Multicenter, phase 1 study of etavopivat (FT-4202) treatment for up to 12 weeks in patients with sickle cell disease.

Etavopivat is an investigational, once-daily, oral, selective erythrocyte pyruvate kinase (PKR) activator. A multicenter, randomized, placebo-controlled, double-blind, 3-part, phase 1 study (https://clinicaltrials.gov/study/NCT03815695) was conducted to characterize the safety and clinical activity of etavopivat. Thirty-six patients with sickle cell disease (SCD) were enrolled into 4 cohorts: one single-dose; two multiple ascending doses; one open-label [OL]. In the OL cohort, 15 patients (median age 33.0 [range, 17‒55] years received 400-mg etavopivat once daily for 12 weeks; 14 completed treatment. Consistent with the mechanism of PKR activation, increases in ATP and decreases in 2,3 diphosphoglycerate were observed and sustained over 12 weeks' treatment. This translated clinically to an increase in hemoglobin (mean maximal increase 1.6 [range, 0.8‒2.8] g/dL), with >1 g/dL increase in 11 (73%) patients during treatment. Additionally, oxygen tension at which hemoglobin is 50% saturated was reduced (P=.0007) with concomitant shift in point-of-sickling (P=.0034) to lower oxygen tension in oxygen-gradient ektacytometry. Hemolysis markers (absolute reticulocyte count, indirect bilirubin, lactate dehydrogenase) decreased from baseline, along with matrix metalloproteinase-9 and erythropoietin. In the OL cohort, adverse events (AEs) were mostly grade 1/2, consistent with underlying SCD; 5 patients had serious AEs. Vaso-occlusive pain episode was the most common treatment-emergent AE (n=7) in the OL cohort. In this first study of etavopivat in SCD, 400 mg once daily for 12 weeks was well-tolerated, resulting in rapid and sustained increases in hemoglobin, improved RBC physiology, and decreased hemolysis.

Modeling responses of macaque and human retinal ganglion cells to natural images using a convolutional neural network.

Linear-nonlinear (LN) cascade models provide a simple way to capture retinal ganglion cell (RGC) responses to artificial stimuli such as white noise, but their ability to model responses to natural images is limited. Recently, convolutional neural network (CNN) models have been shown to produce light response predictions that were substantially more accurate than those of a LN model. However, this modeling approach has not yet been applied to responses of macaque or human RGCs to natural images. Here, we train and test a CNN model on responses to natural images of the four numerically dominant RGC types in the macaque and human retina - ON parasol, OFF parasol, ON midget and OFF midget cells. Compared with the LN model, the CNN model provided substantially more accurate response predictions. Linear reconstructions of the visual stimulus were more accurate for CNN compared to LN model-generated responses, relative to reconstructions obtained from the recorded data. These findings demonstrate the effectiveness of a CNN model in capturing light responses of major RGC types in the macaque and human retinas in natural conditions.

Characterization of cerebral radiation necrosis following the treatment of sinonasal malignancies.

Objectives: Our study aims to determine the incidence and potential risk factors for cerebral radiation necrosis (CRN) following treatment of sinonasal malignancies. Methods: One hundred thirty-two patients diagnosed with sinonasal malignancies over an 18-year period were identified at two institutions. Forty-six patients meeting inclusion criteria and treated with radiation therapy were included for analysis. Demographic and clinical-pathologic characteristics were collected and reviewed. Post-treatment magnetic resonance imaging (MRI) at least 1 year following treatment was reviewed to determine presence or absence of CRN. Results: CRN was identified on MRI in 8 of 46 patients (17.4%) following radiation treatment. Patients with a history of reirradiation were more likely to develop CRN (50% vs. 10.5%, p < .05). The BEDs of radiation were also higher in CRN patients compared to non-CRN patients, but this difference was not significant (p > .05). CRN patients had a higher proportion of tumors with skull base involvement than non-CRN patients (100% vs. 57.9%, p = .037). Demographics, comorbidities, pathology, primary tumor subsite, chemotherapy use, and stage of disease demonstrated no significant increase in risk of CRN. Conclusions: Reirradiation and tumor skull base involvement were significant risk factors associated with CRN. Higher average total prescribed and BEDs of radiation were seen in the CRN groups, but these differences were not statistically significant. Gender, comorbidities, tumor subsite, tumor location, and treatment type were not significantly different between groups. Level of evidence: Level 3.

