THE "NEW" PROSTATE CANCER INFOLINK

Dr. Guy Dimonte is a specialist in fluid dynamics who works at the Los Alamos National Laboratory in  New Mexico. He has recently applied the mathematical approaches used to model dynamic systems to develop a new model for the progression of prostate cancer from diagnosis onwards.

In the February issue of the Journal of Theoretical Biology (for which, some 40 years ago, your correspondent was the publisher’s editorial and publishing assistant), Dr. Dimonte describes the development of a cell kinetics model of the evolution of prostate cancer from initial diagnosis to prostate cancer-specific mortality. Such a model, if developed with sufficient predictive accuracy, could be used to estimate an individual patient’s potential outcome over time and thus to inform decisions about his therapy.

The  cell kinetics model requires the application of coupled differential equations in order to describe the growth of prostate cancer over time, and also involves multiple assumptions that may also need to be refined over time. Those who understand things like coupled differential equations can look at the paper’s abstract to learn more. However, if the assumptions can be appropriately validated, The “New” Prostate Cancer InfoLink assumes that it would be relatively straightforward to program the solutions to these equations such that a patient and his doctor could simply insert values into some form of online algorithm to develop a prognostic outcome, and that this process could be continued over time to refine the prognosis.

Dimonte’s current model proposes three categories of prostate cancer cell population: 

• Cells that are local to the prostate and sensitive to hormones
• Cells that are regional and also still hormone sensitive
• Cells that are systemic systemic and hormone resistant

Now it is possible that this model may be overly simplistic, and may need modification over time. However, it is the concept behind the model that is worth thinking about rather than the precise details at this stage. The details can probably be worked out if the general premise behind the model can be validated.

Dr. Dimonte has, to date, applied this model to assess the progression of prostate cancer in two just individuals for whom he had access to complete diagnostic data. The first is the patient described in a ”vignette” of a patient with early stage disease published by Walsh et al. The second is a patient with more advanced disease, who has already undergone both local and systemic treatments: that patient is Dr. Dimonte.

Interestingly, in the same issue of the same journal, Hirata et al. describe a mathematical model for the dynamics of serum PSA levels in patients receiving intermittent androgen suppression (IAS) for prostate cancer. These authors state that the validity of their model is supported by patient data obtained from a clinical trial of IAS.

Clearly the ability to structure highly refined mathematical models of the progression of prostate cancer, given specific clinical and therapeutic information, is becoming much more refined. It is therefore possible that the accuracy of current prognostic models (based on nomograms) will be replaced in the foreseeable future with models that are considerably more sophisticated (and potentially more accurate).

Filed under: Living with Prostate Cancer, Management, Risk Tagged: | model, prognosis, progression