Bevacizumab increases the risk of infections in cancer patients: A systematic review and pooled analysis of 41 randomized controlled trials

Critical Reviews in Oncology/Hematology 94 (2015) 323–336

Bevacizumab increases the risk of infections in cancer patients: A systematic review and pooled analysis of 41 randomized controlled trials Wei-Xiang Qi a,b , Shen Fu a,b,∗ , Qing Zhang a , Xiao-Mao Guo a,b a

b

Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center (SPHIC), Fudan University Cancer Hospital, 4365 Kang Xin Road, Shanghai 201318, China Department of Radiation Oncology, Fudan University Shanghai Cancer Center (FUSCC), 270 Dong’An Road, Shanghai 200032, China Accepted 3 February 2015

Contents 1. 2.

3.

4. 5.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Data sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Study selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Data extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4. Statistical analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Search results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Overall incidence of infections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Relative risk of infections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Sensitivity analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Subgroup analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6. Risk of specific infections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7. Publication bias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflicts of interest statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Author contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Funding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reviewers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix A. Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Biography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

324 324 324 324 325 325 325 325 329 330 330 330 331 331 331 333 333 333 333 333 334 334 336

Abstract Background: Bevacizumab, a recombinant humanized monoclonal antibody that targets the vascular endothelial growth factor, has been approved for use in a variety of malignancies. There have been reports of infections associated with the use of bevacizumab. We performed this meta-analysis to determine the overall incidence and risk of infections associated with bevacizumab in cancer patients. Methods: Pubmed and oncology conference proceedings were searched for relevant studies from January 2000 to June 2014. Studies were limited to phase II and phase III randomized controlled trials (RCTs) of bevacizumab in cancer patients with adequate safety profiles. Summary incidences, relative risks (RRs), and 95% confidence intervals (95%CIs) were calculated by using either random effects or fixed effect models according to the heterogeneity of included studies. ∗ Corresponding author at: Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center (SPHIC), Fudan University Cancer Hospital, 4365 Kang Xin Road, Shanghai 201318, China. Tel.: +86 021 6417 5590; fax: +86 021 6417 4774. E-mail address: [email protected] (S. Fu).

http://dx.doi.org/10.1016/j.critrevonc.2015.02.007 1040-8428/© 2015 Elsevier Ireland Ltd. All rights reserved.

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Results: In total 33,526 patients from 41 RCTs were included. The use of bevacizumab significantly increased the risk of developing all-grade (RR 1.45, 95%CI: 1.27–1.66, p < 0.001) and high-grade (RR 1.59, 95%CI: 1.42–1.79, p < 0.001) infections in cancer patients. Sensitivity analysis indicated that the significance estimate of pooled RRs was not significantly influenced by omitting any single study. On subgroup analysis, the risk of developing high-grade infection varied significantly with concomitant drugs (p = 0.008). When stratified according to specific infectious events, the use of bevacizumab significantly increased the risk of developing severe febrile neutropenia (RR 1.57, 95%CI: 1.34–1.84; p < 0.001) and fistulae/abscesses (RR 2.13, 95%CI: 1.06–4.27; p = 0.033). No evidence of publication bias was observed. Conclusions: Bevacizumab treatment significantly increases the risk of infectious events developing in cancer patients. The risk may vary with concomitant drugs. Clinicians should be aware of the risks of infections with the administration of this drug in cancer patients. © 2015 Elsevier Ireland Ltd. All rights reserved.

Keywords: Bevacizumab; Infections; Cancer; Meta-analysis

1. Introduction Angiogenesis, the process of new blood vessel formation, plays an essential role in tumor growth, progression and metastasis [1,2]. For this reason, the molecular mechanism of angiogenesis has been of particular interest in the field of cancer research. Of these, the vascular endothelial growth factor (VEGF) pathway is considered the most important and is a well-characterized contributor to angiogenesis [3]. As a result, VEGF and the process of its receptor bindings are regarded as attractive therapeutic targets in the treatment of cancers [3]. Bevacizumab, a recombinant humanized monoclonal antibody targeting the VEGF, has been widely used in a variety of malignancies. Based on a significant survival benefit, bevacizumab is currently approved by the US Food and Drug Administration for use in metastatic colorectal cancer, metastatic renal-cell carcinoma, non-small-cell lung cancer and glioblastoma [4]. However, VEGF plays multiple roles in physiologic processes, and thus its inhibition could have potentially serious systemic consequences. Indeed, several recent meta-analyses have shown that the use of bevacizumab significantly increases the risk of developing anti-VEGF adverse events, including hypertension [5], congestive heart failure (CHF) [6], arterial thrombosis [7], hemorrhage [8,9], proteinuria [10,11] and gastrointestinal perforation [12,13]. Additionally, high-grade infection (Grades 3–4) is a rare but potentially life-threatening adverse event with bevacizumab; this has been observed in clinical trials with an incidence ranging from 0% to 23.2% [14,15]. However, the contribution of bevacizumab to infections remains poorly defined due to the low incidence of high-grade infections in a single clinical trial. The mechanism of bevacizumab-induced infections may be related directly to its inhibitory effect on the VEGF signaling pathway: VEGF can affect the function of immune cells that are present in the tumor microenvironment and, consequently, it can affect the host response to infections [16,17]. In addition, VEGF receptors may regulate the function of fibroblasts in the tumor stroma [18]. Knowledge of the incidence and risk of infections with bevacizumab may allow for more accurate and prompt diagnoses and timely clinical interventions, which could minimize the disruption

of bevacizumab treatment in the underlying malignancy, as well as improving patients’ quality of life. However, as far as we know, the incidence and risk of infections with bevacizumab has not been systematically defined. Therefore, we performed this up-to-date meta-analysis of randomized controlled trials (RCTs) to determine whether or not the addition of bevacizumab to therapies increases the risk of infections in cancer patients.