Treatment Patterns and FLT3 Mutation Testing Among Patients with Acute Myeloid Leukemia in China: A Retrospective Observational Study.

Introduction: For acute myeloid leukemia (AML), prognosis is particularly poor in patients harboring FMS-like tyrosine kinase 3 (FLT3) gene mutations, though routine screening for these mutations at diagnosis has been shown to be insufficient. The understanding of the impact of FLT3 mutations on treatment decisions is limited. Methods: In this retrospective, observational study, we investigated the key epidemiological characteristics, treatment patterns and responses among adult patients with newly diagnosed (ND) AML in China, who initiated treatment from January 1, 2015, to December 31, 2019, or progressed to relapsed/refractory (R/R) AML by December 31, 2020. Results: Of the 853 ND AML patients included, 63.4% were screened for FLT3 status, and 20.1% tested positive (FLT3MUT) at initial diagnosis. Of 289 patients who progressed to R/R AML during the study period, 24.9% were screened at the diagnosis of R/R AML, and 19.4% tested positive; 20.5% of screened patients changed FLT3 status at first diagnosis of R/R AML. Initial treatment regimens or treatment responses did not seem to differ in patients with ND AML by FLT3 mutation status. In patients with R/R AML, there was an apparent difference in second-line treatment choices by FLT3 mutation status; however, the number of FLT3-mutated patients were limited to demonstrate any meaningful distinction. FLT3-mutated R/R AML was associated with shorter relapse time. Conclusion: Study findings showed that there was a lack of routine testing for FLT3 mutations at first diagnosis of R/R AML, and initial treatment decisions did not differ by FLT3 mutation status. Given the clinical burden of FLT3MUT, likelihood of FLT3 status changes, and emerging FLT3 inhibitors, further routine FLT3 screening is needed to optimize treatment of R/R AML.

Impaired Brain-Heart Relation in Patients With Methamphetamine Use Disorder During VR Induction of Drug Cue Reactivity.

Methamphetamine use disorder (MUD) is an illness associated with severe health consequences. Virtual reality (VR) is used to induce the drug-cue reactivity and significant EEG and ECG abnormalities were found in MUD patients. However, whether a link exists between EEG and ECG abnormalities in patients with MUD during exposure to drug cues remains unknown. This is important from the therapeutic viewpoint because different treatment strategies may be applied when EEG abnormalities and ECG irregularities are complications of MUD. We designed a VR system with drug cues and EEG and ECG were recorded during VR exposure. Sixteen patients with MUD and sixteen healthy subjects were recruited. Statistical tests and Pearson correlation were employed to analyze the EEG and ECG. The results showed that, during VR induction, the patients with MUD but not healthy controls showed significant [Formula: see text] and [Formula: see text] power increases when the stimulus materials were most intense. This finding indicated that the stimuli are indiscriminate to healthy controls but meaningful to patients with MUD. Five heart rate variability (HRV) indexes significantly differed between patients and controls, suggesting abnormalities in the reaction of patient's autonomic nervous system. Importantly, significant relations between EEG and HRV indexes changes were only identified in the controls, but not in MUD patients, signifying a disruption of brain-heart relations in patients. Our findings of stimulus-specific EEG changes and the impaired brain-heart relations in patients with MUD shed light on the understanding of drug-cue reactivity and may be used to design diagnostic and/or therapeutic strategies for MUD.

PEPSI: Polarity measurements from spatial proteomics imaging suggest immune cell engagement.

