Yingwei Xie1, Zhiliang Chen1, Qiyu Zhong1, Yuqing Chen2, Wentai Shangguan1, Wenlian Xie1. 1. Department of Urology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China. 2. Department of Pathology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Abstract
BACKGROUND: Immune checkpoint inhibitors (ICIs) have shown promising results for the second-line treatment of metastatic renal cell carcinoma (mRCC). Several randomized controlled trials have so far also evaluated the efficacy of ICIs for first-line treatment of mRCC. In this study, we conducted a meta-analysis of relevant studies to further clarify the efficacy and safety of ICIs combined with anti-angiogenic drugs for the treatment of mRCC. METHODS: We searched the PubMed, Embase, and Cochrane libraries for RCT trials of ICIs combined with anti-angiogenic drugs for first-line treatment of mRCC published before November 20, 2019. A meta-analysis was conducted based on methodological recommendations by the Cochrane Collaboration. RESULTS: Four articles with a total of 2,967 patients met the inclusion criteria. Our meta-analysis revealed that progression-free survival (PFS) and objective response rate (ORR) were significantly improved in the experimental group while there was no significant difference in overall survival (OS) (HR 0.75, 95% CI: 0.67-0.84; HR 1.43, 95% CI: 1.07-1.91; HR 0.74, 95% CI: 0.53-1.03). After stratification for PD-L1 expression, OS, PFS, and ORR of PD-L1 positive patients were significantly increased in the experimental group (HR 0.74, 95% CI: 0.56-0.96; HR 1.66, 95% CI: 1.11-2.49; HR 0.65, 95% CI: 0.57-0.75). CONCLUSIONS: Immunological checkpoint inhibitors combined with anti-angiogenic drugs as a first-line treatment for mRCC improve PFS and ORR. This effect is more pronounced in PD-L1 positive patients, where ICIs also improve OS. ICIs do not increase the incidence of adverse events. 2021 Translational Andrology and Urology. All rights reserved.
BACKGROUND: Immune checkpoint inhibitors (ICIs) have shown promising results for the second-line treatment of metastatic renal cell carcinoma (mRCC). Several randomized controlled trials have so far also evaluated the efficacy of ICIs for first-line treatment of mRCC. In this study, we conducted a meta-analysis of relevant studies to further clarify the efficacy and safety of ICIs combined with anti-angiogenic drugs for the treatment of mRCC. METHODS: We searched the PubMed, Embase, and Cochrane libraries for RCT trials of ICIs combined with anti-angiogenic drugs for first-line treatment of mRCC published before November 20, 2019. A meta-analysis was conducted based on methodological recommendations by the Cochrane Collaboration. RESULTS: Four articles with a total of 2,967 patients met the inclusion criteria. Our meta-analysis revealed that progression-free survival (PFS) and objective response rate (ORR) were significantly improved in the experimental group while there was no significant difference in overall survival (OS) (HR 0.75, 95% CI: 0.67-0.84; HR 1.43, 95% CI: 1.07-1.91; HR 0.74, 95% CI: 0.53-1.03). After stratification for PD-L1 expression, OS, PFS, and ORR of PD-L1 positive patients were significantly increased in the experimental group (HR 0.74, 95% CI: 0.56-0.96; HR 1.66, 95% CI: 1.11-2.49; HR 0.65, 95% CI: 0.57-0.75). CONCLUSIONS: Immunological checkpoint inhibitors combined with anti-angiogenic drugs as a first-line treatment for mRCC improve PFS and ORR. This effect is more pronounced in PD-L1 positive patients, where ICIs also improve OS. ICIs do not increase the incidence of adverse events. 2021 Translational Andrology and Urology. All rights reserved.