2. Methods 2.1. Data sources We searched the Pubmed (data from 2000 to Jun 2014), Embase (data from 2000 to Jun 2014) and the Cochrane Library electronic databases. Keywords were “bevacizumab”, “Avastin”, “cancer”, “carcinoma”, “neoplasm”, “randomized controlled trial” and “infections”. The search was limited to prospective randomized clinical trials published in English. We also searched abstracts containing the term “bevacizumab” that were presented at the American Society of Clinical Oncology (ASCO) and European Society of Medical Oncology (ESMO) annual meetings from 2004 to 2014 to identify relevant studies. Additionally, we searched the clinical trial registration website (http://www.ClinicalTrials.gov) to obtain information on the registered prospective trials. Each publication was reviewed, and in cases of duplicate publication only the most complete, recent, and updated report of the clinical trial was included in the meta-analysis. The reporting of this systematic review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements [19]. 2.2. Study selection The primary goal of our study was to determine the overall incidence of infections associated with bevacizumab and to establish the association between bevacizumab treatment and the risk of developing infections. Thus, only prospective phase II and phase III RCTs evaluating bevacizumab in cancer patients with adequate safety data on infections were

W.-X. Qi et al. / Critical Reviews in Oncology/Hematology 94 (2015) 323–336

incorporated in the analysis. Phase I and single-arm phase II trials were excluded due to lack of control groups. Clinical trials that met the following criteria were included: (1) prospective phase II or III RCTs involving cancer patients; (2) participants assigned to treatment with or without bevacizumab in addition to concurrent chemotherapy and/or biologic agent(s); and (3) available data regarding events or incidence of infections and sample size. 2.3. Data extraction Data abstraction was conducted independently by two investigators (WXQ and SF), and any discrepancy between the reviewers was resolved by consensus. For each study, the following information was extracted: first author’s name, year of publication, phase of trials, number of enrolled subjects, treatment arms, number of patients in treatment and control groups, underlying malignancy, median age, median treatment duration, median progression-free survival, adverse outcomes of interest (infections) and bevacizumab dosage. The following adverse outcomes were considered as infectious events and were included for analyses: colitis, unspecified infections, viral hepatitis, febrile neutropenia, abscess, sepsis, septic shock, and pneumonia. Adverse events of all- and high-grade (≥grade 3), as assessed and recorded according to the National Cancer Institute’s common terminology criteria (NCI-CTC, version 2 or 3; http://ctep.cancer.gov), were extracted for analysis, which had been widely used in the cancer clinical trials. In the event that a study reported high-grade but not low-grade infectious events, we calculated only the pooled incidence and risk of high-grade infectious events, and no assumption of all-grade incidence and risk was made.

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out meta-regressions with differences in median length of experimental treatments (expressed in months) as predictor and relative risk as the dependent variable. Between-study heterogeneity was estimated using the χ2 -based Q statistic [21]. Heterogeneity was considered statistically significant when pheterogeneity < 0.1. If heterogeneity existed, the pooled estimate calculated on the basis of the random-effects model was reported using the method of DerSimonian et al. [22]. In the absence of heterogeneity, the pooled estimate calculated on the basis of the fixed-effects model was reported using an inverse variance method. A statistical test with a p-value < 0.05 was considered significant. In addition, we calculated RRs for each study using an empirical continuity correction, Peto methods, and continuity correction of 0.5 in all studies with zeros to investigate the sensitivity and stability of our results. For calculating RR by using empirical continuity correction, we added kc = R/R + Ω to each control group cell and kt = Ω/R + Ω to the treatment arm cells. ‘R’ was calculated as the group ratio imbalance and Ω as the estimated pooled odds ratio (Mantel–Haenszel method) in the studies without zero events in either arms [23]. The presence of publication bias was evaluated by using the Begg and Egger tests [24]. The Jadad scale was used to assess the quality of included trials based on the reporting of the studies’ methods and results [25]. All statistical analyses were performed by using Version 2 of the Comprehensive MetaAnalysis program (Biostat, Englewood, NJ) and Open Meta-Analyst software version 4.16.12 (Tufts University).

3. Results 3.1. Search results

2.4. Statistical analysis For the calculation of incidence, the number of patients with infections in the bevacizumab group and the total number of patients receiving bevacizumab were extracted from the selected clinical trials; the proportions of patients with infections and 95% confidence intervals (95%CI) were derived for each study. For one study that reported zero events in either the treatment or the control arms, we applied the classic half-integer correction to calculate the RR and variance [20]. For exploring a potential dose–effect relationship by further dividing bevacizumab therapy into low-dose (5 or 7.5 mg/kg per dose per schedule, which was equivalent to 2.5 mg/kg per week) and high-dose (10 or 15 mg/kg per dose per schedule, which was equivalent to 5 mg/kg per week). We also conducted the following prespecified subgroup analyses to find potential risk factors for infections: tumor types, concomitant drugs, phase of trials and treatment lines. To assess the stability of the pooled results, sensitivity analysis was performed by sequential omission of individual studies. Additionally, to test whether effect sizes were moderated by differences in length of treatment, we carried

