Population-wide Screening Research Articles

Abstract A061: A cost-effective two-step approach for multi-cancer early detection in general population

Abstract In population-wide cancer screening, three key issues need to be focused on: number of cancer cases identified, the issue of false positives, and cost. A high false positive rate can result in a significant waste of healthcare resources. Large-scale screening inevitably leads to significant financial burdens on the healthcare system which is a key factor constraining nationwide screening. OncoSeek is a multi-cancer early detection (MCED) test using a panel of seven plasma protein tumor markers (PTMs) and artificial intelligence (AI). SeekInCare is a MCED test that integrates the seven PTMs and four cancer genomic features (aneuploidy, fragment size, end motifs, and oncogenic viruses) from cell-free DNA (cfDNA) by shallow whole-genome sequencing (sWGS). In a two-step approach, the initial screening is conducted using OncoSeek and SeekInCare is then used as the secondary test for those individuals who tested positive by OncoSeek. In a case-control study (n = 1197) including both OncoSeek and SeekInCare testing results, OncoSeek showed 49.9% sensitivity at 91.0% specificity, while SeekInCare demonstrated 60.0% sensitivity at 98.3% specificity. In the two-step process, specificity significantly increased from 91.0% to 99.3%, while sensitivity decreased from 49.9% to 39.9%. We modeled a screening in five million adults aged ≥ 50 years with a cancer incidence rate of 1.9%. The simulated real-world sensitivities of OncoSeek and two-step were adjusted downward proportionally to 28.0% and 22.4% based on the sensitivity differences observed between GRAIL’s CCGA study (case-control, 51.5%) and PATHFINDER study (prospective, 28.9%). While at 91.0% specificity OncoSeek had 441,450 cases of false positives, using the two-step approach significantly reduced false positives to 34,335 (0.7%). Although Galleri ($949 per test) identified more cancer cases than the two-step MCED, with 27,455 and 21,280 cases respectively, its total cost for the former reached $4,745 million. As the positive predictive value (PPV) of two-step (38.3%) was the same as Galleri (38.3%), it reduced cost 6.6-fold, amounting to a total cost of $713.6 million and a cost of $143 per individual screened. The cost of per cancer case detected using Galleri is $172,828 compared to $33,534 using the two-step MCED, which represents a 5.2-fold difference. In conclusion, the two-step approach not only significantly reduces false positives, but also cuts the screening cost down substantially, making it a cost-effective strategy for population-wide cancer screening. Citation Format: Mao Mao, Geng shuai peng, Li shi yong, Wu Wei, Chang Yin Yin. A cost-effective two-step approach for multi-cancer early detection in general population [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A061.

Populationwide Screening for Chronic Kidney Disease

Sodium-glucose cotransporter-2 (SGLT2) inhibitors have changed clinical management of chronic kidney disease (CKD) and made populationwide screening for CKD a viable strategy. Optimal age of screening initiation has yet to be evaluated. To compare the clinical benefits, costs, and cost-effectiveness of population-wide CKD screening at different initiation ages and screening frequencies. This cost-effectiveness study used a previously published decision-analytic Markov cohort model that simulated progression of CKD among US adults from age 35 years and older and was calibrated to population-level data from the National Health and Nutrition Examination Survey (NHANES). Effectiveness of SGLT2 inhibitors was derived from the Dapagliflozin and Prevention of Adverse Outcomes in Chronic Kidney Disease (DAPA-CKD) trial. Mortality, quality-of-life weights, and cost estimates were obtained from published cohort studies, randomized clinical trials, and US Centers for Medicare & Medicaid Services data. Analyses were performed from June 2023 through September 2024. One-time or periodic (every 10 or 5 years) screening for albuminuria, initiated at ages between 35 and 75 years, with and without addition of SGLT2 inhibitors to conventional CKD therapy (angiotensin-converting enzyme inhibitors/angiotensin receptor blockers). Cumulative incidence of kidney failure requiring kidney replacement therapy (KRT); life years, quality-adjusted life years (QALYs), lifetime health care costs (2024 US currency), and incremental cost-effectiveness ratios discounted at 3% annually. For those aged 35 years, starting screening at age 55 years, and continuing every 5 years through age 75 years, combined with SGLT2 inhibitors, decreased the cumulative incidence of kidney failure requiring KRT from 2.4% to 1.9%, increased life expectancy by 0.13 years, and cost $128 400 per QALY gained. Although initiation of screening every 5 years at age 35 or 45 years yielded greater gains in population-wide health benefits, these strategies cost more than $200 000 per additional QALY gained. The comparative values of starting screening at different ages were sensitive to the cost and effectiveness of SGLT2 inhibitors; if SGLT2 inhibitor prices drop due to patent expirations, screening at age 55 years continued to be cost-effective even if SGLT2 inhibitor effectiveness were 30% lower than in the base case. This study found that, based on conventional benchmarks for cost-effectiveness in medicine, initiating population-wide CKD screening with SGLT2 inhibitors at age 55 years would be cost-effective.

