Incremental Utility Research Articles

Cost-effectiveness of HCV testing strategies for hepatitis C elimination in general population in China

Objective: To evaluate the cost-effectiveness of hepatitis C screening in general population in China, and find the age group in which hepatitis C screening can achieve the best cost-effectiveness. Methods: A decision-Markov model was constructed by using software TreeAge pro 2019 to simulate the outcomes of hepatitis C disease pregression of 100 000 persons aged 20-59 years. The cost-effectiveness of the strategies were evaluated from societal perspectives by using incremental cost-effectiveness ratio (ICER) and net monetary benefit (NMB). One-way sensitivity analysis and probability sensitivity analysis were used to evaluate the uncertainty of parameters and model. Results: Hepatitis C screening was cost-effective in people aged 20- 59 years and the cost effectiveness was best in age group 40-49 years. Compared with non-screening strategy of hepatitis C in people aged 20-59 years, the incremental cost was 161.24 yuan, the incremental utility was 0.003 6 quality adjusted life years (QALYs)/per person, ICER was 45 197.26 yuan/QALY, ICER was less than the willing payment threshold. The ICER and NMB in all age groups were 42 055.06-53 249.43 yuan/QALY and 96.52-169.86 yuan/per person. Hepatitis C screening in people aged 40-49 years had the best cost-effectiveness. The results of one-way sensitivity analysis showed that the discount rate, anti-HCV detection cost, anti-HCV infection rate and the cost of direct antiviral agents were the main factors influencing economic evaluation. The results of the probability sensitivity analysis indicated that the model analysis was stable. Conclusions: Implementing hepatitis C screening based on medical institutions is cost-effective in people aged 20- 59 years, especially in those aged 40-49 years. Implementing the HCV screening strategy of be willing to test as far as possible in general population can reduce hepatitis C disease burden in China.

A Generalizable Decision-Making Framework for Selecting Onsite versus Send-out Clinical Laboratory Testing.

Laboratory networks provide services through onsite testing or through specimen transport to higher-tier laboratories. This decision is based on the interplay of testing characteristics, treatment characteristics, and epidemiological characteristics. Our objective was to develop a generalizable model using the threshold approach to medical decision making to inform test placement decisions. We developed a decision model to compare the incremental utility of onsite versus send-out testing for clinical purposes. We then performed Monte Carlo simulations to identify the settings under which each strategy would be preferred. Tuberculosis was modeled as an exemplar. The most important determinants of the decision to test onsite versus send-out were the clinical utility lost due to send-out testing delays and the accuracy decrement with onsite testing. When the sensitivity decrements of onsite testing were minimal, onsite testing tended to be preferred when send-out delays reduced clinical utility by >20%. By contrast, when onsite testing incurred large reductions in sensitivity, onsite testing tended to be preferred when utility lost due to delays was >50%. The relative cost of onsite versus send-out testing affected these thresholds, particularly when testing costs were >10% of treatment costs. Decision makers can select onsite versus send-out testing in an evidence-based fashion using estimates of the percentage of clinical utility lost due to send-out delays and the relative accuracy of onsite versus send-out testing. This model is designed to be generalizable to a wide variety of use cases. The design of laboratory networks, including the decision to place diagnostic instruments at the point-of-care or at higher tiers as accessed through specimen transport, can be informed using the threshold approach to medical decision making.The most important determinants of the decision to test onsite versus send-out were the clinical utility lost due to send-out testing delays and the accuracy decrement with onsite testing.The threshold approach to medical decision making can be used to compare point-of-care testing accuracy decrements with the lost utility of treatment due to send-out testing delays.The relative cost of onsite versus send-out testing affected these thresholds, particularly when testing costs were >10% of treatment costs.