Our search yielded 887 clinical studies relevant to bevacizumab. After excluding review articles, phase I studies, single-arm phase II trials, case reports, editorial, letters, commentaries, meta-analyses and systematic reviews (Fig. 1), we selected 41 RCTs, including 34 phase III and seven phase II trials (Table 1). In total 33,526 patients were included for analysis. The characteristics of patients and studies are listed in Table 1. According to the inclusion criteria of each trial, patients were required to have adequate hepatic, renal and hematologic function. Underlying malignancies included colorectal cancer (11 trials) [14,26–35], non-smallcell lung cancer (four trials) [36–39], breast cancer (nine trials) [40–48], gastric cancer (two trials) [49,50], renal-cell carcinoma (two trials) [51,52], ovarian cancer (four trials) [53–56], prostate cancer (one trial) [15], pancreatic cancer (one trial) [57], small-cell lung cancer (one trial) [58], melanoma (one trial) [59], malignant mesothelioma (one trial) [60], multiple myeloma (one trial) [61], glioblastoma (one trial) [62], lymphoma (one trial) [63] and cervical cancer (one trial) [64]. The quality of the 41 trials included was high: 20 trials had Jadad scores of 5. Another 21 trials did not

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Table 1 Baseline characteristics of 41 randomized controlled trials in the meta-analysis (n = 33,526). Histology

Treatment line

Patients enrolled

Kabbinavar F.F. et al./2003/II

First-line

104

First-line

210

First-line

209

First-line

1401

First-line

2710

First-line

471

First-line

73

First-line

214

First-line

3451

Hurwitz H.I. et al./2005/III Kabbinavar F.F. et al./2005/II Saltz L.B. et al./2008/III Allergra C.J. et al./2009/III CRC

Tebbutt N.C. et al./2010/III Kemeny N.E. et al./2011/II Guan Z.Z. et al./2011/III de Gramount A. et al./2012/III Bennouna J. et al./2013/III Cunningham D. et al./2013/III

NSCLC

Second-line 820 First-line

280

Johnson D.H. et al./2004/II

First-line

99

Sandler A. et al./2006/III

First-line

878

Reck M. et al./2009/III

First-line

1043

Herbst R.S. et al./2011/III

Second-line 636

Miller K.D. et al./2005/III Miller K. et al./2007/III Miles D.W. Breast cancer et al./2010/III

Second-line 462 First-line

722

First-line

736

Treatment arms

Median age, y

Median duration, m

Median PFS, m

Median OS, m

No. for High-grade analysis infections

Bev 2.5 mg/kg/wk + FU/LV Bev 5 mg/kg/wk + FU/LV FU/LV Bev 2.5 mg/kg/wk + IFL Placebo + IFL Bev 2.5 mg/kg/wk + FU/LV Placebo + FU/LV Bev 2.5 mg/kg/wk + XELOX/FOLFOX Placebo + XELOX/FOLFOX Bev 2.5 mg/kg/wk + FOLFOX FOLFOX Bev 2.5 mg/kg/wk + capecitabine Bev 2.5 mg/kg/wk + capecitabine + mitomycin Capecitabine Bev 2.5 ng/kg/wk + HAI plus systematic therapy Placebo + HAI plus systematic therapy Bev 2.5 mg/kg/wk + irinotecan + Fu/LV Irinotecan + Fu/LV Bev 2.5 mg/kg/wk + FOLFOX Bev 2.5 mg/kg/wk + XELOX FOLFOX Bev 2.5 mg/kg/wk + chemotherapy Chemotherapy Bev 2.5 mg/kg/wk + capecitabine Capecitabine

NR NR NR 59.7 60.3 71.3 70.7 60 60 NR NR 67 67 69 NR NR 53 50 58 58 58 63 63 76 77

NR NR NR NR NR 7.2 5.4 6.3 5.9 11.5 NR 6.3 7 5.6 NR NR 6.2 2.3 10.6 10.4 5.3 3.9 3.2 5.8 4.2

9 7.2 5.2 8.8 6.8 9.2 5.5 9.4 8 NR NR 8.4 8.5 5.7 NR NR 8.3 4.2 NR NR NR 5.7 4.1 9.1 5.1

21.5 16.1 13.8 18.3 15.1 16.6 12.9 21.3 19.9 NR NR 16.4 18.9 18.9 NR NR 13.4 18.7 NR NR NR 11.2 9.8 20.7 16.8

35 32 35 109 98 104 100 694 675 1354 1356 157 158 150 38 35 141 70 1145 1135 1126 401 409 134 136

0 1 0 0 1 0 3 6 0 47 15 20 20 15 0 2 2 2 16 10 4 0 1 2 2

Bev 2.5 mg/kg/wk + PTX + CBP Bev 5 mg/kg/wk + PTX + CBP PTX + CBP Bev 5 mg/kg/wk + PTX + CBP PTX + CBP Bev 5 mg/kg/wk + gemcitabine + cisplatin Bev 2.5 mg/kg/wk + GEM + cisplatin Placebo + GEM + cisplatin Bev 5 mg/kg/wk + erlotinib Placebo + erlotinib

NR NR NR NR NR 59 57 59 64.8 65

6.3 7 4.2 4.9 3.5 4.4 4.9 3.5 2.8 1.4

4.3 7.4 4.2 6.2 4.5 6.7 6.5 6.1 3.4 1.7

11.6 17.7 14.9 12.3 10.3 NR NR NR 9.3 9.2

32 34 32 440 427 329 330 327 313 313

0 2 1 22 9 7 7 3 2 4

Bev 5 mg/kg/wk + capecitabine Capecitabine Bev 5 mg/kg/wk + PTX PTX Bev 5 mg/kg/wk + DOC Bev 2.5 mg/kg/wk + DOC Placebo + DOC