Entities:
Keywords:
Immune checkpoint inhibitors (ICIs); anti-angiogenic drugs; meta-analysis; renal cancer
Renal cell carcinoma (RCC) is a common tumor and originates from tubular epithelial cells (1). According to the latest cancer statistics released at CA Cancer J Clin in 2016, the number of new cases of renal cancer in China is 66,800, and the number of deaths was 23,400, ranking 15th and 17th respectively in population morbidity and mortality (2). Renal cancer is not sensitive to radiotherapy and chemotherapy. For early stage renal cancer, surgical resection is the most effective treatment, but nearly one-third of patients have had distant metastases at the time of diagnosis, and even if they have undergone surgery, 30% of patients still have tumor recurrence or metastasis (2).Currently, targeted drug therapy and immunotherapy were used to treat metastatic renal cell carcinoma (mRCC). Molecular targeted drug therapy targeting VEGF, mTOR and other targets had achieved positive results (3). However, the final destination of targeted drug therapy in clinical applications was almost all patients with drug resistance, which leaded to the failure of targeted therapy.In recent years, immunological checkpoint inhibitors (ICIs) have continued to develop. Inhibitors of programmed cell death protein 1 (PD-1) and its ligand (PD-L1) had shown significant efficacy in the treatment of mRCC. They improved the prognosis of patients after failed targeted therapy and effectively prolong their survival (4). Some studies had shown that anti-angiogenic drugs may have a role in regulating the immune system, and the combination of ICIs will enhance the effectiveness of the latter (5-7). Preliminary clinical trials have shown that combined use of ICIs and anti-angiogenic drugs as first-line therapy can improve progression-free survival (PFS) and objective response rate (ORR) in patients with mRCC (8-11). Thus, in this study, we have performed a meta-analysis of the available evidence in order to assess the efficacy and safety of ICIs combined with anti-angiogenic drugs as first-line therapy for mRCC. We present the following article in accordance with the PRISMA reporting checklist (available at http://dx.doi.org/10.21037/tau-20-969) (12).
Methods
Literature search
We searched PubMed, Embase, the Cochrane Library databases, Web of Science and grey literature for studies published before November 20, 2019. Queries were structured as follows: “Nivolumab” or “Pembrolizumab” or “Atezolizumab” or “Avelumab” or “immunological checkpoint inhibitors” or “immunotherapy” or “ICIs” or “anti-PD-L1” and “renal cell cancer” or “renal cell carcinoma” or “kidney tumor”. If necessary, we contacted the appropriate authors for more information. The studies we searched included only Phase II or Phase III studies. Computer searches retrieved review articles, and the main research cited in these articles was manually searched.
Inclusion and exclusion criteria
The two authors independently screened out each study. If there is any dispute, the decision should be made after consultation with the third author. Studies were included based on the inclusion criteria: English publication; RCT; immunological checkpoint inhibitor combined with anti-angiogenic drugs as the experimental group; first-line metastatic clear cell renal cell carcinoma (mccRCC) participants; The primary outcome was overall survival (OS), PFS, and ORR, and the secondary outcome was adverse events.The exclusion criteria were as follows: animal studies; non-randomized studies; combination drugs were not anti-angiogenic drugs; studies were not first lines of treatment for mRCC.
Data extraction
We extracted relevant data, including trial name, first author, year of publication, patient characteristics, study design, medication regimen, mean follow-up time, survival outcomes expressed as OS and PFS, ORRs, patients with adverse events total.
Quality assessment
The Cochrane Collaborative Risk Bias Assessment Tool was used to assess the quality of clinical trials (13). The quality of the study was judged based on five domains (random sequence generation, allocation concealment, outcome evaluation blindness, result data integrity, and selective reporting of research results). The evaluator assessed each study for a low, high, or unclear risk of bias. Low-risk studies in at least three areas are considered at low-risk of bias, while studies in ≤2 low-risk areas are considered to be at some or high risk of bias. The literature quality evaluation was carried out by two authors.