Benefits of prophylactic carotid revascularization in patients with asymptomatic carotid artery stenosis undergoing coronary artery bypass surgery: A narrative review.

Patients undergoing coronary artery bypass grafting (CABG) are at increased risk of perioperative stroke. Carotid atherosclerosis has been identified as an independent risk factor for stroke during and in the early postoperative period of cardiac surgery. However, the pathogenesis of peri-CABG stroke is multifactorial and frequently involves other noncarotid causes, such as cardiac emboli and aortic atheroma. Therefore, routine population-wide screening of carotid stenosis is not recommended, but target screening of patients at high risk of carotid-related perioperative stroke can have benefits. Carotid duplex sonography is recommended as an initial screening tool. Elimination of carotid stenosis before cardiac surgery is indicated in patients in whom carotid atherosclerosis is suspected to be the primary contributor to perioperative stroke. In patients with advanced carotid atherosclerosis, an individualized revascularization approach, including simultaneous or staged procedures, is advocated. The prevailing consensus is that synchronous surgery is safer than staged procedures. Carotid artery stenting represents a less invasive alternative, but its role in high-risk patients requires further investigation. In conclusion, the risk of perioperative stroke in patients undergoing CABG involves different factors, and carotid artery stenosis is involved in its pathogenesis only in some patients. Therefore, individualized approaches and careful consideration of patient risk factors are essential in determining the need for carotid screening and revascularization before CABG.

Abdominal aortic aneurysm repair in Sweden vs. Finland: benefits of population-wide screening.

In 2006, screening of 65-year-old men for abdominal aortic aneurysm (AAA) was started in Sweden. Decline in aneurysm-related mortality has been reported since, but aneurysm incidence has been diminishing globally. Neighbouring Finland with similar population structure and health care system has no AAA screening programme. The aim of this study was to compare incidence and results of AAA repair in Sweden and Finland to differentiate the effect of screening from other changes in the epidemiology and treatment of AAA. All repairs for intact AAA (iAAA) or ruptured AAA (rAAA) from 1998 to 2017 were identified from national registers, and mortality data for these patients were collected. A total of 15 927 operations for iAAA were performed in Sweden and 6933 in Finland. In Sweden, the yearly operation volume increased after introduction of screening. Both countries showed a decrease in number of rAAA operations, but the decrease was more pronounced in Sweden. Sweden had a higher proportion of all AAA repairs because of rupture in the start of the study but by the end, the proportions were similar in both countries. Long-term survival improved for 65-79-old men in Sweden after start of screening. This study reveals improvements in results of AAA repair in Sweden. A decrease in rAAA repair and increase in iAAA repair were evident after AAA screening was started in 2006 and resulted in better outcomes. These changes are likely the result of AAA screening as they cannot be seen in neighbouring Finland that is lacking an AAA screening programme.

