AstraZeneca’s FASENRA® (benralizumab) is now approved by the US Food and Drug Administration (FDA) for add-on maintenance treatment for patients with severe asthma aged 6 to 11 with an eosinophilic phenotype.1 FASENRA was first approved in 2017 as an add-on maintenance for the treatment of severe eosinophilic asthma (SEA) in patients aged 12 and older.1

This additional indication for FASENRA was supported by evidence from TATE, an open-label, multinational, non-randomized, parallel assignment Phase III trial, as well as adequate and well-controlled trials in adult and adolescent populations.2 In the TATE study, FASENRA met the primary endpoints, demonstrating pharmacokinetics (PK) and pharmacodynamics (PD) in children aged 6 to 11 years old with SEA were consistent with those seen in prior trials.

The safety and tolerability of FASENRA in the trial was also consistent with the known profile of the medicine.2 The recommended dose for FASENRA is 30 mg for patients 6 years and older who weigh 35 kg or more. For patients aged 6 to 11 who weigh less than 35 kg, a new 10 mg dose will be available.1 FASENRA is administered by subcutaneous injection every 4 weeks for the first 3 doses, and then every 8 weeks.

Lynda Mitchell, MA, CAE, CEO, of the Allergy & Asthma Network, said: “We welcome additional treatment options for children living with severe asthma, a condition that remains complicated to manage, further helping to address the unmet need in this patient population and reducing the burden of disease for the broader asthma community.”

Asthma is the most common chronic childhood disease and can cause serious symptoms such as coughing, wheezing and difficulty breathing.3 Children with severe asthma and their families face a significant burden, including impaired school performance, substantially higher healthcare resource use and a poorer quality of life.4 Severe asthma is a debilitating type of asthma that can be complicated and challenging to treat.4

Liz Bodin, Vice President, US Respiratory & Immunology, AstraZeneca said: “We’re proud that FASENRA has helped more than 100,000 patients in the US to date. Expanding options for children whose quality of life has been drastically impacted by severe eosinophilic asthma with the help of FASENRA is an exciting step in our mission to revolutionize asthma care.”

FASENRA is currently approved as an add-on maintenance treatment for patients aged 6 and older with SEA in the US.1

IMPORTANT SAFETY INFORMATION

CONTRAINDICATIONS

Known hypersensitivity to benralizumab or excipients.

WARNINGS AND PRECAUTIONS

Hypersensitivity Reactions

Hypersensitivity reactions (e.g., anaphylaxis, angioedema, urticaria, rash) have occurred after administration of FASENRA. These reactions generally occur within hours of administration, but in some instances have a delayed onset (i.e., days). Discontinue in the event of a hypersensitivity reaction.

Acute Asthma Symptoms or Deteriorating Disease

FASENRA should not be used to treat acute asthma symptoms, acute exacerbations, or acute bronchospasm.

Reduction of Corticosteroid Dosage

Do not discontinue systemic or inhaled corticosteroids abruptly upon initiation of therapy with FASENRA. Reductions in corticosteroid dose, if appropriate, should be gradual and performed under the direct supervision of a physician. Reduction in corticosteroid dose may be associated with systemic withdrawal symptoms and/or unmask conditions previously suppressed by systemic corticosteroid therapy.

Parasitic (Helminth) Infection

It is unknown if FASENRA will influence a patient’s response against helminth infections. Treat patients with pre-existing helminth infections before initiating therapy with FASENRA. If patients become infected while receiving FASENRA and do not respond to anti-helminth treatment, discontinue FASENRA until infection resolves.

ADVERSE REACTIONS

The most common adverse reactions (incidence ≥ 5%) include headache and pharyngitis.

Injection site reactions (e.g., pain, erythema, pruritus, papule) occurred at a rate of 2.2% in patients treated with FASENRA compared with 1.9% in patients treated with placebo.

USE IN SPECIFIC POPULATIONS

A pregnancy exposure registry monitors pregnancy outcomes in women exposed to FASENRA during pregnancy. To enroll call 1-877-311-8972 or visit www.mothertobaby.org/Fasenra.

