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Advancements over the past few decades in novel therapies and improved imaging techniques have substantially improved the prognosis for patients with the once-debilitating disorder hemophilia, Annette von Drygalski, MD, PharmD, RMSK, highlighted in a session at the 2024 ASH Annual Meeting.

"Over the past decade, there were remarkable scientific and technical advancements, and those have propelled hemophilia care on all levels," said von Drygalski, from the University of California San Diego. "Outcomes have gone from incurable and untreatable, where patients died in childhood in the 1960s, to treatable and now potentially curable with normal lifespans due to innovative prophylactic treatments including novel clotting factor molecules, factor-less treatments, and gene therapy."

With a focus on clinical advancements, von Drygalski outlined the evolution of care, particularly the mechanisms behind bleeding and the growing array of therapeutic and imaging options for patients.

Mechanisms of Bleeding and the Evolution of Hemophilia Care

The incidence of hemophilia is approximately 25 cases per 100,000 males for hemophilia A and 5 per 100,000 for hemophilia B. "It is characterized by a deficiency in clotting factors—factor VIII in hemophilia A and factor IX in hemophilia B. This leads to spontaneous joint and muscle bleeds presenting in childhood," said von Drygalski.

The severity of the disease is categorized by the level of clotting factor activity present in the blood. Severe cases, defined as having less than 1% of normal clotting factor activity, are typically characterized by spontaneous joint and muscle bleeds. These often begin in childhood and can lead to debilitating musculoskeletal damage if left unaddressed.

For many years, the primary treatment for hemophilia involved frequent intravenous infusions of clotting factors. These infusions were necessary to maintain clotting factor levels above a certain threshold and prevent spontaneous bleeding; however, these therapies often led to inconsistent clotting factor levels, characterized by "sawtooth" patterns of high peaks and low troughs. This fluctuation left patients vulnerable to breakthrough bleeds between infusions, said von Drygalski.

Advances in Prophylaxis and Novel Treatment Strategies

The introduction of extended half-life clotting factor products helped to address these challenges by providing more stable levels of factor activity in the blood, reducing the frequency of infusions and minimizing the risk of bleeding. These advances represented the beginning of a new era in hemophilia care.

"The pillars of prophylaxis are still clotting factor, either conventional half-life or extended half-life products with at least once weekly intravenous infusions," said von Drygalski. "Then we have so-called rebalancing agents with factor VIII mimetic and just recently with the TFPI inhibitor. These are subcutaneous treatments weekly to monthly. And then we now have gene therapy, with 3 approved ones: 2 for hemophilia B and 1 for hemophilia A. These are an intravenous infusion presumably once in a lifetime."

Rebalancing agents, such as factor VIII mimetics, work by replacing or mimicking the activity of missing clotting factors. Marstacimab (Hympavzi) helps to rebalance by inhibiting TFPI, which prevents inhibition of factor Xa. Emicizumab (Hemlibra) is a bispecific antibody that is specific to factor IXa and X, which activates the coagulation cascade. "This agent mimics or replaces factor XIII activity," von Drygalski said.

Additionally, gene therapy has emerged as a potential long-term solution for hemophilia. By introducing a functional copy of the clotting factor gene, these therapies aim to restore normal clotting factor production in a single infusion. The 3 agents approved by the FDA are etranacogene dezaparvovec (Hemgenix) and fidanacogene elaparvovec (Beqvez) for hemophilia B and valoctocogene roxaparvovec (Roctavian) for hemophilia A.

Hemophilic Arthropathy: A Persistent Challenge

Despite the significant advancements in prophylactic treatments, hemophilic arthropathy remains a major concern for patients. Hemophilic arthropathy refers to the progressive joint damage caused by recurrent bleeds into the joint space. Although prevention of joint bleeding through prophylaxis has improved, von Drygalski emphasized that breakthrough and spontaneous bleeds still occur, leading to long-term musculoskeletal complications.

The pathobiology of hemophilic arthropathy is complex and involves multiple factors. One key factor is iron deposition in the joint space, which occurs when red blood cells are lysed and their contents, including iron, are released into the tissue. "Iron is a toxic payload," von Drygalski said. "Iron is the incendiary agent propelling joint deterioration."

Iron accumulation, specifically in the form of hemosiderin, is a hallmark of hemophilic arthropathy, she noted. The early signs of this process are typically synovial hypertrophy, accompanied by neovascularization and vascular remodeling. These newly formed vessels are particularly fragile, making them prone to rebleeding, which exacerbates joint damage.

"The prevention of joint and other bleeding complications is key," von Drygalski stated. "Absent the elimination of joint bleeding, we will have progression of musculoskeletal complications with a need for understanding the pathobiology of hemophilic arthropathy and also optimization of point of care imaging tools to support prompt and tailored management."

