Study shows it would lead to increases in stages I–III diagnoses and a large decrease in stage IV diagnoses.
Photo by National Cancer Institute on Unsplash
Routine screening is limited to only a few cancer types. New research indicates that routine liquid biopsy testing (multi-cancer early detection testing) could substantially reduce late-stage cancer diagnoses, allowing patients to receive treatment at earlier cancer stages, which are more likely to respond to interventions. The findings are published by Wiley online in CANCER, a peer-reviewed journal of the American Cancer Society.
Currently, routine screening is only recommended for four types of cancer, leaving approximately 70% of new cancer cases to be detected only after symptoms appear, often at an advanced stage when survival rates are lower. Multi-cancer early detection tests offer a revolutionary approach by screening for multiple cancer types simultaneously from a single blood draw.
To evaluate the impact of one such test, Cancerguard, investigators used epidemiological data from the Surveillance, Epidemiology, and End Results database and developed a simulation model of 14 cancer types, which account for nearly 80% of cancer incidence and mortality. The researchers simulated 10-year disease progression for 5 million US adults aged 50–84 years and assessed the effects of incorporating an annual blood-based multi-cancer early detection test into standard care.
The model estimated that over 10 years, supplemental multi-cancer early detection testing would lead to a 10% increase in stage I diagnoses, a 20% increase in stage II diagnoses, a 30% increase in stage III diagnoses, and a 45% decrease in stage IV diagnoses, relative to standard care. The largest absolute reductions in stage IV diagnoses were in lung, colorectal, and pancreatic cancers. The largest relative reductions were in cervical, liver, and colorectal cancers.
“Our analysis shows that multi-cancer blood tests could be a game changer for cancer control,” said Jagpreet Chhatwal, PhD, the study’s lead author and Director of the Institute for Technology Assessment at Massachusetts General Hospital and Harvard Medical School. “By detecting cancers earlier – before they spread – these tests could potentially improve survival and reduce the personal and economic burden of cancer.”
An analysis of data from almost two dozen long-term studies finds that even low-intensity smokers have a substantially higher risk of heart disease and death compared to people who never smoked, even years after they quit. Michael Blaha of the Johns Hopkins Ciccarone Center for Prevention of Cardiovascular Disease, USA, and colleagues report these findings November 18th in the open-access journal PLOS Medicine.
Previous research has shown that smoking cigarettes increases a person’s risk of developing cardiovascular disease, but the exact relationship between how heavily a person smokes and their risks is still unclear, especially for low-intensity smokers. Today, more people are smoking fewer cigarettes, but it’s still important to understand the cardiovascular risks and long-term benefits of quitting, even for individuals who aren’t smoking a pack a day.
Blaha’s team analysed data from more than 300 000 adults enrolled in 22 longitudinal studies – which involve following groups of individuals over time – for up to 19.9 years. In that time, they documented more than 125 000 deaths and 54 000 cardiovascular events, such as heart attacks, strokes and heart failure. The analysis showed that even very low-intensity smoking, defined as two to five cigarettes per day, was associated with a 50% higher risk of heart failure and a 60% higher risk of death from any cause, compared to never smoking. A person’s risk of cardiovascular events dropped most substantially in the first decade after quitting smoking and continued to decrease over time. However, even up to three decades later, former smokers may still exhibit higher risk compared to those who never smoked.
Considering that even occasional or very low-intensity smoking significantly increases a person’s risk of cardiovascular disease and death, the researchers conclude that quitting smoking at younger ages is the best way to decrease your risk, rather than reducing the number of cigarettes smoked each day. These findings reinforce established public health guidelines – that smokers should quit as early as possible instead of just cutting back – and emphasize the importance of smoking prevention programs.
The authors add, “This is one of the largest studies of cigarette smoking to date using the highest quality data in the cardiovascular epidemiology literature. It is remarkable how harmful smoking is – even low doses of smoking confer large cardiovascular risks. As far as behaviour change, it is imperative to quit smoking as early in life as possible, as the among of time passed since complete cessation from cigarettes is more important prolonged exposure to a lower quantity of cigarettes each day.”