51 52 56 55 55 54 55

NR NR 7.1 5.1 NR NR NR

4.86 4.17 11.3 5.8 10.1 9 8.2

15.1 14.5 25.6 24.8 30.2 30.8 31.9

229 215 365 346 247 252 231

2 1 34 10 2 5 6

Reported infectious events

Infection Febrile neutropenia, septicemia Sepsis Fistula/intra-abdominal abscess Febrile neutropenia Febrile neutropenia, Infection Infection Febrile neutropenia Fistula/abscess Infection Pneumonia Infection, pneumonitis Febrile neutropenia Febrile neutropenia Pneumonia Infection Infection Infection, fistula/abscess

W.-X. Qi et al. / Critical Reviews in Oncology/Hematology 94 (2015) 323–336

Authors/year/ phase

Brufsky A.M. et al./2011/III

Second-line

648

Robert N.J. et al./2011/III

First-line

1237

RCC

Escudier B. et al./2007/III Rini B.I. et al./2010/III Burger R.A. et al./2011/III

Perren T.J. et al./2011/III Aghajanian C. et al./2012/III PujadeLauraine E. et al./2014/III Ohtsu A. et al./2011/III Gastric cancer Shen L. et al./2014/III Ovarian cancer

Neoadjuvant 1206 Neoadjuvant 1948 First-line

2591

First-line

424

First-line

649

First-line

732

First-line

1873

First-line

1528

Second-line

484

Second-line

361

First-line

774

First-line

202

55 55 56 57 55 55 55 55 NR NR 49 48 50 50 53 55

6 4 NR NR NR NR NR NR NR NR NR NR NR NR 11.7 NR

7.2 5.1 8.6 5.7 9.2 8 9.2 8 NR NR NR NR NR NR 16.5 13.7

18 16.4 NR NR NR NR NR NR NR NR NR NR NR NR NR NR

458 221 404 201 203 102 210 100 595 596 956 969 1271 1288 215 206

10 6 0 0 17 2 8 5 78 42 97 66 2 0 25 18

Bev 5 mg/kg/wk + interferon alfa Placebo + interferon alfa Bev 5 mg/kg/wk + interferon alfa Interferon alfa

61 60 61 62

9.7 5.1 5.7 2.9

10.2 5.4 8.5 5.2

NR 19.8 18.3 17.4

337 304 362 347

3 0 1 3

Bev 5 mg/kg/wk initiation therapy + PTX + CBP Bev 5 mg/kg/wk throughout therapy + PTX + CBP Placebo + PTX + CBP Bev 2.5 mg/kg/wk + PTX + CBP PTX + CBP Bev 5 mg/kg/wk + GEM + cisplatin Placebo + GEM + cisplatin Bev 5 mg/kg/wk + chemotherapy Chemotherapy

60 60 60 57 57 60 61 NR NR

NR NR NR NR NR 8.4 7 NR NR

11.2 14.1 10.3 19 17.3 12.4 8.4 6.7 3.4

38.7 39.7 39.3 NR NR 33.3 35.2 NR NR

607 608 601 745 753 247 233 179 182

30 26 21 26 20 NR NR 1 1

Bev 2.5 mg/kg/wk + cisplatin + capecitabine Placebo + cisplatin + capecitabine Bev 2.5 mg/kg/wk + capecitabine Placebo + capecitabine

58 59 54.2 55.5

6.8 5.8 4.4 4.8

6.7 5.3 6.3 6

12.1 10.1 10.5 11.4

386 381 100 102

18 16 3 0

Pancreatic cancer

Van Cutsem E. et al./2009/III

First-line

607

Bev 2.5 mg/kg/wk + GEM + erlotinib Placebo + GEM + erlotinib

61 62

3.5 3.3

4.6 3.6

7.1 6

287 3 296 1

SCLC

Spigel D. R. et al./2011/III

First-line

102

Bev 5 mg/kg/wk + etoposide + platium Placebo + etoposide + platinum

60 64

NR NR

5.5 4.4

9.4 10.9

51 3 47 2

Febrile neutropenia

Febrile neutropenia

Febrile neutropenia, infection in wound Febrile neutropenia, infection Febrile neutropenia Febrile neutropenia, pneumonia Pneumonia Pneumonitis

Febrile neutropenia Febrile neutropenia, Fistula/abscess Febrile neutropenia, Fistula/abscess Fistula/abscess Febrile neutropenia, Fistula/abscess

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Bear H.D. et al./2012/III von Minckwitz G. et al./2012/III Cameron D. et al./2013/III Gianni L. et al./2013/III

Bev 5 mg/kg/wk + chemotherapy Placebo + chemotherapy Bev 5 mg/kg/wk + capecitabine Placebo + capecitabine Bev 5 mg/kg/wk + taxanes Placebo + taxanes Bev 5 mg/kg/wk + anthracycline Placebo + anthracyclines Bev 5 mg/kg/wk + chemotherapy Chemotherapy Bev 5 mg/kg/wk + chemotherapy Chemotherapy Bev 5 mg/kg/wk + chemotherapy Chemotherapy Bev 5 mg/kg/wk + DOC + trastuzumab DOC + trastuzumab

