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BMC Urology

, 19:49 | Cite as

Hypertension as a prognostic factor in metastatic renal cell carcinoma treated with tyrosine kinase inhibitors: a systematic review and meta-analysis

  • Yu Liu
  • Liang Zhou
  • Yuntian Chen
  • Banghua Liao
  • Donghui Ye
  • Kunjie WangEmail author
  • Hong Li
Open Access
Research article
  • 145 Downloads
Part of the following topical collections:
  1. Urological oncology

Abstract

Background

Conflicting evidence exists regarding the effect of hypertension on the prognosis of metastatic renal cell carcinoma (mRCC) patients treated with tyrosine kinase inhibitors (TKIs). This study aimed to assess the predictive value of TKIs-induced hypertension in patients with mRCC.

Methods

This study was registered in PROSPERO (CRD42019129593). PubMed, Embase, Web of Science and the Cochrane Library database were searched with terms: “renal cell carcinoma”, “hypertension”, “blood pressure”, “tyrosine kinase inhibitor”, “sunitinib”, “axitinib”, “sorafenib” and “pazopanib” until March 21, 2019. Hazard Ratios (HR) and 95% confidence intervals (CI) for progression-free survival (PFS) or overall survival (OS) were extracted and analyzed with Stata 15.0 software. Heterogeneity was assessed using the I2 value. Meta-regression, subgroup analysis and sensitivity analysis were also performed to explore heterogeneity. Publication bias was assessed with funnel plots and precisely assessed by Egger’s and Begg’s tests. The quality of evidence of outcomes was generated according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE).

Results

A total of 4661 patients from 22 studies were included in the study. The results showed that the increase of blood pressure was an effective predictor for longer PFS (HR = 0.59, 95% CI: 0.48–0.71, p < 0.001; I2 = 77.3%) and OS (HR = 0.57, 95% CI: 0.45–0.70, p < 0.001; I2 = 77.4%) of patients with mRCC. Subgroup analysis revealed that patients receiving sunitinib and pazopanib could have longer PFS and OS.

Conclusions

This study indicated that TKIs-induced hypertension may be a good predictor for better prognosis of patients with mRCC receiving TKIs treatment, especially using sunitinib or pazopanib.

Keywords

Metastatic renal cell carcinoma Tyrosine kinase inhibitors Hypertension Prognosis Meta-analysis 

Abbreviations

AEs

Adverse events

BP

Blood pressure

CI

Confidence intervals

DBP

Diastolic blood pressure

ECOG PS

Eastern Cooperative Oncology Group performance status

GRADE

Grading of Recommendations Assessment, Development and Evaluation

HR

Hazard Ratios

MAP

Mean arterial blood pressure

mRCC

Metastatic renal cell carcinoma

MSKCC

Memorial Sloan Kettering Cancer Center

NO

Nitric oxide

NOS

Newcastle-Ottawa Scale

OS

Overall survival

PFS

Progression-free survival

RCC

Renal cell carcinoma

SBP

Systolic blood pressure

TKIs

Tyrosine kinase inhibitors

Background

Renal cell carcinoma (RCC) is the 9th most common cancer in men and 14th most common cancer in women worldwide [1]. Its incidence (3–6/100,000) and mortality (1.2–2.5/100,000) are increasing rapidly, which has a great negative effect on our society [2, 3]. In addition, about 25–30% of patients have evidence of metastasis upon its diagnosis [4]. Now, vascular endothelial growth factor receptor tyrosine kinase inhibitors (TKIs), like sunitinib, pazopanib, sorafenib or axitinib, are the favored medicine for metastatic RCC (mRCC). Several clinical trials showed that response to TKIs was uncertain (objective response rate was 31–67.4%) [5, 6, 7, 8], which indicated the existence of wide inter-individual variation and the lack of reliable factors for predicting the outcomes of mRCC patients. Therefore, a big challenge faced by urologists is how to predict the prognosis of mRCC patients receiving TKIs more precisely.

