Evidence map›Paper›PMID 34972998›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

A Method to Identify Potential Prognostic Markers Across Distinct Tumor Types.

Boxi Zhang, Elena Kochetkova, Erik Norberg

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 48% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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 at 2 institutions in 2 countries.

Boxi ZhangDepartment of Physiology and Pharmacology, Biomedicum, Karolinska Institutet, Stockholm, Sweden.
Elena KochetkovaDepartment of Physiology and Pharmacology, Biomedicum, Karolinska Institutet, Stockholm, Sweden.
Erik NorbergDepartment of Physiology and Pharmacology, Biomedicum, Karolinska Institutet, Stockholm, Sweden. Erik.Norberg@ki.se.
Karolinska Institutet · SEInstitute of Cytology · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The identification of novel biomarkers in cancer patients often requires both survival and gene expression analyses. The Kaplan-Meier survival analysis is one of the most common methods to assess the fraction of subjects living for a certain amount of time.Here, we describe a method for researchers to identify potential prognostic markers across distinct tumor types. We utilize The Cancer Genome Atlas (TCGA) as this is one of the most extensive and successful cancer genomics programs to date that includes expression data and clinical follow-up information for up to 33 distinct tumor types. Nevertheless, the method described here can also be applied to any open-source dataset where the RNA expression and clinical outcome are provided.We provide detailed practical instructions and advices for investigators to be able to successfully identify prognostic markers in cancer patients.

Indexed as

Biomarkers, TumorNeoplasmsGene Expression Regulation, NeoplasticGenomicsHumansKaplan-Meier EstimatePrognosisBiomarkers, TumorAutophagyCancerKaplan–MeierLung adenocarcinomaLung cancerNext-generation sequencingRNA-seqSurvival analysisTCGAThe cancer genome atlas

Identifiers

PMID34972998
OpenAlexW4205978234

What OpenQuestion holds

Textmetadata
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.