Lung infection, Febrile neutropenia, septic shock Pneumonia

327

328

Treatment arms

Median age, y

Median duration, m

Median PFS, m

Median OS, m

1050

Bev 5 mg/kg/wk + DOC + prednisone Placebo + DOC + prednisone

68.8 69.3

5.6 5.6

9.9 7.5

22.6 21.5

First-line

214

Bev 5 mg/kg/wk + PTX + CBP PTX + CBP

60 60

4.2 3.5

5.6 4.2

Kindler H.L. et al./2012/II

First-line

115

Bev 5 mg/kg/wk + GEM + cisplatin Placebo + GEM + cisplatin

62 65

4.9 4.2

Multiple myeloma

White D. et al./2013/II

Second-line

102

Bev 5 mg/kg/wk + bortezomib Placebo + bortezomib

65 65

Lymphoma

Seymour J.F. et al./2014/III

First-line

787

Bev 5 mg/kg/wk + R-CHOP R-CHOP

Cervical cancer

Tewari K.S. et al./2014/III

Second-line

452

Bev 5 mg/kg/wk + chemotherapy Chemotherapy

Glioblastoma

Chinot O.L. et al./2014/III

First-line

921

Bev 5 mg/kg/wk + TMZ + radiotherapy 57 Placebo + TMZ + radiotherapy 56

Histology

Authors/year/ phase

Treatment line

Patients enrolled

CRPC

Kelly W.K. et al./2012/III

First-line

Melanoma

Kim K.B. et al./2012/II

Malignant mesothelioma

No. for analysis

High-grade infections

Reported infectious events

504 505

0 2

12.3 8.6

143 69

7 1

Colitis, infectious, febrile neutropenia, infection Febrile neutropenia

6.9 6

15.6 14.7

53 55

5 2

4.2 NR

6.2 5.1

NR 24

50 50

1 0

Febrile neutropenia, Infection without neutropenia Upper respiratory tract infection

61 61

NR NR

40.2 42.9

NR NR

395 386

85 64

Febrile neutropenia, pneumonia

NR NR

NR NR

NR NR

17 13.3

220 219

12 12

Febrile neutropenia

NR NR

10.6 6.2

16.8 16.7

461 450

8 6

Infection

CRC, colorectal cancer; NSCLC, non-small-cell lung cancer; RCC, renal-cell cancer; SCLC, small-cell lung cancer; CRPC, castration-resistant prostate cancer; Bev, bevacizumab; Fu/LV, folinic acid (leucovorin) and fluorouracil; FOLFOX, folinic acid (leucovorin), fluorouracil and oxaliplatin; XELOX, capecitabine and oxaliplatin; PTX, paclitaxel; DOC, docetaxel; CBP, carboplatin; GEM, gemcitabine; R-CHOP, rituximab, cyclophosphamide, doxorubicin and prednisone; TMZ, temozolomide; HAI, hepatic arterial infusion; PFS, progression-free survival; OS, overall survival; NR, not reported.

W.-X. Qi et al. / Critical Reviews in Oncology/Hematology 94 (2015) 323–336

Table 1 (Continued)

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Fig. 1. Selection process for prospective randomized controlled trials included in the meta-analysis.

mention the blinding of allocation clearly in the randomization process, thus had Jadad scores of 3. 3.2. Overall incidence of infections For calculating the incidence of all-grade infections, 5950 patients from 16 RCTs who received bevacizumab were included for analysis. Infections–regardless of grade – occurred in 525 patients, representing a total incidence of 7.8% (95%CI, 4.8–12.4%). As for high-grade

infection, 17,808 patients from 40 RCTs who received bevacizumab were included. Using a random-effects model, the summary incidence of high-grade infections was 3.0% (95%CI, 2.1–4.3%). Severe infections can be fatal in many instances. The overall incidence of fatal infections was 0.9% (95%CI: 0.5–1.4%) according to our metaanalysis of trials with available data. Among patients with bevacizumab-associated infections, meta-analysis showed that mortality from the infections was 3.9% (95%CI: 2.8–5.5%).

Fig. 2. Relative risk of all-grade infections associated with bevacizumab versus control.

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Fig. 3. Relative risk of high-grade infections associated with bevacizumab versus control.

3.3. Relative risk of infections To determine the specific contribution of bevacizumab to the development of infections, and to exclude the effect of any confounding factors, we calculated the overall relative risk of infections from these RCTs. For calculating all-grade RR of infections, 16 RCTs representing 11,582 patients were included. Among the 5950 patients treated with bevacizumab, 525 presented with all-grade infections, whereas 282 of 5632 patients in controlled groups had an any-grade infectious event. This conferred an overall RR of developing all-grade infections of 1.45 (95%CI, 1.27–1.66; p < 0.001; Fig. 2). No significant heterogeneity was observed in the RR analysis of all-grade infectious events (Q = 14.66; p = 0.47; I2 = 0%). Considering only high-grade infectious events, 793 of 17,808 patients treated with bevacizumab and 430 of 14,511 patients in controlled arms experienced them. This conferred an overall RR of 1.59 by using a fixed-effect model (95% CI, 1.42–1.79; p < 0.001; Fig. 3). No significant heterogeneity was observed in the RR analysis of high-grade infectious events (Q = 44.87; p = 0.24; I2 = 13.1%). We also analyzed the stability and reliability of pooled RRs by sequential omission of individual studies. The results indicated that the significance estimate of pooled RRs of high-grade infections was not significantly influenced by omitting any single study (Supplemental Fig. 1). Additionally, a meta-regression analysis was carried out to test whether the RR of severe infections varied as a function of difference in the length of

