ReviewHNO2008
[Cytomics and predictive medicine for oncology].
Review in HNO, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One hundred and fifty years after Virchow introduced his fundamental concept of cellular pathology, we now have tools that allow us to unravel the mechanisms of single living cells on a previously unprecedented level of detail. By exploring the molecular cellular phenotype, multiparametric cytometry not only detects specific cellular functions in general but also offers insights into the interaction of single subunits of proteins (e.g., growth factor receptors). Several quantitative and objective techniques allow analysis of single-cell preparations as well as tissue sections to obtain data on different cellular parameters. This opens the way to quantitative and objective histology, which in the future may be possible even without blood or the need to make an incision. To use this huge amount of data for treatment decisions in an individual patient, novel bioinformatic concepts are needed in order to predict the individual course of a disease. The concept of cytomics centers on the cell as the integral unit of all life and explores diseases starting from the cell and going to subcellular units (top-down analysis).
Indexed as
Identifiers
18351309What 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.