Evidence map›Paper›PMID 40558670›Full record

ReviewJournal of cardiovascular development and disease2025

Navigating the Complexities of Cancer Treatment-Induced Hypertension.

Jose Arriola-Montenegro, John Roth, Maria L Gonzalez Suarez

Abstract readReview
In one paragraph

Review in Journal of cardiovascular development and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

3 authors.

Jose Arriola-MontenegroDivision of Nephrology and Hypertension, Mayo Clinic, Rochester, MN 55905, USA.
John RothDepartment of Medicine, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0009-0000-0954-2947
Maria L Gonzalez SuarezDivision of Nephrology and Hypertension, Mayo Clinic, Rochester, MN 55905, USA.ORCID 0000-0002-8930-4611

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cancer therapy-induced hypertension (HTN) is an increasingly recognized complication associated with a wide range of anticancer agents, including vascular endothelial growth factor (VEGF) inhibitors, proteasome inhibitors, tyrosine kinase inhibitors, and alkylating agents. The pathogenesis of HTN in this setting is multifactorial, involving mechanisms such as endothelial dysfunction, nitric oxide (NO) suppression, sympathetic nervous system activation, and vascular remodeling. Additional factors, including paraneoplastic syndromes, poorly controlled pain, mood disturbances, and overlapping cardiovascular risk factors like obesity and diabetes, further contribute to the complexity of diagnosis and management. Despite its prevalence and clinical implications, cancer therapy-induced HTN is often addressed using general population guidelines, with limited oncology-specific protocols available. Accurate blood pressure measurement and individualized treatment plans are critical to optimize outcomes and avoid interruptions to cancer therapy. Antihypertensive agents such as angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARB), and calcium channel blockers have shown efficacy in both blood pressure control and, in some cases, oncologic outcomes. A multidisciplinary approach involving oncologists, cardiologists, and primary care providers is essential to navigate the interplay between cancer treatment and cardiovascular health. Ongoing research is needed to develop targeted guidelines and improve the long-term care of cancer patients affected by treatment-induced HTN.

Indexed as

cancerhypertensiononconephrologyVEGF

Identifiers

PMID40558670
PMCPMC12194795

What OpenQuestion holds

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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.