the experimental treatments. The result indicated that the RR of high-grade infections tended to be higher in the study in which the experimental treatment was longer, but this effect was not statistically significant (p = 0.25, Supplemental Fig. 2). 3.4. Sensitivity analysis Sensitivity analyses of high-grade infections using an empirical continuity correction (fixed Mantel–Haenszel RR: 1.63, 95%CI: 1.46–1.80), with no continuity correction (fixed Peto method RR 1.69, 95%CI: 1.50–1.91), or with a continuity of 0.5 correction (fixed Mantel–Haenszel RR: 1.63, 95%CI: 1.46–1.83; inverse variance RR: 1.59, 95%CI: 1.42–1.79; random DerSimonian and Laird method RR: 1.59, 95%CI: 1.38–1.83) showed results similar to those of the primary analysis (Table 2). 3.5. Subgroup analysis To determine whether the observed increase in RRs of developing high-grade infections was the result of confounding bias, we performed subgroup analyses according to the underlying malignancy, bevacizumab dosage, phase of trials, concomitant drugs and treatment lines. When stratified by tumor type, a significantly increased risk of high-grade infection was observed in colorectal cancer (RR1.79, 95%: 1.26–2.53, p = 0.001), non-small-cell lung cancer (RR1.85,

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Table 2 Sensitivity analyses for the outcome of high-grade infections. Sensitivity analysis

Statistical model

RR (95%CI), p-value

Empirical continuity correction No continuity correction Continuity correction of 0.5 Continuity correction of 0.5 Continuity correction of 0.5

Fixed (MH) Fixed (Peto) Fixed (MH) Fixed (IV) Random (DL)

1.63 (1.46–1.82), p < 0.001 1.69 (1.50–1.91), p < 0.001 1.63 (1.46–1.83), p < 0.001 1.59 (1.42–1.79), p < 0.001 1.59 (1.38–1.83), p < 0.001

MH, Mantel–Haenszel methods; IV, inverse variance methods; DL, DerSimonian and Laird methods.

95%: 1.03–3.33, p = 0.04), breast cancer (RR1.60, 95%: 1.32–1.93, p < 0.001) and gastric cancer (RR2.43, 95%: 1.29–4.58, p = 0.006), while the use of bevacizumab did not increased the risk of high-grade infections in ovarian cancer (RR 1.31, 95%CI: 0.91–1.90, p = 0.15) and renal-cell carcinoma (RR 0.96, 95%CI: 0.16–5.77, p = 0.96, Table 2). However, clinicians should be cautious when interpreting these results because of the limited number of RCTs of specific types of cancer included for the RR calculation. Currently, there are two approved doses for bevacizumab: 2.5 mg/wk (low dose) and 5.0 mg/wk (high dose). Therefore, we attempted to investigate the RRs stratified by bevacizumab dosage. Our results showed that the risk of high-grade infections with bevacizumab seem to be doseindependent. The relative risk of high-grade infections with low-dose bevacizumab was 1.76 (95%CI: 1.35–2.30, p < 0.001, Table 2), which was comparable to that of highdose bevacizumab (RR 1.66, 95%CI: 1.44–1.91, p < 0.001, Table 2). We also carried out a subgroup risk analysis stratified according to drugs administered concomitantly with bevacizumab. Our results showed that the risk of high-grade infections with bevacizumab significantly varied with concomitant drugs (p = 0.008). There was a significantly increased risk of developing high-grade infections when bevacizumab was used in conjunction with taxanes (RR 1.64, 95%CI: 1.43–1.90, p < 0.001), capecitabine (RR 1.66, 95%CI: 1.10–2.48, p = 0.015), gemcitabine (RR 2.51, 95%CI: 1.02–6.17, p = 0.044) and oxaliplatin (RR 3.29, 95%CI: 2.00–5.41, p < 0.001), while bevacizumab in combination with interferon alfa (RR 0.96, 95%CI: 0.16–5.77, p = 0.96) and irinotecan (RR 0.43, 95%CI: 0.08–2.72, p = 0.32) did not increase the risk of high-grade infections. Additionally, the risk of high-grade infections might be related to the treatment lines of bevacizumab. Our study demonstrated that the use of bevacizumab as first-line (RR 1.64, 95%CI: 1.43–1.88, p < 0.001) and neoadjuvant (RR 1.63, 95%CI: 1.30–2.05, p < 0.001) therapy significantly increased the risk of high-grade infections, while the use of bevacizumab as second-line therapy did not increase the risk of high-grade infections (RR 0.90, 95%CI: 0.53–1.54, p = 0.71). Finally, we did subgroup analysis according to trial phase (phase II versus phase III). Patients from phase III trials had an RR of 1.60 (95%CI: 1.43–1.79, p < 0.001), while patients from phase II studies had an RR of 1.37 (95%CI: 0.56–3.39, p = 0.49, Table 3).

3.6. Risk of specific infections We also calculated the risk of infections stratifying trials according to specific type of infection, and found that the use of bevacizumab significantly increased the risk of febrile neutropenia (RR 1.57, 95%CI: 1.34–1.84, p < 0.001) and fistula/abscess (RR 1.57, 95%CI: 1.34–1.87, p < 0.001), while a non-significantly increased risk of pneumonia was observed (RR 1.26, 95%CI: 0.77–2.08, p = 0.36), but not of colitis or sepsis (Table 4). 3.7. Publication bias No publication bias was detected for the primary endpoint of this study (relative risk of high-grade infections) by the funnel plot (supplemental Fig. 3), Egger’s test and Begg’s test (RR of high-grade infections: Begg’s test p = 0.65; Egger’s test p = 0.53).