Development and validation of a machine learning-based framework for assessing metabolic-associated fatty liver disease risk

BackgroundThe existing predictive models for metabolic-associated fatty liver disease (MAFLD) possess certain limitations that render them unsuitable for extensive population-wide screening. This study is founded upon population health examination data and employs a comparison of eight distinct machine learning (ML) algorithms to construct the optimal screening model for identifying high-risk individuals with MAFLD in China.MethodsWe collected physical examination data from 5,171,392 adults residing in the northwestern region of China, during the year 2021. Feature selection was conducted through the utilization of the Least Absolute Shrinkage and Selection Operator (LASSO) regression. Additionally, class balancing parameters were incorporated into the models, accompanied by hyperparameter tuning, to effectively address the challenges posed by imbalanced datasets. This study encompassed the development of both tree-based ML models (including Classification and Regression Trees, Random Forest, Adaptive Boosting, Light Gradient Boosting Machine, Extreme Gradient Boosting, and Categorical Boosting) and alternative ML models (specifically, k-Nearest Neighbors and Artificial Neural Network) for the purpose of identifying individuals with MAFLD. Furthermore, we visualized the importance scores of each feature on the selected model.ResultsThe average age (standard deviation) of the 5,171,392 participants was 51.12 (15.00) years, with 52.47% of the participants being females. MAFLD was diagnosed by specialized physicians. 20 variables were finally included for analyses after LASSO regression model. Following ten rounds of cross-validation and parameter optimization for each algorithm, the CatBoost algorithm exhibited the best performance, achieving an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.862. The ranking of feature importance indicates that age, BMI, triglyceride, fasting plasma glucose, waist circumference, occupation, high density lipoprotein cholesterol, low density lipoprotein cholesterol, total cholesterol, systolic blood pressure, diastolic blood pressure, ethnicity and cardiovascular diseases are the top 13 crucial factors for MAFLD screening.ConclusionThis study utilized a large-scale, multi-ethnic physical examination data from the northwestern region of China to establish a more accurate and effective MAFLD risk screening model, offering a new perspective for the prediction and prevention of MAFLD.

Cost-effectiveness of population-wide genomic screening for Lynch Syndrome and polygenic risk scores to inform colorectal cancer screening

PurposeGenomic screening to identify individuals with Lynch Syndrome (LS) and those with a high polygenic risk score (PRS) promises to personalize colorectal cancer (CRC) screening. Understanding its clinical and economic impact is needed to inform screening guidelines and reimbursement policies. MethodsWe developed a Markov model to simulate individuals over a lifetime. We compared LS+PRS genomic screening with standard of care (SOC) for a cohort of US adults at age 30. The Markov model included health states of no CRC, CRC stages (A-D), and death. We estimated incidence, mortality, and discounted economic outcomes of the population under different interventions. ResultsScreening 1000 individuals for LS+PRS resulted in 1.36 fewer CRC cases and 0.65 fewer deaths compared with SOC. The incremental cost-effectiveness ratio was $124,415 per quality-adjusted life year; screening had a 69% probability of being cost-effective using a willingness-to-pay threshold of $150,000/quality-adjusted life year . Setting the PRS threshold at the 90th percentile of the LS+PRS screening program to define individuals at high risk was most likely to be cost-effective compared with 95th, 85th, and 80th percentiles. ConclusionPopulation-level LS+PRS screening is marginally cost-effective, and a threshold of 90th percentile is more likely to be cost-effective than other thresholds.

Wearable Sensor-Based Assessments for Remotely Screening Early-Stage Parkinson's Disease.