Statistical analysis
Meta-analysis was performed using the Stata SE12.0 software. Following a heterogeneity test, if I2<50% and P>0.1, a fixed effect model was used for analysis; if I2>50% and P<0.1, a random effect model was used for analysis, and the forest map of the meta-analysis was drawn. Descriptive analysis was required if the indicators were too heterogeneous or the indicators could not be combined. Categorical variable relationships were analyzed using relative risk (RR) and its 95% confidence interval (CI). Each study calculated time to event variables, including OS, PFS, and HR with 95% CI. P<0.05 was considered to be statistically significant. Harbord and Egger tests were used to evaluate the potential publication bias.
Results
The detailed process of study selection is shown in the flow diagram (). A total of 4 studies (8-11) were eventually included in this analysis. summarizes the characteristics of these studies. In all studies, sunitinib alone was used in the control group. The Cochrane Collaboration risk bias assessment score was 5, indicating good quality of the included studies. Due to the small number of trials included, there was no estimate of publication bias.
Figure 1
Flow diagram of the study search and selection.
Table 1
Characteristics of the analysed trials
First author
Item number
Number of patients
Cancer type
Age, years
PD-L1+
Experimental group
Control group
Follow-up time
Evaluation index
Risk bias
McDermott 2018 (8)
IMmotion150
305
mRCC
58
IHC ≥1%
Atezolizumab (1,200 mg) + bevacizumab (15 mg/kg) every three weeks, or atezolizumab (1,200 mg) every 3 weeks
Pembrolizumab (200 mg) once every 3 weeks + axitinib (5 mg) twice daily
Sunitinib (50 mg) once daily for 4 weeks
12.8
OS, PFS, ORR
5
Rini 2019 (11)
IMmotion151
915
mRCC
61
IHC ≥1%
Atezolizumab (1,200 mg) + bevacizumab (15 mg/kg) once every 3 weeks
Sunitinib (50 mg) once daily for 4 weeks
24
PFS, OS, ORR
5
IHC, Immunohistochemistry; PD-L1, programmed death ligand 1; ORR, objective response rate; OS, overall survival; PFS, progression free survival; DOR, duration of overall response; NR, not report.
Flow diagram of the study search and selection.IHC, Immunohistochemistry; PD-L1, programmed death ligand 1; ORR, objective response rate; OS, overall survival; PFS, progression free survival; DOR, duration of overall response; NR, not report.Based on our research requirements, 51 cases treated with atezolizumab were excluded from the study by McDermott (8), leaving a remaining total of 2,916 cases in our analysis. The PD-L1 status was assessed in 2,825 patients, of which 1,529 (54.12%) were positive. Three studies reported OS, 4 studies reported PFS, 4 studies reported ORR, and 4 reported adverse events.There was no statistically significant improvement in the OS of the experimental group (HR 0.74, 95% CI: 0.53–1.03, I2=75.0%) (). Stratification of patients by PD-L1 status revealed that OS was significantly improved in PD-L1 positive patients (HR 0.74, 95% CI: 0.56–0.96, I2=29.5%), while the OS was not statistically significant improvement in PD-L1 negative patients (HR 0.80, 95% CI: 0.53–1.22, I2=56.2%) ().
Figure 2
Meta-analysis of HRs for OS comparing ICIs combined with anti-angiogenic drugs and sunitinib. (A) Unselected patients; (B) PD-L1 positive and negative patients. HR, hazard ratio; OS, overall survival; ICIs, immune checkpoint inhibitors.
Meta-analysis of HRs for OS comparing ICIs combined with anti-angiogenic drugs and sunitinib. (A) Unselected patients; (B) PD-L1 positive and negative patients. HR, hazard ratio; OS, overall survival; ICIs, immune checkpoint inhibitors.PFS was significantly improved in the experimental group (HR 0.75, 95% CI: 0.67–0.84, I2=35.1%) (). When stratifying patients by PD-L1 status, PFS was significantly improved in PD-L1 positive patients (HR 0.65, 95% CI: 0.57–0.75, I2=0.0%) but not in PD-L1 negative patients (HR 0.91, 95% CI: 0.76 to 1.09, I2=0.0%) ().