Budget impact and cost-utility analysis of prophylactic emicizumab versus on-demand bypassing agents for adolescent severe haemophilia A patients with inhibitors in India

IntroductionSevere Haemophilia A patients with inhibitors are currently being treated with bypassing agents like activated prothrombin complex concentrates (aPCC) and recombinant factor VIIa. Emicizumab is a recombinant humanized monoclonal antibody, introduced to reduce the bleeding events, improve treatment adherence, and quality of life. However, cost-effectiveness and long-term sustainability of the intervention is not studied in a low middle income setting like India. AimThe primary objective of this study was to evaluate the cost-utility of Emicizumab compared to traditional bypassing agents in the treatment of severe haemophilia A patients with inhibitors in India. Secondary objective was to analyze the budgetary impact of introducing Emicizumab for this patient population from the perspective of public health system in India. MethodsMarkov model was created to compare the prophylactic emicizumab therapy against bypassing agents for a hypothetical cohort of 10-year-old adolescents in India. The time horizon was 10 years and model built based on health system perspective. Cost utility was expressed as costs per quality-adjusted life-years (QALYs) gained. All costs were expressed as 2021 US dollars. Probabilistic sensitivity analysis was performed to check the robustness of the estimates. ResultsProphylactic emicizumab was a cost saving intervention with negative Incremental Cost Utility Ratio (ICUR) against recombinant factor VIIa of −853,573 USD (INR -63,109,773), and negative ICUR of −211,675 USD (INR -15,650,403) against APCC. The estimated total budget for treating all the severe Haemophilia A patients with inhibitors in India was USD 59,042,000 (INR 4,365,329,312) for 10 years’ time horizon (per patient cost of USD 295,210 [INR 21,826,646.56]). ConclusionProphylactic emicizumab therapy is a cost saving intervention when compared to both the bypassing agents as it is less costly and more effective for severe Haemophilia A patients with inhibitors in India.

The cost-utility of intraoperative tranexamic acid in adult spinal deformity patients undergoing long posterior spinal fusion.

This study aims to evaluate the cost-utility of intraoperative tranexamic acid (TXA) in adult spinal deformity (ASD) patients undergoing long posterior (≥ 5 vertebral levels) spinal fusion. A decision-analysis model was built for a hypothetical 60-year-old adult patient with spinal deformity undergoing long posterior spinal fusion. A comprehensive review of the literature was performed to obtain event probabilities, costs and health utilities at each node. Health utilities were utilized to calculate Quality-Adjusted Life Years (QALYs). A base-case analysis was carried out to obtain the incremental cost and effectiveness of intraoperative TXA. Probabilistic sensitivity analysis was performed to evaluate uncertainty in our model and obtain mean incremental costs, effectiveness, and net monetary benefits. One-way sensitivity analyses were also performed to identify the variables with the most impact on our model. Use of intraoperative TXA was the favored strategy in 88% of the iterations. The mean incremental utility ratio for using intraoperative TXA demonstrated higher benefit and lower cost while being lower than the willingness-to-pay threshold set at $50,000 per quality adjusted life years. Use of intraoperative TXA was associated with a mean incremental net monetary benefit (INMB) of $3743 (95% CI 3492-3995). One-way sensitivity analysis reported cost of blood transfusions due to post-operative anemia to be a major driver of cost-utility analysis. Use of intraoperative TXAs is a cost-effective strategy to reduce overall perioperative costs related to post-operative blood transfusions. Administration of intraoperative TXA should be considered for long fusions in ASD population when not explicitly contra-indicated due to patient factors.

Cost-effectiveness and budget impact analysis of Daratumumab, Lenalidomide and dexamethasone for relapsed-refractory multiple myeloma

BackgroundThe prominent efficacy in terms of increasing progression-free survival (PFS) of Daratumumab, Lenalidomide and dexamethasone (DRd) triplet therapy versus Carfilzomib, Lenalidomide and dexamethasone (KRd) was proven previously in relapsed-refractory multiple myeloma (RRMM). However, the cost effectiveness of DRd versus KRd is unknown.MethodsWe developed a Markov model by using an Iranian payer perspective and a 10-year time horizon to estimate the healthcare cost, Quality-adjusted life years (QALYs) and life years gain (LYG) for DRd and KRd triplet therapies. Clinical data were obtained from meta-analyses and randomized clinical trials (RCTs). One-way and probabilistic sensitivity analysis were performed to assess model uncertainty. Budget impact analysis of 5 years of treatment under the DRd triplet therapy was also analysed.ResultsDRd was estimated to be more effective compared to KRd, providing 0.28 QALY gain over the modelled horizon. DRd-treated patients incurred $264 in total additional costs. The incremental cost utility ratio (ICUR) and cost effectiveness ratio (ICER) were $956/QALY and $472/LYG respectively.The budget impact analysis indicates that adding Daratumumab to Lenalidomide and dexamethasone regimen, in the first 5 years, will increase the healthcare system’s expenses by $6.170.582.ConclusionDRd triplet therapy compared to KRd is a cost-effective regimen for RRMM under Iran willingness-to-pay threshold.