Subcellular protein localization is important for understanding functional states of cells, but measuring and quantifying this information can be difficult and typically requires high-resolution microscopy. In this work, we develop a metric to define surface protein polarity from immunofluorescence (IF) imaging data and use it to identify distinct immune cell states within tumor microenvironments. We apply this metric to characterize over two million cells across 600 patient samples and find that cells identified as having polar expression exhibit characteristics relating to tumor-immune cell engagement. Additionally, we show that incorporating these polarity-defined cell subtypes improves the performance of deep learning models trained to predict patient survival outcomes. This method provides a first look at using subcellular protein expression patterns to phenotype immune cell functional states with applications to precision medicine.

Decomposition of retinal ganglion cell electrical images for cell type and functional inference.

Identifying neuronal cell types and their biophysical properties based on their extracellular electrical features is a major challenge for experimental neuroscience and the development of high-resolution brain-machine interfaces. One example is identification of retinal ganglion cell (RGC) types and their visual response properties, which is fundamental for developing future electronic implants that can restore vision. The electrical image (EI) of a RGC, or the mean spatio-temporal voltage footprint of its recorded spikes on a high-density electrode array, contains substantial information about its anatomical, morphological, and functional properties. However, the analysis of these properties is complex because of the high-dimensional nature of the EI. We present a novel optimization-based algorithm to decompose electrical image into a low-dimensional, biophysically-based representation: the temporally-shifted superposition of three learned basis waveforms corresponding to spike waveforms produced in the somatic, dendritic and axonal cellular compartments. Large-scale multi-electrode recordings from the macaque retina were used to test the effectiveness of the decomposition. The decomposition accurately localized the somatic and dendritic compartments of the cell. The imputed dendritic fields of RGCs correctly predicted the location and shape of their visual receptive fields. The inferred waveform amplitudes and shapes accurately identified the four major primate RGC types (ON and OFF midget and parasol cells), a substantial advance. Together, these findings may contribute to more accurate inference of RGC types and their original light responses in the degenerated retina, with possible implications for other electrical imaging applications.

Does the Traditional Band Picture Describe the Electronic Structure of Doped Conjugated Polymers? TD-DFT and Natural Transition Orbital Study of Doped P3HT.

Polarons and bipolarons are created when one or two electrons are removed from the π-system of a p-type conjugated polymer, respectively. In the traditional band picture, the creation of a polaron causes two electronic energy levels to move into the band gap. The removal of a second electron to form a bipolaron causes the two intragap states to move further into the gap. Several groups, however, who looked at the energies of the Kohn-Sham orbitals from DFT calculations, have recently argued that the traditional band picture is incorrect for explaining the spectroscopy of doped conjugated polymers. Instead, the DFT calculations suggest that polaron creation causes only one unoccupied state to move into the band gap near the valence band edge while half-filled state in the valence band and the conduction band bend downward in energy. To understand the discrepancy, we performed TD-DFT calculations of polarons and bipolarons on poly(3-hexylthiophene) (P3HT). Not only do the TD-DFT-calculated absorption spectra match the experimental absorption spectra, but an analysis using natural transitional orbitals (NTOs), which provides an approximate one-electron picture from the many-electron TD-DFT results, supports the traditional band picture. Our TD-DFT/NTO analysis indicates that the traditional band picture also works for bipolarons, a system for which DFT calculations were unable to determine the electronic structure.

Treatment Patterns and Adverse Event-Related Hospitalization Among Patients with Epidermal Growth Factor Receptor (EGFR)-Mutated Metastatic Non-small Cell Lung Cancer After Treatment with EGFR Tyrosine Kinase Inhibitor and Platinum-Based Chemotherapy Regimens.