Figure 3
Meta-analysis of HRs for PFS comparing ICIs combined with anti-angiogenic drugs and sunitinib. (A) Unselected patients; (B) PD-L1 positive and negative patients. HR, hazard ratio; PFS, progression-free survival; ICIs, immune checkpoint inhibitors.
Meta-analysis of HRs for PFS comparing ICIs combined with anti-angiogenic drugs and sunitinib. (A) Unselected patients; (B) PD-L1 positive and negative patients. HR, hazard ratio; PFS, progression-free survival; ICIs, immune checkpoint inhibitors.ORR was reported in 1,131/2,854 (39.63%) patients over the four studies. These included 681/1,427 patients (47.72%) in the experimental group, and 450/1,525 patients (29.51%) in the control group. Three studies reported an ORR in patients with positive PD-L1 expression. We analyzed the ORR and found that it was significantly increased in the experimental group overall (RR 1.43, 95% CI: 1.07–1.91, I2=87.9%) (), and also significantly increased in the subgroup of PD-L1 positive patients (RR 1.66, 95% CI: 1.11–2.49, I2=80.8%) (). These analyses showed that the ORR of ICIs combined with antiangiogenic drugs was 1.43 times that of sunitinib monotherapy overall (1.66 times in PD-L1-positive patients).
Figure 4
Meta-analysis of HRs for ORR comparing ICIs combined with anti-angiogenic drugs and sunitinib. (A) Unselected patients; (B) PD-L1 positive patients. HR, hazard ratio; ORR, objective response rate; ICIs, immune checkpoint inhibitors.
Meta-analysis of HRs for ORR comparing ICIs combined with anti-angiogenic drugs and sunitinib. (A) Unselected patients; (B) PD-L1 positive patients. HR, hazard ratio; ORR, objective response rate; ICIs, immune checkpoint inhibitors.Adverse events of grade 3–5 were reported in 1,843/2,825 (65.23%) patients in the four analyzed studies. These were reported to have occurred in 880/1,415 patients (62.19%) in the experimental group, and 963/1,410 patients (68.30%) in the control group. We analyzed the adverse reactions and found no significant difference between the two groups (RR 0.93, 95% CI: 0.81–1.08, I85.4%) (). Two of the assessed studies reported incidents of adverse reactions in detail. We therefore selected the top ten adverse events of grade ≥3 in each group (). As shown in , the most common adverse reaction for each group was hypertension.
Figure 5
Meta-analysis of HRs for adverse events (≥ Grade 3) comparing ICIs combined with anti-angiogenic drugs and sunitinib. HR, hazard ratio; ICIs, immune checkpoint inhibitors.
Table 2
Adverse events (≥ Grade 3) comparing ICIs combined with anti-angiogenic drugs and sunitinib
Adverse events
%
Motzer 2019 (9)
Avelumab + Axitinib
Hypertension
25.6
Diarrhea
6.7
Increased alanine aminotransferase level
6
Palmar-plantar erythrodysesthesia syndrome
5.8
Increased aspartate aminotransferase level
3.9
Fatigue
3.5
Dyspnea
3
Decreased weight
2.8
Asthenia
2.5
Decreased appetite
2.1
Sunitinib
Hypertension
17.1
Anemia
8.2
Neutropenia
8
Thrombocytopenia
6.2
Decreased neutrophil count
5.7
Decreased platelet count
5
Palmar-plantar erythrodysesthesia syndrome
4.3
Fatigue
3.6
Asthenia
3
Diarrhea
2.7
Rini 2019 (10)
Pembrolizumab + Axitinib
Hypertension
22.1
Alanine aminotransferase increased
13.3
Diarrhea
9.1
Aspartate aminotransferase increased
7
Palmar-plantar erythrodysesthesia syndrome
5.1
Weight decreased
3
Proteinuria
2.8
Fatigue
2.8
Asthenia
2.6
Dyspnea
1.6
Sunitinib
Hypertension
19.3
Platelet count decreased
7.3
Neutrophil count decreased
6.8
Neutropenia
6.6
Fatigue
6.6
Thrombocytopenia
5.9
Anemia
4.9
Diarrhea
4.7
Palmar-plantar erythrodysesthesia syndrome
3.8
Alanine aminotransferase increased
3.1
ICIs, immune checkpoint inhibitors.