Imaging Advancements: Point-of-Care Ultrasound

For years, the primary tools for monitoring joint health were X-rays and MRIs; however, these methods are not always sensitive to early joint changes and are often costly and cumbersome. Point-of-care musculoskeletal ultrasound has emerged as a valuable tool for detecting joint bleeds and monitoring long-term joint health. "With ultrasound, we can easily differentiate between synovium and fluid in the joint," von Drygalski said.

To this end, von Drygalski detailed the Joint Activity and Damage Exam (JADE), which is a specialized musculoskeletal ultrasound (MSKUS) protocol designed to assess the condition of joints in patients with hemophilia. This protocol provides a comprehensive evaluation by measuring several key parameters, including cartilage thickness, soft tissue expansion, and osteochondral changes.

"It's incorporated into clinical trials and it's suitable for handheld pocket ultrasounds that have taken over our clinics," said von Drygalski. "It is attached to a very effective CME accredited training program that's easily taught to non-radiologists and even patients. Int the future, there could be musculoskeletal ultrasound for rapidly detection and joint health assessments including perhaps patient self-imaging paired with artificial intelligence."

Articles

Advancements in hemophilia care, including novel therapies and improved imaging, have significantly enhanced patient outcomes. Once considered incurable, hemophilia is now treatable and potentially curable, with patients achieving normal lifespans. Key developments include extended half-life clotting factors, rebalancing agents, and gene therapy. Despite these advances, hemophilic arthropathy remains a challenge due to recurrent joint bleeds. Point-of-care musculoskeletal ultrasound, such as the JADE protocol, offers a promising tool for early detection and monitoring of joint health, potentially empowering patients through self-imaging and AI integration.

At ASH 2024, Annette von Drygalski, MD, PharmD, described the paradigm shift that has taken place in hemophilia over the past decade. 

Innovative Hemophilia Treatments Offer Hope Amid Lingering Clinical Challenges

An AI screening tool that was trained to detect geography atrophy (GA) effectively screened participants for clinical trial enrollment, with agreement with retina specialists in nearly three-fourths of cases, according to findings presented in a poster at the 

Association for Research in Vision and Ophthalmology (ARVO) 2024 Meeting

Of the 33 prospectively screened patients, roughly 10 were excluded by the AI as being out of range (30.3%). This compared with 11 who were excluded by graders from the Wisconsin Reading Center who oversaw the research. Overall, the agreement between the AI screening tool and retina specialists was 73% and the agreement was 67% between the AI reports and the Wisconsin Reading Center researchers. "Most disagreements were due to foveal involvement or missed small lesions," said senior researcher Amitha Domalpally, MD, PhD.

"The study highlights the importance of validation and implementation studies to bridge the gap between AI model creation and real-world application," Domalpally, research director of the Wisconsin Reading Center, told 

 over email. "There is a critical need for accurate measurement of GA, a key factor for screening and monitoring in clinical trials. Currently there are no clinical tools to measure GA."

For the prospectively run study, clinical trial eligibility was defined as a uni or multifocal GA area of 1.25 to 23 mm

, along with the absence of neovascular age-related macular degeneration. After these patients were identified by clinical examination, their fundus autofluorescence (FAF) images were captured and uploaded to the AI platform for further validation. This was followed by a human review first by the retina specialists then the researchers in Wisconsin for validation.

"We performed this study to implement an AI model in a clinical trial and test its real-world performance," said Domalpally. In the ARVO poster, researchers concluded that "Al algorithms enhance accuracy of patient selection in clinical trials, expediting enrollment through real-time assessment and reducing screen failure rates."

The AI model was initially trained using FAF images from the Age-Related Eye Disease Studies 2 (AREDS2). These data were annotated by researchers at Wisconsin Reading Center to train the AI to find GA specifically. The model was trained using weak-labeled images, which consisted of measurements only and no GA indicators, and a strong-labeled image, which included GA segmentation masks. Initial findings for the AI were published in 

In this initial AREDS2 dataset, 601 images were analyzed by humans and by AI for both weak- and strong-labeled images. The mean area of GA for each was 6.65 mm

, respectively. The dice coefficient in this example for cross validation was 0.885, meaning there was 88.5% similarity in the areas between the AI and the researchers.

In addition to the AREDS2 data, 156 images were also analyzed from GSK testing data from a clinical trial that was ran between 2011 and 2016 (NCT01342926). This set was annotated by the Reading Center and in this samples the human GA area was 9.79 mm

. The mean difference between the human and the strong labeled was -0.24 mm

. In this case, there was a 91.8% agreement (dice coefficient, 0.918).

In a similar retrospective fashion, which was separate from the research published in 

, another data set was examined that included 48 images from the Moorfields Eye Hospital. These images were reviewed and annotated by researchers at this institution and found a 0.478 mm

 mean difference in GA area between the researcher's measurement and that given by the AI (dice coefficient, 0.895).

