ArticleBiology direct2015
Test on existence of histology subtype-specific prognostic signatures among early stage lung adenocarcinoma and squamous cell carcinoma patients using a Cox-model based filter.
Article in Biology direct, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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.
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.
Who cites it
17 citing papers in PubMed.
- Prognostic Significance ofMedicina (Kaunas, Lithuania) · 2026Article
- Article
- Radiomics-Based Features for Prediction of Histological Subtypes in Central Lung Cancer.Frontiers in oncology · 2021Article
- GEE-TGDR: A Longitudinal Feature Selection Algorithm and Its Application to lncRNA Expression Profiles for Psoriasis Patients Treated with Immune Therapies.BioMed research international · 2021Article
- Identification of long non-coding RNA signatures for squamous cell carcinomas and adenocarcinomas.Aging · 2020Article
- The cox-filter method identifies respective subtype-specific lncRNA prognostic signatures for two human cancers.BMC medical genomics · 2020Article
- Construction of subtype-specific prognostic gene signatures for early-stage non-small cell lung cancer using meta feature selection methods.Oncology letters · 2019Article
- FOXM1 is a novel predictor of recurrence in patients with oral squamous cell carcinoma associated with an increase in epithelial‑mesenchymal transition.Molecular medicine reports · 2019Article
- Identification of monotonically differentially expressed genes for non-small cell lung cancer.BMC bioinformatics · 2019Article
- Identification of subtype-specific prognostic signatures using Cox models with redundant gene elimination.Oncology letters · 2018Article
- Article
- Classification and survival prediction for early-stage lung adenocarcinoma and squamous cell carcinoma patients.Oncology letters · 2017Article
- Identification of prognostic genes and gene sets for early-stage non-small cell lung cancer using bi-level selection methods.Scientific reports · 2017Article
- Classification of Non-Small Cell Lung Cancer Using Significance Analysis of Microarray-Gene Set Reduction Algorithm.BioMed research international · 2016Article
- Expression of Ribonucleotide Reductase Subunit-2 and Thymidylate Synthase Correlates with Poor Prognosis in Patients with Resected Stages I-III Non-Small Cell Lung Cancer.Disease markers · 2015Article
- Article
- Radiomics for Classifying Histological Subtypes of Lung Cancer Based on Multiphasic Contrast-Enhanced Computed Tomography.Journal of computer assisted tomographyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundNon-small cell lung cancer (NSCLC) is the predominant histological type of lung cancer, accounting for up to 85% of cases. Disease stage is commonly used to determine adjuvant treatment eligibility of NSCLC patients, however, it is an imprecise predictor of the prognosis of an individual patient. Currently, many researchers resort to microarray technology for identifying relevant genetic prognostic markers, with particular attention on trimming or extending a Cox regression model. Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are two major histology subtypes of NSCLC. It has been demonstrated that fundamental differences exist in their underlying mechanisms, which motivated us to postulate the existence of specific genes related to the prognosis of each histology subtype.
resultsIn this article, we propose a simple filter feature selection algorithm with a Cox regression model as the base. Applying this method to real-world microarray data identifies a histology-specific prognostic gene signature. Furthermore, the resulting 32-gene (32/12 for AC/SCC) prognostic signature for early-stage AC and SCC samples has superior predictive ability relative to two relevant prognostic signatures, and has comparable performance with signatures obtained by applying two state-of-the art algorithms separately to AC and SCC samples.
conclusionsOur proposal is conceptually simple, and straightforward to implement. Furthermore, it can be easily adapted and applied to a range of other research settings.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.