Meta-analysis of HRs for adverse events (≥ Grade 3) comparing ICIs combined with anti-angiogenic drugs and sunitinib. HR, hazard ratio; ICIs, immune checkpoint inhibitors.ICIs, immune checkpoint inhibitors.
Discussion
In recent years, the application of ICIs, such as anti-PD-1 or PD-L1 antibodies, has caused about a major breakthrough for the treatment of mRCC (14). In this study, we evaluated immunological checkpoint inhibitors combined with anti-angiogenic drugs for first-line treatment of mRCC. We conducted a meta-analysis of the four relevant studies and found that the combination of ICIs with anti-angiogenic drugs improved PFS and ORR in patients with mRCC. Overall, the OS was not significant difference between the control and experimental groups. Stratification based on PD-L1 expression revealed that addition of ICIs to standard care significantly improved OS, PFS, and ORR in PD-L1 positive patients. In addition, we analyzed adverse events and found no difference between the experimental and control group. This study therefore provides further evidence for the clinical efficacy and safety of ICIs in combination with anti-angiogenic drugs for first-line treatment of mRCC.Several clinical studies combining anti-angiogenic drugs with checkpoint therapies have reported improvements in tumor immune responses with associated clinical benefits. Bevacizumab and ipilimumab combination therapy had been reported to result in increased expression of tumor endothelial cell adhesion molecules and increased intracellular immune cell infiltration in the treatment of advanced metastatic melanoma, which was furthermore related to clinical response (15). In RCC, combination studies using bevacizumab with the anti-PDL1 therapeutic, as well as sunitinib with nivolumab, have been reported (16,17). Bevacizumab treatment has been shown to result in increased intratumoral T cells, and T cell levels were further increased upon combination with MPDL3280A (18). Our study further demonstrates the efficacy of ICIs in combination with anti-angiogenic drugs for first-line treatment of mRCC.Our study found that positive effects of ICIs combined with anti-angiogenic drugs are more pronounced in patients with positive PD-L1 expression. This raised the question where ICI efficacy may be related to PD-L1 expression. In our current study we found that approximately 40–50% of ccRCC cases had positive PD-L1 status (19-21). It has been reported that patients with PD-L1 overexpression have a poor prognosis, and a previous meta-analysis showed that PD-L1 expression is a negative prognostic factor in renal cancer. Furthermore, PD-L1 expression has also been associated more aggressive clinical features of tumors in RCC patients (22). Although PD-L1 status has been studied as a prognostic factor in several tumor types, its role as a predictive marker of response to therapy in patients treated with ICIs is unclear. A meta-analysis involving 20 trials and approximately 6,000 patients with different cancer types, including RCC, reported no significant difference in the response to treatment of RCC patients stratified by PD-L1 status (23). In the CheckMate 025 study, PD-L1 status did not affect efficacy of nicurumab and everolimus (4). Conversely, in the CheckMate 214 study, a beneficial effect of nivolumab and ipilimumab was observed on OS in moderate and low risk PD-L1 positive patients (9). A phase Ib trial assessing the use of axitinib and avemumab in mRCC showed that patients with PD-L1 >1% had a higher ORR (24). These differences may be explained by the intratumoral heterogeneity of PD-L1 expression. PD-L1 is generally assessed in the primary nephrectomy, but in about 20% of patients with metastatic renal cancer, PD-L1 staining shows a discrepancy between primary tumor and corresponding metastasis. Conversely, when only assessing PD-L1 expression in tumor metastasis samples from the same patient, higher consistency was found (25).However, several limitations should be acknowledged. First, the study is based on a meta-analysis of the literature rather than direct patient data. Second, our meta-analysis involved only a limited number of studies and these studies used different medications in experimental groups. Third, IMDC subgroups and geographical features could have been important confounding factors affecting the analysis. In addition, it should be mentioned that PD-L1 status assessments still suffer from shortcomings, such as intratumoral heterogeneity mentioned above.