The data on pregnancy exposure from the clinical trials are insufficient to inform on drug-associated risk. Monoclonal antibodies such as benralizumab are transported across the placenta during the third trimester of pregnancy; therefore, potential effects on a fetus are likely to be greater during the third trimester of pregnancy.

INDICATION

FASENRA is indicated for the add-on maintenance treatment of patients with severe asthma aged 6 years and older, and with an eosinophilic phenotype.

FASENRA is not indicated for treatment of other eosinophilic conditions

FASENRA is not indicated for the relief of acute bronchospasm or status asthmaticus

Myopia, commonly known as nearsightedness, has become a growing concern globally, particularly with its early onset in childhood. The condition, characterized by difficulty seeing distant objects clearly, poses significant risks when left unchecked, including the development of high myopia, which can lead to irreversible retinal damage and even loss of central vision. To address this pressing issue, the research team embarked on a randomized clinical trial involving children aged 6 to 18 years diagnosed with myopia within a certain range of severity.

Over the course of the study, which spanned from May 2022 to February 2023, participants were divided into two groups: one receiving daily 20-minute sessions of NVT and the other continuing with their usual activities without any vision training. The primary goal of the study was to assess whether NVT could effectively halt the progression of myopia, as measured by changes in axial length—a key indicator of eye elongation associated with myopia—over a period of six months. Secondary outcomes included evaluating changes in spherical equivalent refraction (SER), another crucial measure of visual impairment.

Findings:

This underscores the safety profile of the intervention, further supporting its potential as a viable option for managing myopia in children. While the results are promising, researchers acknowledge the need for further investigation to confirm the long-term benefits and optimal implementation of NVT. Nonetheless, the findings represent a significant step forward in the quest to combat myopia and safeguard children’s eye health. As the prevalence of myopia continues to rise worldwide, with profound implications for public health, innovative approaches like NVT offer hope for stemming its progression and preserving vision for future generations. With continued research and collaboration, the prospect of a world where myopia is no longer a looming threat to children’s eye health grows ever closer.

A recent study conducted as part of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) aimed to address this gap in knowledge. The study was published in the journal Obstetrics and Gynecology. The study was conducted by Elfassy T. and colleagues.

Hypertensive disorders of pregnancy are prevalent and can have serious consequences for both maternal and infant health. Understanding their association with cognitive decline later in life is essential for identifying potential long-term health risks among affected individuals, particularly in diverse populations such as Hispanic/Latina communities in the United States.

The study analyzed data from the HCHS/SOL, a population-based study of Hispanic/Latino individuals aged 18–74 years from four U.S. communities. Participants included parous individuals aged 45 years or older who underwent neurocognitive assessments at two study visits: visit 1 (2008–2011) and visit 2 (2015–2018). Hypertensive disorders of pregnancy were retrospectively assessed, and cognitive functioning was measured using standardized tests. Linear regression models were used to assess the association between hypertensive disorders of pregnancy and cognitive decline, adjusting for various factors.

The key findings of the study were as follows:

• The analysis included 3,554 individuals with a mean age of 56.2 years, among whom 13.4% reported at least one hypertensive disorder of pregnancy.

• Gestational hypertension was associated with a 0.17-standard deviation (SD) decline in Digit Symbol Substitution scores (95% CI, −0.31 to −0.04) after an average of 7 years of follow-up.

• However, neither preeclampsia nor eclampsia was associated with neurocognitive differences.

• Individuals with hypertensive disorders of pregnancy had higher mean systolic blood pressure, fasting glucose, and body mass index compared to those without.

The study concludes that among the U.S. Hispanic/Latina individuals, gestational hypertension alone is associated with decreased processing speed and executive functioning later in life. However, there was no significant association observed between preeclampsia or eclampsia and cognitive decline. These findings highlight the importance of identifying and managing gestational hypertension to potentially mitigate the risk of cognitive impairment in later years. Further research is needed to elucidate the underlying mechanisms and develop targeted interventions for at-risk individuals.

