Evidence map›Paper›PMID 34396159›Full record

ArticleJACC. CardioOncology2019

Increase in Blood Pressure Associated With Tyrosine Kinase Inhibitors Targeting Vascular Endothelial Growth Factor.

Sarah Waliany, Kristin L Sainani, Lesley S Park, Chiyuan Amy Zhang, Sandy Srinivas, Ronald M Witteles

Open access · goldAbstract read
In one paragraph

Article in JACC. CardioOncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 2 pooled it
6.3field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

43 citing papers in PubMed, 2 syntheses or guidelines pooled it, 62 citations in OpenAlex.

  1. Pooled it
  2. Brazilian Cardio-oncology Guideline - 2020.Arquivos brasileiros de cardiologia · 2020
    Guideline
  3. Trial
  4. Trial
  5. Article
  6. Article
  7. Review
  8. Review
  9. Caught in the crossfire: cardiac complications of cancer therapy.The Journal of clinical investigation · 2026
    Review
  10. Review
  11. Article
  12. Navigating the Complexities of Cancer Treatment-Induced Hypertension.Journal of cardiovascular development and disease · 2025
    Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Sarah WalianyDepartment of Medicine, Stanford University School of Medicine, Stanford, California, USA.
Kristin L SainaniDepartment of Health Research and Policy, Stanford University School of Medicine, Stanford, California, USA.
Lesley S ParkCenter for Population Health Sciences, Stanford University School of Medicine, Stanford, California, USA.
Chiyuan Amy ZhangDepartment of Urology, Stanford University School of Medicine, Stanford, California, USA.
Sandy SrinivasDivision of Medical Oncology, Stanford University School of Medicine, Stanford, California, USA.
Ronald M WittelesDivision of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA.
Stanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study quantified the change in blood pressure (BP) during antivascular endothelial growth factor (VEGF) tyrosine kinase inhibitor (TKI) therapy, compared BPs between TKIs, and analyzed change in BP during antihypertensive therapy.

backgroundTKIs targeting VEGF are associated with hypertension. The absolute change in BP during anti-VEGF TKI treatment is not well characterized outside clinical trials.

methodsA retrospective single-center study included patients with metastatic renal cell carcinoma who received anti-VEGF TKIs between 2007 and 2018. Mixed models analyzed 3,088 BPs measured at oncology clinics.

resultsIn 228 patients (baseline systolic blood pressure [SBP] 130.2 ± 16.3 mm Hg, diastolic blood pressure [DBP] 76.8 ± 9.3 mm Hg), anti-VEGF TKIs were associated with mean increases in SBP of 8.5 mm Hg (p < 0.0001) and DBP of 6.7 mm Hg (p <0.0001). Of the anti-VEGF TKIs evaluated, axitinib was associated with the greatest BP increase, with an increase in SBP of 12.6 mm Hg (p < 0.0001) and in DBP of 10.3 mm Hg (p < 0.0001) relative to baseline. In pairwise comparisons between agents, axitinib was associated with greater SBPs than cabozantinib by 8.4 mm Hg (p = 0.004) and pazopanib by 5.1 mm Hg (p = 0.01). Subsequent anti-VEGF TKI courses were associated with small increases in DBP, but not SBP, relative to the first course. During anti-VEGF TKI therapy, calcium-channel blockers and potassium-sparing diuretic agents were associated with the largest BP reductions, with decreases in SBP of 5.6 mm Hg (p < 0.0001) and 9.9 mm Hg (p = 0.007), respectively.

conclusionsAnti-VEGF TKIs are associated with increased BP; greatest increases are observed with axitinib. Calcium-channel blockers and potassium-sparing diuretic agents were associated with the largest reductions in BP.

Indexed as

ACE, angiotensin-converting enzymeantiangiogenic therapyantihypertensive agentsARB, angiotensin II receptor blockerblood pressureBP, blood pressurecalcium-channel blockersCCB, calcium-channel blockerCTCAE, Common Terminology Criteria for Adverse EventsDBP, diastolic blood pressurediureticseGFR, estimated glomerular filtration ratehypertensionmRCC, metastatic renal cell carcinomarenal cell cancerSBP, systolic blood pressureTKI, tyrosine kinase inhibitortreatment-related hypertensiontyrosine kinase inhibitorsvascular endothelial growth factor inhibitorsVEGF, vascular endothelial growth factor

Identifiers

PMID34396159
PMCPMC8352203
OpenAlexW2976249548

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.