The occurrence of several adverse events (AEs) during TKIs therapy, such as hypertension, hand-foot syndrome or hypothyroidism, were shown to be correlated with the longer median progression-free survival (PFS) and overall survival (OS) of mRCC patients [9]. Hypertension during TKIs therapy was very common, with incidence ranging from 22 to 81% [9, 10]. Recently, a study found that RCC patients with longer median PFS (>5.3 months) demonstrated a significantly higher incidence of high-grade hypertension (a treatment-associated adverse event) than those with shorter PFS [11]. It indicated that TKIs-induced hypertension may be associated with improved prognosis [12, 13]. However, others reported insignificant results [14, 15]. In 2014, a systematic review and meta-analysis reported that the occurrence of hypertension due to sorafenib therapy may be associated with improved prognosis of patients with cancer. However, this study did not specifically focus on the mRCC patients. Thus, the association between TKIs-induced hypertension and prognosis of mRCC is still controversial. In the present study, we attempt to conduct a systematic review and meta-analysis to assess the predictive value of the TKIs-induced hypertension for PFS and OS in patients with mRCC during TKIs therapy.

Methods

Data sources and literature search strategy

We conducted this meta-analysis in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement. This study was registered in PROSPERO (CRD42019129593). A literature search was performed in the following databases: PubMed, Embase, Web of Science and the Cochrane Library database. The latest search was performed on March 21, 2019. The search keywords were (renal cell carcinoma) AND [(tyrosine kinase inhibitor) OR sunitinib OR axitinib OR sorafenib OR pazopanib] AND [hypertension OR (blood pressure). The resulted literatures were further scanned by Endnote X7 (Thomson Corporation, Canada) to exclude duplications followed by title and abstract screening. In addition, we manually searched the references of the literatures for additional eligible studies.

Inclusion and exclusion criteria

Studies were included in our meta-analysis if the following criteria were met: 1) mRCC patients were treated with TKIs; 2) studies compared Hazard Ratios (HR) between patients with or without TKIs-induced hypertension for PFS or OS.

Studies were excluded based on the following criteria: 1) reviews, meta-analysis, letters, comments, case reports or conference abstracts; 2) duplicated studies and repeated analysis; 3) studies lacking sufficient data for HR and their 95% confidence intervals (CI); 4) studies included mRCC patients received different therapeutic regimen, such as TKIs or radiotherapy.

Quality of original studies

We assessed the quality of the 22 included studies using the Newcastle-Ottawa Scale (NOS). The total score was 9 stars. Studies awarded 7–9 stars were rated as high-quality, 5–6 stars as moderate-quality, and < 5 stars as low-quality.

Data extraction

Eligible studies were read thoroughly and carefully to extract the following information, including first author, year, region, sample size, male/female ratio, mean age, histology, number of disease sites, prior nephrectomy, Memorial Sloan Kettering Cancer Center (MSKCC) score, Eastern Cooperative Oncology Group performance status (ECOG PS) score, definition of hypertension, type of analysis (univariate or multivariate), study design (prospective or retrospective), type of TKIs. The primary outcome was HR and 95% CI between patients with or without hypertension for PFS and secondary one for OS. The definition of PFS was time from initiation of TKIs therapy to disease progression or death. OS was defined as time from initiation of TKIs therapy to death. If a study provided both univariate and multivariate analysis results, the multivariate analysis would be selected to achieve higher accuracy. Any discrepancies were resolved by discussion with the third reviewer.

Data synthesis and statistical analysis

Data were extracted and analyzed with Stata 15.0 software (Stata Corporation, College Station, TX, USA). P value<0.05 was considered statistically significant. A merged HR greater than 1 indicated a poorer prognosis for mRCC patients. Heterogeneity was assessed using the I2. We considered I2 > 50% as an indicator of substantial heterogeneity. A random effects model and a fixed effects model were applied for I2>50% and I2<50%, respectively. Then, to determine which factors may contribute to heterogeneity, univariate and multivariate meta-regression analysis were performed. The possible factors were year, sample size, gender, mean age, country, ECOG PS, MSKCC score, histology, prior nephrectomy, Number of disease sites, type of analysis (univariate, multivariate), study design (retrospective, prospective), type of TKIs. Then, subgroup analysis was performed to investigate whether different sample size could explain the heterogeneity and whether relationship between hypertension and PFS or OS still exist in different TKIs subgroups. Factor with P value < 0.05 meant that it may be the source of heterogeneity. We did sensitivity analysis to find if some original studies may mainly contribute to the heterogeneity. Publication bias was assessed with funnel plots and precisely assessed by Egger’s and Begg’s tests.