Prevalence estimates of Parkinson's disease (PD)-the fastest-growing neurodegenerative disease-are generally underestimated due to issues surrounding diagnostic accuracy, symptomatic undiagnosed cases, suboptimal prodromal monitoring, and limited screening access. Remotely monitored wearable devices and sensors provide precise, objective, and frequent measures of motor and non-motor symptoms. Here, we used consumer-grade wearable device and sensor data from the WATCH-PD study to develop a PD screening tool aimed at eliminating the gap between patient symptoms and diagnosis. Early-stage PD patients (n = 82) and age-matched comparison participants (n = 50) completed a multidomain assessment battery during a one-year longitudinal multicenter study. Using disease- and behavior-relevant feature engineering and multivariate machine learning modeling of early-stage PD status, we developed a highly accurate (92.3%), sensitive (90.0%), and specific (100%) random forest classification model (AUC = 0.92) that performed well across environmental and platform contexts. These findings provide robust support for further exploration of consumer-grade wearable devices and sensors for global population-wide PD screening and surveillance.

Chatbot for the Return of Positive Genetic Screening Results for Hereditary Cancer Syndromes: a Prompt Engineering Study.

The growing demand for genomic testing and limited access to experts necessitate innovative service models. While chatbots have shown promise in supporting genomic services like pre-test counseling, their use in returning positive genetic results, especially using the more recent large language models (LLMs) remains unexplored. This study reports the prompt engineering process and intrinsic evaluation of the LLM component of a chatbot designed to support returning positive population-wide genomic screening results. We used a three-step prompt engineering process, including Retrieval-Augmented Generation (RAG) and few-shot techniques to develop an open-response chatbot. This was then evaluated using two hypothetical scenarios, with experts rating its performance using a 5-point Likert scale across eight criteria: tone, clarity, program accuracy, domain accuracy, robustness, efficiency, boundaries, and usability. The chatbot achieved an overall score of 3.88 out of 5 across all criteria and scenarios. The highest ratings were in Tone (4.25), Usability (4.25), and Boundary management (4.0), followed by Efficiency (3.88), Clarity and Robustness (3.81), and Domain Accuracy (3.63). The lowest-rated criterion was Program Accuracy, which scored 3.25. The LLM handled open-ended queries and maintained boundaries, while the lower Program Accuracy rating indicates areas for improvement. Future work will focus on refining prompts, expanding evaluations, and exploring optimal hybrid chatbot designs that integrate LLM components with rule-based chatbot components to enhance genomic service delivery.

Screening for chronic kidney disease: change of perspective and novel developments.

Chronic kidney disease (CKD) is a serious health issue because of its rising global prevalence and its complications, such as kidney failure and cardiovascular disease (CVD). CKD is mainly diagnosed late or undiagnosed, delaying or missing the initiation of preventive interventions. Screening can prevent or delay progressive kidney function decline and CVD. This article reviews diagnostic tests and risk prediction developments for patients with CKD, highlights key evidence for targeted screening, and provides new insights into population-wide screening. Large cohort studies and clinical trial data established the strong association of albuminuria with CKD outcomes, supporting the role of albuminuria as target of CKD screening and treatment. Significant advances in both risk prediction of CKD and CVD in CKD patients and treatment options provided new evidence for the relevance and implications of CKD screening. Guidelines recommend targeted screening in high-risk patients, but evidence suggests limited adherence to guideline recommendations. More recently, population-wide screening has been investigated as another approach, showing potential effectiveness and cost-effectiveness. There is increasing evidence for the methods, implications, and effectiveness of CKD screening. Implementing and optimizing screening strategies requires enhanced awareness and understanding of the possibilities for CKD screening within different healthcare systems.

Protocol for the Australian Type 1 Diabetes National Screening Pilot: Assessing the feasibility and acceptability of three general population screening models in children.

