Ongoing increases in the global number of prostate cancer cases expected to motivate test developers to deliver better screening tests to pathologists and clinical lab scientists
No less an authority than the peer-reviewed healthcare journal The Lancet is drawing attention to predictions of increasing prostate cancer cases across the globe, triggering calls for the development of cheaper, faster, and more accurate assays that pathologists and medical laboratories can use to screen for—and diagnose—prostate cancer.
Swift population growth and rising life expectancy will cause the prostate cancer death rate to nearly double in the next 20 years, according to a new study that has led scientists to call for immediate, critical improvements in clinical laboratory testing for cancer screening, Financial Times (FT) reported.
“Low- and middle-income countries need to prepare to prevent a sharp rise in fatalities while richer nations should pay more attention to young men at higher risk of the disease,” FT noted. The study, titled, “The Lancet Commission on Prostate Cancer: Planning for the Surge in Cases,” predicts cases will jump from 1.4 million in 2020 to 2.9 million by 2040.
“Prostate cancer is the most common cancer in men in 112 countries, and accounts for 15% of cancers. In this Commission, we report projections of prostate cancer cases in 2040 on the basis of data for demographic changes worldwide and rising life expectancy. … This surge in cases cannot be prevented by lifestyle changes or public health interventions alone, and governments need to prepare strategies to deal with it,” the study authors wrote.
“The findings in this Commission provide a pathway forward for healthcare providers and funders, public health bodies, research funders, governments, and the broader patient and clinical community,” the authors noted. In their Lancet paper, the researchers define clear areas for improvement.
Given the shortage worldwide of pathologists—especially highly-trained pathologists—the gap between the demand/need for expanded prostate cancer testing as screens (along with prostate biopsies) and the available supply of pathologists will encourage companies to develop screening and diagnostic tests that are accurate and automated, thus increasing the productivity of the available pathologists.
“As more and more men around the world live to middle and old age, there will be an inevitable rise in the number of prostate cancer cases. We know this surge in cases is coming, so we need to start planning and take action now,” said Nick James, PhD (above), Professor of Prostate and Bladder Cancer Research at The Institute of Cancer Research, in a press release. Pathologists and medical laboratories worldwide will want to monitor progress of The Lancet Commission’s recommendations. (Photo copyright: Institute of Cancer Research.)
“Evidence-based interventions, such as improved early detection and education programs, will help to save lives and prevent ill health from prostate cancer in the years to come. This is especially true for low- and middle-income countries (LMICs) which will bear the overwhelming brunt of future cases,” he said in a press release.
Communication is key. “Improved outreach programs are needed to better inform people of the key signs to look out for and what to do next,” James N’Dow, MD, Professor and Chair in Surgery and Director of the Academic Urology Unit at the University of Aberdeen in the UK, told the Financial Times. “Implementing these in tandem with investments in cost-effective early diagnostic systems will be key to preventing deaths,” he added.
Capitalizing on artificial intelligence (AI) analysis to help translate results was another area The Lancet Commission researchers focused on, Financial Times noted.
AI could “subdivide disease into potentially valuable additional subgroups to help with treatment selection. In environments with few or no pathologists, these changes could be transformational,” the study authors wrote.
High Income Countries (HICs) would benefit from AI by empowering patients. “Linking cloud-based records to artificial intelligence systems could allow access to context-sensitive, up-to-date advice for both patients and health professionals, and could be used to drive evidence-based change in all settings,” the study authors added. Such a trend could lead to specialist prostate cancer pathologists being referred cases from around the world as digital pathology systems become faster and less expensive.
Effective treatment strategies and bolstering areas of need is also key, the study notes. “Many LMICs have urgent need for expansion of radiotherapy and surgery services,” the study authors wrote. The researchers stress the need to immediately implement expansion programs to keep up with anticipated near-future demand.
Cancer drug therapy should follow suit.
“Research and the development of risk-stratified regulatory models need to be facilitated,” the study authors noted, citing a focus on drug repurposing and dose de-escalation. “Novel clinical trial designs, such as multi-arm platforms, should be supported and expanded,” they added.
