Search

Background: Idiopathic pulmonary fibrosis (IPF) carries significant mortality and unpredictable progression, with limited therapeutic options. Designing trials with patient-meaningful endpoints, enhancing the reliability and interpretability of results, and streamlining the regulatory approval process are of critical importance to advancing clinical care in IPF. Methods: A landmark in-person symposium in June 2023 assembled 43 participants from the US and internationally, including patients with IPF, investigators, and regulatory representatives, to discuss the immediate future of IPF clinical trial endpoints. Patient advocates were central to discussions, which evaluated endpoints according to regulatory standards and the FDA's 'feels, functions, survives' criteria. Results: Three themes emerged: 1 ) consensus on endpoints mirroring the lived experiences of patients with IPF; 2 ) consideration of replacing forced vital capacity (FVC) as the primary endpoint, potentially by composite endpoints that include 'feels, functions, survives' measures or FVC as components; 3 ) support for simplified, user-friendly patient-reported outcomes (PROs) as either components of primary composite endpoints or key secondary endpoints, supplemented by functional tests as secondary endpoints and novel biomarkers as supportive measures (FDA Guidance for Industry (Multiple Endpoints in Clinical Trials) available at: https://www.fda.gov/media/162416/download). Conclusions: This report, detailing the proceedings of this pivotal symposium, suggests a potential turning point in designing future IPF clinical trials more attuned to outcomes meaningful to patients, and documents the collective agreement across multidisciplinary stakeholders on the importance of anchoring IPF trial endpoints on real patient experiences-namely, how they feel, function, and survive. There is considerable optimism that clinical care in IPF will progress through trials focused on patient-centric insights, ultimately guiding transformative treatment strategies to enhance patients' quality of life and survival.

Despite progress in elucidation of disease mechanisms, identification of risk factors, biomarker discovery, and the approval of two medications to slow lung function decline in idiopathic pulmonary fibrosis and one medication to slow lung function decline in progressive pulmonary fibrosis, pulmonary fibrosis remains a disease with a high morbidity and mortality. In recognition of the need to catalyze ongoing advances and collaboration in the field of pulmonary fibrosis, the NHLBI, the Three Lakes Foundation, and the Pulmonary Fibrosis Foundation hosted the Pulmonary Fibrosis Stakeholder Summit on November 8-9, 2022. This workshop was held virtually and was organized into three topic areas: 1 ) novel models and research tools to better study pulmonary fibrosis and uncover new therapies, 2 ) early disease risk factors and methods to improve diagnosis, and 3 ) innovative approaches toward clinical trial design for pulmonary fibrosis. In this workshop report, we summarize the content of the presentations and discussions, enumerating research opportunities for advancing our understanding of the pathogenesis, treatment, and outcomes of pulmonary fibrosis.

We explored 10 pregnant women's experiences with antiretroviral therapy (ART) adherence using a qualitative approach. Semistructured interviews were conducted with pregnant ethnic minority women living with HIV and receiving integrated HIV/obstetric care at a Midwestern academic medical center in the United States. Data were analyzed using an interpretive phenomenology approach to identify major themes. We found an overarching theme: ART Adherence as a Balancing Act (striving to adhere to ART while having to simultaneously navigate daily challenges). We also identified four interrelated subthemes: struggles, support, motivators, and reminders. Findings highlight the need for clinicians to be sensitive to the emotional burdens of living with HIV while pregnant, a constant factor affecting quality of life and adherence. Having conversations about barriers and facilitators to adherence and encouraging women to identify strategies that support adherence are needed rather than focusing solely on pill counts and viral load.

Purpose: Reduced blood flow measured with PET and SPECT has been reported in brain surrounding intracerebral hemorrhage (ICH). These studies have not corrected for partial volume effects from adjacent hematomas or ventricles. We have implemented a method to correct for these effects at brain boundaries (but not at internal gray/white matter boundaries), tested it with a brain phantom, and applied it to patients., Method: Using PET and X-ray CT images of a Hoffman brain phantom containing artificial hematomas, we segmented CT images to binary images representing brain tissue and convolved these to the 3D resolution of the PET. PET images were then scaled by this net tissue contribution. Corrected images were compared with other images of the same phantom without hematomas. The same correction was then applied to human images., Results: Uncorrected phantom images had artifactual reductions surrounding hematomas that were eliminated by the correction. Corrected images of patients with acute ICH had areas of reduced flow in white and deep gray matter, whereas overlying cortical flow was preserved., Conclusion: We have validated a method to correct for artifactual reductions in blood flow measurements at brain boundaries. Using this method, we observe areas with reduced flow near acute hematomas.

This paper considers the problem of classifying an input vector of measurements by a nearest neighbor rule applied to a fixed set of vectors. The fixed vectors are sometimes called characteristic feature vectors, codewords, cluster centers, models, reproductions, etc. The nearest neighbor rule considered uses a non-Euclidean information-theoretic distortion measure that is not a metric, but that nevertheless leads to a classification method that is optimal in a well-defined sense and is also computationally attractive. Furthermore, the distortion measure results in a simple method of computing cluster centroids. Our approach is based on the minimization of cross-entropy (also called discrimination information, directed divergence, K-L number), and can be viewed as a refinement of a general classification method due to Kullback. The refinement exploits special properties of cross-entropy that hold when the probability densities involved happen to be minimum cross-entropy densities. The approach is a generalization of a recently developed speech coding technique called speech coding by vector quantization.