New mathematical model may lead to safer chemotherapy
The study explains why certain patients develop severe infections after chemotherapy and points to ways of averting this side-effect
- Date : 13 Sep 2012
- Topic : Basic science
Cancer chemotherapy can be a life-saver, but it could be fraught with severe side effects, among them an increased risk of infection. Until now, the major criterion for assessing this risk has been the blood cell count: if the number of white blood cells falls below a critical threshold, the risk of infection is thought to be high. A new model built by Weizmann Institute mathematicians in collaboration with physicians from the Meir Medical Center in Kfar Saba, Israel and from the Hoffmann-La Roche research center in Basel, Switzerland, suggests that for proper risk assessment, it is essential to evaluate not only the quantity of these blood cells, but also their quality, which varies from one person to another.
This research may represent an important step in the emerging field of personalised medicine, leading to a more individualised approach to chemotherapy. In particular, better precautions might need to be taken to prevent infection in high-risk patients whereas those at a low risk could be spared unnecessary preventive treatments.
The study, recently published in the Journal of Clinical Investigation, brought together the expertise of researchers from such diverse disciplines as applied mathematics, electrical engineering, oncology, immunology and paediatrics.
A mathematical model reveals previously unknown mechanisms responsible for the variability in the vulnerability of neutropenia patients to infections
The new model reveals how the immune system functions under conditions of neutropenia. In this condition, which often emerges after chemotherapy or bone marrow transplant, severe infections can develop if the immune system fails to perform the crucial function of devouring and destroying bacteria. According to the study research leader, Prof. Vered Rom-Kedar of the Weizmann Institute’s Computer Science and Applied Mathematics Department, this mathematical model has revealed previously unknown mechanisms responsible for the variability in the vulnerability of neutropenia patients to infections.
The model suggests that in neutropenia, the tug of war between the blood cells and the bacteria cannot be explained away by the simple bacteria-to-cell ratio, nor by the threshold that the blood cell count must exceed. Rather, when neutrophil counts are low, the patient’s immune system enters a fragile equilibrium
which can easily be disrupted, with dramatic consequences, by even minute changes in bacterial concentration or neutrophil numbers. Other factors that can radically affect this equilibrium include the effectiveness of the neutrophil functioning and the permeability of tissues to bacteria, which can increase due to cancer therapy.
Thus according to the model, in healthy people, the fact that the effectiveness of neutrophils varies from one person to another usually has no significant consequences. In contrast, in patients with neutropenia, this individual variability can make a difference between life and death. This conclusion is drawn from the study based upon the blood analysis of four healthy volunteers. To use the model in the clinic, such analysis should be applied to large populations.
The model has already offered a plausible explanation for a number of medical uncertainties. It helps explain, for example, why after chemotherapy, some cancer patients contract life-threatening infections even when in isolation under sterile conditions.
The study also explains why certain patients, following chemotherapy or a bone marrow transplant, may develop acute infections even if their neutrophil levels have returned to relatively normal levels. The chemotherapy lowers both neutrophil levels and function, making the tissues of these patients more penetrable to bacteria. The model suggests that as a result, in some patients the bacterial concentrations might increase so quickly that by the time the neutrophil counts rise back to “normal,” the rapidly multiplying bacteria have already gained a head start, so that the neutrophil recovery is insufficient for overcoming the infection. This scenario may eventually also shed light on the rare cases in which acute bacterial infections develop in individuals with normal immunological function. The model suggests that in such cases, a high growth rate of unusually virulent bacteria could overcome the appropriate quantitative and qualitative neutrophil response.
The study suggests that to achieve optimal results in applying chemotherapy, and/or in patients with innate neutrophil dysfunction, it is of value to assess the patient’s neutrophils periodically, as well as the bacterial concentration. Such assessments will help reduce the morbidity and the mortality, as well as the cost, associated with unnecessary hospitalisations and the administration of expensive medications. Moreover, by cutting down on the use of antibiotics, these assessments can help in preventing the rise in antibiotic resistance.
Prof. Vered Rom-Kedar heads the Moross Research School of Mathematics and Computer Science; and her research is supported by the Yeda-Sela Centre for Basic Research. Prof. Rom-Kedar is the incumbent of the Estrin Family Chair of Computer Science and Applied Mathematics.
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