Sunitinib alone or in combination with chemotherapy for the treatment of advanced breast cancer: A systematic review and meta-analysis

Abstract

INTRODUCTION:

Sunitinib is an orally delivered tyrosine kinase inhibitor that exhibits antiangiogenic effects. FDA has approved sunitinib for the treatment of metastatic renal cell carcinoma. However, its efficacy for the treatment of advanced breast cancer (ABC) remains controversial. Therefore, we performed this systematic review and meta-analysis to synthesize evidence from published randomized controlled trials (RCTs) about the efficacy of sunitinib alone and in combination with chemotherapy for the treatment of ABC.

METHODS:

We followed PRISMA statement guidelines during the preparation of this systematic review and meta-analysis. A computer literature search of PubMed, SCOPUS, web of knowledge, and Cochrane Central Register of Controlled Trials (CENTRAL) has been conducted using relevant keywords. Studies were screened for eligibility and data were extracted to an online data extraction form. Progression free survival (PFS) and overall survival (OS) were pooled as Hazard ratio (HR) in a meta-analysis model using generic inverse variance method. Objective response rate (ORR) and complications were pooled as relative risk (RR) in a random effect model meta-analysis using Mantel–Haenzel method.

RESULTS:

Six RCTs, with a total sample size of 2273 patients, met our eligibility criteria and were included in this meta-analysis. Sunitinib monotherapy was not superior to chemotherapy in terms of PFS (HR = 1.00, 95% CI [0.86 to 1.16], P = 0.99), OS (HR = 1.07; 95% CI [0.87 to 1.32], P = 0.5), or ORR (RR = 0.70, 95% CI [0.74 to 1.03], P = 0.07). Sunitinib in combination with chemotherapy did not show superiority to chemotherapy in terms of PFS (HR = 0.99, 95% CI [0.86 to 1.14], P = 0.89) and OS (HR = 1.04, 95% CI [0.85 to 1.28], P = 0.69). However, the ORR favored sunitinib in combination with chemotherapy group (RR = 1.15, 95% CI [1.01 to 1.31]) with a statistically significant P value (P = 0.03).

CONCLUSIONS:

Current evidence shows that sunitinib, either alone or in combination with chemotherapy, has no clinical benefit for patients with advanced breast cancer. However, previous studies did not considered patient stratification and outcome assessment based on molecular markers. In terms of safety, toxicity was common with sunitinib treatment.

Keywords

Breast cancer sunitinib tyrosine kinase inhibitor vascular endothelium growth factor metastasis chemotherapy

Introduction

Advanced Breast Cancer (ABC) is an incurable disease with median overall survival of 2–3 years [1–3]. In 2010, up to third of patients with newly diagnosed breast cancer were expected to develop metastasis with approximately 15% of all breast cancer cases are of Triple-negative breast cancer (TNBC) subtype. TNBC affects younger women and has poor prognosis and limited treatment options [4,5].

Although the underlying mechanisms of tumor progression are still not fully understood, a significant relationship between angiogenesis and tumor progression was found. It was found that the expression of VEGF correlates with the microvessel density of breast tumor and therefore with tumor progression and spread [6–8].

Increased level of VEGF was found to be associated with poor prognosis and less survival of ABC patients [9,10]. Therefore, antiangiogenic agents have been developed to inhibit VEGF in two mechanisms: (1) Targeting VEGF ligands by monoclonal antibodies as Bevacizumab and (2) Inhibition of downstream tyrosine kinases in VEGF pathway.

Several anti-VEGF monoclonal antibodies have been introduced to improve progression-free survival (PFS) and overall survival (OS) of advanced tumors. Based on phase 3 clinical trials, FDA approved single-targeted bevacizumab in treatment of metastatic colorectal cancer, non-small lung cancer and Her-2 negative metastatic breast cancer [11–13]. In contrast to bevacizumab, sunitinib malate (Sutent; Pfizer) is, a small molecule, orally-delivered, multikinase inhibitor that targets VEGF tyrosine kinase and platelet derived growth factor. Sunitinib has been approved for the treatment of metastatic renal cell carcinoma and gastrointestinal stromal cancer [14,15].

Early clinical trials on sunitinib for ABC showed a promising efficacy and a manageable safety profile [16]. However, recent randomized controlled trials failed to show its superiority to traditional chemotherapy [17,18].

Therefore, we performed this systematic review and meta-analysis to synthesize evidence about the safety and efficacy of sunitinib, either alone or in combination with chemotherapy, for patients with ABC.