Quality of evidence

The quality of evidence of the predictive effect of TKIs-induced hypertension for the outcomes in mRCC patients was assessed according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) [16].

Results

Study selection

The searching process is shown in Additional file 1: Figure S1. A total of 982 studies were searched in the database. We excluded 345 duplicated articles. After screening title and abstract, 26 relevant studies were identified. In addition, three relevant studies were obtained from the references and seven articles were excluded due to lack of HR and 95% CI for PFS or OS. Finally, 22 studies were selected for the meta-analysis.

Study characteristics and quality

The baseline characteristics of these studies were demonstrated in Table 1. All the studies were published between 2011 and 2017. Of them, 3 were prospective and 19were retrospective. The sample size ranged from 28 to 770 patients. The total number of included patients was 4661 and hypertension occurred in 2932 (62.9%). The male/female ratio included in each study ranged from 1.4 to 3.5%, and the median age of the study patients was between 54 years and 66 years. The histology of most RCC is clear cell (61–100%). Most patients had received nephrectomy, cytokine therapy, targeted therapy or radiation therapy. Among the 22 studies providing HR, four reported univariate HR, which did not adjust for the potential confounding factors. The standard of hypertension or BP increasement during TKIs therapy varied between studies, including systolic blood pressure (SBP) ≥140/135 mmHg, diastolic blood pressure (DBP) ≥90/85 mmHg, mean arterial blood pressure (MAP) > 110 mmHg, an increase in BP (SBP, DBP, MAP) > 10/15 mmHg from baseline, or grades of hypertension according to National Cancer Institute Common Terminology Criteria for Adverse Events Version 3.0 or 4.0 [34, 35]. The quality of the studies varied from a NOS score of 6 to 9, most of which were high-quality (Table 2).
Table 1

Baseline characteristics of eligible studies in the meta-analyses

Study

Year

Country

Study design

Sample size

Male/ Female ratio

Mean age

Histology (clear cell%)

Survival analysis

Definition of hypertension

Type of analysis

TKIs

Quality Assessment (NOS Score = 9)

Rini (a) [10]

2011

the USA

R

534

2.3

60.6

98%

PFS, OS

SBP ≥ 140 mmHg, DBP ≥ 90 mmHg

multivariate

SUN

7

Szmit [12]

2011

Poland

R

111

3.0

55.9

100%

PFS, OS

BP ≥ 140/90 mmHg

univariate

SUN

9

Bono [17]

2011

Finland

R

64

1.7

64

92%

PFS

BP > 150/100 mmHg OR blood pressure requiring intensifi cation of pre-existing anti-hypertensive medication.

multivariate

SUN

7

Fujita [18]

2012

Japan

R

41

2.7

64

100%

PFS

univariate

SUN

7

Eechoute [19]

2012

Netherlands

R

158

1.7

60

87%

PFS, OS

SBP > 140 mmHg, DBP > 90 mmHg, MAP > 110 mmHg

multivariate

SUN

7

Rini (b) [13]

2013

the USA

R

168

2.5

60

PFS, OS

DBP ≥90 mmHg

multivariate

AXI

7

Motzer (a) [20]

2013

the USA

P

350

2.8

61

100%

PFS, OS

SBP > 140 mmHg, DBP > 90 mmHg

multivariate

AXI

6

Motzer (b) [20]

2013

the USA

P

336

2.5

61

100%

PFS, OS

SBP > 140 mmHg, DBP > 90 mmHg

multivariate

SOR

6

Hong [21]

