Evidence map›Paper›PMID 39759492›Full record

ReviewJournal of clinical medicine research2024

Clinical Implications of Skin Cancer in Kidney Transplant Recipients in the Era of Immune Checkpoint Inhibitors.

Lakshmi Manogna Chintalacheruvu, Vamsi Krishna Chilluru

Abstract readReview
In one paragraph

Review in Journal of clinical medicine research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Lakshmi Manogna ChintalacheruvuHematology/Oncology, Southern Illinois Health Cancer Institute, Carterville, IL, USA.
Vamsi Krishna ChilluruNephrology, Southern Illinois Health, Carbondale, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long-term survival has improved in kidney transplant recipients (KTRs) due to effective surgical techniques and anti-rejection therapies. Chronic immunosuppression associated with it has led to several types of skin cancers leading to substantial morbidity and mortality. Structured patient education including sun protective behaviors, regular dermatological surveillance, nicotinamide, long-chain omega-3 polyunsaturated fatty acids (PUFAs), early switch to mammalian target of rapamycin inhibitors (mTORis), combining them with low-dose calcineurin inhibitors (CNIs), can decrease the cancer risk. Checkpoint inhibitors (CPIs) are the major backbone of the treatment of advanced skin cancers. Unfortunately, these agents can increase the risk of graft rejection. Prospective studies done so far looking at combining steroids with CPI in treatment of skin cancer in KTRs have shown mixed results. Adoption of the weight-based approach of CPI has shown to decrease the amount of drug exposure with acceptable outcomes in the general population, which is something that can be studied in KTRs with skin cancer. Also, it is reasonable to consider surveillance allograft biopsies in KTRs receiving CPIs to detect early subclinical rejection. More studies are needed to develop guidelines to safely treat this population with minimal graft rejection. We conducted a comprehensive literature review from PubMed on skin cancer in kidney transplant patients, focusing on incidence, risk factors, protective behaviors, financial and treatment implications, especially with regards to CPIs therapy. We also discussed potential newer treatment options that will decrease skin cancer risk, as well as graft rejection.

Indexed as

Immune checkpoint inhibitorsImmunosuppressionKidney transplantSkin cancer and prevention

Identifiers

PMID39759492
PMCPMC11699868

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Registered trials

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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.