ReviewJournal of mammary gland biology and neoplasia2012
Translating mathematical modeling of tumor growth patterns into novel therapeutic approaches for breast cancer.
Review in Journal of mammary gland biology and neoplasia, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Self-targeting of TNF-releasing cancer cells in preclinical models of primary and metastatic tumors.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
- Estimating Tumor Growth Rates In Vivo.Bulletin of mathematical biology · 2015Article
- Dose-Dependent Mutation Rates Determine Optimum Erlotinib Dosing Strategies for EGFR Mutant Non-Small Cell Lung Cancer Patients.PloS one · 2015Article
- Modeling cancer-immune responses to therapy.Journal of pharmacokinetics and pharmacodynamics · 2014Article
- A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics.Systems and synthetic biology · 2014Article
- Epithelial-mesenchymal transition markers in lymph node metastases and primary breast tumors - relation to dissemination and proliferation.American journal of translational research · 2014Article
- Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues.Frontiers in oncology · 2013Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In breast cancer, mortality is driven by the metastatic process, whereby some cancer cells leave their primary site of origin and travel to distant vital organs. Despite improved screening and therapies to treat breast cancers, metastasis continues to undermine these advances. The pervasive albatross of metastasis necessitates improved prevention and treatment of metastasis. To this end, clinicians routinely employ post-operative or adjuvant therapy to decrease the risk of future metastasis and improve the chance for cure. This article evaluates the limitations of breast cancer therapies within the context of growth curves, and in doing so, provides new insight into the metastatic process as well as more effective means for therapeutic delivery. Two critical developments evolve from this mathematical analysis: first, the use of dose dense chemotherapy to improve survival among breast cancer patients; and second, the theory of self-seeding, which fundamentally changes our understanding of metastasis and the trajectory of drug development.
Indexed as
Identifiers
23011603What 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.