2013

China

R

136

2.0

56

93%

OS

Hypertension class III/IV

multivariate

SUN

7

Nakano [22]

2013

Japan

R

36

3.5

65.8

61%

PFS

grade 1–3 (NCI-CTCAE, version 3.0)

multivariate

SOR

7

Fujita [23]

2014

Japan

R

44

2.7

63.5

95%

PFS

multivariate

SUN

7

Eto [24]

2014

Japan

R

64

2.2

63

97%

OS

DBP ≥90 mmHg

AXI

7

Rini (c) [25]

2015

the USA

P

203

2.0

61.9

PFS

DBP change from baseline ≥10/15 mmHg

AXI

7

Zhang (a) [26]

2015

China

R

256

2.5

58

79%

OS

multivariate

SOR

7

Kucharz [27]

2015

Poland

R

28

2.1

65

PFS

office SBP ≥140 and/or DBP ≥90 mmHg; home SBP ≥135 and/or DPB ≥85 mmHg; pre-existing medication-controlled arterial hypertension and required additional antihypertensive medication during treatment

multivariate

SUN

7

Izzedine [28]

2015

France

R

212

3.4

57.7

86%

PFS, OS

multivariate

SUN

8

Donskov [29]

2015

the USA

R

770

2.6

60

98%

PFS

SBP ≥ 140 mmHg

multivariate

SUN

7

Zhang (b) [30]

2016

China

R

134

2.4

59.8

77%

OS

multivariate

SOR

7

Goldstein (a) [14]

2016

Australia

R

479

2.2

59.5

PFS, OS

MAP change from baseline>10 mmHg

univariate

PAZ

9

Goldstein (b) [14]

2016

Australia

R

506

2.6187

61

PFS, OS

SBP > 140 mm H, DBP > 90 mmHg, MAP change from baseline>10 mmHg, SBP change from baseline>10 mmHg

univariate

PAZ

9

Goldstein (c) [14]

2016

Australia

R

475

3.3394

60.9

PFS, OS

SBP > 140 mm H, DBP > 90 mmHg, MAP change from baseline>10 mmHg, SBP change from baseline>10 mmHg

univariate

SUN

9

Cecere [31]

2016

Italy

R

38

1.375

61

84.2%

OS

grade ≥ 3 (NCI-CTCAE, version 4.0)

multivariate

PAZ

7

Miyake [32]

2016

Japan

R

50

4.0000

64

80%

PFS

SBP ≥ 140 or DBP ≥ 90 mmHg

multivariate

SUN

7

Fukuda [15]

2016

Japan

R

62

2.4444

66

92%

PFS, OS

univariate

SUN

7

Matias [33]

2017

France

P

106

2.3125

54

90%

PFS, OS

grade ≥ 3 (NCI-CTCAE, version 4.0)

univariate

AXI

7

R Retrospective, P Prospective, PFS Progression-free survival, OS Overall survival, SBP Systolic blood pressure, DBP Diastolic blood pressure, MAP ≈ 2/3 DBP + 1/3 SBP; SUN Sunitinib, AXI Axitinib, SOR Sorafenib, PAZ Pazopanib, NCI-CTCAE National Cancer Institute Common Terminology Criteria for Adverse Events

—: The data were not available in this study

Table 2

Newcastle-Ottawa scale score of the reviewed studies

Study

Selection (4 stars)

Comparability (2 stars)

Outcome (3 stars)

Total score

Representativeness of the hypertensive cohort

Selection of the non-hypertensive cohort

Ascertainment of hypertension

Demonstration that outcome of interest was not present at start of study

Assessment of outcome

Was follow up long enough for outcomes to occur?

