ReviewZhongguo fei ai za zhi = Chinese journal of lung cancer2017
[Quantitative Imaging Assessment of Tumor Response to Chemoradiation in Lung Cancer].
Review in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 3 citations in OpenAlex.
- Predicting the risk category of thymoma with machine learning-based computed tomography radiomics signatures and their between-imaging phase differences.Scientific reports · 2024Article
- Impact of Computer-Aided CT and PET Analysis on Non-invasive T Staging in Patients with Lung Cancer and Atelectasis.Molecular imaging and biology · 2018Article
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Precision medicine demands accurate assessment of tumor response to therapies with the purpose of timely optimization or adjustment of the given treatment regimens. Chemoradiation remains the standard of care in advanced lung cancers and imaging-based noninvasive response evaluation could improve therapeutic efficacy and reduce treatment-related severe side effects. In this review, we overviewed the applications and pitfalls of major imaging modalities in response evaluation in lung cancer from a quantitative perspective. The development of radiomics will provide more precise information for treatment predicting, evaluation and prognosis.
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.