"The model performed consistently across all datasets–clinical, clinical trial, retrospective, and prospective–showcasing the generalizability and robustness of the model," said Domalpally. "We had 2 important goals: one, to assess the AI tool’s effectiveness in measuring GA in 4 diverse datasets; and 2, to analyze clinicians use of AI-generated reports on GA area to decide clinical trial eligibility."

Slater R, Chandra S, Saunders T, et al. Real-World Assessment and Clinician Acceptance of AI in GA Measurement. Paper presented at the Association for Research in Vision and Ophthalmology (ARVO) 2024 Meeting, May 5–9, 2024.

Domalpally A, Slater R, Linderman R, et al. Strong vs Weak Data Labeling for Artificial Intelligence Algorithms in the Measurement of Geographic Atrophy. 

. 2024;S2666-9145(24)00013-7: Doi:10.1016/j.xops.2024.100477

Retina specialists and an AI screening tool trained to measure geographic atrophy agreed in a majority of cases, potentially expediting clinical trial enrollment and increasing consistency in measuring the disease. 

AI an Effective Geographic Atrophy Screening Tool 

Intravitreal treatment with tarcocimab tedromer (KSI-301) resulted in a significant 41.1% 2-step or greater improvement in diabetic retinopathy severity score (DRSS) for patients with anti-VEGF naive non-proliferative diabetic retinopathy (NPDR), according to findings presented in a poster at the 

Treatment with tarcocimab was compared with a sham injection, which saw just a 1.4% improvement in 2-step or greater DRSS. Overall, there was a 29-times increase in response rate ratio with tarcocimab (

 <.0001), which was administered at up to a 6-month interval. These results successfully met the primary end point of the phase 3 GLOW1 study, resulting in a rejuvenation in interest for the medication.

"Tarcocimab given at up to 6-month dosing resulted in clinically meaningful reduction in severity of diabetic retinopathy, specifically 41% of subjects improved at least 2 steps in diabetic retinopathy severity scores compared to sham," lead investigator Robert W. Wong, MD, from Austin Retina Associates, told 

 over email. "We also found an 89% reduction in sight threatening complications such as advancement to proliferative diabetic retinopathy or anterior segment neovascularization when given 4 doses over twelve months as compared to sham. There was a 95% reduction of risk of developing diabetic macular edema as compared to sham."

Tarcocimab tedromer consist of an anti-VEGF antibody conjugated to a biopolymer, which is meant to extend the duration of effect for the medication by providing biologic benefits within the retina and by reducing friction. Additionally, the polymer contains other small and bioactive molecules, with a high overall drug-to-antibody ratio. "Tarcocimab is an anti-VEGF antibody biopolymer conjugate that allows for sustained treatment effect and durability as compared to current therapeutics available on the market," said Wong.

In the GLOW1 trial, the treatment was given at a progressively extended treatment interval, starting at day 1, then week 8 followed by week 20 and then every 24 weeks thereafter for a treatment-free interval of 6 months.

"As a clinician, what it is most relevant is the potential of 6-month dosing," said Wong. "The adoption of treatment has been historically limited due to the high treatment burden, so having this extended interval option can make a significant difference in the treatment of this patient."

The baseline characteristics were well matched between the groups, with a mean age across arms of 56.7 years. In the tarcocimab arm (n = 128), the mean best corrected visual acuity (BCVA) at entry was 81.8 ETDRS letters (±5.79) and in the sham group (n = 125) it was 81.2 letters (±5.76). The central subfield thickness (CST) was a mean of 268.6 (±26.3) in the tarcocimab group and 265.3 (±25.05) in the sham arm. The baseline DRSS was at 53 or greater for 64.1% of those in the tarcocimab group compared with 64.0% in the sham arm. Overall, nearly all patients completed 48 weeks on the study, at 93.8% in the tarcocimab arm and 92% in the sham group.

For the key secondary end points, tarcocimab was found to reduce the risk of developing any sight-threatening complications, with 21.0% of those in the sham group developing these complications compared with only 2.3% in the treatment arm, an 89% risk reduction (

 <.0001). Diabetic macular edema occurred in 13.7% of those in the sham group compared with 0.7% in the tarcocimab arm, which was a 95% reduction in risk (

Overall, 70% of patients treated with tarcocimab had at least a 1-step improvement in DRSS as compared with 10% of those in the sham group. A small portion of patients (5.6%) experienced a 3-step improvement in DRSS with the anti-VEGF agent compared with none in the sham arm. Overall, there was no change in DRSS seen for 78% of those in the sham group compared with 27.3% of those in the tarcocimab arm.