Unique Needs of LMICs, HICs
The Lancet Commission researchers’ recommendations shift depending on the financial health of a specific area. HICs are experiencing a 30-year decline in the number of deaths resulting from prostate cancer, presumably from additional testing measures and public health campaigns that may be lacking in LMICs, Financial Times reported. And as population growth soars, low-to-middle income populations “will need to be prepared for the strain the expected surge in cases will put on health resources.”
For HICs, the study dissected the limitations of prostate-specific antigen (PSA) testing. The researchers pointed out that PSA’s inaccuracies in screening symptomless patients can pinpoint “cancers that may never cause symptoms and need no treatment,” Financial Times reported.
Missing high-risk cases was also a cause for concern. “Diagnostic pathways should be modified to facilitate early detection of prostate cancer while avoiding overdiagnosis and overtreatment of trivial disease,” the study notes.
Screenings for high-risk younger men, and continuing public campaigns about prostate cancer, should be a focus for HICs, the study authors noted. “These would include people who have a family history of the disease, are of African ancestry, or carry a genetic mutation known as BRCA2,” Financial Times reported.
While the undertaking may sound intimidating—there is already such a heavy impact worldwide from prostate cancer—the researchers are optimistic of their recommendations.
“Options to improve care are already available at moderate cost. We found that late diagnosis is widespread worldwide, but especially in LMICs, where it is the norm. Early diagnosis improves prognosis and outcomes, and reduces societal and individual costs, and we recommend changes to the diagnostic pathway that can be immediately implemented,” the study authors wrote.
What Comes Next
“More research is needed among various ethnic groups to expand understanding of prostate cancer beyond the findings from studies that were largely based on data from white men,” The Lancet Commission told the Financial Times.
Astute pathologists and medical laboratories will want to monitor efforts to develop assays that are inexpensive, more accurate, and produce faster answers. Demand for these tests will be substantial—both in developed and developing nations.
Study findings could lead to new clinical laboratory diagnostics that give pathologists a more detailed understanding about certain types of cancer
New studies proving artificial intelligence (AI) can be used effectively in clinical laboratory diagnostics and personalized healthcare continue to emerge. Scientists in the UK recently trained an AI model using machine learning and deep learning to enable earlier, more accurate detection of 13 different types of cancer.
DNA stores genetic information in sequences of four nucleotide bases: A (adenine), T (thymine), G (guanine) and C (cytosine). These bases can be modified through DNA methylation. There are millions of DNA methylation markers in every single cell, and they change in the early stages of cancer development.
One common characteristic of many cancers is an epigenetic phenomenon called aberrant DNA methylation. Modifications in DNA can influence gene expression and are observable in cancer cells. A methylation profile can differentiate tumor types and subtypes and changes in the process often come before malignancy appears. This renders methylation very useful in catching cancers while in the early stages.
However, deciphering slight changes in methylation patterns can be extremely difficult. According to the scientists, “identifying the specific DNA methylation signatures indicative of different cancer types is akin to searching for a needle in a haystack.”
Nevertheless, the researchers believe identifying these changes could become a useful biomarker for early detection of cancers, which is why they built their AI models.
“Computational methods such as this model, through better training on more varied data and rigorous testing in the clinic, will eventually provide AI models that can help doctors with early detection and screening of cancers,” said Shamith Samarajiwa, PhD (above), Senior Lecturer and Group Leader, Computational Biology and Genomic Data Science, Imperial College London, in a news release. “This will provide better patient outcomes.” With additional research, clinical laboratories and pathologists may soon have new cancer diagnostics based on these AI models. (Photo copyright: University of Cambridge.)
The researchers then used a combination of machine learning and deep learning techniques to train an AI algorithm to examine DNA methylation patterns of the collected data. The algorithm identified and differentiated specific cancer types, including breast, liver, lung and prostate, from non-cancerous tissue with a 98.2% accuracy rate. The team evaluated their AI model by comparing the results to independent research.
In their Biology Methods and Protocols paper, the authors noted that their model does require further training and testing and stressed that “the important aspect of this study was the use of an explainable and interpretable core AI model.” They also claim their model could help medical professionals understand “the underlying mechanisms that contribute to the development of cancer.”