Adequacy of follow up of cohort

Rini (a)

7

Szmit

★★

9

Bono

7

Fujita

7

Eechoute

7

Rini (b)

7

Motzer

6

Hong

7

Nakano

7

Fujita

7

Eto

7

Rini (c)

7

Zhang (a)

7

Kucharz

7

Izzedine

8

Donskov

7

Zhang (b)

7

Goldstein

★★

9

Miyake

7

Fukuda

7

Matias

7

—: The data were not available in this study

Relationship between TKIs-induced hypertension and PFS or OS of mRCC patients

HR of PFS and OS were quantitatively synthesized and data were shown in Figs. 1 and 2. Elevated blood pressure was positively correlated with better PFS (HR = 0.59, 95% CI: 0.48–0.71, p < 0.001; I2 = 77.3%) and OS (HR = 0.57, 95% CI: 0.45–0.70, p < 0.001; I2 = 77.4%). It meant that patients developing hypertension may have a lower mortality risk and live longer without progression of mRCC. The heterogeneity was obvious between studies.
Fig. 1

Forest plot reflects the association between TKIs -induced hypertension and oncologic outcomes (progression free survival) in different TKIs subgroups (1: axitinib; 2: sorafenib; 3: sunitinib; 4: pazopanib)

Fig. 2

Forest plot reflects the association between TKIs-induced hypertension and oncologic outcomes (overall survival) in different TKIs subgroups (1: axitinib; 2: sorafenib; 3: sunitinib; 4: pazopanib)

Meta-regression analysis

Univariate meta-regression analysis was performed for PFS and results were showed in Table 3. Among the variables above mentioned, only sample size (Adjusted R2 = 27.34%, P = 0.019) might contribute to the inter-study heterogeneity, while others did not (P = 0.052–0.942).
Table 3

Meta-regression and subgroup analyses of pooled hazard ratios for progression-free survival

Subgroup

Meta-regression

Pooled HR of PFS

Heterogeneity

No. of studies

Coefficient

Standard error

T value

P value

Tau2

Adjusted R2

HR (95% CI)

P value

I2

P value

Year

20

0.060

0.228

0.26

0.795

0.182

−8.86%

    

 2011–2014

       

0.56 (0.40–0.77)

<0.001

83.00%

<0.001

 2015–2017

       

0.61 (0.48–0.77)

<0.001

73.60%

<0.001

Sample size

20

0.507

0.197

2.57

0.019

0.122

27.34%

    

 <200

       

0.43 (0.30–0.61)

<0.001

72.10%

<0.001

 ≥200

       

0.73 (0.60–0.89)

0.002

75%

<0.001

Gender (male/female ratio)

20

−0.117

0.228

−0.51

0.614

0.177

−5.64%

    

 <2.5

       

0.66 (0.53–0.82)

<0.001

54.50%

0.025

 ≥2.5

       

0.55 (0.40–0.74)

<0.001

84.70%

<0.001

Mean age

20

0.320

0.264

2.21

0.241

0.156

6.69%

    

 <60

       

0.44 (0.23–0.86)

0.015

89.40%

<0.001

 ≥60

       

0.64 (0.53–0.78)

<0.001

69.70%

<0.001

Country

20

0.168

0.301

0.56

0.584

0.173

−3.31%

    

 the USA, Europe

       

0.60 (0.49–0.74)

<0.001

81.40%

<0.001

 Asia

       

0.51 (0.31–0.83)

0.006

39.50%

0.158

ECOG PS (grade 0%)

20

0.036

0.133

0.27

0.79

0.182

−8.59%

    

 <0.5

       

0.35 (0.14–0.89)

0.028

87.20%

<0.001

 ≥0.5

       

0.64 (0.52–0.79)

<0.001

71.90%

<0.001

MSKCC score (favorable%)

20

0.231

0.111

2.08

0.052

0.123

26.74%

    

 <0.25

       

0.43 (0.21–0.87)

0.019

76%

0.002

 ≥0.25

       

0.86 (0.73–1.02)

0.076

40.30%

0.137

Histology (clear cell%)

20

−0.139

0.126

−1.11

0.283

0.166

1.11%

    

 <0.9

       

0.53 (0.39–0.71)

<0.001

29.30%

0.226

 ≥0.9

       

0.51 (0.33–0.79)

0.002

87.90%

<0.001

Prior nephrectomy (%)

