Based on data from over 80,000 patients, an international research group (led by the Institute for Global Health, University College London) has developed a programme that can predict the individual risk of developing active TB based on a quantitative measure of T cell sensitisation and clinical covariates. The development of the underlying algorithm is the first time that patient histories have been utilised to predict the risk of developing active TB. Latently TB-infected persons may be treated preventively, however this involves a months-long course of antibiotics. PERISKOPE-TB allows individual risk of each patient to be assessed to determined when preventative treatment is appropriate.
The discovery and validation of the personalised risk predictor for incident TB was published in October 2020 in Nature Medicine.