Clarifying the relationship between mental illness and recidivism using machine learning: A retrospective study.

There is currently inconclusive evidence regarding the relationship between recidivism and mental illness. This retrospective study aimed to use rigorous machine learning methods to understand the unique predictive utility of mental illness for recidivism in a general population (i.e.; not only those with mental illness) prison sample in the United States. Participants were adult men (n = 322) and women (n = 72) who were recruited from three prisons in the Midwest region of the United States. Three model comparisons using Bayesian correlated t-tests were conducted to understand the incremental predictive utility of mental illness, substance use, and crime and demographic variables for recidivism prediction. Three classification statistical algorithms were considered while evaluating model configurations for the t-tests: elastic net logistic regression (GLMnet), k-nearest neighbors (KNN), and random forests (RF). Rates of substance use disorders were particularly high in our sample (86.29%). Mental illness variables and substance use variables did not add predictive utility for recidivism prediction over and above crime and demographic variables. Exploratory analyses comparing the crime and demographic, substance use, and mental illness feature sets to null models found that only the crime and demographics model had an increased likelihood of improving recidivism prediction accuracy. Despite not finding a direct relationship between mental illness and recidivism, treatment of mental illness in incarcerated populations is still essential due to the high rates of mental illnesses, the legal imperative, the possibility of decreasing institutional disciplinary burden, the opportunity to increase the effectiveness of rehabilitation programs in prison, and the potential to improve meaningful outcomes beyond recidivism following release.

Assessment of PTSD and Trauma Symptoms With the MMPI–3 in College Students: Validity and Incremental Utility of the Anxiety Related Experiences (ARX) Scale

Post Traumatic Stress Disorder (PTSD) is heterogeneous in nature, which complicates diagnostic efforts and makes accurate assessment tools critical. The MMPI family of instruments are widely used broadband measures of psychopathology, including trauma symptomology. The MMPI–3’s Anxiety Related Experiences scale (ARX) is an expansion of the MMPI–2–RF Anxiety (AXY) scale which has historically represented the MMPI family’s best measure of trauma symptoms. This study expands research on ARX in 2 samples of college students (n = 332 [PCL–5 Criterion] & n = 58 [CAPS–5 Criterion]) by examining ARX’s incremental, criterion, and classification validity. ARX incrementally predicted PCL–5 total and cluster scores beyond that accounted for by AXY (R 2Δ = .01–.09). ARX accounted for the most unique variance, beyond RCd and RC7, in CAPS-5 interview ratings of intrusion symptoms (R 2Δ = .16). ARX was strongly related to trauma symptomology broadly (r = .42–.58) and demonstrated strong screening ability at T65 (sensitivity = .37–.40; specificity = .91–.92) and stronger diagnostic screening at T75 (sensitivity = .31; specificity = .93). We discuss clinical considerations when using ARX for assessing PTSD.

MMPI-2-RF validity scales add utility for predicting treatment engagement during partial psychiatric hospitalizations.

Partial psychiatric hospitalizations are resource-intensive clinical services designed to stabilize patients in the short term, prevent inpatient hospitalizations, and encourage long-term recovery. Typically, providers base their referral decisions on categorical diagnoses and subjective impressions of patient distress without closely considering the evidence for reporting biases. The present study followed veterans (n = 430) participating in partial psychiatric hospitalization services. We evaluated the extent to which clinical diagnoses at intake predicted treatment variables and changes in later mental health care utilization. Using hierarchical linear regressions with bootstrap confidence intervals, Minnesota Multiphasic Personality Inventory-2-Restructured Form content-based validity scales demonstrated incremental utility for predicting patient outcomes beyond intake diagnoses. Elevated Fp-r ("Infrequent Psychopathology Responses") scores independently predicted an increased number of times arriving late for partial hospitalization programming, self-report of worse current functioning at intake, and a relative increase in mental health care encounters in the 12 months following discharge. Low K-r ("Adjustment Validity") scores independently predicted self-report of worse current functioning at both intake and later discharge from partial hospitalization. Thus, indicators of severe psychopathology overreporting as well as the unlikely disavowal of emotional adjustment (i.e., high Fp-r, low K-r) predicted engagement with health care services and self-presentations of symptoms over and above the diagnostic impressions from referring providers. We discuss how indicators of content-based invalid responding on the Minnesota Multiphasic Personality Inventory-2-Restructured Form have real-world value for understanding patient behavior and shaping clinical interventions among vulnerable populations. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis.

Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Lumbar Decompression With and Without Fusion for Lumbar Stenosis With Spondylolisthesis: A Cost Utility Analysis.

Markov model. To compare the cost-effectiveness of lumbar decompression alone (DA) with lumbar decompression with fusion (DF) for the management of adults undergoing surgery for lumbar stenosis with associated degenerative spondylolisthesis. Rates of lumbar fusion have increased for all indications in the United States over the last 20 years. Recent randomized controlled trial data, however, have suggested comparable functional outcomes and lower reoperation rates for lumbar decompression and fusion as compared with DA in the treatment of lumbar stenosis with degenerative spondylolisthesis. A multistate Markov model was constructed from the US payer perspective of a hypothetical cohort of patients with lumbar stenosis with associated spondylolisthesis requiring surgery. Data regarding clinical improvement, costs, and reoperation were generated from contemporary randomized trial evidence, meta-analyses of recent prospective studies, and large retrospective cohorts. Base case, one-way sensitivity analysis, and probabilistic sensitivity analyses were conducted, and the results were compared with a WTP threshold of $100,000 (in 2022 USD) over a two-year time horizon. A discount rate of 3% was utilized. The incremental cost and utility of DF relative to DA were $12,778 and 0.00529 aggregated quality adjusted life years. The corresponding incremental cost-effectiveness ratio of $2,416,281 far exceeded the willingness to pay threshold of $100,000. In sensitivity analysis, the results varied the most with respect to rate of improvement after DA, rate of improvement after lumbar decompression and fusion, and odds ratio of reoperation between the two groups. Zero percent of one-way and probabilistic sensitivity analyses achieved cost-effectiveness at the willingness-to-pay threshold. Within the context of contemporary surgical data, DF is not cost-effective compared with DA in the surgical management of lumbar stenosis with associated spondylolisthesis over a two-year time horizon.

Integration of Psychosocial Theory into Palliative Care: Implications for Care Planning and Early Palliative Care.

Palliative care improves patients' symptoms, quality of life and family satisfaction with caregiving, reduces hospital admissions and promotes alignment of medical care with the patient's needs and goals. This article proposes the utility of integrating three psychosocial theories into standard palliative care with implications for care planning, early palliative care and optimizing quality of life. First, Control Theory focuses on the complex juxtaposition of promoting agency/empowerment in patients and carers and coping with often highly uncertain outcomes. Second, Optimal Matching Theory accounts for the alignment of need and provision of care to potentiate the quality of life effects of supportive care in a complex social process involving health care providers, patients and carers. Third, Hope Theory represents a dynamic process, which is marked by variation in the qualities of hope as the patient and carer confront challenges during palliative care. Future work will be translational in nature to adapt both assessment and interventions based on this theoretically driven augmentation of palliative care as well as to evaluate whether it provides a conceptual framework that has incremental utility in palliative care planning.

Incremental prognostic utility of left ventricular and left atrial strains in coronary artery disease patients with reduced systolic function.

