Evidence map›Paper›PMID 37151396›Full record

ArticleJournal of Cancer2023

High levels of baseline serum IL-10 are associated with reduced clinical benefit from first-line immune checkpoint inhibitor therapy in advanced renal cell carcinoma.

Youngun Kim, Hannah Yang, Won Suk Lee, Jaekyung Cheon, Yun Beom Sang, Beodeul Kang, Hong Jae Chon, Chan Kim

Open access · goldAbstract read
In one paragraph

Article in Journal of Cancer, 2023. 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
3.1field-weighted citation impact, top 8% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Youngun KimCHA University School of Medicine, Seongnam, Korea.
Hannah YangCHA University School of Medicine, Seongnam, Korea.
Won Suk LeeCHA University School of Medicine, Seongnam, Korea.
Jaekyung CheonCHA University School of Medicine, Seongnam, Korea.
Yun Beom SangCHA University School of Medicine, Seongnam, Korea.
Beodeul KangCHA University School of Medicine, Seongnam, Korea.
Hong Jae ChonCHA University School of Medicine, Seongnam, Korea.
Chan KimCHA University School of Medicine, Seongnam, Korea.
CHA University · KRCHA University Bundang Medical Center · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint inhibitor (ICI) became a standard treatment for advanced renal cell carcinoma (RCC). However, clinically valid biomarkers of therapeutic outcome are lacking. We investigated the role of interleukin-10 (IL-10) as a predictive biomarker for first-line ICI therapy in patients with advanced RCC. Baseline serum samples were prospectively collected and analyzed using a cytometric bead assay. Patients were divided into two groups according to their serum IL-10 levels using maximally selected rank statistics. A fraction (13.0%) of patients had high levels of serum IL-10 at baseline. High serum IL-10 levels (> 4.3 ng/mL) were associated with a significantly shorter progression-free (median: 5.2 months vs. not reached, P = 0.007) and overall survival (median: 13.9 months vs. not reached, P < 0.001). Multivariate Cox regression analysis confirmed the independent association between high serum IL-10 levels and poor survival outcomes. Effector cytokine production and the proliferative response of CD8

Indexed as

advanced renal cell carcinomabiomarkersimmune checkpoint inhibitorinterleukin-10survival

Identifiers

PMID37151396
PMCPMC10158513
OpenAlexW4364857357

What OpenQuestion 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 OpenQuestion graph.