Using AI to Lower Cancer Rates Worldwide
According to the Centers for Disease Control and Prevention (CDC), cancer ranks as the second leading cause of death in the United States with 608,371 deaths reported in 2022. The leading cause of death in the US is heart disease with 702,880 deaths reported in the same year.
Globally cancer diagnoses and death rates are even more alarming. World Health Organization (WHO) data shows an estimated 20 million new cancer cases worldwide in 2022, with 9.7 million persons perishing from various cancers that year.
The UK researchers are hopeful their new AI model will help lower those numbers. They state in their paper that “most cancers are treatable and curable if detected early enough.”
More research and studies are needed to confirm the results of this study, but it appears to be a very promising line of exploration and development of using AI to detect, identify, and diagnose cancer earlier. This type of probing could provide pathologists with improved tools for determining the presence of cancer and lead to better patient outcomes.
As this therapeutic approach gains regulatory approval, clinical laboratory tests to determine condition of patient’s gut microbiota and monitor therapy will be needed
Some developments in the clinical laboratory industry are less about diagnostic tests and more about novel approaches to therapy. Such is the case with a new carbon bead technology developed by researchers from University College London (UCL) and the Royal Free Hospital intended to remove harmful bacteria toxins from the gut before they leak to the liver. The macroporous beads, which come in small pouches, are delivered orally and could be utilized in the future to treat a number of diseases.
Why is this relevant? Once a new treatment is accepted for clinical use, demand increases for a clinical laboratory test that confirms the therapy will likely work and to monitor its progress.
In collaboration with Yaqrit, a UK-based life sciences company that develops treatments for chronic liver disease, the UCL and Royal Free Hospital scientists engineered the carbon beads—known as CARBALIVE—to help restore gut health. They measured the technology’s impact on liver, kidney, and brain function in both rats and mice.
“The influence of the gut microbiome on health is only just beginning to be fully appreciated,” said Rajiv Jalan, PhD, Professor of Hepatology at UCL in a press release. “When the balance of the microbiome is upset, ‘bad’ bacteria can proliferate and out-compete the ‘good’ bacteria that keeps the gut healthy.
“One of the ways [the ‘bad’ bacteria] do this is by excreting endotoxin, toxic metabolites, and cytokines that transform the gut environment to make it more favorable to them and hostile to good bacteria,” he continued. “These substances, particularly endotoxin, can trigger gut inflammation and increase the leakiness of the gut wall, resulting in damage to other organs such as the liver, kidneys, and brain.”
“I have high hopes that the positive impact of these carbon beads in animal models will be seen in humans, which is exciting not just for the treatment of liver disease but potentially any health condition that is caused or exacerbated by a gut microbiome that doesn’t work as it should,” said Rajiv Jalan, PhD (above), Professor of Hepatology, University College London, in a press release. “This might include conditions such as irritable bowel syndrome (IBS), for example, which is on the rise in many countries.” Though not a clinical laboratory diagnostic test, new therapies like CARBALIVE could be a boon to physicians treating patients with IBS and other gastrointestinal conditions.
Developing the Carbon Beads
The team discovered CARBALIVE is effective in the prevention of liver scarring and injury in animals with cirrhosis when ingested daily for several weeks. They also found a reduced mortality rate in test animals with acute-on-chronic-liver-failure (ACLF).
After achieving success with CARBALIVE in animals, the researchers tested the technology on 28 cirrhosis patients. The carbon beads proved to be safe for humans and had inconsequential side effects.
“In cirrhosis, a condition characterized by scarring of the liver, it is known that inflammation caused by endotoxins can exacerbate liver damage,” Jalan explained. “Part of the standard treatment for cirrhosis is antibiotics aimed at controlling bad bacteria, but this comes with the risk of antibiotic resistance and is only used in late-stage disease.”
The beads, which are smaller than a grain of salt, contain an exclusive physical structure that absorbs large and small molecules in the gut. They are intended to be taken with water at bedtime as harmful bacteria is more likely to circulate through the body at night which could result in damage. The carbon beads do not kill bacteria, which decreases the risk of antibiotic resistance. They eventually pass through the body as waste.