Citation: Tasdighi E, Yao Z, Dardari ZA, Jha KK, Osuji N, Rajan T, et al. (2025) Association between cigarette smoking status, intensity, and cessation duration with long-term incidence of nine cardiovascular and mortality outcomes: The Cross-Cohort Collaboration (CCC). PLoS Med 22(11): e1004561. https://doi.org/10.1371/journal.pmed.1004561
The vestibular system is responsible for the sense of balance in the inner ear. Prolonged use of toxic substances, such as certain antibiotics or anticancer drugs, can damage the hair cells that form part of this system, leading to alterations in balance and other motor skills. Now, a team from the University of Barcelona and the Bellvitge Biomedical Research Institute (IDIBELL) has identified the genetic mechanisms involved in the degradation of the vestibular system regarding the damage caused by these ototoxic compounds that affect the vestibule. The results could help improve the diagnosis of chronic vestibular ototoxicity and other pathologies related to the hair cells of the vestibular system.
The study, published in the Journal of Biomedical Science, is led by Jordi Llorens, professor at the UB’s Faculty of Medicine and Health Sciences and researcher at the Institute of Neurosciences (UBneuro) and IDIBELL. Researchers from the National Centre for Genomic Analysis (CNAG) also took part in the study.
The main causes of chronic vestibular ototoxicity are antibiotics of the aminoglycoside family, such as streptomycin – an antibiotic of choice in case of tuberculosis relapses – or anticancer drugs, such as cisplatin. Continued use of these drugs initiates a process of degeneration that causes “the hair cells to detach from the neurons, begin to deform and end up being expelled from their place in the sensory tissue,” explains Llorens.
This is a serious problem because the hair cells of the vestibular system do not regenerate. “We only have the ones we are born with. If we lose them, we also lose our balance, with very diverse consequences: from not being able to ride a bicycle to suffering blurred vision while moving, falls, orientation difficulties, dizziness or vertigo,” explains the UB professor.
Using RNA-seq analysis, i.e. a study of the global expression of genes that reveals which genes are activated or deactivated in the tissues of the vestibular system, the researchers discovered that, in the initial stages of degeneration, the hair cells change the expression of their genes to adapt to the progressive damage caused by otototoxic drugs. “The expression of many genes that define the identity of the hair cell, i.e. those that determine its shape and its ability to respond to movement by generating the signals that are sent to the brain, is reduced,” explains Llorens.
These results, together with the fact, discovered by the researchers, that the damage is reversible during the early stages of the degeneration process, indicate that it is essential to detect the problem as early as possible to stop the toxicity and avoid irreversible damage. “Hair cells become disconnected from neurons and stop sending information to the brain, but if the toxicity is interrupted, the connections can be repaired and function is restored. This increases the chances of avoiding a permanent loss of function,” the researcher stresses.
A potential biomarker
This study may also contribute to advances in the diagnosis and treatment of the pathology, since, according to the researchers, the genetic mechanisms they have identified in response to the stress caused by ototoxic drugs will make it possible, in the future, to “measure this stress and evaluate the effect of possible therapies, such as the development of drugs capable of stopping the process of eliminating hair cells or promoting their repair.”
In addition, the study has identified a new gene, Vsig10l2, expressed by hair cells, which significantly reduces its expression in all the models analysed. “This gene is of great interest as a possible marker of chronic ototoxicity in preclinical studies,” says Llorens.
The same response to different toxics
One of the most remarkable elements of the study is that the analysis has been carried out with four different models of chronic ototoxicity, using two different animal species and two different toxins, and then cross-checking the results of all experiments.
This comprehensive analysis has allowed them to determine that the degradation process occurs in response to very different toxins. “It is not a response conditioned by a particular toxin, it is the basic response of hair cells, which is always there, in response to chronic ototoxicity of any kind,” stresses the UB professor.
