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Correspondence |
The erudite commentary by Prof. A J Munro [1] expresses the genuine concern of many Oncologists that the randomized control trial is only one of many useful weapons within the arsenal of medicine. The commentary fully meets its aim the justification of observational studies, exemplified by the magisterial review of stereotactic radiosurgery from St Bartholomew's Hospital [2] that followed it. However, it might be useful to state that the problems in Oncology are also amenable to study by other research tools. In any meaningful dialogue between the quantitative aspects of physics with biology/medicine, where variables are frequently categorical, the language of mathematics has to be used [3]. The expansion in bio-informatics mentioned by Prof. Munro is already producing a vast amount of data which can only be rationalized by application of mathematical techniques; this may prove to be more complex than the analysis of quantum mechanics in the early 20th century.
In routine clinical practice, simple mathematical models have helped to guide clinical practice in difficult situations that are not amenable to clinical trials, for example following treatment interruptions [4] or inadvertent mistakes in treatment delivery. Predictions that optimized types of highly conformal radiotherapy (including protons and ions) would be given safely and most efficiently using high doses per fraction are now being realised [5, 6]. In brachytherapy, rigorous attention to modelled dose rate fluctuations can reduce treatment toxicity [7]. Such practical advances are likely to increase with time.
We share the enthusiasm of Prof. Munro for individualization. Indeed, it is only by optimization of therapy in individual patients that marked improvements in outcomes significantly larger than the marginal gains found in conventional clinical trials can easily be simulated [8]. This is a consequence of the shallow dose response curves for pooled patient populations due to heterogeneity; individual dose responses must follow steeper dose responses and greater gains should follow the pursuit of optimization based on the parameters that operate in each patient.
Because of the large numbers of controllable variables (a reduced list would be dose, time fractionation, adjuvant treatment dose and scheduling, radiation technique/modalities, treatment volumes etc.), we cannot hope that randomized control trial evidence will ever be obtained to test all the potential combinations of therapies. It is hoped that the Research Councils will eventually accept that alternatives to clinical trials are necessary and that modified clinical trials with novel end points, based on quality adjusted survival, must be considered in certain situations. A more "modern engineering" approach would at least be to simulate as many permutations of therapies as possible on computer, which may effectively eliminate options that have a high probability of being unsatisfactory, leaving the best remaining options as the ones to choose for comparative clinical trials.
Oncology needs to have closer links with engineering, computer science, medical physics, as well as biology, in order to make more progress than is presently achieved from laborious, expensive and so frequently disappointing clinical trials.
Yours etc.,
1 Birmingham Cancer Centre, University Hospital Birmingham, B15 2TH, UK 2 Department of Radiation Physics & Radiobiology, Charing Cross Hospital, London, W6 8RF, UK
Received for publication May 16, 2005. Revision received July 12, 2005. Accepted for publication July 25, 2005.
References
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B Jones Implications of quality adjusted survival for clinical trials in radiation oncology. Br. J. Radiol., April 1, 2006; 79(940): 353 - 355. [Abstract] [Full Text] [PDF] |
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