Despite growing efforts spanning over several decades, most of the world was not able to satisfactorily prevent TB, prevent conversion of latent TB into active TB disease, diagnose the disease timely or put all those diagnosed on effective standard treatments - and most importantly, avert untimely deaths.
Why are we off-track on most TB targets?
During the Covid-19 pandemic, another global health threat that has become even more severe is of TB. We are off track on most of the global TB targets, such as, the goal to end TB by 2030 which is enshrined in the United Nations Sustainable Development Goals (SDGs), or the targets of the World Health Organization (WHO)'s End TB Strategy, or promises made in the 2018 Political Declaration of the UN High-Level Meeting on TB.
We missed to deliver on TB promises for 2020
The End TB Strategy milestones for 2015-2020 aimed at a 35% reduction in the number of TB deaths and a 20% reduction in the TB incidence. However, TB deaths and incidence have reduced by only 9.2% and 11% respectively during this period. The negative impacts on TB mortality and TB incidence in 2020 are expected to become much worse in 2021 and beyond.
Will new better tools to diagnose and treat TB, zoom us towards #endTB targets?
Concerted efforts at all fronts, including scientific breakthroughs, are crucial to break the chain and end TB by 2030. Providing a glimmer of hope, several advances in the field of TB care and control were presented during the recent virtual 52nd Union World Conference on Lung Health. Here is a glimpse of some of these exciting researches for TB diagnosis and treatment:
Short, all-oral treatment for Rifampicin-resistant TB
Bern Thomas Myanga, Medical Director of Nobel prize-winning Medicins Sans Frontieres (MSF or Doctors Without Borders), UK, and Chief Investigator of the TB-PRACTECAL Trial, reported results of the MSF-led first-ever multi-country, randomised, controlled clinical phase 2/3 study on the efficacy and safety of the all oral, 24-week BPaLM (bedaquiline, pretomanid, linezolid, and moxifloxacin) regimen against the standard of care treatment for rifampicin-resistant TB. The study was conducted at 7 sites across Uzbekistan, Belarus and South Africa.
The new treatment regimen was found to be safer and more effective for patients with rifampicin-resistant TB than the current accepted standard of care that lasts for 9 to 24 months. 89% of the patients in the BPaLM group were cured, compared to 52% in the standard of care group. Tragically four patients died from TB or treatment side effects in the control group, while there were no deaths or failures in the new regimen arm. In addition, study results showed that the new drugs lead to a significantly lower rate of major side effects, with 80% of patients avoiding any major side effects compared to 40% in the control group.
A study done in Peru, used genome sequencing to effectively predict strains of drug-susceptible TB that were likely to develop drug resistance in future.
Whole-genome sequencing was performed on 3000 sputum of samples of all patients presenting with TB symptoms at health centres in Lima, Peru, over a period of 17 years. Whole-genome sequencing was performed on each of these samples-whether of drug-susceptible or of drug-resistant TB. The researchers looked at drug-susceptible bacteria and aimed to identify mutations that would increase the probability of a bacteria becoming resistant in the future.
Presenting the study data, lead author Arturo Torres Ortiz, a researcher from Imperial College London, shared that, "We looked for any signs in drug-susceptible bacteria that they will become resistant in future. We identified those 'signatures' and saw that once the bacteria acquires resistance to one antibiotic, it is more likely that they will keep acquiring resistance to other antibiotics. We found that if the bacteria become resistant to isoniazid then they are upto 15 times more likely to acquire further resistance to rifampicin. We identified specific polymorphisms that can be used to make a molecular test in the future to tell us whether this drug-susceptible bacteria will become resistant in the future. This could be a potential game changer for preventing multidrug-resistant TB (MDR-TB)."
"We found that isoniazid mono-resistance backgrounds have a much higher risk of acquiring further rifampicin resistance than susceptible backgrounds. Rapid molecular tests usually focus on rifampicin resistance, which means that isoniazid mono-resistance is missed. This result in amplification into multi-drug resistance. We thus recommend that rapid molecular tests also identify regions associated to isoniazid resistance conferring mutations.
The mutations confer “pre-resistance”. Monitoring these mutations could prevent the amplification of drug resistance in the population by targeting those bacteria more likely to become resistant”, he added.