One third of Australian children diagnosed with type 1 diabetes present with life-threatening diabetic ketoacidosis (DKA) at diagnosis. Screening for early-stage, presymptomatic type 1 diabetes, with ongoing follow-up, can substantially reduce this risk (<5% risk). Several screening models are being trialled internationally, without consensus on the optimal approach. This pilot study aims to assess three models for a routine, population-wide screening programme in Australia. An implementation science-guided pilot study to evaluate the feasibility, acceptability and costs of three screening models in children will be conducted between July 2022 and June 2024. These models are as follows: (1) Genetic risk-stratified screening using newborn heel prick dried bloodspots, followed by autoantibody testing from 11 months of age; (2) genetic risk-stratified screening of infant (6-12 months) saliva followed by autoantibody testing from 10 months of age; and (3) autoantibody screening using capillary dried bloodspots collected from children aged 2, 6 or 10 years. Cohorts for each model will be recruited from targeted geographic areas across Australia involving ≥2 states per cohort, with a recruitment target of up to 3000 children per cohort (total up to 9000 children). The primary outcome is screening uptake for each cohort. Secondary outcomes include programme feasibility, costs, parental anxiety, risk perception, satisfaction, well-being and quality of life, and health professional attitudes and satisfaction. This pilot is the first direct comparison of three screening implementation models for general population screening. Findings will provide evidence to inform a potential national screening programme for Australian children. ACTRN12622000381785.

Racial, Ethnic, and Sex Differences in Incidence-Based Mortality of Aggregate Upper Gastrointestinal Cancers.

Current strategies for upper gastrointestinal (UGI) cancer screening primarily target cancer-specific risk, with the strongest focus on esophageal adenocarcinoma (EAC). However, all UGI cancers are amendable to screening and early detection with an upper endoscopic examination. This study assesses and explores incidence-based mortality (IBM) for cumulative UGI cancers, aiming to identify race-based or sex-based disparities. We used Surveillance, Epidemiology, and End Results Research data to analyze patients diagnosed with EAC, esophageal squamous cell carcinoma, cardia gastric cancer, noncardia gastric cancer, or colorectal adenocarcinoma from 2000 to 2019. Age-adjusted IBM was calculated as a rate per 100,000 population and stratified by sex and race/ethnicity. We also compared UGI cancer IBM with that of colorectal cancer, a cancer with established population-wide endoscopic screening guidelines. Cumulative IBM for UGI cancers was 8.40 (95% confidence interval [CI] 8.34-8.46). The highest cancer-specific IBM rates were for EAC (2.26, 95% CI 2.23-2.29), followed by noncardia gastric cancer (2.07, 95% CI 2.04-2.10), cardia gastric cancer (1.60, 95% CI 1.57-1.62), esophageal squamous cell carcinoma (1.21, 95% CI 1.19-1.23), and miscellaneous UGI cancer (1.27, 95% CI 1.13-1.40). UGI cancer IBM was highest among Black men (16.43, 95% CI 15.97-16.89), American Indian/Alaska Native men (15.23, 95% CI 13.75-16.82), and Hispanic men (13.76, 95% CI 13.42-14.11). These rates are significantly greater than among White men (12.81, 95% CI 12.68-12.95). UGI cancers impose a significantly higher mortality burden on non-White population subgroups that are not currently targeted by any systematic screening approach.

Radiation exposure and screening yield by digital breast tomosynthesis compared to mammography: results of the TOSYMA Trialbreast density related.