Reference:

Elfassy, T., Kulandavelu, S., Dodds, L., Mesa, R. A., Rundek, T., Sharashidze, V., Paidas, M., Daviglus, M. L., Kominiarek, M. A., Stickel, A. M., Perreira, K. M., Kobayashi, M. A., Garcia, T. P., Isasi, C. R., Lipton, R. B., & González, H. M. (2024). Association between hypertensive disorders of pregnancy and interval neurocognitive decline: An analysis of the Hispanic Community Health Study/study of Latinos. Obstetrics and Gynecology, 10.1097/AOG.0000000000005571. https://doi.org/10.1097/aog.0000000000005571

The researchers developed an algorithm that identified normal mammograms with very high sensitivity.

They then ran a simulation on patient data to see what would have happened if all of the very low-risk mammograms had been taken off radiologists’ plates, freeing the doctors to concentrate on the more questionable scans.

The simulation revealed that fewer people would have been called back for additional testing but that the same number of cancer cases would have been detected.

“False positives are when you call a patient back for additional testing, and it turns out to be benign,” explained senior author Richard L. Wahl, MD, a professor of radiology at Washington University’s Mallinckrodt Institute of Radiology (MIR) and a professor of radiation oncology.

“That causes a lot of unnecessary anxiety for patients and consumes medical resources. This simulation study showed that very low-risk mammograms can be reliably identified by AI to reduce false positives and improve workflows.”

The study is published April 10 in the journal Radiology: Artificial Intelligence.

Wahl previously collaborated with Whiterabbit.ai on an algorithm to help radiologists judge breast density on mammograms to identify people who could benefit from additional or alternative screening.

That algorithm received clearance from the Food and Drug Administration (FDA) in 2020 and is now marketed by Whiterabbit.ai as WRDensity.

In this study, Wahl and colleagues at Whiterabbit.ai worked together to develop a way to rule out cancer using AI to evaluate mammograms.

They trained the AI model on 123,248 2D digital mammograms (containing 6,161 showing cancer) that were largely collected and read by Washington University radiologists.

Then, they validated and tested the AI model on three independent sets of mammograms, two from institutions in the U.S. and one in the United Kingdom.

First, the researchers figured out what the doctors did: how many patients were called back for secondary screening and biopsies; the results of those tests; and the final determination in each case.

Then, they applied AI to the datasets to see what would have been different if AI had been used to remove negative mammograms in the initial assessments and physicians had followed standard diagnostic procedures to evaluate the rest.

For example, consider the largest dataset, which contained 11,592 mammograms.

When scaled to 10,000 mammograms (to make the math simpler for the purposes of the simulation), AI identified 34.9% as negative.

If those 3,485 negative mammograms had been removed from the workload, radiologists would have made 897 callbacks for diagnostic exams, a reduction of 23.7% from the 1,159 they made in reality.

At the next step, 190 people would have been called in a second time for biopsies, a reduction of 6.9% from the 200 in reality.

At the end of the process, both the AI rule-out and real-world standard-of-care approaches identified the same 55 cancers.

In other words, this study of AI suggests that out of 10,000 people who underwent initial mammograms, 262 could have avoided diagnostic exams, and 10 could have avoided biopsies, without any cancer cases being missed.

“At the end of the day, we believe in a world where the doctor is the superhero who finds cancer and helps patients navigate their journey ahead,” said co-author Jason Su, co-founder and chief technology officer at Whiterabbit.ai. “The way AI systems can help is by being in a supporting role. By accurately assessing the negatives, it can help remove the hay from the haystack so doctors can find the needle more easily. This study demonstrates that AI can potentially be highly accurate in identifying negative exams. More importantly, the results showed that automating the detection of negatives may also lead to a tremendous benefit in the reduction of false positives without changing the cancer detection rate.”

Reference: Stefano Pedemonte, Trevor Tsue, Brent Mombourquette, Yen Nhi Truong Vu, Thomas Matthews, Rodrigo Morales Hoil, Meet Shah, Nikita Ghare, Naomi Zingman-Daniels, Susan Holley, Catherine M. Appleton, Jason Su, Richard L. Wahl. A Semiautonomous Deep Learning System to Reduce False-Positive Findings in Screening Mammography. Radiology: Artificial Intelligence, 2024; DOI: 10.1148/ryai.230033