ReviewGenes2023
Prognostic Factors and Markers in Non-Small Cell Lung Cancer: Recent Progress and Future Challenges.
Review in Genes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 10 citations in OpenAlex.
- Balance Between Order and Disorder: Quantum-Epigenetic Pathways for the Emergence and Continuous Evolution of Life.Acta biotheoretica · 2026Review
- Lung cancer research: how natural language processing enhances clinical data extraction.Journal of thoracic disease · 2026Article
- Overexpression and prognostic value of aspartate β-hydroxylase in lung adenocarcinoma: a comprehensive study based on bioinformatics and clinical tissue sample validation.World journal of surgical oncology · 2026Article
- The TEAD4-DYNLL1 axis accelerates cell cycle progression and augments malignant properties of lung adenocarcinoma cells.European journal of medical research · 2025Article
- Comparison of inflammatory indices in patients with metastatic non-small cell lung cancer.Revista da Associacao Medica Brasileira (1992) · 2025Article
- CD34 evaluation of microvasculature in lung adenocarcinoma and its microvascular density predicts postoperative tumor recurrence.Pathology oncology research : POR · 2025Article
- Integrating frontiers: a holistic, quantum and evolutionary approach to conquering cancer through systems biology and multidisciplinary synergy.Frontiers in oncology · 2024Review
- The role of immunotherapy in early-stage and metastatic NSCLC.Pathology oncology research : POR · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
37 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer is a highly aggressive neoplasm and, despite the development of recent therapies, tumor progression and recurrence following the initial response remains unsolved. Several questions remain unanswered about non-small cell lung cancer (NSCLC): (1) Which patients will actually benefit from therapy? (2) What are the predictive factors of response to MAbs and TKIs? (3) What are the best combination strategies with conventional treatments or new antineoplastic drugs? To answer these questions, an integrative literature review was carried out, searching articles in PUBMED, NCBI-PMC, Google Academic, and others. Here, we will examine the molecular genetics of lung cancer, emphasizing NSCLC, and delineate the primary categories of inhibitors based on their molecular targets, alongside the main treatment alternatives depending on the type of acquired resistance. We highlighted new therapies based on epigenetic information and a single-cell approach as a potential source of new biomarkers. The current and future of NSCLC management hinges upon genotyping correct prognostic markers, as well as on the evolution of precision medicine, which guarantees a tailored drug combination with precise targeting.
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.