Kodiak, the company developing tarcocimab tedromer, had previously paused development into the VEGF ABC, following disappointing results in studies exploring the agent for macular edema. However, findings from the GLOW1 study, which were initially presented in November 2023, resulted in the research program being restarted and dialogues between Kodiak and the FDA to commence regarding a potential pivotal study for the agent. The new development path for tarcocimab is for macular edema following retinal vein occlusion (RVO), wet age-related macular degeneration (wAMD), and NPDR, the company noted. The phase 3 GLOW2 study is currently enrolling patients with NPDR (NCT06270836).

Wong RW, Janer D, Zawadzki R, et al. Tarcocimab tedromer (KSI-301) 5mg: outcomes of the Phase 3 GLOW Study in patients with non-proliferative diabetic retinopathy. Paper presented at the Association for Research in Vision and Ophthalmology (ARVO) 2024 Meeting, May 5–9, 2024.

The anti-VEGF agent tarcocimab significantly improved diabetic retinopathy severity score compared with SHAM in a phase 3 study. 

Tarcocimab Tedromer Shows Promise for Diabetic Retinopathy in GLOW1

Several case studies are emerging for the use of artificial intelligence (AI) to help improve patient literacy and education, according to findings presented at the 2024 American College of Physicians Internal Medicine Meeting.

 ChatGPT effectively and accurately modified chronic kidney disease (CKD) text into patient friendly and easily readable information, providing the potential to substantially improve patient literacy. In another presentation,

 on applying augmented intelligence and machine learning, a presenter showed an effective case study of translating their discharge instructions from medical abbreviations and text into a patient friendly format.

 completed by Oscar Pena, MD, and Monika Mishra, MD, both at the Hartford HealthCare St. Vincent's Medical Center, researchers identified 33 questions and answers specific to CKD that were related to risk factors, disease, and forms of kidney replacement therapy. For each, they prompted ChatGPT to "make the text readable for someone at 6th grade or below." The output from the artificial intelligence (AI) tool were then tested against Flesh Kincaid grade level (FKGL) test to assess the final reading level and whether the process effectively converted the medical text into an easily readable format.

"Our study demonstrated that ChatGPT, an artificial intelligence tool, can make medical information on CKD more comprehensible and more accessible to everyone, regardless of their literacy levels," the authors wrote in their poster. "This shows that Al has the potential not only to convey information effectively but also to tailor it to specific audiences.”

The text that was used for the simplification process was from a recompilation of materials from the National Kidney Foundation website. The reading level varied on each of the 33 answers at baseline. The average original reading level for these answers was grade 9.1 (confidence interval [CI], 8.3-10, standard deviation [SD], ± 2.4). After the ChatGPT modifications, the reading level average was grade 7.0 (CI, 6.5-7.6, SD ± 1.6), per the FKGL test.

The original readability score varied significantly from answer to answer, with the most complicated reaching grade nearly to grade 17 in complexity. The most dramatic improvement was seen on a question originally scored at a reading level of grade 11.8. In this example, ChatGPT modified the answer to a grade 5.2 reading level. Each result represented a statistically significant improvement in readability (

"By using Al to enhance readability, we can increase awareness and understanding of CKD among the general public, especially those who may find traditional medical information too complicated," the authors noted. "Our research indicates that incorporating Al into health communication strategies can improve public health literacy and enable individuals to make informed decisions about their well-being."

 Ivana Jankovic, MD, Adjunct Clinical Assistant Professor, Division of Endocrinology, Diabetes and Clinical Nutrition Oregon Health & Sciences University, presented similar success translating medical jargon into patient friendly output. This case study was in diabetes and sought to change medical notes into a grade 8 reading level.

For the input, Jankovic included discharge instructions (abbreviated in the prompt as D/C). The input included several common abbreviations, such as BID, BG, qAC, QIDHS, and PCP and the prompt was again a simple "please write this following instructions at an eight grade level." The response not only simplified the instructions for a patient but also included addition tips, such as setting phone reminders and keeping a blood sugar log.

“It did a really good job of breaking this down for the patient. Not only did it do this but without me asking, it gave tips,” Jankovic said. “It can make your job faster and easier. It can take things to the level of your patient without you expending effort for it.”

Pena, O, Mishra M. ChatGPT in CKD: Using Artificial Intelligence for Health Literacy. Poster presented at: ACP Internal Medicine Meeting; April 19, 2024; Boston, MA. https://annualmeeting.acponline.org/ Accessed April 19, 2024.

Pandita D, Chen J, Jankovic, I. Applying Augmented Intelligence and Machine Learning in Your Practice. Session presented at: ACP Internal Medicine Meeting; April 19, 2024; Boston, MA. https://annualmeeting.acponline.org/ Accessed April 19, 2024.

Large language model AI tools like ChatGPT quickly, easily, and effectively modified dense medical information into grade 6 to 8 reading levels. 