The randomized TOmosynthesis plus SYnthesized MAmmography (TOSYMA) screening trial has shown that digital breast tomosynthesis plus synthesized mammography (DBT + SM) is superior to digital mammography (DM) in invasive breast cancer detection varying with breast density. On the other hand, the overall average glandular dose (AGD) of DBT is higher than that of DM. Comparing the DBT + SM and DM trial arm, we analyzed here the mean AGD and their determinants per breast density category and related them to the respective invasive cancer detection rates (iCDR). TOSYMA screened 99,689 women aged 50 to 69 years. Compression force, resulting breast thickness, the calculated AGD obtained from each mammography device, and previously published iCDR were used for comparisons across breast density categories in the two trial arms. There were 196,622 exposures of 49,227 women (DBT + SM) and 197,037 exposures of 49,132 women (DM) available for analyses. Mean breast thicknesses declined from breast density category A (fatty) to D (extremely dense) in both trial arms. However, while the mean AGD in the DBT + SM arm declined concomitantly from category A (2.41 mGy) to D (1.89 mGy), it remained almost unchanged in the DM arm (1.46 and 1.51 mGy, respectively). In relative terms, the AGD elevation in the DBT + SM arm (64.4% (A), by 44.5% (B), 27.8% (C), and 26.0% (D)) was lowest in dense breasts where, however, the highest iCDR were observed. Women with dense breasts may specifically benefit from DBT + SM screening as high cancer detection is achieved with only moderate AGD elevations. TOSYMA suggests a favorable constellation for screening with digital breast tomosynthesis plus synthesized mammography (DBT + SM) in dense breasts when weighing average glandular dose elevation against raised invasive breast cancer detection rates. There is potential for density-, i.e., risk-adapted population-wide breast cancer screening with DBT + SM. Breast thickness declines with visually increasing density in digital mammography (DM) and digital breast tomosynthesis (DBT). Average glandular doses of DBT decrease with increasing density; digital mammography shows lower andmore constant values. With the smallest average glandular dose differencein dense breasts, DBT plus SM had thehighest difference in invasive breast cancer detection rates.

Evaluating and mapping the evidence that screening for diabetic foot disease meets the criteria for population-wide screening: a scoping review

ObjectiveTo evaluate and map the evidence around diabetes-related foot screening using the World Health Organisation screening principles, which set the gold standard for determining the appropriateness of introducing population-wide screening...

Emotional health screening of mothers, preliminary validation of a 3-item instrument: A research brief

A number of countries now recommend population-wide depression screening for perinatal women, using validated tools. A stepped-approach to screening – involving universal screening with a brief measure, followed by targeted screening using a longer measure for those women identified as at greater risk – is used in some settings. This brief report describes the test performance characteristics of a 3-item mood screening instrument, developed for use within a digital parenting program. Participants (n = 404) in this cross-sectional study were mothers of children aged up to 3 years. The majority (65.5 %) were first-time mothers, and their mean age was 32.8 years. Data were collected using an online survey. The test performance of the brief 3-item mood screening instrument (possible score range = 0–300) was examined using Receiver Operating Characteristic (ROC) analysis, with a score of 13 or more on the Edinburgh Postnatal Depression Scale (EPDS) used as the reference standard. The mood screening instrument demonstrated excellent range when compared to the reference standard. Optimal balance between sensitivity (0.77) and specificity (0.78), was achieved at a cut-point of 160 or less. Analysis was limited by using only the EPDS as the reference standard. This preliminary data supports the use of this 3-item mood screening instrument to screen for postnatal depression symptoms and may be integrated into a mobile Health or online tool. Future research should examine the test performance of the 3-item mood screening instrument against a diagnostic tool.

Distribution and reference values of peripheral perfusion index in neonates from population-wide screening

BackgroundPeripheral perfusion index (PPI) is useful in a variety of neonatal settings. Currently, available reference values are from small numbers and highly variable.MethodsWe sought to generate reference values of PPI...

Accelerating the elimination of hepatitis B virus infection: expert recommendations for expanding prevention and treatment

In order to achieve the early goal of "eliminating viral hepatitis as a public health threat by 2030" as proposed by the World Health Organization, the relevant issues that have not yet reached consensus on the aspects of hepatitis B prevention and treatment, including population-wide screening, adult hepatitis B vaccination, the evaluation of quantitative values of hepatitis B virus DNA, the alanine aminotransferase threshold for initiating antiviral therapy, the treatment of patients in the "indeterminate phase," the treatment of patients with co-infections and comorbidities, and others. Thus, experts have formulated recommendations to further expand hepatitis B prevention and treatment, with the aim of accelerating the elimination of hepatitis B virus infection.

Association of enrollment in Medicare Advantage plans versus fee-for-service in patients with a late-stage diagnosis of gynecologic cancer.

