Gregory, Walter Martin; (1993) The evaluation of durations of response to cancer treatments. Doctoral thesis (Ph.D.), University College London (United Kingdom).

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Abstract

The current methodology for scientific progress in clinical medicine is reviewed. Special attention is given to the randomised controlled trial, with particular emphasis on statistical considerations, especially the analysis of survival and response duration data. The principles commonly employed in designing and improving treatments for cancer are reviewed, discussed, and demonstrated in practice by reference to progress made in the treatment of, among others, breast cancer and testicular teratoma. Improvements are shown to have concentrated on ways to circumvent resistance to therapy, and on exploiting the growth kinetics of tumours. However, quantitative information on either of these factors has been difficult to obtain, with the result that new trials are often designed on largely theoretical grounds, using principles that are unvalidated, and understood in a qualitative fashion only. Two new mathematical models which seek to derive this quantitative information are presented, developed, and validated, and their assumptions discussed in detail. One population based model seeks to derive distributions of resistance and growth rate parameters for groups of patients from their durations of response to treatment. Applications are presented in acute leukaemia, breast cancer, Hodgkin's disease and multiple myeloma. A multivariate version of this model is presented and applied to help in the understanding and use of prognostic factors in breast cancer. The second model, for individuals, uses sequential tumour volume measurements before each treatment. An application is given in lung cancer, where the volumes were measured by CT scan. Results from the model appear to indicate when changing or stopping treatment may be beneficial. Application of these mathematical models often seems to generate new ideas for treatment, and leads to a better understanding of how the treatment may be working. They should enhance the conventional approaches, and hopefully enable research to proceed more rapidly and successfully.

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