Jan 17,2024 TOP STORY

Better Therapeutics Announces Publication of Cost-Effectiveness Analysis Demonstrating AspyreRx is More Effective and Less Costly than Standard of Care Alone

Better Therapeutics announced the publication of health economic data for its prescription-only digital behavioral treatment for type 2 diabetes (T2D), AspyreRx. The study, titled "Cost-Effectiveness Analysis of a Prescription Digital Therapeutic in Type 2 Diabetes'' has been published in Advances in Therapy peer-reviewed medical journal. This latest study modeled the cost-effectiveness of AspyreRx plus standard of care (SoC) versus SoC alone in T2D over a lifetime horizon. From a healthcare payer perspective, AspyreRx plus SoC versus SoC alone was dominant because AspyreRx was associated both with gains in quality-adjusted life years (QALYs) and cost savings of $7,343 per patient over the lifetime horizon. AspyreRx plus SoC was cost-effective at a willingness-to-pay of $100,000 per QALY over SoC alone, with an incremental net monetary benefit (INMB) of $17,443. At other commonly applied thresholds of $50,000 and $150,000 per QALY, the study yielded INMBs of $12,393 and $22,493, respectively. Savings were primarily driven by a reduction in drug costs, followed by reductions in adverse event costs.

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Jan 11,2024

UK study backs whole-genome screening for cancer care

A major new study in the UK has shown that combining whole-genome sequencing (WGS) and real-world clinical data at a national scale can help deliver tailored, personalised cancer therapy. Researchers from Genomics England, NHS England, Queen Mary University of London, Guy’s and St Thomas’ NHS Foundation Trust, and the University of Westminster analysed data from more than 30 types of solid tumour in 13,000 patients over a five-year period. Published in the journal Nature Medicine, the study showed various benefits of including WGS data from a simple blood test when assessing patients; for example, revealing that 90% of brain tumours and more than 50% of colon and lung cancers have genetic changes that could affect how patients are treated. The trial – said to be the largest of its kind – drew on the UK’s 100,000 Genomes Project and NHS records and has already led to calls for greater use of genomic testing in cancer care, as it can help select effective therapies for patients and avoid those more likely to cause serious side effects.

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Jan 10,2024

Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study

The study aims to systematically evaluate the value of routine laboratory tests on the prediction of ovarian cancer, and develop a robust and generalisable ensemble artificial intelligence (AI) model to assist in identifying patients with ovarian cancer. In this multicentre, retrospective cohort study, researchers collected data from 98 laboratory tests and clinical features of women with or without ovarian cancer in three Chinese hospitals. Employing a multi-criteria decision-making-based classification fusion (MCF) risk prediction framework, the study developed an ensemble artificial intelligence (AI) model, combining estimations from 20 AI classification models. Notably, the model outperformed traditional biomarkers like CA125 and HE4, providing a low-cost, easily accessible, and accurate diagnostic tool for ovarian cancer, especially in early-stage cases.

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Dec 22,2023

Thermal device shows feasibility in managing prostate cancer–related hot flashes

A recent study published in Prostate Cancer and Prostatic Diseases shows the feasibility of a wearable thermal device for the management of hot flashes due to treatment for prostate cancer. The device works by using a thermoelectric heat pump to provide either heating or cooling to participants’ wrists upon activation. "During treatment for prostate cancer, there are many complications we consider when we think about how to optimize survivorship. This study, using a novel technology to manage hot flashes, truly moves the field forward in improving the quality of life for men with prostate cancer,” said Alicia K. Morgans, MD, MPH, in a news release on the findings. Overall, 44 patients completed the 4-week prospective study, and 39 had retrievable device usage data for analysis. The primary outcome was device usage, indicated by hours and sessions of use per day. On average, participants used the device for 3.2 (SD, 2.5) hours per day for 7.6 (SD, 3.6) sessions per day. Among all participants, 67% reported using the device 7 days and 7 nights each week. Although the device could provide heating and cooling, all participants used the device exclusively for cooling. Across all secondary measures analyzed, the investigators observed statistically significant changes from baseline to week 4. Regarding patient reported outcome measures, most participants (69%) indicated that the device was effective in helping them manage their hot flashes, and 77% reported being somewhat to very satisfied with the device.

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Nov 28,2023

Validation of a Composite Real-World Mortality Variable Among Patients with Hematologic Malignancies Treated in the United States

Real-world data (RWD) is being increasingly used to support clinical and regulatory decisions where utilization of clinical trial data is difficult or impractical. With this expanded utilization comes a need to ensure RWD is of sufficient quality and completeness to adequately answer relevant research questions. Given the importance of overall survival (OS) for oncology research, treatment and care, complete and accurate real-world mortality data capture is of critical importance. This study sought to validate and benchmark a composite real-world mortality variable, using the COTA real-world database, a de-identified database derived from the electronic health records (EHRs) of partnered healthcare providers in the United States, against the gold standard data source from the National Death Index (NDI). The final study population included 21,567 patients across 7 cancer types. Within the overall study population, validation analysis comparing the real-world composite mortality variable to the NDI demonstrated high sensitivity (87.8) and specificity (95.7). Date concordance between the real-world composite mortality variable and NDI dates of death was high. In the study population (N=21,567), exact date concordance was observed in 88.0% of patients. These findings are critical to ensure the reliability of results generated using RWD, and further establish the use of a composite real-world mortality variable as best practice.

