Evidence map›Paper›PMID 38201531›Full record

ReviewCancers2023

Predictive Factors in Metastatic Melanoma Treated with Immune Checkpoint Inhibitors: From Clinical Practice to Future Perspective.

Stefano Poletto, Luca Paruzzo, Alessandro Nepote, Daniela Caravelli, Dario Sangiolo, Fabrizio Carnevale-Schianca

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 7 citations in OpenAlex.

  1. Challenges in tracer development for tumor microenvironment (TME) imaging.European journal of nuclear medicine and molecular imaging · 2026
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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

6 authors at 3 institutions in 2 countries.

Stefano PolettoDepartment of Oncology, University of Turin, AOU S. Luigi Gonzaga, 10043 Orbassano, Italy.ORCID 0000-0002-0404-9683
Luca ParuzzoDepartment of Oncology, University of Turin, 10124 Turin, Italy.
Alessandro NepoteDepartment of Oncology, University of Turin, AOU S. Luigi Gonzaga, 10043 Orbassano, Italy.
Daniela CaravelliMedical Oncology Division, Candiolo Cancer Institute, FPO-IRCCs, 10060 Candiolo, Italy.
Dario SangioloDepartment of Oncology, University of Turin, 10124 Turin, Italy.ORCID 0000-0002-7163-7071
Fabrizio Carnevale-SchiancaMedical Oncology Division, Candiolo Cancer Institute, FPO-IRCCs, 10060 Candiolo, Italy.
Candiolo Cancer Institute · ITOspedale San Luigi Gonzaga · ITUniversity of Turin · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The introduction of immunotherapy revolutionized the treatment landscape in metastatic melanoma. Despite the impressive results associated with immune checkpoint inhibitors (ICIs), only a portion of patients obtain a response to this treatment. In this scenario, the research of predictive factors is fundamental to identify patients who may have a response and to exclude patients with a low possibility to respond. These factors can be host-associated, immune system activation-related, and tumor-related. Patient-related factors can vary from data obtained by medical history (performance status, age, sex, body mass index, concomitant medications, and comorbidities) to analysis of the gut microbiome from fecal samples. Tumor-related factors can reflect tumor burden (metastatic sites, lactate dehydrogenase, C-reactive protein, and circulating tumor DNA) or can derive from the analysis of tumor samples (driver mutations, tumor-infiltrating lymphocytes, and myeloid cells). Biomarkers evaluating the immune system activation, such as IFN-gamma gene expression profile and analysis of circulating immune cell subsets, have emerged in recent years as significantly correlated with response to ICIs. In this manuscript, we critically reviewed the most updated literature data on the landscape of predictive factors in metastatic melanoma treated with ICIs. We focus on the principal limits and potentiality of different methods, shedding light on the more promising biomarkers.

Indexed as

biomarkerimmune checkpoint inhibitorsimmunotherapymelanomapredictive factor

Identifiers

PMID38201531
PMCPMC10778365
OpenAlexW4390176558

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.