Article

PODSE: A computer program for optimal design of trials with discrete-time survival endpoints.

Utrecht University, The Netherlands. Electronic address: .
Computer methods and programs in biomedicine (Impact Factor: 1.56). 04/2013; DOI: 10.1016/j.cmpb.2013.02.005
Source: PubMed

ABSTRACT In experimental settings, one or more groups of subjects receive a treatment and they are compared to a group of subjects that receives a standard treatment or no treatment at all. These compared groups might have an equal number of subjects or some of the groups might have more participants relative to the other groups. Moreover, subjects in these groups can be followed over a short or a long period. To conduct experiments in a sufficient way, researchers should find a good design in the planning phase of the trial. The optimal design for experimental studies on event occurrence with discrete-time survival endpoints where two treatment groups are followed over time, is an optimal combination of the number of time periods, the total number of participants in the trial and the proportion of subjects in the experimental group. It is easy to find the best design for such studies using the PODSE program.

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    ABSTRACT: Purpose The accuracy of dose delivery and the evaluation of differences between calculated and delivered dose distributions, has been studied by several groups. The aim of this investigation is to extend the gamma index by including radiobiological information and to propose a new index that we will here forth refer to as the gamma plus (γ+). Furthermore, to validate the robustness of this new index in performing a quality control analysis of an IMRT treatment plan using pure radiobiological measures such as the biologically effective uniform dose (D¯¯) and complication-free tumor control probability (P+). Material and Methods A new quality assurance index, the (γ+), is proposed based on the theoretical concept of gamma index presented by Low et al. (1998). In this study, the dose difference, including the radiobiological dose information (biological effective dose, BED) is used instead of just the physical dose difference when performing the γ+ calculation. An in-house software was developed to compare different dose distributions based on the γ+ concept. A test pattern for a two-dimensional dose comparison was built using the in-house software platform. The γ+ index was tested using planar dose distributions (exported from the treatment planning system) and delivered (film) dose distributions acquired in a solid water phantom using a test pattern and a theoretical clinical case. Furthermore, a lung cancer case for a patient treated with IMRT was also selected for the analysis. The respective planar dose distributions from the treatment plan and the film were compared based on the γ+ index and were evaluated using the radiobiological measures of P+ and D¯¯. Results The results for the test pattern analysis indicate that the γ+ index distributions differ from those of the gamma index since the former considers radiobiological parameters that may affect treatment outcome. For the theoretical clinical case, it is observed that the γ+ index varies for different treatment parameters (e.g. dose per fraction). The dose area histogram (DAH) from the plan and film dose distributions are associated with P+ values of 50.8% and 49.0%, for a D¯¯ to the target of 54.0 Gy and 53.3 Gy, respectively. Conclusion The γ+ index shows advantageous properties in the quantitative evaluation of dose delivery and quality control of IMRT treatments because it includes information about the expected responses and radiobiological doses of the individual tissues.
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