This study aimed to investigate the predictive value of left ventricular global longitudinal strain (GLS) and left atrial reservoir strain (LARS) on adverse events in chronic coronary artery disease (CAD) patients with reduced systolic function. A total of 192 consecutive patients clinically diagnosed with chronic CAD and left ventricular ejection fraction (LVEF)≤50% were finally included. Multiple strain parameters were analyzed with speckle tracking echocardiography. The composite endpoint included all-cause mortality, rehospitalization due to heart failure, myocardial infarction, and stroke. Patients experiencing the endpoint showed lower LVEF, lower absolute GLS and LARS than those without events. Both GLS (AUC=0.82 [GLS] vs. 0.58 [LVEF], p < 0.001) and LARS (AUC=0.71 [LARS] vs. 0.58 [LVEF], p=0.033) were superior to LVEF in predicting adverse events. Multivariate cox regression analysis showed that both GLS (hazard ratio, 0.71; 95% CI, 0.63-0.79; p < 0.001) and LARS (hazard ratio, 0.96; 95% CI, 0.93-0.98; p < 0.001) were independent predictors for the endpoint. The addition of LARS (global chi-squared, 35.7vs. 17.4; p < 0.05), GLS (global chi-squared, 58.6vs. 17.4; p < 0.05) or both LARS and GLS (global chi-squared, 79.6vs. 17.4; p < 0.05) to LVEF in the prediction model significantly improved its performance. The same significant improvement was also shown in the subgroups of mild (30%<LVEF≤50%) and severe (LVEF≤30%) reduced systolic function. Regarding CAD patients with reduced LVEF, both GLS and LARS are superior to LVEF in predicting adverse events, providing significant incremental value to LVEF.

Incremental Top-k High Utility Pattern Mining and Analyzing Over the Entire Accumulated Dynamic Database

Incremental Top-k High Utility Pattern Mining and Analyzing Over the Entire Accumulated Dynamic Database

The cost-utility of an intervention for children and adolescents with a parent having a mental illness in the framework of the German health and social care system: a health economic evaluation of a randomized controlled trial

BackgroundChildren of families with a parent with a mental illness have an increased risk of developing social and mental health problems resulting in decreased quality of life. Therefore, children and adolescents living in families with a parent with mental illness are regarded as a target group for preventive interventions. To date, only a few economic evaluation studies for interventions directed at preventing the intergenerational transmission of mental health problems exist. In this investigation we estimated the cost utility of an intervention for the support of children and adolescents with a parent having a mental illness from the perspective of the German health and social care system.MethodsWe randomly assigned a total of 214 families with 337 children and adolescents to the intervention (INT) group (108/170) or the control (TAU) group (106/167). Families in the intervention group received on average eight intervention sessions (50–90 min) over 6 months. We estimated total cost of illness by means of the Children and Adolescent Mental Health Service Receipt Inventory (CAMHSRI) over 24 months. For the estimation of Quality-Adjusted Live Years (QALYs) we applied the KIDSCREEN-10. For estimating the incremental cost-utility of the intervention compared to treatment as usual we used the net-benefit approach.ResultsWe estimated the annual cost of illness amounting to € 3784.59 (SD € 8581.11) in the TAU group and € 3264.44 (SD € 9431.89) in the INT group. The annual cost difference between INT and TAU was € − 516.14 (SE 1124.95) which was not significant (p ≤ 0.05). We estimated the average QALY to be 0.759 (SD 0.073) in the TAU group and 0.763 (SD 0.072). The QALY difference between INT and TAU was 0.0037 (SE 0.0092) which was not significant (p ≤ 0.05). The incremental cost utility ratio (ICUR) indicated that the gain of one additional year in full health by means of the intervention was associated with the saving of € 139.49. However, the stochastic insecurity of the ICUR did not allow a unique decision about the cost-utility of the intervention.ConclusionsMore information on the economic value of the intervention for families with a parent with mental illness in comparison to treatment as usual in Germany is needed.Trial registration: ClinicalTrials.gov, identifier NCT02308462; German Clinical Trials Register: DRKS00006806.

Prognostic value of left atrial strain in patients with tetralogy of fallot.