BACKGROUND: Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR TKIs) are established first-line treatments among patients with metastatic non-small cell lung cancer harboring EGFR-sensitizing mutations. Upon EGFR TKI resistance, there are scant data supporting a standard of care in subsequent lines of therapy. OBJECTIVE: We aimed to characterize real-world treatment patterns and adverse events associated with hospitalization in later lines of therapy. METHODS: This retrospective analysis of administrative claims included adults with metastatic non-small cell lung cancer who initiated a next line of therapy (index line of therapy) following EGFR TKI and platinum-based chemotherapy discontinuation on/after 1 November, 2015. Treatment regimens and adverse event rates during the index line of therapy were described. RESULTS: Among 195 eligible patients (median age: 59 years; female: 60%), the five most common index line of therapy regimens were immune checkpoint inhibitor monotherapy (29%), EGFR TKI monotherapy (21%), platinum-based chemotherapy (19%), non-platinum-chemotherapy (13%), and EGFR TKI combinations (9%). The overall median (95% confidence interval) time to discontinuation of the index line of therapy was 2.8 (2.1-3.2) months. Common adverse events associated with hospitalizations included infection/sepsis, pneumonia/pneumonitis, and anemia (2.9, 2.8, and 2.0 per 100 person-months, respectively). CONCLUSIONS: Among EGFR TKI-resistant patients who discontinued platinum-based chemotherapy, the duration of the next line of therapy was short, treatment was highly variable, and re-treatment with EGFR TKIs and platinum-based regimens was common, suggesting a lack of standard of care in later lines. Adverse event rates associated with hospitalization were high, especially among platinum-treated patients. These results underscore the unmet need for new therapies in a later line of treatment to reduce the clinical burden among patients in this population.

Treatment Patterns and Healthcare Resource Use in Medicare Beneficiaries with Parkinson's Disease.

Background: Studies on real-world treatment patterns and long-term economic burden of Parkinson's disease (PD) have been limited. Objective: To assess treatment patterns, healthcare resource utilization (HRU), and costs associated with PD symptoms and treatment-related adverse events (AEs) among Medicare beneficiaries in the United States. Methods: A 100% Medicare Fee-For-Service data (2006-2020) of patients with PD were analyzed. PD treatment patterns were described for the subset of patients who had no previously observed PD treatments or diagnoses (ie, the incident cohort). HRU and healthcare costs associated with PD symptoms were assessed for all patients with PD (ie, the overall cohort) and that associated with treatment-related AEs were assessed for the subset of patients who received PD treatments after PD diagnosis (ie, the active treatment cohort), using longitudinal models with repeated measures. Results: Overall, 318,582 patients were included (mean age at PD diagnosis: 77.4 years; 53.3% female). Among patients in the incident cohort (N=214,829), 51.1% initiated levodopa monotherapy and 5.9% initiated dopamine agonists (DAs) monotherapy as first-line treatment. The proportion of incident patients treated with DAs and other PD therapies generally increased from post-diagnosis years 1 to 10. The median time from diagnosis to PD treatment initiation was 2.0 months; the median time to treatment discontinuation was the longest with levodopa (18.7 months), followed by DAs (9.5 months). In the overall cohort, PD symptoms, especially motor symptoms and severe motor symptoms, were associated with significantly higher rates of HRU and costs. In the active treatment cohort (N=234,298), treatment-related AEs were associated with significantly higher rates of HRU and medical costs. Conclusion: While levodopa is still the mainstay of PD management, considerable heterogeneity exists in real-world treatment patterns. Overall, PD symptoms and AEs were associated with significantly higher HRU and healthcare costs, suggesting unmet medical needs for PD treatments with better tolerability profiles.

Long-Term Effectiveness of Dupilumab in Patients with Atopic Dermatitis: Results up to 3 Years from the RELIEVE-AD Study.