These results, together with the fact, discovered by the researchers, that the damage is reversible during the early stages of the degeneration process, indicate that it is essential to detect the problem as early as possible to stop the toxicity and avoid irreversible damage.
Impact on other pathologies
The study could have implications for understanding other pathologies, as the researchers suggest that the response they have demonstrated in chronic ototoxicity might represent a general response to chronic stress of any origin. “The results could be relevant to any chronic pathology with progressive loss of vestibular hair cells, including age-related loss of vestibular function. We also hypothesise that auditory hair cells might respond in a similar way, so they could help understanding deafness,” explains Llorens.
In this sense, the research team is studying – within the framework of a project funded by La Marató de TV3 – the possible relevance of the loss of vestibular function in patients with vestibular schwannoma, a tumour of the audiovestibular nerve that appears spontaneously or as a consequence of a minority disease, neurofibromatosis type 2. “Thanks to this project, we have been able to develop a culture model that allows us to study these chronic effects or how the hair cells become progressively more damaged before dying,” he concludes.
By Vishal Barapatre, Group Chief Technology Officer at In2IT Technologies
Artificial Intelligence (AI) is revolutionising healthcare as profoundly as the discovery of antibiotics or the invention of the stethoscope. From analysing X-rays in seconds to predicting disease outbreaks and tailoring treatment plans to individual patients, AI has opened new possibilities for precision medicine and increased efficiency. In emergency rooms, AI-driven diagnostic tools are already helping doctors detect heart attacks or strokes faster than human eyes alone.
However, as AI systems become increasingly embedded in the patient journey, from diagnosis to aftercare, they raise critical ethical questions. Who is accountable when an algorithm gets it wrong? How can we ensure that patient data remains confidential in the era of cloud computing? And how can healthcare institutions, often stretched thin on resources, balance innovation with responsibility?
When algorithms diagnose: the promise and the problem
AI’s strength lies in its ability to process massive amounts of data, such as medical histories, imaging scans, and lab results, and detect patterns that human clinicians might miss. This can dramatically improve diagnostic accuracy and treatment outcomes. For instance, AI models trained on thousands of mammogram images can help identify subtle indicators of breast cancer earlier than traditional methods.
However, the same data that powers AI can also introduce bias. If the datasets used to train an algorithm are skewed, say, over-representing one demographic group, the results may unfairly disadvantage others. A diagnostic model trained primarily on data from urban hospitals, for example, might misinterpret symptoms in patients from rural areas or underrepresented ethnic groups. Bias in healthcare AI isn’t just a technical flaw; it’s an ethical hazard with real-world consequences for patient trust and equity.
The privacy paradox
The integration of AI in healthcare requires access to vast quantities of sensitive data. This creates a privacy paradox: the more data AI consumes, the smarter it becomes, but the greater the risk to patient confidentiality. The digitisation of health records, combined with AI’s hunger for data, exposes systems to new vulnerabilities. A single breach can compromise thousands of medical histories, potentially leading to identity theft or misuse of personal health information. The paradox underscores the need for robust data protection measures in AI-driven healthcare systems.
Striking a balance between data utility and privacy protection has become one of the healthcare industry’s most pressing ethical dilemmas. Encryption, anonymisation, and strict access controls are essential, but technology alone isn’t enough. Patients need transparency: clear explanations of how their data is used, who has access to it, and what safeguards are in place. Ethical AI requires not only compliance with regulations but also the cultivation of trust through open communication.
Accountability in the age of automation
When an AI system makes a medical recommendation, who is ultimately responsible for the outcome – the algorithm’s developer, the healthcare provider, or the institution that deployed it? The opacity of AI decision-making, often referred to as the “black box” problem, complicates accountability and transparency. Clinicians may rely on algorithmic outputs without fully understanding how conclusions were reached. This can blur the line between human and machine judgment.