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Jan 04,2024

Alex Therapeutics Reports Positive Results from the Randomized-Controlled Trial of its Digital Therapy for Anxiety

Alex Therapeutics and Vicore Pharma today announced positive results of the COMPANION study, investigating the efficacy of Almee, a 9-week digital CBT intervention accessed through a smartphone or tablet. Almee, developed by Alex Therapeutics in partnership with Vicore Pharma, is an app that offers personalized treatment for anxiety based on cognitive behavioral therapy (CBT). The COMPANION study enrolled 108 participants from across the United States in a randomized, controlled, parallel-group clinical investigation evaluating the impact of Almee on the psychological symptom burden in adults diagnosed with PF. The study met its primary endpoint, change from baseline in GAD-7 anxiety scores, with a statistically significant 2.7-point improvement compared to control, where a change in GAD-7 score of more than 1.8 is considered clinically meaningful. Quality of life, measured by the K-BILD, was a key secondary endpoint and improved by 4.4 points compared to control, and the K-BILD psychological domain improved by 6.5 points.

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Dec 21,2023

Association of Continuous Glucose Monitoring Metrics With Pregnancy Outcomes in Patients With Preexisting Diabetes

Continuous glucose monitoring (CGM) improves maternal glycemic control and neonatal outcomes in type 1 diabetes pregnancies compared with self-monitoring of blood glucose. However, CGM targets for pregnancy are based on expert opinion. The study aimed to evaluate the association between CGM metrics and perinatal outcomes and identify evidence-based targets to reduce morbidity. This was a retrospective cohort study of pregnant patients with type 1 or 2 diabetes who used real-time CGM and delivered at a U.S. tertiary center (2018–2021). Multiple gestations, fetal anomalies, and early pregnancy loss were excluded. Exposures included time in range (TIR; 65–140 mg/dL), time above range (TAR), time below range (TBR), glucose variability, average glucose, and glucose management indicator. The primary outcome was a composite of fetal or neonatal mortality, large or small for gestational age at birth, neonatal intensive care unit admission, hypoglycemia, shoulder dystocia or birth trauma, and hyperbilirubinemia. Of 117 patients, 16 (13.7%) used CGM before pregnancy and 68 (58.1%) had type 1 diabetes. Overall, 98 patients (83.8%) developed the composite neonatal outcome. All CGM metrics, except TBR, were associated with neonatal morbidity. The statistically optimal TIR was 66–71%. Nearly all CGM metrics were associated with adverse neonatal morbidity and mortality and may aid management of preexisting diabetes in pregnancy. The findings support the American Diabetes Association recommendation of 70% TIR.

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Dec 21,2023

Randomized Trial of the Insulin-Only iLet Bionic Pancreas for the Treatment of Cystic Fibrosis– Related Diabetes

Cystic fibrosis–related diabetes (CFRD) affects up to 50% of adults with cystic fibrosis and adds significant morbidity and treatment burden. The study evaluated the safety and efficacy of automated insulin delivery with the iLet bionic pancreas (BP) in adults with CFRD in a single-center, open-label, random-order, crossover trial. Twenty participants with CFRD were assigned in random order to 14 days each on the BP or their usual care (UC). No restrictions were placed on diet or activity. The primary outcome was the percent time sensor-measured glucose was in target range 70–180 mg/dL on days 3–14 of each arm, and key secondary outcomes included mean continuous glucose monitoring (CGM) glucose and the percent time sensor-measured glucose was in hypoglycemic range <54 mg/dL. Results showed that TIR was significantly higher in the BP arm than the UC arm. There was no significant difference in percent time with sensor-measured glucose <54 mg/dL, although self-reported symptomatic hypoglycemia episodes were higher during the BP arm than the UC arm. Adults with CFRD had improved glucose control without an increase in CGM-measured hypoglycemia with the BP compared with their UC, suggesting that this may be an important therapeutic option for this patient population.

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Dec 20,2023

Efficacy and Safety of Continuous Glucose Monitoring and Intermittently Scanned Continuous Glucose Monitoring in Patients With Type 2 Diabetes: A Systematic Review and Meta-analysis of Interventional Evidence

Traditional diabetes self-monitoring of blood glucose (SMBG) involves inconvenient finger pricks. Continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems offer CGM, enhancing type 2 diabetes (T2D) management with convenient, comprehensive data. This study aims to assess the benefits and potential harms of CGM and isCGM compared with usual care or SMBG in individuals with T2D.The researchers conducted a comprehensive search of MEDLINE, Embase, the Cochrane Library, Web of Science, and bibliographies up to August 2023. They included 26 RCTs (17 CGM and 9 isCGM) involving 2,783 patients with T2D. CGM reduced HbA1c and glycemic medication effect score, reduced user satisfaction, and increased the risk of adverse events. isCGM reduced HbA1c by ?0.31%, increased user satisfaction, improved CGM metrics, and increased the risk of adverse events. Accordingly, both CGM and isCGM demonstrated a reduction in HbA1c levels in individuals with T2D, and unlike CGM, isCGM use was associated with improved user satisfaction. The impact of these devices on body composition, blood pressure, and lipid levels remains unclear, while both CGM and isCGM use were associated with increased risk of adverse events.

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Dec 11,2023

Predicting Rescue Medication Use to Help Prevent Exacerbations: The Intersection of AI, Data, and Asthma Management

A recent study examined over 13,000 asthma participants utilizing Propeller's FDA-cleared digital therapeutic platform. Analyzing more than 1.2 million days of data, the study revealed that digital health platforms, combined with predictive models, can effectively collect, analyze, and predict trends in asthma rescue medication usage, a key indicator of impending exacerbations. The study employed machine learning models, including a temporal-convolutional neural network, which demonstrated an impressive performance in predicting days with increased short-acting beta agonist (SABA) medication use. Further research is warranted to validate these findings in real-world applications.

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