To demonstrate prognostic utility of left atrial strain (LAS) in adult patients with repaired Tetralogy of Fallot (rTOF). Adults patients with rTOF were prospectively enrolled in this study between years 2011 and 2015. Left atrium (LA) phasic functions were assessed using 2D speckle tracking echocardiography. Association of LA strain (LAS) with primary (any cardiovascular event) and secondary (death, heart failure or arrhythmia) composite endpoints was assessed using Cox regression analysis. Hundred-and-twelve rTOF patients, in whom LAS was feasible and were in sinus rhythm, were included in the final analysis (age 33 ± 10years, 68[61%] male). Median duration of follow-up was 8.6 [4.2-9.7] years in the study group. Primary composite endpoint was reached in 48 patients (mean event-free survival time: 7.2 [6.6-7.9] years), and secondary composite endpoint was reached in 22 patients (mean event-free survival time: 8.7 [8.1-9.2] years). LA reservoir strain (LAS-r) was defined as tertile groups (1st tertile < 33%, 2nd tertile = 33-44%, 3rd tertile > 44%). Decreasing tertiles of LAS-r was associated with primary and secondary composite endpoints in Kaplan-Meier analysis (p = 0.02 and 0.002, respectively). In univariable Cox-regression, both decreasing LAS-r and LAS-r tertiles were associated with primary and secondary composite endpoints. Adjusted by initial repair age and NT-proBNP quartiles, increased LAS-r was associated with significantly decreased occurrence of experiencing any events (HR = 0.97, CI 0.93-0.99, p < 0.001). Decreasing LAS-r was still associated with primary endpoint when adjusted by left atrium volume index (LAVImax) (HR = 0.96, CI 0.92-0.99, p = 0.01), left ventricle global longitudinal strain (HR = 0.96, CI 0.93-0.99, p < 0.001) or right ventricle free wall longitudinal strain (HR = 0.96, CI 0.93-0.99, p = 0.03). Assessment of LA mechanics with the use of STE has incremental utility in determination of mortality and morbidity in rTOF, and may be implemented in clinical practice.

Primary Care Detection of Cognitive Impairment Leveraging Health &amp; Consumer Technologies in Underserved Communities: The MyCog Strategy

AbstractBackgroundEarly identification of cognitive impairment (CI), including Alzheimer’s disease and related dementias (ADRD), is a top public health priority. Yet in primary care settings that manage the health of most community‐dwelling older adults, less than half of patients with any CI are detected and/or diagnosed. Among community health centers that serve marginalized patients, rates of detection may be far lower. To address this, we sought to test a primary care‐based strategy (‘MyCog’) to improve CI detection as part of an NIH‐sponsored consortium (DetectCID).MethodThe MyCog strategy includes a brief iPad‐based, self‐administered, electronic health record (EHR)‐linked cognitive assessment that leverages two well validated measures from the NIH Toolbox Cognition Battery and has easily interpretable results with ‘turnkey’ recommendations to enhance clinical decision making. Clinician and practice administrator feedback was sought via cognitive interviews and focus groups to ensure the assessment could properly function in typical workflows. Based on this feedback a self‐administered tool was built, with a simple interpretable result (yes or no, cognitive impairment detected). It was then validated in one academic geriatrics practice among 111 older adults.ResultThe refined self‐administered tool was further validated in a geriatric clinical population, with interviewer and self‐administered MyCog versions strongly correlated (Spearman r = 0.75) and similar average response time per trial (0.914 sec. vs. 0.958 sec.). Use of the two tests demonstrated acceptable AUC values separately for detecting CI (0.84 and 0.79, respectively). But combined, these measures provide incremental diagnostic utility (AUC = 0.95).ConclusionWe will launch the MyCog Trial at 24 practices from a national network of primary care centers for older adults on Medicare that will be randomized to MyCog or usual care. Clinics receiving MyCog will utilize a protocol to implement the intervention during Medicare Annual Wellness Visits and whenever a cognitive concern is expressed. Findings from the DetectCID consortium and MyCog Trial will directly inform future standards in primary care settings, especially those that serve health disparate patient populations.

A Markov model-based cost-effectiveness analysis comparing zanubrutinib to ibrutinib for treating relapsed and refractory chronic lymphocytic leukemia

ABSTRACT Objective This article examined the cost-effectiveness of zanubrutinib and ibrutinib for managing relapsed and refractory chronic lymphocytic leukemia from the viewpoint of payers in China and the US. Methods Markov models were employed to conduct comparisons. Baseline characteristics and clinical data were extracted from the ALPINE study. The cost-effectiveness outcome indicators encompassed cost, quality-adjusted life years, and the incremental cost-effectiveness ratio. Results The Markov model analysis revealed that the zanubrutinib group incurred an incremental cost per patient of $-24,586.53 compared to the ibrutinib group. The zanubrutinib group exhibited an incremental utility per capita of 0.28 quality-adjusted life years, resulting in an incremental cost-effectiveness ratio of $-88,068.16 per quality-adjusted life year, which is lower than the payment threshold in China. The willingness-to-pay value in China for 2022 was three times the country’s gross domestic product per capita. In the US, patients in the zanubrutinib group experienced per capita incremental costs of $-79,421.56, per capita incremental utility of 0.28 quality-adjusted life years, and an incremental cost-effectiveness ratio of $-284,485.45 per quality-adjusted life year. Conclusion For Chinese payers, zanubrutinib exhibited superior cost-effectiveness compared to ibrutinib. Zanubrutinib proved to be a more affordable option for US payers when considering the payment threshold.

