ReviewJournal of the National Cancer Institute2016
Current and Evolving Methods to Visualize Biological Data in Cancer Research.
Review in Journal of the National Cancer Institute, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- A modification of swimmer plot for overviewing the postoperative longitudinal course.JPRAS open · 2025Article
- Statistical plots in oncologic imaging, a primer for neuroradiologists.The neuroradiology journal · 2024Review
- Treatment-Free Survival After Nivolumab vs Pembrolizumab vs Nivolumab-Ipilimumab for Advanced Melanoma.JAMA network open · 2023Article
- Correlation of treatment outcome in sanger/RT‑qPCROncology reports · 2022Article
- Review
- Independent Drug Action in Combination Therapy: Implications for Precision Oncology.Cancer discovery · 2022Review
- Making Patient-Specific Treatment Decisions Using Prognostic Variables and Utilities of Clinical Outcomes.Cancers · 2021Review
- Characterizing tumor shrinkage as a measure of clinical benefit for immune checkpoint inhibitors.Journal for immunotherapy of cancer · 2021Article
- Article
- A Single Visualization Technique for Displaying Multiple Metabolite-Phenotype Associations.Metabolites · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although the measurements of clinical outcomes for cancer treatments have become diverse and complex, there remains a need for clear, easily interpreted representations of patients' experiences. With oncology trials increasingly reporting non-time-to-event outcomes, data visualization has evolved to incorporate parameters such as responses to therapy, duration and degree of response, and novel representations of underlying tumor biology. We review both commonly used and newly developed methods to display outcomes in oncology, with a focus on those that have evolved to represent complex datasets.
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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.