20

−0.162

0.129

−1.25

0.226

0.166

1.16%

    

 <0.9

       

0.52 (0.40–0.67)

0.296

17.50%

<0.001

 ≥0.9

       

0.52 (0.33–0.81)

<0.001

89.30%

0.005

No. of disease sites (1%)

20

−0.253

0.139

−1.81

0.086

0.144

13.81%

    

 <0.2

       

0.41 (0.28–0.60)

<0.001

62.40%

0.047

 ≥0.2

       

0.52 (0.37–0.74)

<0.001

0

0.594

Type of analysis

20

−0.030

0.231

−0.13

0.898

0.182

−8.91%

    

 Univariate

       

0.59 (0.42–0.82)

0.002

82.70%

<0.001

 Multivariate

       

0.58 (0.46–0.75)

<0.001

74.50%

<0.001

Study design

20

0.343

0.257

1.34

0.198

0.157

6.32%

    

 Retrospective

       

0.54 (0.44–0.67)

<0.001

74.90%

<0.001

 Prospective

       

0.77 (0.53–1.12)

0.175

76.20%

0.006

Type of TKIs

20

−0.073

0.114

−0.64

0.942

0.178

−10.49%

    

 Axitinib

       

0.70 (0.48–1.03)

0.07

80.90%

0.001

 Sorafenib

       

0.86 (0.65–1.13)

0.277

0

0.339

 Sunitinib

       

0.47 (0.34–0.64)

<0.001

77.90%

<0.001

 Pazopanib

       

0.79 (0.66–0.94)

0.010

0

1.000

No. number, HR hazard ratio, PFS progression-free survival, ECOG PS Eastern Cooperative Oncology Group performance status, MSKCC score Memorial Sloan Kettering Cancer Center score

Multivariate meta-regression analysis revealed that P value of sample size changed to 0.025. The overall adjusted R2 was 74.84% (P = 0.239), which meant that all these factors together could account for 74.84% of heterogeneity.

Subgroup analysis

Subgroup analysis for PFS revealed that sample size could not change the subgroup heterogeneity significantly (I2 = 72.1 and 75%) (Table 3). In addition, for different TKIs, only patients with TKIs-induced hypertension in sunitinib subgroup (HR = 0.47, 95% CI: 0.34–0.64, p<0.001) and pazopanib subgroup (HR = 0.79, 95% CI: 0.66–0.94, p = 0.01) could have longer PFS. However, development of hypertension in four different TKIs subgroups could all predict longer OS, including sunitinib subgroup (HR = 0.48, 95% CI: 0.30–0.78, p = 0.003), pazopanib subgroup (HR = 0.73, 95% CI: 0.55–0.97, p = 0.032), axitinib subgroup (HR = 0.62, 95% CI: 0.43–0.88, p = 0.007) and sorafenib subgroup (HR = 0.66, 95% CI: 0.48–0.91, p = 0.010) (Figs. 1 and 2).

Sensitivity analysis

As shown in Fig. 3, study of “Szmit”, “Motzer (a)” and “Donskov” could affect the heterogeneity for PFS. We excluded these studies and found that I2 decreased to 44.6% (P = 0.03), with pooled HR = 0.665 (0.579–0.764, P = 0.025). Then, we reviewed these studies carefully to find something they had in common. Interestingly, most of the mRCC patients in these three studies had failed one previous cytokine immunotherapy. Maybe it was the reason for high heterogeneity.
Fig. 3

Sensitivity analysis of progression free survival for the evaluation of potential heterogeneity

Publication bias

We assessed the publication bias with funnel plot and Egger’s and Begg’s tests (Fig. 4). The shape of funnel plots was not symmetric. The Egger’s and Begg’s tests were further performed. The results indicated significant publication bias for studies, with merged PFS (Begg’s test, P = 0.015; Egger’s test, P = 0.028) and merged OS (Begg’s test, P = 0.026; Egger’s test, P = 0.085).
Fig. 4

Funnel plot for publication bias. a progression free survival, b overall survival