4. Discussion Infections are emerging complications of many targeted agents, and concerns have arisen regarding the risk of infections with the use of these targeted drugs. A previous meta-analysis conducted by Kaymakcalan et al. [65] demonstrated that treatment with mTOR inhibitors was associated with a significant increase in the risk of developing infections. More recently, two meta-analyses also found that the use of anti-EGFR monoclonal antibodies (cetuximab and panitumumab) was associated with a significantly higher risk of developing high-grade infections and febrile neutropenia [66,67]. However, the incidence and risk of infections with bevacizumab remains unknown. Our metaanalysis includes a total of 33,526 patients from 41 RCTs. To our best knowledge, this is the first large meta-analysis of RCTs demonstrating a significant increase in the risk of infection with the use of bevacizumab in cancer patients. Our analysis finds that there is a 1.45-fold higher risk of developing an infection of any grade in patients treated with bevacizumab. And, more importantly, there is a 1.59-fold increase in the risk of high-grade infection with the use of bevacizumab. Meta-regression analysis indicates that the RR of high-grade infections tends to be associated with cumulative bevacizumab exposure, but this effect was not statistically significant. Additionally, we investigated the outcome of

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Table 3 Relative risk of high-grade infectious events with bevacizumab according to tumor type, bevacizumab dose, trial phase, treatment line and concomitant drugs. Groups

Tumor type CRC NSCLC Breast cancer Gastric cancer RCC Ovarian cancer Others Bevacizumab dosea Low dose 2.5 mg/kg/wk High dose 5.0 mg/kg/wk Concomitant drugs Taxanes Capecitabine Gemcitabine Oxaliplatin Interferon alfa Irinotecan Treatment line First-line Second-line Neoadjuvant Trial phase Phase II Phase III Overall

Studies, n

High-grade infectious events, n/total

RR (95%CI)

p-Value

p-Value for group difference

Bevacizumab

Control

11 4 9 2 2 3 9

124/5637 40/1478 280/5405 21/286 4/699 83/2139 241/2164

45/4190 17/1099 156/4475 16/483 3/651 42/1536 151/2077

1.79 (1.26–2.53) 1.85 (1.03–3.33) 1.60 (1.32–1.93) 2.43 (1.29–4.58) 0.96 (0.16–5.77) 1.31 (0.91–1.90) 1.55 (1.28–1.87)

0.001 0.04 <0.001 0.006 0.96 0.15 <0.001

0.80

27 17

185/7502 608/10,271

92/6277 348/8824

1.76 (1.35–2.30) 1.66 (1.44–1.91)

<0.001 <0.001

0.95

13 5 3 3 2 2

500/6166 65/964 22/999 79/4328 4/699 2/250

271/5056 34/984 6/678 19/3157 3/651 3/168

1.64 (1.43–1.90) 1.66 (1.10–2.48) 2.51 (1.02–6.17) 3.29 (2.00–5.41) 0.96 (0.16–5.77) 0.43 (0.08–2.72)

<0.001 0.015 0.044 <0.001 0.96 0.32

0.008

31 7 2

590/14,407 28/1850 175/1551

297/11,337 25/1609 108/1565

1.64 (1.43–1.88) 0.90 (0.53–1.54) 1.63 (1.30–2.05)

<0.001 0.71 <0.001

0.10

7 33 40

16/521 793/17,287 793/17,808

9/376 430/14,511 430/14,511

1.37 (0.56–3.39) 1.60 (1.43–1.79) 1.59 (1.42–1.79)

0.49 <0.001 <0.001

0.79 NA

RR, relative risk; CRC, colorectal cancer; NSCLC, non-small-cell lung cancer; RCC, renal-cell carcinoma; NA, not available. a Four trials were three-arm studies containing low-dose and high-dose bevacizumab treatment.

bevacizumab-associated high-grade infections and found that the overall incidence of fatal infections with bevacizumab is 0.9%. The pathogenesis of bevacizumab-related infections is currently unknown, and neutropenia could be a possible mechanism that links VEGF-targeted agents and the risk of infections. A previous meta-analysis conducted by Schutz et al. [68] from 23 RCTs demonstrated that the use of bevacizumab was associated with a significant increase of 15% and 8% in the risk of all-grade and high-grade neutropenia, respectively, and a 31% significant increase in the risk of febrile neutropenia. Two recent meta-analyses also demonstrated that small molecular VEGF-receptor tyrosine-kinase inhibitors, sorafenib and sunitinib, was associated with a significantly increased risk

of hematologic toxicities, including neutropenia (sorafenib: all-grade RR1.69; 95%CI, 1.33–2.17; high-grade RR 1.61; 95%CI, 1.02–2.57; sunitinib: all-grade RR 3.58; 95%CI, 1.71–7.49; high-grade, RR3.32; 95%CI, 1.60–6.90) [69,70]. Another potential explanation is that inhibition of the VEGF signal pathway could affect the function of immune cells that are present in the tumor microenvironment and, consequently, it could affect the host response to infections [16,17]. Furthermore, inhibition of VEGF receptor could block hematopoietic stem-cell cycling, differentiation and hematopoietic recovery after bone-marrow suppression [71]. Recently, a study demonstrated a significantly impaired repopulation of the hematopoietic compartment after treatment with cytotoxic chemotherapy in a mouse model in which VEGF receptors 1 and 2 were blocked. The risk of