“They work by absorbing the endotoxins and other metabolites produced by ‘bad’ bacteria in the gut, creating a better environment for the good bacteria to flourish and helping to restore microbiome health,” said Michal Kowalski, M.Sc.Eng, Director and VP of Operations at Yaqrit, in the UCL news release.
“This prevents these toxins from leaching into other areas of the body and causing damage, as they do in cirrhosis,” he added. “The results in animal models are very positive, with reduction in gut permeability, liver injury, as well as brain and kidney dysfunction.”
Additional Research
The researchers plan to perform further clinical trials in humans to determine if the carbon beads are effective at slowing the progression of liver disease. If the benefits that were observed in lab animals prove to be compelling in humans, the technology may become an invaluable tool for the treatment of liver disease and other diseases associated with poor microbiome health in the future.
According to the American Liver Foundation, 4.5 million adults in the US have been diagnosed with liver disease. However, it is estimated that 80 to 100 million adults have some form of fatty liver disease and are unaware of it. Liver disease was the 12th leading cause of death in the US in 2020 with 51,642 adults perishing from the disease that year.
According to BMC Public Health, globally there were 2.05 million new cases of liver cirrhosis diagnosed in 2019. In that year, 1.47 million people around the world died from the disease.
More research and clinical studies are needed before this novel technology can be used clinically. When and if that happens, the demand for clinical laboratory tests that measure microbiome deficiencies and monitor patient progress during therapy will likely be high.
Researchers used CRISPR-based assays to develop new clinical laboratory point-of-care blood test which boasts accuracy, affordability, and accessibility
According to UPI, the test can “distinguish between influenza A and influenza B—the two main types of seasonal flu—as well as identifying more virulent strains like H1N1 and H3N2.”
Many research teams are working to develop paper-based diagnostic screening tests because of their lower cost to produce and usefulness in remote locations. Should this near-patient point-of-care test become clinically viable, it could mean shorter times to answer, enabling speedier diagnoses and earlier start of treatment.
It also means patient specimens do not have to be transported to a clinical laboratory for testing. And reduced cost per test makes it possible to test more people. This serves the public health aspect of monitoring outbreaks of influenza and other diseases and gives hope for improved treatment outcomes.
“Being able to tease apart what strain or subtype of influenza is infecting a patient has repercussions both for treating them and public health interventions, said Jon Arizti Sanz, PhD, co-lead study author and postdoctoral researcher at the Broad Institute of Harvard and MIT, in a Broad Institute news release.
“Ultimately, we hope these tests will be as simple as rapid antigen tests, and they’ll still have the specificity and performance of a nucleic acid test that would normally be done in a laboratory setting,” Cameron A. Myhrvold, PhD (above), Assistant Professor of Molecular Biology at Princeton University in New Jersey, told CIDRAP. Influenza tests that can be performed at the point of care and in remote locations may reduce the number of screening tests performed by clinical laboratories. (Photo copyright: Michael James Butts/Hertz Foundation.)
Her team developed their tests using Streamlined Highlighting of Infections to Navigate Epidemics (SHINE), “a clustered regularly interspaced short palindromic repeats (CRISPR)-based RNA detection platform,” the researchers wrote in their Journal of Molecular Diagnostics paper.
“SHINE has a runtime of 90 minutes, can be used at room temperature and only requires an inexpensive heat block to heat the reaction. The SHINE technology has previously been used to identify SARS-CoV-2 and later to distinguish between the Delta and Omicron variants,” Bioanalysis Zone reported.
“The test uses genetically engineered enzymes to identify specific sequences of viral RNA in samples,” the researchers told UPI. Originally designed to detect COVID-19, the team adapted the technology to detect influenza in 2022 “with the aim of creating a screening tool that could be used in the field or in clinics rather than hospitals or high-tech diagnostic labs,” they said.
Influenza A and B as well as H1N1 and H3N2 subtypes were the targets of the four SHINE assays. “When tested on clinical samples, these optimized assays achieved 100% concordance with quantitative RT-PCR. Duplex Cas12a/Cas13a SHINE assays were also developed to detect two targets simultaneously,” the researchers wrote in their paper.