Evaluation of the quality of evidence according to GRADE system

The assessment of the quality of evidence was performed for PFS and OS which were critical in evaluating the outcome of mRCC patients. The quality of evidence of PFS and OS was both “very low” due to retrospective studies, publication bias and high heterogeneity (Table 4).
Table 4

Evaluation of the quality of evidence according to GRADE system

Quality assessment

No. of patients

Hazard Ratios (95% CI)

Quality

Importance

No of studies

Design

Risk of bias

Inconsistency

Indirectness

Imprecision

Other considerations

TKI-induced hypertension

Control

Progression-free survival (follow-up median 5.6–43.2 years; measured with: follow-up)

 20

observational studies

no serious risk of bias

serious1

no serious indirectness

no serious imprecision

reporting bias2

3021

1327

0.59 (0.48–0.71)

Very low

Critical

Overall survival (follow-up median 5.2–61.8 months; measured with: follow-up)

 17

observational studies

no serious risk of bias

serious1

no serious indirectness

no serious imprecision

reporting bias3

2313

1804

0.57 (0.45–0.70)

Very low

Critical

1The heterogeneity of this outcome was obvious between studies

2The shape of funnel plots was not symmetric. The Egger’s and Begg’s tests were further performed. The results indicated significant publication bias for studies, with merged PFS (Begg’s test, P = 0.015; Egger’s test, P = 0.028).

3The shape of funnel plots was not symmetric. The Egger’s and Begg’s tests were further performed. The results indicated significant publication bias for studies, with merged OS (Begg’s test, P = 0.026; Egger’s test, P = 0.085)

Discussion

This meta-analysis and systematic review investigated whether TKIs-induced hypertension can predict the prognosis of patients suffering from mRCC. AEs, like hypothyroidism, though shown to be a good predictor of PFS or OS, was usually diagnosed later than hypertension [17, 36]. Thus, it would be better if we can predict the prognosis of mRCC patients based on the TKIs-induced hypertension. It will help urologists decide whether patients should continue this TKIs therapy or not, which may help patients get more suitable treatments as soon as possible. Based on 22 original studies, our results showed that the occurrence of hypertension during treatment may predict better survival for mRCC, with longer PFS and OS. Additionally, when it comes to different TKIs, sunitinib or pazopanib therapy were both associated with longer PFS and OS.

The mechanisms of hypertension induced by TKIs are complicated. First, activation of VEGF receptor-2 via phosphoinositide 3-kinase and its downstream serine protein kinase Akt can stimulate endothelium-derived nitric oxide synthase, leading to the production of nitric oxide (NO). Therefore, the inhibition of VEGF receptor might lead to a decrease in NO bioavailability, followed by vasoconstriction and increased blood pressure (BP) [17, 37, 38, 39]. Second, plasma vasoconstrictor endothelin-1, a vasoconstrictor produced by the endothelium, also increased in patients or rats receiving sunitinib [40, 41, 42]. Third, NO is also involved in the control of renal and glomerular hemodynamics, tubuloglomerular feedback response, release of renin and sympathetic transmitters, tubular ion transport. As a result, reduction of NO can also result in renal water and sodium retention, leading to hypertension [43]. TKIs may also directly cause renal injury and proteinuria, which could play a role in long-lasting hypertension [44]. Finally, hypertension may also result from structural or functional vascular rarefaction [45, 46, 47]. VEGF is also crucial in the maintenance of endothelial viability [48, 49]. Therefore, the inhibition of VEGF and PDGF receptors can induce endothelial cell apoptosis, reduction in capillary density, vascular diameter and microvascular flow, and thus increase the blood pressure.

The reason why TKIs-induced hypertension might be a prognostic factor in patients with mRCC is still not quite clear. The anticarcinogenic effect of TKIs relies on the block of VEGF receptor, which may also lead to hypertension as above mentioned. Thus, when TKIs inhibit the progress of mRCC and prolong the PFS or OS of patients, hypertension may occur at the same time. It may be the reason why the rise of blood pressure could indicate a better prognosis in mRCC patients.