Although TB in children commonly presents with symptoms mimicking pneumonia, its diagnosis is usually considered only if they have repeated antibiotic treatment failures or if symptoms have been present for long. Thus diagnosis of TB in kids is often missed or delayed, causing high mortality in them as they cannot access treatment because they are not diagnosed, said Dr Olivier Marcy, Research Director, University of Bordeaux. He was presenting the results of the TB Speed Pneumonia study on the yield of systematic TB molecular testing performed on nasopharyngeal aspirates and stool samples in children with severe pneumonia in countries with high TB incidence. The study investigated if offering systematic molecular testing for TB in all children with pneumonia is feasible and whether it will affect mortality.
The study was done on 1169 children aged upto 5 years, with WHO-defined severe pneumonia, enrolled in 15 hospitals from 6 high TB incidence countries- Cambodia, Cameroon, Côte d’Ivoire, Mozambique, Uganda, and Zambia.
“Unlike adults, children below age 5 are unable to expectorate to produce sputum for molecular testing. So one has to use easier sample collection methods. We collected stool samples and nasopharyngeal aspirate samples (that involve non-invasive methods). Although taking stool samples seem rather easy in children, it takes time to collect them and it is not as easy as the other option. We could collect nasopharyngeal aspirate samples in 97% children and stool samples in 81% children. Molecular testing of stool samples and nasopharyngeal aspirates was done using Gene Xpert Ultra. 8.0% of the children with severe pneumonia were diagnosed with TB in the intervention arm”, informed Marcy.
“These are important findings. Although we have more and more data that TB is frequent in children with pneumonia, the guidelines and clinical practices are not taking this information into consideration. So we need to have better tools to detect TB in this group. Getting nasopharyngeal aspirates from them is not difficult. So it is important to convince doctors around the world that they can use this technique to diagnose TB in children”, he emphasized.
Scientists at Shenzhen Zhying Medical Imaging in Guangdong, China, have developed an automated detection system based on artificial intelligence (AI) for screening active TB disease on CT images.
They conducted a study to test the accuracy of this detection system that can automatically read DICOM CT images to diagnose active TB disease and also differentiate between TB and pneumonia. This AI-based system, followed with a self-organized clustering algorithm in the study was found to accurately diagnose active TB disease during its earlier stages, and distinguish between active TB disease and non-active TB (i.e. pneumonia and normal cases). It simplifies the diagnosis process and lays a solid foundation for AI in CT diagnosis of active TB disease in a large-scale clinical application.
The sensitivity and specificity for artificial intelligence are very high (0.935 and 0.971 respectively), which show that the AI-tool performs well for diagnosis of active TB disease and differential diagnosis of active TB disease and pneumonia. It can be implemented with minimal need for human intervention. However, while presenting results of this study, Dr Fleming Lure investigator of the study cautioned that, “AI can function as a second pair of eyes. It does not replace the humans but provides references for healthcare professionals to make a final diagnosis. Also, this small study lays good groundwork for the future of AI in the large clinical evaluations and simplify the diagnosis process”.
The fight to end TB is a human rights imperative. We have to use all existing tools to prevent, diagnose and treat TB rationally and to maximal potential, as well as, fully fund the research and development of new and better tools - and - also ensure that new tools are rolled out equitably, and reach the people in-need as soon as possible without any delay.
Genome sequencing to identify TB strains that are likely to become drug-resistant
A study done in Peru, used genome sequencing to effectively predict strains of drug-susceptible TB that were likely to develop drug resistance in future.
Whole-genome sequencing was performed on 3000 sputum of samples of all patients presenting with TB symptoms at health centres in Lima, Peru, over a period of 17 years. Whole-genome sequencing was performed on each of these samples-whether of drug-susceptible or of drug-resistant TB. The researchers looked at drug-susceptible bacteria and aimed to identify mutations that would increase the probability of a bacteria becoming resistant in the future.
Presenting the study data, lead author Arturo Torres Ortiz, a researcher from Imperial College London, shared that, "We looked for any signs in drug-susceptible bacteria that they will become resistant in future. We identified those 'signatures' and saw that once the bacteria acquires resistance to one antibiotic, it is more likely that they will keep acquiring resistance to other antibiotics. We found that if the bacteria become resistant to isoniazid then they are upto 15 times more likely to acquire further resistance to rifampicin. We identified specific polymorphisms that can be used to make a molecular test in the future to tell us whether this drug-susceptible bacteria will become resistant in the future. This could be a potential game changer for preventing multidrug-resistant TB (MDR-TB)."