The team used “20 nasal swabs from people with flu-like symptoms during the 2020-2021 flu season, nasal fluid from healthy people as the control, and 2016-2021 influenza sequences downloaded from the National Center for Biotechnology Information Influenza (NICB) database. They compared the results with those from quantitative reverse transcription-polymerase chain reaction (RT-PCR) tests,” CIDRAP reported.
The original 2020 test (shown above) takes 90 minutes to develop at room temperature. The test developers aim to drop this down to 15 minutes. In comparison, typical polymerase chain reaction (PCR) testing requires medical laboratories to have specialized equipment, trained staff, and prolonged processing times, the Broad Institute news release notes. (Photo copyright: Broad Institute.)
Implications of the New Tests
The ease of the new tests is an important development since approximately only 1% of individuals who come down with the flu see doctors for testing, according to the news release. And researchers had this in mind, looking at speed, accuracy, and affordability as a means to “improve outbreak response and infection care around the world,” UPI reported.
There are great benefits to strain differentiation that be achieved with the new test. Doctors are hopeful the test will help dial in the best treatment plans for patients since some strains are resistant to the antiviral medication oseltamivir (Tamiflu), UPI noted. This is significant since Tamiflu “is a common antiviral,” said Sanz in the Broad Institute news release.
“These assays have the potential to expand influenza detection outside of clinical laboratories for enhanced influenza diagnosis and surveillance,” the Journal of Molecular Diagnostics paper noted. This allows for more strategic treatment planning.
“Using a paper strip readout instead of expensive fluorescence machinery is a big advancement, not only in terms of clinical care but also for epidemiological surveillance purposes,” said Ben Zhang, an MD candidate in the Health Sciences and Technology at Harvard and co-first author of the study, in the Broad Institute news release.
Future Plans for Tests
“With further development, the test strip could be reprogrammed to distinguish between SARS-CoV-2 and flu and recognize swine flu and avian flu, including the H5N1 subtype currently causing an outbreak in US dairy cattle,” the study authors told CIDRAP.
The team is also looking at ways to help prevent H5N1 from crossing into human contamination, Sanz told UPI.
The new Princeton/MIT/Harvard tests echo the trend to bring in affordability and ease-of-use with accurate results as an end goal. Faster results mean the best treatments for each person can start sooner and may render the transport of specimens to a clinical laboratory as a second step unnecessary.
As research teams work to develop paper-based viral tests for their plethora of benefits, clinical laboratories will want to pay close attention to this development as it can have a big implication on assisting with future outbreaks.
Additional research is needed before these tests are going to be commonplace in homes worldwide, but this first step brings inspiration and hope of what’s to come.
Use of artificial intelligence in clinical laboratory testing could improve the diagnosis of cancer worldwide
In a proof of concept study, scientists at Shanghai Jiao Tong University in China have developed a clinical laboratory test that utilizes artificial intelligence (AI) to diagnose three types of cancer from a single drop of dried blood. The paper-based test was able to identify patients with colorectal, gastric, and pancreatic cancers and distinguish between patients with and without cancer.
The team’s goal was to develop a way to diagnose cancer while the disease is still in the earlier stages, especially in rural areas.
“Over a billion people across the world experience a high rate of missed disease diagnosis, an issue that highlights the need for diagnostic tools showing increased accuracy and affordability. In addition, such tools could be used in ecologically fragile and energy-limited regions, pointing to the need for developing solutions that can maximize health gains under limited resources for enhanced sustainability,” the researchers wrote in an article published in the journal Nature Sustainability titled, “A Sustainable Approach to Universal Metabolic Cancer Diagnosis.”
The researchers determined that by using less than 0.05 millimeters of dried blood, their test could accurately and quickly identify if a patient had cancer between 82% to 100% of the time.