11140 Background: In the United States, uterine cancer is the most common gynecologic (GYN) cancer; and ovarian cancer causes more deaths each year than any other GYN cancer. There are currently no recommended population-wide screening tests for ovarian or uterine cancer, which are heavily concentrated in older women. Medicare is the primary health insurer for 97% of Americans aged 65 years and older. This study is the first to examine the association between Medicare enrollment plan – Medicare Advantage (MA) versus fee-for-service (FFS) – and stage at diagnosis among older women newly diagnosed with ovarian or uterine cancer. Methods: Using the linked Surveillance, Epidemiology, and End Results (SEER) registries and Medicare enrollment data, we identified 101,193 women aged 65 years and older with newly diagnosed ovarian or uterine cancer between 2007-2019. We categorized patients into two groups: 1) those continuously enrolled in Medicare MA for six months prior to their diagnosis, through the diagnosis month, and the month following diagnosis; 2) those continuously enrolled in Medicare FFS within the same eight-month window. Late-stage was defined as “Distant” stage (with “Local” and “Regional” stages representing an earlier-stage diagnosis) using the SEER Summary Stage variable. The association between Medicare enrollment plan and stage was examined through multivariable logistic regression modeling that adjusted for sociodemographic characteristics. The influence of each predictor on the difference in the probability of late stage was summarized as an adjusted marginal effect (ME). Results: Among uterine cancer patients, 37% had MA insurance. Compared with Medicare FFS enrollees, the adjusted percentage of late-stage diagnosis was 0.6 percentage points (ppt) lower for MA enrollees (95% CI = -1.1-(-0.1); P&lt;0.05). Notably, patients were more likely to have a late-stage uterine diagnosis if they were: non-Hispanic Black or Hispanic (vs. non-Hispanic White); age 75 and older (vs. between 65 -74); and residing in a lower SES neighborhood. Among ovarian cancer patients, 34% had MA insurance. We found no significant difference between Medicare MA and FFS enrollees in ovarian cancer stage at diagnosis. Of note, Non-Hispanic Black patients were significantly more likely to be diagnosed with late-stage disease compared to Non-Hispanic White, and likewise for patients aged 75 and older (vs. between 65-74). Conclusions: Among Medicare beneficiaries (age 65+) diagnosed with uterine cancer, those enrolled in an MA plan were significantly less likely to be diagnosed at a later stage. In similar analyses for ovarian cancer, there was no such MA - FFS difference in the probability of late-stage. As enrollment in Medicare Advantage plans continues to grow, it becomes increasingly important to identify whether there are significant outcome differences between MA and FFS plans.

Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection Using Eight Million Samples Labeled With Imprecise Arrhythmia Alarms.

Atrial fibrillation (AF) is a common cardiac arrhythmia with serious health consequences if not detected and treated early. Detecting AF using wearable devices with photoplethysmography (PPG) sensors and deep neural networks has demonstrated some success using proprietary algorithms in commercial solutions. However, to improve continuous AF detection in ambulatory settings towards a population-wide screening use case, we face several challenges, one of which is the lack of large-scale labeled training data. To address this challenge, we propose to leverage AF alarms from bedside patient monitors to label concurrent PPG signals, resulting in the largest PPG-AF dataset so far (8.5 M 30-second records from 24,100 patients) and demonstrating a practical approach to build large labeled PPG datasets. Furthermore, we recognize that the AF labels thus obtained contain errors because of false AF alarms generated from imperfect built-in algorithms from bedside monitors. Dealing with label noise with unknown distribution characteristics in this case requires advanced algorithms. We, therefore, introduce and open-source a novel loss design, the cluster membership consistency (CMC) loss, to mitigate label errors. By comparing CMC with state-of-the-art methods selected from a noisy label competition, we demonstrate its superiority in handling label noise in PPG data, resilience to poor-quality signals, and computational efficiency.