Conclusions
Our meta-analysis reveals efficacy and safety of the combination of ICIs and anti-angiogenic drugs for first-line treatment for mccRCC patients. This therapeutic regimen can improve OS, PFS, ORR and ORR in mccRCC patients with positive PD-L1 status. Our analysis revealed that the combination of ICIs and anti-angiogenic drugs did not increase the incidence of adverse events However, more prospective studies are needed to further confirm these findings, as well as studies involving other types of renal cancer.The article’s supplementary files as
Authors: Brian I Rini; Elizabeth R Plimack; Viktor Stus; Rustem Gafanov; Robert Hawkins; Dmitry Nosov; Frédéric Pouliot; Boris Alekseev; Denis Soulières; Bohuslav Melichar; Ihor Vynnychenko; Anna Kryzhanivska; Igor Bondarenko; Sergio J Azevedo; Delphine Borchiellini; Cezary Szczylik; Maurice Markus; Raymond S McDermott; Jens Bedke; Sophie Tartas; Yen-Hwa Chang; Satoshi Tamada; Qiong Shou; Rodolfo F Perini; Mei Chen; Michael B Atkins; Thomas Powles Journal: N Engl J Med Date: 2019-02-16 Impact factor: 91.245
Authors: Brian I Rini; Thomas Powles; Michael B Atkins; Bernard Escudier; David F McDermott; Cristina Suarez; Sergio Bracarda; Walter M Stadler; Frede Donskov; Jae Lyun Lee; Robert Hawkins; Alain Ravaud; Boris Alekseev; Michael Staehler; Motohide Uemura; Ugo De Giorgi; Begoña Mellado; Camillo Porta; Bohuslav Melichar; Howard Gurney; Jens Bedke; Toni K Choueiri; Francis Parnis; Tarik Khaznadar; Alpa Thobhani; Shi Li; Elisabeth Piault-Louis; Gretchen Frantz; Mahrukh Huseni; Christina Schiff; Marjorie C Green; Robert J Motzer Journal: Lancet Date: 2019-05-09 Impact factor: 79.321
Authors: Marcella Callea; Laurence Albiges; Mamta Gupta; Su-Chun Cheng; Elizabeth M Genega; André P Fay; Jiaxi Song; Ingrid Carvo; Rupal S Bhatt; Michael B Atkins; F Stephen Hodi; Toni K Choueiri; David F McDermott; Gordon J Freeman; Sabina Signoretti Journal: Cancer Immunol Res Date: 2015-05-26 Impact factor: 11.151
Authors: Alessandro Liberati; Douglas G Altman; Jennifer Tetzlaff; Cynthia Mulrow; Peter C Gøtzsche; John P A Ioannidis; Mike Clarke; P J Devereaux; Jos Kleijnen; David Moher Journal: PLoS Med Date: 2009-07-21 Impact factor: 11.069
Authors: Robert J Motzer; Konstantin Penkov; John Haanen; Brian Rini; Laurence Albiges; Matthew T Campbell; Balaji Venugopal; Christian Kollmannsberger; Sylvie Negrier; Motohide Uemura; Jae L Lee; Aleksandr Vasiliev; Wilson H Miller; Howard Gurney; Manuela Schmidinger; James Larkin; Michael B Atkins; Jens Bedke; Boris Alekseev; Jing Wang; Mariangela Mariani; Paul B Robbins; Aleksander Chudnovsky; Camilla Fowst; Subramanian Hariharan; Bo Huang; Alessandra di Pietro; Toni K Choueiri Journal: N Engl J Med Date: 2019-02-16 Impact factor: 91.245