According to Chaoyuan Kuang, MD, PhD (above), an oncologist at Montefiore Health System and assistant professor at the Albert Einstein College of Medicine, unlike liquid blood, dried serum can be “collected, stored, and transported at much lower cost and with much simpler equipment,” Live Science reported. “This could help democratize the availability of cancer early detection testing across the world,” he added. A paper-based clinical laboratory test that can detect and distinguish one cancer type from another would be a boon to cancer diagnosis worldwide. (Photo copyright: Albert Einstein College of Medicine.)
Improving Cancer Screening in Rural Areas
An earlier study conducted in China in 2022 examined results from 1,570 cancer survivors from both urban and rural areas of China. That study showed that 84.1% of the patients were diagnosed with cancer only after developing symptoms and that urban patients were more likely to be diagnosed in the early stages of cancer. In addition, rural patients also had less screening and treatment options available to them.
The researchers in this latest Chinese study tested their AI model on blood donors with and without cancer and compared the results to traditional liquid-blood biopsy tests.
“Based on modeling they performed, they reported the new tool could reduce the estimated proportion of undiagnosed cases of pancreatic, gastric, and colorectal cancers by about 20% to 50% if it was used for population-level cancer screening in rural China,” Live Science reported.
The scientists used dried serum spots (DSS) and machine learning to perform the research. According to their Nature Sustainability paper, DSS can be challenging in cancer research because sensitive biomarkers in the samples are often degraded or have inadequate amount of blood for proper analysis. To circumvent these issues, the researchers used nanoparticle-enhanced laser desorption/ionization mass spectrometry (NPELDI MS) to increase reliability and sensitivity. Inorganic nanoparticles were applied to the samples to strengthen selectivity and refine metabolic compounds from the samples.
However, the study authors noted that “the adaptation of NPELDI MS to dried spot analysis has not been validated,” Interesting Engineering reported.
A ‘Great Start’
The machine learning algorithm the Chinese scientists created demonstrates that DSS samples can be used to preserve important biological markers and could be beneficial in the diagnosis of cancer.
Their research indicated an overall reduction rate of undiagnosed cancers in the range of 20.35% to 55.10%. The researchers estimated the implementation of their AI tool could reduce the proportion of specific undiagnosed cancer cases in rural China by:
84.30% to 29.20% for colorectal cancer,
77.57% to 57.22% for gastric cancer, and
34.56% to 9.30% for pancreatic cancer.
It’s a “great start,” Chaoyuan Kuang, MD, PhD, an oncologist at Montefiore Health System and assistant professor at the Albert Einstein College of Medicine told Live Science. “This cancer test won’t enter use for a long time,” he said. Nevertheless, the potential of the tool is “immense,” he added, but that “we are still years away from being able to offer this test to patients.
“With further development, it could theoretically be used for the early detection of other types of cancer or for other diseases, or to monitor the progression of disease in patients who have already been diagnosed,” he noted.
Further research and clinical trials are needed before this AI tool can be used in a clinical diagnostic setting. This study is another example of researchers looking for cancer biomarkers in specimen types that are not tissue and further supports the hope that machine learning may one day detect cancer in earlier stages, increase survival rates, and save healthcare costs.
One factor motivating this type of research in China is the fact that the nation has more than 36,000 hospitals and approximately 20,000 anatomic pathologists. Of this total, only a minority of these pathologists have been trained to the standards of North America and Northern Europe.
Like other nations, China’s demand for subspecialist pathology services outstrips its supply of such pathologists. This is the reason why researchers in that country want to develop diagnostic assays for cancer and other diseases that are faster, cheaper, and comparable to a human pathologist in accuracy.
Study results from Switzerland come as clinical laboratory scientists seek new ways to tackle the problem of antimicrobial resistance in hospitals
Microbiologists and clinical laboratory scientists engaged in the fight against antibiotic-resistant (aka, antimicrobial resistant) bacteria will be interested in a recent study conducted at the University of Basel and University Hospital Basel in Switzerland. The epidemiologists involved in the study discovered that some of these so-called “superbugs” can remain in the body for as long as nine years continuing to infect the host and others.
