients with tumor marker data in the 34 BCAC studies assessed in this study. Table S4 Distribution of tumor characteristics according to breast cancer subtypes. Table S5 Association between parity (ever versus never) and BC subtypes for age overall and for specific ages (40, 50 and 60 years). Table S6 Frequency table showing parity by subtype and age group. Table S7 Associations between age at menarche, age at FFTP and breast cancer subtypes. The same analysis as in Table 4 is performed but here parity is considered a continuous variable. Table S8 Effect of parity (ever versus never) on BC subtype risk across all ages at BC diagnosis and corrected for BMI. Associations between age at menarche, age at FFTP and breast cancer subtype risk. (DOCX 60 kb

Frequencies and ORs for the c.541C>T mutation among the different patient subgroups in the Helsinki, Tampere, Oulu, and Belarus series.

<p>Frequencies and ORs for the c.541C>T mutation among the different patient subgroups in the Helsinki, Tampere, Oulu, and Belarus series.</p

Variants identified in the screening of the <i>RAD51B</i> gene (RefSeq NM_133509.3).

<p>Variants identified in the screening of the <i>RAD51B</i> gene (RefSeq NM_133509.3).</p

Two independent association signals at the 1p11.2 locus: Association results for breast cancer risk among European women in BCAC, by tumor characteristic.

<p>Two independent association signals at the 1p11.2 locus: Association results for breast cancer risk among European women in BCAC, by tumor characteristic.</p

Regional plots of breast cancer association in 1p12-11.2.

<p>Regional plot of association result, recombination hotspots and linkage disequilibrium for the 1p12-11.2:120,505,799–121,481,132 breast cancer susceptibility loci. Association result from a trend test in—log10<i>P</i>values (y axis, left; red diamond, the top ranked breast cancer associated locus in the region; blue diamond, best conditioned analysis results conditioned on rs11249433; black diamonds, genotyped SNPs; gray diamonds, imputed SNPs) of the SNPs are shown according to their chromosomal positions (x axis). Linkage disequilibrium structure based on the 1000 Genomes CEU data (n = 85) was visualized by snp.plotter software. The line graph shows likelihood ratio statistics (y axis, right) for recombination hotspot by SequenceLDhot software based on the background recombination rates inferred by PHASE v2.1. Physical locations are based on hg19. Gene annotation was based on the NCBI RefSeq genes from the UCSC Genome Browser.</p

Sensitivity analyses using pooled data for associations between genetically predicted BMI and breast cancer risk in the BCAC.

<p>(A) Adjusted for age, study sites, and the first eight principal components. (b) Adjusted for age, study sites, the first eight principal components, and additional breast cancer risk factors: age at menarche, parity, use of contraceptive, use of hormone replacement therapy, breast feeding, and smoking status. Weighted: the BMI-GS was constructed using the additive model weighted by external beta reported from previous literatures. Unweighted: the BMI-GS was constructed using the additive model without any weight.</p

Meta-analysis of the association between genetically predicted BMI and breast cancer risk in the BCAC.

<p>The summary OR was calculated by combining individual analysis results from each study in BCAC (<i>p</i> for heterogeneity = 0.06).</p