Methods

We followed the PRISMA statement guidelines during the preparation of this review and meta-analysis.

Inclusion and exclusion criteria

We included randomized controlled trials (RCTs) with the following criteria: (1) studies that examined the efficacy of sunitinib in patients with ABC irrespective of their clinical subtypes; (2) studies providing sufficient data reliable for pooling in meta-analysis; and (3) studies written in English. In case of multiple reports for the same study population, we analyzed data of the most complete dataset. Studies were excluded for the following reasons: (1) Thesis and conference abstracts; (2) studies with premature termination without addressing efficacy endpoints.

Literature search

A computer literature search was conducted, through October 2015, for four electronic databases: PubMed, Scopus, Web of Science and Cochrane Central Register of Controlled Trials (CENTRAL). Articles were identified using the search query (Sunitinib AND “Breast Neoplasms” [MESH]). The detailed search strategy is attached in supplementary file.1.

Selection of studies

Three authors (Ghanem E, Osama O, and Omar A) applied the selection criteria. Eligibility screening was performed in two steps: the first step was to screen abstracts for eligibility and in the second step, full-text articles of eligible abstracts were retrieved and screened for eligibility to meta-analysis.

Data extraction

Three authors (Elgebaly A, El Ashal G, and Menshawy A) extracted the data independently using an online data extraction form. The extracted data include the following: (1) characters of study design (Study design, interventional regimens, population, sample size and main findings); (2) characters of study population (Age, ECOG performance status, primary diagnosis, number of metastatic sites ≥2, prior therapy); (3) risk of bias domains (Random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting and other bias); and (4) study outcomes (number of events, and Hazard ratio (HR) of main outcomes). Disagreements were resolved by consensus.

Quality assessment

The quality of the retrieved RCTs was assessed according to Cochrane handbook of systematic reviews of interventions 5.1.0 (updated March 2011). We used the quality assessment table provided in (part 2, Chapter 8.5) the same book.

Measures of treatment effect

The primary efficacy measures are: (1) Progression Free Survival (PFS); (2) Overall Survival (OS); (3) Objective Response Rate (ORR); and (4) Safety outcomes (common adverse events occurred in >5% of study population).

Dealing with missing data

In case of missing Standard error (SE) of HR, it was estimated from the reported confidence intervals (CI) or log-rank P values when available.

Data synthesis

PFS and OS were pooled as HR in generic inverse variance model. ORR and complications were pooled as relative risk (RR) in a random effect model using Mantel–Haenzel (M–H) method. We used a random effect model due to clinical heterogeneity of included studies attributed to different treatment strategies. Statistical analysis was conducted using Review Manager (RevMan) version 5.3 for windows.

Assessment of heterogeneity

Statistical heterogeneity was assessed by visual inspection of the forest plots and measured by I-square and Chi-Square tests. A significant heterogeneity was defined as (P value <0.1) for chi-square test of heterogeneity. While I-square test was used to quantify the magnitude of heterogeneity according to recommendations of Cochrane Handbook of Systematic reviews and meta-analysis.

Publication bias

According to egger and colleagues [19,20], publication bias assessment is not reliable for less than 10 pooled studies. Therefore, in the present study, we could not assess the existence of publication bias by egger’s test for funnel plot asymmetry.

Results

Our search retrieved 527 unique citations. Following abstract and full text screening, six RCTs [18,21–25] with a total of 2273 patients were included in this study (See PRISMA flow diagram; Fig. 1). Reasons for exclusion of full text articles are shown in supplementary file no. 2.

Sunitinib was administered orally at 37.5 mg starting dose in five RCTs [18,21–24], and at starting dose of 50 mg which then has been reduced to 37.5 mg in one RCT [25]. Three trials assessed sunitinib as monotherapy, while the other trials assessed it in combination with chemotherapies. Summary of included studies and their main results is shown in Table 1 and baseline characteristics of their populations are shown in Table 2.

The quality of the included studies were from moderate to high quality according to the Cochrane risk of bias assessment tool. Summary of quality assessment domains is shown in Fig. 2. Authors’ judgment with justifications is shown in supplementary file no. 3.

