Evidence map›Paper›PMID 33427023›Full record

ArticleHuman vaccines & immunotherapeutics2021

The interplay between cholesterol (and other metabolic conditions) and immune-checkpoint immunotherapy: shifting the concept from the "inflamed tumor" to the "inflamed patient".

Melissa Bersanelli, Alessio Cortellini, Sebastiano Buti

Abstract read
In one paragraph

Article in Human vaccines & immunotherapeutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Melissa BersanelliMedical Oncology Unit, University Hospital of Parma, Parma, Italy.ORCID 0000-0002-6527-6281
Alessio CortelliniDepartment of Biotechnological and Applied Clinical Sciences, St. Salvatore Hospital, University of L'Aquila, L'Aquila, Italy.ORCID 0000-0002-1209-5735
Sebastiano ButiMedical Oncology Unit, University Hospital of Parma, Parma, Italy.ORCID 0000-0003-0876-0226

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The predictive ability of metabolic conditions, such as hypercholesterolemia, on the outcome of cancer patients to immune-checkpoint inhibitors (ICIs) therapy, has been recently explored. The reasons for their value in this setting are to be searched in the individual himself more than in his tumor, as the target of the immune-checkpoint blockade is the immune system. The efficacy of ICIs on the tumor may be based on two simple premises: 1) the physiological immune function has been blocked, and 2) the tumor progression (mainly) depends on this block. The metabolic syndrome may represent the epiphenomenon of an "inflamed patient," no longer able of physiological functions required to prevent chronic inflammatory events. The metabolic dysfunction could represent merely "a biomarker" of the patient who satisfies both the two premises reported above. Suggestions from preclinical and translational researches should be transferred in the clinical setting, implementing randomized clinical trials with observational endpoints such as the effect of concomitant drug medications and the impact of blood cholesterol levels and other metabolic conditions on the outcome of ICI treatment.

Indexed as

ImmunotherapyNeoplasmsCholesterolHumansImmune Checkpoint InhibitorsImmunologic FactorsCholesterolImmune Checkpoint InhibitorsImmunologic FactorscancerCholesterolimmune-checkpoint inhibitorsimmune systemimmunotherapyinflammationmetabolic syndromeobesityoutcomeparadox index

Identifiers

PMID33427023
PMCPMC8189053

What OpenQuestion holds

Textmetadata
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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.