Of note, the intention of therapy is not to drive all patients into a hypertensive state. On the contrary, when hypertension occurs, patients should receive antihypertensive therapy as soon as possible. Additionally, despite the PFS and OS of mRCC patients have prolonged because of TKIs therapy, few comparable benefits have been described in terms of the quality of life [50, 51]. An innovative study that compared sunitinib with pazopanib to evaluate patient preferences suggested that the toxicity profile may have an impact on quality of life and the choice of treatment when two comparable options are on offer [52]. In addition, sunitinib-induced hypertension may be associated with cardiotoxicity or reversible posterior leukoencephalopathy [53, 54, 55]. Thus, the panel of National Cancer Institute of the USA had several recommendations for mRCC patients received TKIs [56]. First, urologists should recognize the preexisting hypertension prior to therapy or actively monitor BP throughout treatment. Early use of antihypertensive medication is necessary when high blood pressure occurs, and it is critical for maintaining dose intensity and improving a patient’s quality of life simultaneously [56]. If possible, the goal of management is to reduce BP below 140/90 mmHg. It was also suggested that there was no need to reduce the dose of antihypertensive medication because it did not compromise efficacy of TKIs [57]. Some evidence indicated that using Angiotensin receptor blockers (ARBs) or angiotensin-I-converting enzyme inhibitors may even protect against cancer [58, 59, 60]. ARBs were shown to induce apoptosis and inhibit the proliferation of RCC cells in vitro [28]. Thus, some randomized prospective studies could be carried out to see if it is better to use more than one drugs with different antihypertensive mechanisms, which may improve the prognosis [12]. Second, doctors should assess the risk of potential cardiovascular complications.

Several underlying limitations of the study should be presented. First, most eligible studies were retrospective, though with high NOS scores. Second, the reciprocal correlation between the hypertension and other AEs should be noted. Patients with more than one adverse event of any grade had longer PFS and OS [61]. Thus, further studies are needed to analyze the relationship between several adverse events and mRCC. Third, obvious inter-study heterogeneity was observed in this meta analysis, which may be due to different therapies mRCC patients had received before, such as cytokine immunotherapy. In addition, a publication bias was detected in this study. The potential reason may be that studies with non-significant results were not published. High heterogeneity and publication bias weakened the quality of evidence, which may be improved by more randomized prospective trials.

However, our analysis also has some advantages. First, we conducted this review with enough data available for extraction by a comprehensive and robust search strategy. Second, we applied a rigorous inclusion/exclusion criterion. Additionally, most of the studies operated multivariable analysis, which could eliminate the co-factors affecting the PFS and OS of mRCC patients.

Conclusions

In summary, our analysis of currently available clinical evidence suggests that TKIs-induced hypertension may predict longer PFS and OS in patients with mRCC during TKIs therapy, especially using sunitinib or pazopanib.

Notes

Acknowledgements

Not applicable.

Authors’ contributions

LY was mainly responsible for the design of the work, the acquisition and analysis of data and manuscript writing. ZL carried out the acquisition of data. CYT and YDH participated in the analysis of data. LBH, WKJ and LH revised the manuscript. All authors read and approved the final manuscript.

Funding

This study was funded by 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (ZY2016104), Project of Sichuan Provincial Health Department (ZH2017–101) and The National Natural Science Fund of China (81800667).

Ethics approval and consent to participate

All analyses were based on previous published studies. Thus, no ethical approval and patient consent are required.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Supplementary material

12894_2019_481_MOESM1_ESM.docx (140 kb)
Additional file 1: Figure S1. Flow chart showing literature searching process of meta-analysis. The search keywords are (renal cell carcinoma) AND [(tyrosine kinase inhibitor) OR sunitinib OR axitinib OR sorafenib OR pazopanib] AND [hypertension OR (blood pressure). (DOCX 140 kb)

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Authors and Affiliations

  1. 1.Department of UrologyInstitute of Urology (Laboratory of Reconstructive Urology), West China Hospital, Sichuan UniversityChengduPeople’s Republic of China

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