Efficacy of sunitinib monotherapy

The overall effect estimate did not favor sunitinib in term of: PFS rate (HR = 1.00, 95% CI 0.86 to 1.16; P = 0.99; Fig. 3a), pooled studies were homogenous (I2 = 0%, P = 0.48); OS (HR = 1.07, 95% CI 0.87 to 1.32; P = 0.5; Fig. 3b) with no significant heterogeneity (I2 = 0%, P = 1.00); and ORR (RR = 0.70, 95% CI 0.47 to 1.03; P = 0.07; Fig. 3c) with no significant heterogeneity (I2 = 0%, P = 0.96).

Efficacy of sunitinib in combination with chemotherapy

The overall effect estimate did not favor Sunitinib in term of: (1) PFS (HR = 0.99, 95% CI 0.86 to 1.14; P = 0.89; Fig. 4a), pooled studies were homogenous (I2 = 0%, P = 0.55); and (2) OS (HR = 1.04, 95% CI 0.85 to 1.28; P = 0.69; Fig. 4b) with no significant heterogeneity (I2 = 0%, P = 0.81). The overall effect estimate favored Sunitinib combination group in terms of ORR (RR = 1.15, 95% CI 1.01 to 1.31, P = 0.03; Fig. 4c), pooled studies were homogenous (I2 = 0%, P = 0.84).

Safety of sunitinib monotherapy

Sunitinib group showed an increase in the risk of developing grade three or four adverse events (RR = 1.64, 95% CI 1.04 to 2.58, P = 0.03) and hypertension (RR = 11.58, 95% CI 2.65 to 50.63, p = 0.001), “Forest plots are shown in supplementary file no. 4.”

Safety of sunitinib in combination with chemotherapy

Sunitinib and chemotherapy combination group showed an increase in the risk of developing grade three and four adverse events (RR = 1.32, 95% CI 1.04 to 1.69, P = 0.02), fatigue (RR = 1.15, 95% CI 1.02 to 1.30, P = 0.02), nausea (RR = 1.21, 95% CI 1.03 to 1.42, P = 0.02), and diarrhea (RR = 1.50, 95% CI 1.27 to 1.77, P < 0.00001). “Forest plots are shown in supplementary file no. 4.”

Due to heterogeneity of the pooling of hypertension RR, Sensitivity analysis was conducted. Heterogeneity was best resolved by the exclusion of Robert et al. [21] sunitinib group showed an increase in the risk of hypertension (RR = 7.18, 95% CI 3.76 to 13.73, P = 0.00001). Robert et al. [21] caused heterogeneity because they compared sunitinib with bevacizumab, an Anti-VEGF agent that is known to significantly increase the risk of hypertension [26].

Discussion

Summary of main results

This study provides class one evidence that sunitinib either alone or in combination with chemotherapy does not improve clinical outcomes in patients with ABC. Both PFS and OS did not differ significantly in sunitinib groups in comparison with control group. Only ORR showed a slight improvement when sunitinib was administrated with standard chemotherapy. In addition, grade (3∕4) adverse events, hypertension and nausea were more likely to occur in patients receiving sunitinib.

Though, a number of early phase 2 trials suggested a beneficial effect of sunitinib-chemotherapy combination [16,27], none of the included RCTs showed a clinically significant benefit, whether as monotherapy [23–25] or in combination with chemotherapy [18,21,22]. Our pooled estimates confirm that lack of any improvement in terms of primary outcomes (PFS and OS).

Because loss of expression of KIT is associated with poor prognosis in breast cancer [28], the difference in expression of tyrosine kinase among ABC patients may provide an explanation for lack of significant improvement. A recent study showed that only 45% of TNBC cases expressed KIT [29] which implies that inhibition of tyrosine kinase as a therapeutic target might not be effective for all ABC patients. Keyvanjah et al. [30] correlated plasma concentrations of sKIT and VEGF with the clinical outcome of sunitinib in 61 ABC patients, they found that sKIT and VEGF levels may predict the outcome.

Unfortunately, investigators of the six studies did not measure the expression of VEGF receptor and tyrosine kinase and therefore a correlation between clinical outcomes and VEGF expression was not established.

But, if the reason for this failure was the lack of expression of KIT in some patients, we would expect a better result with bevacizumab which does not target tyrosine kinase but targets VEGF ligands. However, in two systematic reviews by Wagner et al. [31] and Kümler et al. [32], bevacizumab failed to improve survival rate for patients with breast Cancer. Taking both systematic reviews together with our results, we think that anti-angiogenic agents (Sunitinib and Bevacizumab) do not increase survival of ABC patients.