INTRODUCTION: Atopic dermatitis (AD) can require long-term therapy. Few real-world studies have evaluated long-term effectiveness from the patients' perspective. The aim of this study was to evaluate patient-reported outcomes (PROs) during long-term dupilumab treatment. METHODS: Adults with moderate-to-severe AD who initiated dupilumab through the US manufacturer patient support program and participated in RELIEVE-AD (a prospective patient survey study with a 12-month follow-up) were recontacted 30-36 months post-initiation regardless of current dupilumab use. The online questionnaire consisted of PROs, including the Atopic Dermatitis Control Tool (ADCT), use of concomitant AD therapies, satisfaction with current therapy, global change in itch relative to before dupilumab initiation, non-itch skin symptoms (skin pain/soreness, hot/burning feeling, and sensitivity to touch), flares, Dermatology Life Quality Index, sleep problems, and the AD-specific Work Productivity and Activity Impairment Questionnaire. RESULTS: Of 698 patients who initiated dupilumab (baseline) and were recontacted, 425 completed the 30-36-month survey. Significant reductions from baseline were reported in concomitant AD therapy use (P < 0.05); 54.4% reported not using other AD medications vs. 12.8% at baseline. At 30-36 months, all results (non-itch skin symptoms, flares, sleep problems, health-related quality of life work/activity impairment, disease control, and treatment satisfaction) were similar to or incrementally better than the 12-month timepoint, with significant improvements vs. baseline (P < 0.001). Global change in itch was reported as "very much better" by 75.3% of respondents. Adequate disease control (score < 7 on ADCT) was reported by 80.7% of respondents, and 86.8% were satisfied with the treatment. CONCLUSIONS: In clinical practice settings, patient-reported benefits of dupilumab were maintained in survey respondents during long-term treatment up to 36 months while the use of concomitant AD therapies reduced.

Atopic dermatitis (also known as eczema) is a chronic skin disease that can have a profoundly negative effect on patients' quality of life. To control disease symptoms, patients often need long-term treatment. Dupilumab is a treatment that has shown benefits in adults with moderate-to-severe atopic dermatitis (AD) when used in long-term (under 4 years) clinical trials; however, few studies have evaluated patients' experiences of long-term dupilumab treatment outside of a clinical trial setting. This study was conducted to do so: 425 adults with moderate-to-severe AD who received dupilumab through a US manufacturer patient support program filled in an online questionnaire 30­36 months after starting treatment. The questionnaire included items on use of additional AD therapies, AD symptoms, quality of life, disease control, and satisfaction with treatment. Patients' responses showed that, at 30­36 months after starting dupilumab treatment, 54% of patients reported not using any other medications for AD vs. 13% of patients when starting dupilumab treatment. In addition, since starting dupilumab, 75% of patients reported one of the most burdensome AD symptoms, itch, as being "very much better" vs. before starting treatment; 81% reported control of AD symptoms; 85% reported a meaningful improvement in quality of life; and 76% were "extremely" or "very" satisfied with the treatment. In summary, this study showed that long-term dupilumab treatment provides continued improvement in symptoms, treatment satisfaction, disease control, and quality of life in adults with moderate-to-severe AD while reducing the need for other AD treatments. Video abstract: How do patients with atopic dermatitis perceive long-term dupilumab treatment in the real world? (MP4 31888 kb).

Fixational Eye Movements Enhance the Precision of Visual Information Transmitted by the Primate Retina.

Fixational eye movements alter the number and timing of spikes transmitted from the retina to the brain, but whether these changes enhance or degrade the visual signal is unclear. To quantify this, we developed a Bayesian method for reconstructing natural images from the recorded spikes of hundreds of macaque retinal ganglion cells (RGCs) of the major cell types, combining a likelihood model for RGC light responses with the natural image prior implicitly embedded in an artificial neural network optimized for denoising. The method matched or surpassed the performance of previous reconstruction algorithms, and provided an interpretable framework for characterizing the retinal signal. Reconstructions were improved with artificial stimulus jitter that emulated fixational eye movements, even when the jitter trajectory was inferred from retinal spikes. Reconstructions were degraded by small artificial perturbations of spike times, revealing more precise temporal encoding than suggested by previous studies. Finally, reconstructions were substantially degraded when derived from a model that ignored cell-to-cell interactions, indicating the importance of stimulus-evoked correlations. Thus, fixational eye movements enhance the precision of the retinal representation.

Direct-print three-dimensional electrodes for large- scale, high-density, and customizable neural inter- faces.

