ArticleJournal of theoretical biology2007
Second cancers after fractionated radiotherapy: stochastic population dynamics effects.
Article in Journal of theoretical biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Second primary cancer risk and survival in prostate cancer patients: A nationwide analysis.Prostate international · 2025Article
- Mathematical modeling in radiotherapy for cancer: a comprehensive narrative review.Radiation oncology (London, England) · 2025Review
- Clinical and Functional Assays of Radiosensitivity and Radiation-Induced Second Cancer.Cancers · 2017Review
- Estimation of second cancer risk after radiotherapy for rectal cancer: comparison of 3D conformal radiotherapy and volumetric modulated arc therapy using different high dose fractionation schemes.Radiation oncology (London, England) · 2016Article
- A review of stereotactic body radiotherapy - is volumetric modulated arc therapy the answer?Journal of medical radiation sciences · 2015Review
- Modeling age-dependent radiation-induced second cancer risks and estimation of mutation rate: an evolutionary approach.Radiation and environmental biophysics · 2015Article
- Minimizing second cancer risk following radiotherapy: current perspectives.Cancer management and research · 2015Review
- Dosimetric advantages of a "butterfly" technique for intensity-modulated radiation therapy for young female patients with mediastinal Hodgkin's lymphoma.Radiation oncology (London, England) · 2014Article
- Repopulation of interacting tumor cells during fractionated radiotherapy: stochastic modeling of the tumor control probability.Medical physics · 2013Article
- Malignant induction probability maps for radiotherapy using X-ray and proton beams.The British journal of radiology · 2011Article
- The balance between initiation and promotion in radiation-induced murine carcinogenesis.Radiation research · 2010Article
- A new view of radiation-induced cancer: integrating short- and long-term processes. Part II: second cancer risk estimation.Radiation and environmental biophysics · 2009Article
- A new view of radiation-induced cancer: integrating short- and long-term processes. Part I: approach.Radiation and environmental biophysics · 2009Article
- Research Progress of Multiple Primary Malignancies Associated With Esophageal Cancer.Cancer control : journal of the Moffitt Cancer CenterReview
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Authors and funding
6 authors.
Funding
Abstract
When ionizing radiation is used in cancer therapy it can induce second cancers in nearby organs. Mainly due to longer patient survival times, these second cancers have become of increasing concern. Estimating the risk of solid second cancers involves modeling: because of long latency times, available data is usually for older, obsolescent treatment regimens. Moreover, modeling second cancers gives unique insights into human carcinogenesis, since the therapy involves administering well-characterized doses of a well-studied carcinogen, followed by long-term monitoring. In addition to putative radiation initiation that produces pre-malignant cells, inactivation (i.e. cell killing), and subsequent cell repopulation by proliferation, can be important at the doses relevant to second cancer situations. A recent initiation/inactivation/proliferation (IIP) model characterized quantitatively the observed occurrence of second breast and lung cancers, using a deterministic cell population dynamics approach. To analyze if radiation-initiated pre-malignant clones become extinct before full repopulation can occur, we here give a stochastic version of this IIP model. Combining Monte-Carlo simulations with standard solutions for time-inhomogeneous birth-death equations, we show that repeated cycles of inactivation and repopulation, as occur during fractionated radiation therapy, can lead to distributions of pre-malignant cells per patient with variance>>mean, even when pre-malignant clones are Poisson-distributed. Thus fewer patients would be affected, but with a higher probability, than a deterministic model, tracking average pre-malignant cell numbers, would predict. Our results are applied to data on breast cancers after radiotherapy for Hodgkin disease. The stochastic IIP analysis, unlike the deterministic one, indicates: (a) initiated, pre-malignant cells can have a growth advantage during repopulation, not just during the longer tumor latency period that follows; (b) weekend treatment gaps during radiotherapy, apart from decreasing the probability of eradicating the primary cancer, substantially increase the risk of later second cancers.
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