"We found that isoniazid mono-resistance backgrounds have a much higher risk of acquiring further rifampicin resistance than susceptible backgrounds. Rapid molecular tests usually focus on rifampicin resistance, which means that isoniazid mono-resistance is missed. This result in amplification into multi-drug resistance. We thus recommend that rapid molecular tests also identify regions associated to isoniazid resistance conferring mutations.
The mutations confer “pre-resistance”. Monitoring these mutations could prevent the amplification of drug resistance in the population by targeting those bacteria more likely to become resistant”, he added.
Molecular testing for TB in children with severe pneumonia
Although TB in children commonly presents with symptoms mimicking pneumonia, its diagnosis is usually considered only if they have repeated antibiotic treatment failures or if symptoms have been present for long. Thus diagnosis of TB in kids is often missed or delayed, causing high mortality in them as they cannot access treatment because they are not diagnosed, said Dr Olivier Marcy, Research Director, University of Bordeaux. He was presenting the results of the TB Speed Pneumonia study on the yield of systematic TB molecular testing performed on nasopharyngeal aspirates and stool samples in children with severe pneumonia in countries with high TB incidence. The study investigated if offering systematic molecular testing for TB in all children with pneumonia is feasible and whether it will affect mortality.
The study was done on 1169 children aged upto 5 years, with WHO-defined severe pneumonia, enrolled in 15 hospitals from 6 high TB incidence countries- Cambodia, Cameroon, Côte d’Ivoire, Mozambique, Uganda, and Zambia.
“Unlike adults, children below age 5 are unable to expectorate to produce sputum for molecular testing. So one has to use easier sample collection methods. We collected stool samples and nasopharyngeal aspirate samples (that involve non-invasive methods). Although taking stool samples seem rather easy in children, it takes time to collect them and it is not as easy as the other option. We could collect nasopharyngeal aspirate samples in 97% children and stool samples in 81% children. Molecular testing of stool samples and nasopharyngeal aspirates was done using Gene Xpert Ultra. 8.0% of the children with severe pneumonia were diagnosed with TB in the intervention arm”, informed Marcy.
“These are important findings. Although we have more and more data that TB is frequent in children with pneumonia, the guidelines and clinical practices are not taking this information into consideration. So we need to have better tools to detect TB in this group. Getting nasopharyngeal aspirates from them is not difficult. So it is important to convince doctors around the world that they can use this technique to diagnose TB in children”, he emphasized.
Artificial Intelligence based automatic detection system to improve diagnostic accuracy for active TB
Scientists at Shenzhen Zhying Medical Imaging in Guangdong, China, have developed an automated detection system based on artificial intelligence (AI) for screening active TB disease on CT images.
They conducted a study to test the accuracy of this detection system that can automatically read DICOM CT images to diagnose active TB disease and also differentiate between TB and pneumonia. This AI-based system, followed with a self-organized clustering algorithm in the study was found to accurately diagnose active TB disease during its earlier stages, and distinguish between active TB disease and non-active TB (i.e. pneumonia and normal cases). It simplifies the diagnosis process and lays a solid foundation for AI in CT diagnosis of active TB disease in a large-scale clinical application.
The sensitivity and specificity for artificial intelligence are very high (0.935 and 0.971 respectively), which show that the AI-tool performs well for diagnosis of active TB disease and differential diagnosis of active TB disease and pneumonia. It can be implemented with minimal need for human intervention. However, while presenting results of this study, Dr Fleming Lure investigator of the study cautioned that, “AI can function as a second pair of eyes. It does not replace the humans but provides references for healthcare professionals to make a final diagnosis. Also, this small study lays good groundwork for the future of AI in the large clinical evaluations and simplify the diagnosis process”.
109 months are left to end TB worldwide: will new tools be pivotal?
The fight to end TB is a human rights imperative. We have to use all existing tools to prevent, diagnose and treat TB rationally and to maximal potential, as well as, fully fund the research and development of new and better tools - and - also ensure that new tools are rolled out equitably, and reach the people in-need as soon as possible without any delay.
Shobha Shukla is the award-winning founding Managing Editor and Executive Director of CNS (Citizen News Service) and is a feminist, health and development justice advocate. She is a former senior Physics faculty of prestigious Loreto Convent College and current Coordinator of Asia Pacific Regional Media Alliance for Health and Development (APCAT Media).
Follow her on Twitter @shobha1shukla or visit www.bit.ly/ShobhaShukla
29 October 2021
- CNS
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- Press 1001 Solutions Network
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