The study of Chincar et al. [33] which investigated the mechanism of sunitinib invitro provides another explanation. They found that Sunitinib significantly suppressed the proliferation, migration, apoptosis resistance, tumor angiogenesis and growth of TNBC but increased breast cancer stem cells. Therefore, sunitinib may be more effective in combination with γ -secretase inhibitor to block the contradictory pathway that increases breast cancer stem cells.

Overall completeness of evidence

Due to the aggressive nature of the disease and the nature of treatment, discontinuation existed in all trials. Common reasons were “death, violating the study protocol, and withdrawing due to adverse events”. All discontinuations were described and justified in all studies. The proportion of patients who were lost in the follow up was (21∕2274 patients = ∼1%) which is not likely to affect the study outcomes. Authors of all studies analyzed their data in an intention to treat analysis; they considered the total number of patients allocated to the treatment groups irrespective to any discontinuation or withdrawal after randomization.

Agreements and disagreements with other studies

The discrepancy between results of this systematic review and earlier clinical studies of sunitinib for ABC can be justified by: (1) different dose schedule; sunitinib was administered at starting dose of 37.5 mg once daily in all included RCTs, in contrast to the dose of 50 mg per day used in the earlier phase II studies; (2) Higher incidence of adverse events in the included studies, especially grade 3∕4, led to much dose reduction, interruptions, and treatment discontinuations which may explain this difference from earlier studies [18,22].

Agreements and disagreements with other reviews

To the best of our knowledge, this is the first systematic review and meta-analysis study to evaluate safety and efficacy sunitinib alone and in combination with chemotherapy for ABC. Currently available class one evidence about sunitinib efficacy is scarce and yet, in 2012, an international consensus guidelines been developed [34]. A previous meta-analysis on multiple antiangiogenic tyrosine kinase inhibitors included two RCTs comparing sunitinib and chemotherapy; They found a better ORR with antiangiogenic factors but there was no superiority for sunitinib in comparison with chemotherapy in terms of PFS and OS [35]. These results are consistent with our findings.

Quality of the evidence

The quality of this evidence is credible as it is based on high quality studies as indicated by risk of bias assessment. Search method was rigorous; we searched multiple electronic databases and we used MESH terms for sensitive search strategy. Eligibility criteria was well-defined. Screening and data extraction were performed by multiple authors independently to reduce the possibility of errors. The most important item that we followed the preferred reporting items of systematic reviews and meta-analysis (PRISMA checklist) and we performed all steps in strict accordance to Cochrane handbook of systematic reviews for interventions.

Limitations

Sunitinib is a tyrosine kinase inhibitors acting on multiple receptors in this family. However, clinical trials on sunitinib did not consider patient stratification and outcome assessment based on molecular markers.

Our study relied on published data only; individual patient data were not available and so were not pooled which might have given more precise estimations. Although no significant statistical heterogeneity was detected in the pooled efficacy endpoints, there was a high variability in employed treatment regimens and a significant heterogeneity was detected in pooled safety endpoints which may attributed to different combination regimens and different comparators.

Authors’ conclusions

Footnotes

Acknowledgements

The authors would like to thank members of Medical Research Group of Egypt for their support and encouragement. Ahmed Negida would like to thank his senior oncologist professor: Rasha Haggag, MD, PhD for providing senior support and advice to the team. Ahmed Negida has full access to all data in the study and takes responsibility for the integrity of presented information and accuracy of the data analysis.

Study concept and design: Ahmed Elgebaly.

Internet searching: Ahmed Elgebaly, Ahmed Menshawy, Gehad El Ashal, Omnya Osama, Esraa Ghanem, and Ahmed Omar.

Selection of studies: Omnya Osama, Esraa Ghanem, and Ahmed Omar.

Data extraction: Ahmed Elgebaly, Ahmed Menshawy, Gehad El Ashal, Omnya Osama, and Ahmed Omar.

Quality assessment: Ahmed Elgebaly, Ahmed Menshawy, and Gehad El Ashal.

Data analysis: Ahmed Elgebaly and Ahmed Negida.

Drafting the manuscript:AhmedElgebaly,Ahmed Menshawy, Gehad El Ashal, Omnya Osama, Esraa Ghanem, Ahmed Omar, and Ahmed Negida.

Revision and appraisal of the manuscript: Ahmed Negida.

Proofreading the manuscript: Ahmed Negida.

Study monitoring & supervision: Ahmed Negida.

Conflict of interest

All authors confirm they do not have any conflict of interest to declare.

Funding source

Authors confirm they did not receive any funding to do this work.

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