Table 4 Relative risk of severe specific infectious events with bevacizumab. Studies, n

Unspecified Specified Febrile neutropenia Fistula/abscess Pneumonia Colitis infection Sepsis

14 26 20 4 8 1 1

High-grade infectious events, n/total, n Bevacizumab

Control

283/4728 510/16,690 431/10,122 42/4218 37/1742 0/504 0/104

151/4210 279/13,482 236/8407 11/2785 27/1685 2/505 3/100

RR (95%CI)

p-Value

1.69 (1.39–2.04) 1.55 (1.34–1.79) 1.57 (1.34–1.84) 2.13 (1.06–4.27) 1.26 (0.77–2.08) 0.20 (0.01–4.16) 0.14 (0.007–2.63)

<0.001 <0.001 <0.001 0.033 0.36 0.30 0.19

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myelosuppression and delayed bone marrow recovery is additive when VEGF blockade is used with cytotoxic agents such as 5-fluorouracil, carboplatin and adriamycin [72]. These findings are noted in several forms of anti-VEGF blockade, including the inhibition of the tyrosine-kinase (TK) domain of the receptor or through antibodies directed to the VEGF ligand, such as bevacizumab. Our results are consistent with these preclinical observations and corroborate the hypothesis that VEGF blockade in vivo might increase the risk of infections. However, further studies are still needed to investigate the mechanism of infections with VEGF inhibitors. Risk factors for severe infections (≥ grade 3) associated with bevacizumab are poorly understood. We carried out a subgroup analysis to identify potential risk factors for bevacizumab-related infection. When stratified by tumor type, there is a significantly increased risk of developing high-grade infections with bevacizumab in colorectal cancer, non-small-cell lung cancer, breast cancer and gastric cancer. Interestingly, no increased risk of high-grade infections is observed in renal-cell carcinoma. We also find that the use of bevacizumab significantly increases the risk of developing high-grade infections when used in conjunction with taxanes, capecitabine, gemcitabine and oxaliplatin. Additionally, no significant differences in the risk of high-grade infections with bevacizumab are found according to bevacizumab dosage, treatment line and trial phase. Currently, there are no specific guidelines for the treatment of bevacizumab-induced infections because there is a dearth of controlled studies addressing the subject. With an increased RR of bevacizumab-related infections, it is clear that proper monitoring, immediate intervention, and effective management are crucial to achieve the maximal therapeutic benefit of bevacizumab. Before the initiation of bevacizumab, clinicians must fully treat patients with any active infection and must monitor patients during the course of bevacizumab treatment. Typically, patients with active or recently active infections are excluded from clinical trials; therefore, the true incidence of these infections could be widely underreported. More trials and reporting on these patients must be done in order to gain more insight into the management of this subgroup of patients. Despite the size of this meta-analysis, our study has the following limitations. First, all included studies exclude patients with poor renal, hematologic, and hepatic functions, and are performed mostly at major academic centers and research institutions; the analysis of these studies may not apply to patients with organ dysfunctions and in the community in common oncology practice. It is conceivable that the true incidences and risk of treatment-related infections from this study may be underestimated. Second, although infectious events are prospectively collected for each individual study, this analysis is retrospective, and there are potentially important differences among the studies, including

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differing tumor types, dosage of bevacizumab, periods of study conduct and study investigators. All of these would increase the clinical heterogeneity among included trials, which also makes the interpretation of a meta-analysis more problematic. Third, despite our attempts, the reported safety data do not disclose the specific etiologies of all the infections that occur. Finally, this is a meta-analysis at study level, and confounding factors at the patient level – such as comorbidities, previous treatment exposure and dose interruptions – cannot be assessed properly or incorporated into the analysis.

5. Conclusion In conclusion, bevacizumab treatment is associated with an increased risk of the patient developing all-grade and high-grade infections. The risk may vary with concomitantly administered drugs. Early detection and effective management of infections that can occur with bevacizumab are crucial for safer use of this drug. Further studies are still recommended to investigate risk reduction and the possible mechanism of bevacizumab-induced infections.

Conflicts of interest statement All authors declare that they have no potential conflicts of interests.

Author contributions Wei-Xiang Qi involved in the preparation of tables and figures. Wei-Xiang Qi in association with Shen Fu involved in designing the concept, writing and reviewing the manuscript, search and collection of data. Data analysis and interpretation were carried out by Qing Zhang and Xiao-Mao Guo. All authors approved the final manuscript.

Funding None.

Reviewers Dr Antonis Valachis, Mälarsjukhuset, Oncology, Mälarsjukhuset 63188 Eskilstuna, Eskilstuna, Sweden. Dr Matteo Santoni, Medical Oncology, AOU Ospedali Riuniti, Polytechnic University of the Marche Region, via Conca 71, I-60126 Ancona, Italy.

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Dr Benjamin A. Gatrell, Montefiore Medical Center, 111 East 210th Street, Hofheimer Main, Room 100, Bronx, NY 10467, United States. Dr Linda Elting, Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Blvd (Unit 447), Houston, TX 77030, United States.

Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/ j.critrevonc.2015.02.007.

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Biography Shen Fu, M.D., Ph.D., is the vice director of radiation oncology at Fudan University Shanghai Cancer Center

and Chairman of Radiation Oncology Department, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Hospital. He is the Vice President of Shanghai Medical Association Committee of Radiation Therapy. He has expertise in the field of prostate cancer radiation therapy. He is also interested in the development of novel agents in cancer.