NLRX1: a key regulator in mitochondrial respiration and colorectal cancer progression.

Colorectal cancer (CRC) is a prevalent and aggressive malignancy with high mortality rates and significant risks to human well-being. Population-wide screening for tumor suppressor genes and oncogenes shows promise for reducing the incidence and fatality of CRC. Recent studies have suggested that NLRX1, an innate immunity suppressor, may play a role in regulating chronic inflammation and tumorigenesis. However, further investigation is needed to understand the specific role of NLRX1 in CRC. To evaluate the impact of NLRX1 on migration, invasion, and metastasis, two human colon cancer cell lines were studied in vitro. Additionally, a knockout mouse tumor-bearing model was used to validate the inhibitory effect of NLRX1 on tumor emergence and progression. The Seahorse XF96 technology was employed to assess mitochondrial function and glycolysis in colorectal cancer cells overexpressing NLRX1. Moreover, public databases were consulted to analyze gene and protein expression levels of NLRX1. Finally, the results were validated using a series of CRC patient samples. Our findings demonstrate that downregulation of NLRX1 enhances proliferation, colony formation, and tumor-forming capacity in HCT116 and LoVo cells. Conversely, overexpression of NLRX1 negatively impacts basal respiration and mitochondrial ATP-linked respiration in both cell lines, resulting in a notable decrease in maximal respiration during the standard mitochondrial stress test. Furthermore, analysis of data from the TCGA database reveals a significant reduction in NLRX1 expression in colon and rectal cancer tissues compared to normal tissues. This result was validated using clinical samples, where immunohistochemistry staining and western blotting demonstrated a notable reduction in NLRX1 protein levels in CRC compared to adjacent normal tissues. The decreased expression of NLRX1 may serve as a significant prognostic indicator and diagnostic biomarker for CRC patients.

A Multi-Stage Approach for Cardiovascular Risk Assessment from Retinal Images Using an Amalgamation of Deep Learning and Computer Vision Techniques.

Cardiovascular diseases (CVDs) are a leading cause of mortality worldwide. Early detection and effective risk assessment are crucial for implementing preventive measures and improving patient outcomes for CVDs. This work presents a novel approach to CVD risk assessment using fundus images, leveraging the inherent connection between retinal microvascular changes and systemic vascular health. This study aims to develop a predictive model for the early detection of CVDs by evaluating retinal vascular parameters. This methodology integrates both handcrafted features derived through mathematical computation and retinal vascular patterns extracted by artificial intelligence (AI) models. By combining these approaches, we seek to enhance the accuracy and reliability of CVD risk prediction in individuals. The methodology integrates state-of-the-art computer vision algorithms and AI techniques in a multi-stage architecture to extract relevant features from retinal fundus images. These features encompass a range of vascular parameters, including vessel caliber, tortuosity, and branching patterns. Additionally, a deep learning (DL)-based binary classification model is incorporated to enhance predictive accuracy. A dataset comprising fundus images and comprehensive metadata from the clinical trials conducted is utilized for training and validation. The proposed approach demonstrates promising results in the early prediction of CVD risk factors. The interpretability of the approach is enhanced through visualization techniques that highlight the regions of interest within the fundus images that are contributing to the risk predictions. Furthermore, the validation conducted in the clinical trials and the performance analysis of the proposed approach shows the potential to provide early and accurate predictions. The proposed system not only aids in risk stratification but also serves as a valuable tool for identifying vascular abnormalities that may precede overt cardiovascular events. The approach has achieved an accuracy of 85% and the findings of this study underscore the feasibility and efficacy of leveraging fundus images for cardiovascular risk assessment. As a non-invasive and cost-effective modality, fundus image analysis presents a scalable solution for population-wide screening programs. This research contributes to the evolving landscape of precision medicine by providing an innovative tool for proactive cardiovascular health management. Future work will focus on refining the solution's robustness, exploring additional risk factors, and validating its performance in additional and diverse clinical settings.