Accountability must therefore be clearly defined. Human oversight should remain central to any AI-powered decision, ensuring that technology supports rather than replaces clinical expertise. Ethical frameworks that mandate explainability, where AI systems must provide understandable reasoning for their outputs, are key to maintaining trust. Moreover, continuous auditing of AI models, which involves regularly reviewing and testing the system performance, can help detect and correct biases or errors before they lead to harm, thereby ensuring the ongoing ethical use of AI in healthcare.
Behind the code: who keeps AI ethical
While hospitals and clinics focus on patient care, many lack the internal capacity to manage the complex ethical, security, and technical demands of AI adoption. This is where third-party IT providers play a pivotal role. These partners act as the backbone of responsible innovation, ensuring that AI systems are implemented securely and ethically.
By embedding ethical principles into system design, such as fairness, transparency, and accountability, IT providers help healthcare institutions mitigate risks before they become crises. They also play a crucial role in securing sensitive data through advanced encryption protocols, cybersecurity monitoring, and compliance management. In many ways, they serve as both architects and custodians of ethical AI, ensuring that the pursuit of innovation does not compromise patient welfare.
Building a culture of ethical innovation
Ultimately, the ethics of AI in healthcare extend beyond technology; they are about culture and leadership. Hospitals and healthcare networks must foster environments where ethical reflection is as integral as technical innovation. This involves establishing multidisciplinary ethics committees, conducting bias audits, and training clinicians to critically evaluate and question AI outputs rather than accepting them without examination.
The future of AI in healthcare depends not on how advanced our algorithms become, but on how wisely we use them. Ethical frameworks, transparent governance, and responsible partnerships with IT providers can transform AI from a potential risk into a powerful ally. As the healthcare sector continues to evolve, the institutions that will thrive are those that remember that technology should serve humanity, not the other way around.
If you’ve ever walked through a neonatal intensive care unit (NICU), you’ll know the atmosphere – quiet, sterile, filled with tiny machines keeping even tinier lives stable. What you might not see, though, is the emotional toll it takes on mothers standing behind that glass.
For many moms of premature babies, the NICU isn’t just a place of healing – it’s a battlefield of fear, hope, and heartache. Studies suggest that up to 70% of mothers with babies in NICU experience symptoms of anxiety or depression, and a significant number show signs of post-traumatic stress disorder (PTSD) even months after discharge.
“Having a baby in NICU can be one of the most emotionally isolating experiences a mother faces,” says Sr Londe, independent midwife and Vital Baby South Africa’s trusted advisor. “You’re told to be strong, to hold it together. But inside, you’re scared and feel powerless.”
Unlike traditional postpartum depression, which often develops after birth, NICU-related mental health challenges can begin immediately; triggered by medical uncertainty, feelings of guilt, or the inability to bond physically with your baby.
“You may only be allowed to touch your baby for minutes at a time,” says Sr Londe. “That separation can deeply impact bonding and confidence.”
Feeling numb, struggling to sleep even when your baby is safe, replaying traumatic moments, or feeling disconnected from your child – these are all warning signs of trauma or depression. And yet, many mothers dismiss them.
“There’s still a stigma around maternal mental health,” says Sr Londe. “We need to normalise the conversation and remind mothers that they’re not alone.”
Talking to your healthcare provider, joining a support group, or connecting with a therapist who specialises in perinatal mental health can make a world of difference. Hospitals are also increasingly introducing peer-support programmes where NICU graduates’ parents help new families navigate the emotional maze.
“It’s okay to need help,” says Sr Londe. “You’re not failing as a mother, you’re processing an extraordinary experience.”
As the conversation around maternal mental health grows, brands like Vital Baby are helping raise awareness that caring for moms is as important as caring for their babies. Because behind every incubator, there’s a mother who needs healing too.
Vital Baby is a family-run business with over 45 years of experience in the baby industry. Our mission is to create products that make family time effortless and enjoyable for parents. The Vital Baby range is 100% BPA-free and covers every stage of your baby’s development, from feeding and weaning to hygiene and soothing. Explore the range online at Vital Baby® (vitalbabyshop.co.za) and enjoy delivery within South Africa or find us on shelf at Clicks and Dischem.