Silicon-based planar microelectronics is a powerful tool for scalably recording and modulating neural activity at high spatiotemporal resolution, but it remains challenging to target neural structures in three dimensions (3D). We present a method for directly fabricating 3D arrays of tissue-penetrating microelectrodes onto silicon microelectronics. Leveraging a high-resolution 3D printing technology based on 2-photon polymerization and scalable microfabrication processes, we fabricated arrays of 6,600 microelectrodes 10-130 µm tall and at 35-µm pitch onto a planar silicon-based microelectrode array. The process enables customizable electrode shape, height and positioning for precise targeting of neuron populations distributed in 3D. As a proof of concept, we addressed the challenge of specifically targeting retinal ganglion cell (RGC) somas when interfacing with the retina. The array was customized for insertion into the retina and recording from somas while avoiding the axon layer. We verified locations of the microelectrodes with confocal microscopy and recorded high-resolution spontaneous RGC activity at cellular resolution. This revealed strong somatic and dendritic components with little axon contribution, unlike recordings with planar microelectrode arrays. The technology could be a versatile solution for interfacing silicon microelectronics with neural structures and modulating neural activity at large scale with single-cell resolution.

GPT detectors are biased against non-native English writers.

GPT detectors frequently misclassify non-native English writing as AI generated, raising concerns about fairness and robustness. Addressing the biases in these detectors is crucial to prevent the marginalization of non-native English speakers in evaluative and educational settings and to create a more equitable digital landscape.

Inferring light responses of primate retinal ganglion cells using intrinsic electrical signatures.

Objective. Retinal implants are designed to stimulate retinal ganglion cells (RGCs) in a way that restores sight to individuals blinded by photoreceptor degeneration. Reproducing high-acuity vision with these devices will likely require inferring the natural light responses of diverse RGC types in the implanted retina, without being able to measure them directly. Here we demonstrate an inference approach that exploits intrinsic electrophysiological features of primate RGCs.Approach.First, ON-parasol and OFF-parasol RGC types were identified using their intrinsic electrical features in large-scale multi-electrode recordings from macaque retina. Then, the electrically inferred somatic location, inferred cell type, and average linear-nonlinear-Poisson model parameters of each cell type were used to infer a light response model for each cell. The accuracy of the cell type classification and of reproducing measured light responses with the model were evaluated.Main results.A cell-type classifier trained on 246 large-scale multi-electrode recordings from 148 retinas achieved 95% mean accuracy on 29 test retinas. In five retinas tested, the inferred models achieved an average correlation with measured firing rates of 0.49 for white noise visual stimuli and 0.50 for natural scenes stimuli, compared to 0.65 and 0.58 respectively for models fitted to recorded light responses (an upper bound). Linear decoding of natural images from predicted RGC activity in one retina showed a mean correlation of 0.55 between decoded and true images, compared to an upper bound of 0.81 using models fitted to light response data.Significance.These results suggest that inference of RGC light response properties from intrinsic features of their electrical activity may be a useful approach for high-fidelity sight restoration. The overall strategy of first inferring cell type from electrical features and then exploiting cell type to help infer natural cell function may also prove broadly useful to neural interfaces.

7-UP: Generating in silico CODEX from a small set of immunofluorescence markers.

Multiplex immunofluorescence (mIF) assays multiple protein biomarkers on a single tissue section. Recently, high-plex CODEX (co-detection by indexing) systems enable simultaneous imaging of 40+ protein biomarkers, unlocking more detailed molecular phenotyping, leading to richer insights into cellular interactions and disease. However, high-plex data can be slower and more costly to collect, limiting its applications, especially in clinical settings. We propose a machine learning framework, 7-UP, that can computationally generate in silico 40-plex CODEX at single-cell resolution from a standard 7-plex mIF panel by leveraging cellular morphology. We demonstrate the usefulness of the imputed biomarkers in accurately classifying cell types and predicting patient survival outcomes. Furthermore, 7-UP's imputations generalize well across samples from different clinical sites and cancer types. 7-UP opens the possibility of in silico CODEX, making insights from high-plex mIF more widely available.

