ArticleGlobal advances in health and medicine2014
A novel use of biomarkers in the modeling of cancer activity based on the theory of endobiogeny.
Article in Global advances in health and medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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0 citing papers in PubMed, 5 citations in OpenAlex.
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5 authors at 3 institutions in 1 country.
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Abstract
introductionCancer is a complex disorder whose detection and monitoring remains challenging. A biological modeling system, the biology of functions (BoF), claims to be able to evaluate physiologic elements related to carcinogenic activity. A pilot study was undertaken to evaluate the accuracy of the BoF in detecting differences between cancer cases and matched controls. MATERIALS AND
methodsA retrospective case control study was performed using the BoF analyses of 46 patients with all types of solid and hematgenous cancers, active and inactive (total cases), and 46 controls from a private practice. The standard BoF panel of 17 biomarkers was evaluated. Sixty-two of 150 BoF indices derived from these biomarkers were pre-selected for analysis based on their relationship to cancer physiology. The data was analyzed with the Wilcoxon Signed Ranks Test using SPSS software.
resultsOf the 62 indices, 7 were found to be statistically significant in comparing total cancer cases to controls: βMSH/αMSH, Estrogen Fraction #5, Comparative Genital Androgeny, Thyroid, Genito-thyroid, Catabolism/Anabolism and Pro-inflammatory.
conclusionsIn a small retrospective case control study, statistically significant differences were found between cancer cases and controls in 7 BoF indices. These indices are indicators of physiological conditions consistent with cancer growth. These results warrant further study of this biological modeling system in cancer patients.
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