Current treatment of TB is long, complicated to administer, and can have severe side-effects. To prevent recurrence of the disease after treatment is stopped patients undergoing treatment must take a combination of different antibiotics for at least six months– this often leads to improper adherence, which consequently can result in the development of multi-drug-resistant TB (MDR). Treatment for drug-resistant TB can take up to two years, and is yet more complex, expensive, and toxic. The staggering cost of curing MDR-TB poses a significant challenge to governments, health systems, and other payers – and still, many patients are unable to even access treatment. Among those who do receive treatment for MDR TB, only 50% survive.
Thus, shortening of standard treatment is a main priority of current TB research. Previous studies of treatment shortening, usually to four months, have all been unsuccessful when compared to standard six-month treatment. Six-month courses cure 95% of patients and shorter courses only 80-85% of patients. This still means, however, that most patients are cured after four months - but we cannot currently know beforehand which patients belong to that group. If it were possible to identify the patients who only require four-month therapy, we would be able to reduce treatment duration in the vast majority of patients.
This is precisely what the Predict-TB consortium wants to do:
Over the next five years, the consortium, led by Prof. Clifton Barry from the US National Institutes of Health and Prof. Gerhard Walzl from Stellenbosch University in South Africa, is planning to develop a smart set of treatment stopping criteria, and a point-of-care device to measure immunological markers that can contribute to the decision making. The group will perform an ambitious phase 2B clinical trial in South Africa and China, looking at demographic, radiographic, bacteriologic and immunologic parameters, to answer two key questions:
- can those patients who cure with shorter treatment duration be identified? and
- what combination of parameters can best identify these patients?
This new method – if successful – could be a true game changer, advancing treatment standards from the current practice of "one size fits all" to precision-guided individualised therapy, which would allow for shortened treatment in a significant proportion of drug sensitive TB patients.
Millions of patients could benefit from a much shorter treatment. This will not only make their lives much easier: Reducing the TB burden will have a beneficial effect on the economic situation in many developing countries, and less drug resistance will benefit public health on a global scale.
The Predict-TB project will receive over 20 million EUR funding from the EDCTP, the Bill & Melinda Gates Foundation through the Foundation for the National Institutes of Health, National Institutes of Health, the National Science Foundation of China (NSFC) and China Ministry of Science and Technology (MOST).