Estimation of Left Ventricular Stroke Work for Rotary Left Ventricular Assist Devices.

Continuous monitoring of left ventricular stroke work (LVSW) may improve the medical management of patients with rotary left ventricular assist devices (LVAD). However, implantable pressure-volume sensors are limited by measurement drift and hemocompatibility. Instead, estimator algorithms derived from rotary LVAD signals may be a suitable alternative. An LVSW estimator algorithm was developed and evaluated in a range of in vitro and ex vivo cardiovascular conditions during full assist (closed aortic valve [AoV]) and partial assist (opening AoV) mode. For full assist, the LVSW estimator algorithm was based on LVAD flow, speed, and pump pressure head, whereas for partial assist, the LVSW estimator combined the full assist algorithm with an estimate of AoV flow. During full assist, the LVSW estimator demonstrated a good fit in vitro and ex vivo (R 2 : 0.97 and 0.86, respectively) with errors of ± 0.07 J. However, LVSW estimator performance was reduced during partial assist, with in vitro : R 2 : 0.88 and an error of ± 0.16 J and ex vivo : R 2 : 0.48 with errors of ± 0.11 J. Further investigations are required to improve the LVSW estimate with partial assist; however, this study demonstrated promising results for a continuous estimate of LVSW for rotary LVADs.

Real-world Outcomes Associated With Poly(ADP-ribose) Polymerase Inhibitor Monotherapy Maintenance in Patients With Primary Advanced Ovarian Cancer.

OBJECTIVE: This study used real-world population data to assess the trends of first-line (1L) poly(ADP-ribose) polymerase inhibitor (PARPi) maintenance treatment uptake and outcomes in patients with primary advanced ovarian cancer (AOC). METHODS: Patients diagnosed with AOC between January 1, 2017, and June 30, 2021, who completed 1L chemotherapy were selected from a real-world database. Descriptive analyses were performed to evaluate patient demographics, clinicopathological characteristics, and 1L treatment patterns. Time to next treatment or death was used as a proxy for real-world progression-free survival (rwPFS). Kaplan-Meier methods and Cox models were used for statistical analyses. RESULTS: Of 705 patients who completed 1L chemotherapy, 166 received PARPi monotherapy and 539 underwent active surveillance (AS). Median follow-up was 10.9 months for PARPi monotherapy and 20.6 months for AS. PARPi monotherapy use increased from 6% in 2017 to 53% in 2021. Overall, patients receiving PARPi monotherapy had longer rwPFS than those who underwent AS (not reached vs 9.53 mo) respectively. rwPFS was also longer in patients who received PARPi monotherapy compared with AS in patients with BRCA- mutated disease (not reached vs 11.4 mo), BRCA- wild-type disease (13.5 vs 9.1 mo), homologous recombination-deficient tumors (not reached vs 10.2 mo), and homologous recombination-proficient or unknown status tumors (13.5 vs 9.3 mo). CONCLUSIONS: Our real-world analysis suggested that 47% of patients with primary AOC did not receive PARPi maintenance in the year 2021. PARPi use was associated with significantly improved outcomes compared with AS.

Leveraging physiology and artificial intelligence to deliver advancements in health care.

Artificial intelligence in health care has experienced remarkable innovation and progress in the last decade. Significant advancements can be attributed to the utilization of artificial intelligence to transform physiology data to advance health care. In this review, we explore how past work has shaped the field and defined future challenges and directions. In particular, we focus on three areas of development. First, we give an overview of artificial intelligence, with special attention to the most relevant artificial intelligence models. We then detail how physiology data have been harnessed by artificial intelligence to advance the main areas of health care: automating existing health care tasks, increasing access to care, and augmenting health care capabilities. Finally, we discuss emerging concerns surrounding the use of individual physiology data and detail an increasingly important consideration for the field, namely the challenges of deploying artificial intelligence models to achieve meaningful clinical impact.