The researchers wanted to see how two species of drug-resistant bacteria—K. pneumoniae and E. coli—changed over time in the body, according to a press release from the university. They analyzed samples of the bacteria collected from patients who were admitted to the hospital over a 10-year period, focusing on older individuals with pre-existing conditions. They found that K. pneumoniae persisted for up to 4.5 years (1,704 days) and E. coli persisted for up to nine years (3,376 days).
“These patients not only repeatedly become ill themselves, but they also act as a source of infection for other people—a reservoir for these pathogens,” said Lisandra Aguilar-Bultet, PhD, the study’s lead author, in the press release.
“This is crucial information for choosing a treatment,” explained Sarah Tschudin Sutter, MD, Head of the Division of Infectious Diseases and Hospital Epidemiology, and of the Division of Hospital Epidemiology, who specializes in hospital-acquired infections and drug-resistant pathogens. Sutter led the Basel University study.
“The issue is that when patients have infections with these drug-resistant bacteria, they can still carry that organism in or on their bodies even after treatment,” said epidemiologist Maroya Spalding Walters, MD (above), who leads the Antimicrobial Resistance Team in the Division of Healthcare Quality Promotion at the federal Centers for Disease Control and Prevention (CDC). “They don’t show any signs or symptoms of illness, but they can get infections again, and they can also transmit the bacteria to other people.” Clinical laboratories working with microbiologists on antibiotic resistance will want to follow the research conducted into these deadly pathogens. (Photo copyright: Centers for Disease Control and Prevention.)
COVID-19 Pandemic Increased Antibiotic Resistance
The Basel researchers looked at 76 K. pneumoniae isolates recovered from 19 patients and 284 E. coli isolates taken from 61 patients, all between 2008 and 2018. The study was limited to patients in which the bacterial strains were detected from at least two consecutive screenings on admission to the hospital.
“DNA analysis indicates that the bacteria initially adapt quite quickly to the conditions in the colonized parts of the body, but undergo few genetic changes thereafter,” the Basel University press release states.
The researchers also discovered that some of the samples, including those from different species, had identical mechanisms of drug resistance, suggesting that the bacteria transmitted mobile genetic elements such as plasmids to each other.
One limitation of the study, the authors acknowledged, was that they could not assess the patients’ exposure to antibiotics.
Meanwhile, recent data from the World Health Organization (WHO) suggests that the COVID-19 pandemic might have exacerbated the challenges of antibiotic resistance. Even though COVID-19 is a viral infection, WHO scientists found that high percentages of patients hospitalized with the disease between 2020 and 2023 received antibiotics.
“While only 8% of hospitalized patients with COVID-19 had bacterial co-infections requiring antibiotics, three out of four or some 75% of patients have been treated with antibiotics ‘just in case’ they help,” the WHO stated in a press release.
WHO uses an antibiotic categorization system known as AWaRe (Access, Watch, Reserve) to classify antibiotics based on risk of resistance. The most frequently prescribed antibiotics were in the “Watch” group, indicating that they are “more prone to be a target of antibiotic resistance and thus prioritized as targets of stewardship programs and monitoring.”
“When a patient requires antibiotics, the benefits often outweigh the risks associated with side effects or antibiotic resistance,” said Silvia Bertagnolio, MD, Unit Head in the Antimicrobial resistance (AMR) Division at the WHO in the press release. “However, when they are unnecessary, they offer no benefit while posing risks, and their use contributes to the emergence and spread of antimicrobial resistance.”
Citing research from the National Institutes of Health (NIH), NPR reported that in the US, hospital-acquired antibiotic-resistant infections increased 32% during the pandemic compared with data from just before the outbreak.
“While that number has dropped, it still hasn’t returned to pre-pandemic levels,” NPR noted.
The UPenn researchers have already developed an antimicrobial treatment derived from guava plants that has proved effective in mice, Vox reported. They’ve also trained an AI model to scan the proteomes of extinct organisms.
“The AI identified peptides from the woolly mammoth and the ancient sea cow, among other ancient animals, as promising candidates,” Vox noted. These, too, showed antimicrobial properties in tests on mice.
These findings can be used by clinical laboratories and microbiologists in their work with hospital infection control teams to better identify patients with antibiotic resistant strains of bacteria who, after discharge, may show up at the hospital months or years later.
