Evidence map›Paper›PMID 38837683›Full record

ReviewCancer reports (Hoboken, N.J.)2024

Diagnostic, predictive and prognostic molecular biomarkers in clear cell renal cell carcinoma: A retrospective study.

Jian Deng, ShengYuan Tu, Lin Li, GangLi Li, YinHui Zhang

Abstract readReview
In one paragraph

Review in Cancer reports (Hoboken, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

5 authors.

Jian DengDepartment of Oncology, Hejiang Hospital of Traditional Chinese Medicine, Luzhou, People's Republic of China.
ShengYuan TuSchool of Basic Medical Sciences, Southwest Medical University, Luzhou, People's Republic of China.
Lin LiSchool of Stomatology, Southwest Medical University, Luzhou, People's Republic of China.
GangLi LiDepartment of Oncology, Hejiang Hospital of Traditional Chinese Medicine, Luzhou, People's Republic of China.
YinHui ZhangDepartment of Pharmacy, The Affiliated Hospital of Southwest Medical University, Luzhou, People's Republic of China.ORCID 0009-0005-9094-2986

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive subtype of kidney cancer. Many patients are diagnosed at advanced stages, making early detection crucial. Unfortunately, there are currently no noninvasive tests for ccRCC, emphasizing the need for new biomarkers. Additionally, ccRCC often develops resistance to treatments like radiotherapy and chemotherapy. Identifying biomarkers that predict treatment outcomes is vital for personalized care. The integration of artificial intelligence (AI), multi-omics analysis, and computational biology holds promise in bolstering detection precision and resilience, opening avenues for future investigations. The amalgamation of radiogenomics and biomaterial-basedimmunomodulation signifies a revolutionary breakthrough in diagnostic medicine. This review summarizes existing literature and highlights emerging biomarkers that enhance diagnostic, predictive, and prognostic capabilities for ccRCC, setting the stage for future clinical research.

Indexed as

Biomarkers, TumorCarcinoma, Renal CellKidney NeoplasmsHumansPrognosisRetrospective StudiesBiomarkers, Tumorbiomarkersclear cell renal cell carcinomadiagnostic markerspredictive markersprognostic markers

Identifiers

PMID38837683
PMCPMC11150078

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.