Acta oncologica
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The availability of quality assured, population-based cancer registries and biobanks with high quality samples makes it possible to conduct research on large samples sets with long follow-up within a reasonable time frame. Defined quality for both cancer registries and biobanks is essential for enabling high quality biobank-based research. Recent networking projects have brought these infrastructures together to promote the combined use of cancer registries and biobanks in cancer research. ⋯ Major conclusions for future improvements are that the research exploiting cancer registries and biobanks, and the research that is building and optimising the infrastructure, should evolve together for maximally relevant progress. Population-based and sustainable biobanks that continuously and consecutively store all samples ("Biological registries") under strict quality control are needed. There is also a need for increased education, information and visibility of the interdisciplinary sciences required for optimal exploitation of these resources.
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To investigate the capacity of two phenomenological expressions to describe the population tumor response in case of a heterogeneous irradiation of the tumor. The generalization of the individual tumor control probability (TCP) models to include the case of a heterogeneous irradiation is a trivial problem. However, an analytical solution that results in a closed form population TCP formula for the heterogeneous case is, unfortunately, a very complex mathematical problem. Therefore we applied a numerical approach to the problem. ⋯ Pseudo-experimental data sets are constructed through the generation of dose distributions and population TCP data obtained by a numerical solution of a multi-dimensional integral over an individual TCP model. The capacity of the following two phenomenological - Poisson and equivalent uniform dose (EUD) based - TCP expressions: [Figure: see text] to describe the population tumor response in case of heterogeneous irradiation is investigated through their fitting to the psuedo-experimental data sets. RESULTS AND CONCLUSIONS. While both expressions produce statistically acceptable fits to the pseudo-experimental data within 2% TCP error band, the use of the second expression is preferable since it produces considerably better fits to the data sets.
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Classical expressions for the tumor control probability (TCP) are based on models for the survival fraction of cancer cells after radiation treatment. We focus on the derivation of expressions for TCP from dynamic cell population models. In particular, we derive a TCP formula for a generalized cell population model that includes the cell cycle by considering a compartment of actively proliferating cells and a compartment of quiescent cells, with the quiescent cells being less sensitive to radiation than the actively proliferating cells. ⋯ The cell cycle can be understood as the sequestration of cells in the quiescent compartment, where they are less sensitive to radiation. We suggest that our model can be used in combination with synchronization methods to optimize treatment timing.