Epicardial and Pericoronary Adipose Tissue, Coronary Inflammation, and Acute Coronary Syndromes

Vascular inflammation is recognized as the primary trigger of acute coronary syndrome (ACS). However, current noninvasive methods are not capable of accurately detecting coronary inflammation. Epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT), in addition to their role as an energy reserve system, have been found to contribute to the development and progression of coronary artery calcification, inflammation, and plaque vulnerability. They also participate in the vascular response during ischemia, sympathetic stimuli, and arrhythmia. As a result, the evaluation of EAT and PCAT using imaging techniques such as computed tomography (CT), cardiac magnetic resonance (CMR), and nuclear imaging has gained significant attention. PCAT-CT attenuation, which measures the average CT attenuation in Hounsfield units (HU) of the adipose tissue, reflects adipocyte differentiation/size and leukocyte infiltration. It is emerging as a marker of tissue inflammation and has shown prognostic value in coronary artery disease (CAD), being associated with plaque development, vulnerability, and rupture. In patients with acute myocardial infarction (AMI), an inflammatory pericoronary microenvironment promoted by dysfunctional EAT/PCAT has been demonstrated, and more recently, it has been associated with plaque rupture in non-ST-segment elevation myocardial infarction (NSTEMI). Endothelial dysfunction, known for its detrimental effects on coronary vessels and its association with plaque progression, is bidirectionally linked to PCAT. PCAT modulates the secretory profile of endothelial cells in response to inflammation and also plays a crucial role in regulating vascular tone in the coronary district. Consequently, dysregulated PCAT has been hypothesized to contribute to type 2 myocardial infarction with non-obstructive coronary arteries (MINOCA) and coronary vasculitis. Recently, quantitative measures of EAT derived from coronary CT angiography (CCTA) have been included in artificial intelligence (AI) models for cardiovascular risk stratification. These models have shown incremental utility in predicting major adverse cardiovascular events (MACEs) compared to plaque characteristics alone. Therefore, the analysis of PCAT and EAT, particularly through PCAT-CT attenuation, appears to be a safe, valuable, and sufficiently specific noninvasive method for accurately identifying coronary inflammation and subsequent high-risk plaque. These findings are supported by biopsy and in vivo evidence. Although speculative, these pieces of evidence open the door for a fascinating new strategy in cardiovascular risk stratification. The incorporation of PCAT and EAT analysis, mainly through PCAT-CT attenuation, could potentially lead to improved risk stratification and guide early targeted primary prevention and intensive secondary prevention in patients at higher risk of cardiac events.

Cost-effectiveness analysis of artificial intelligence-based diabetic retinopathy screening in rural China based on the Markov model.

This study assessed the cost-effectiveness of different diabetic retinopathy (DR) screening strategies in rural regions in China by using a Markov model to make health economic evaluations. In this study, we determined the structure of a Markov model according to the research objectives, which required parameters collected through field investigation and literature retrieval. After perfecting the model with parameters and assumptions, we developed a Markov decision analytic model according to the natural history of DR in TreeAge Pro 2011. For this model, we performed Markov cohort and cost-effectiveness analyses to simulate the probabilistic distributions of different developments in DR and the cumulative cost-effectiveness of artificial intelligence (AI)-based screening and ophthalmologist screening for DR in the rural population with diabetes mellitus (DM) in China. Additionally, a model-based health economic evaluation was performed by using quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios. Last, one-way and probabilistic sensitivity analyses were performed to assess the stability of the results. From the perspective of the health system, compared with no screening, AI-based screening cost more (the incremental cost was 37,257.76 RMB (approximately 5,211.31 US dollars)), but the effect was better (the incremental utility was 0.33). Compared with AI-based screening, the cost of ophthalmologist screening was higher (the incremental cost was 14,886.76 RMB (approximately 2,070.19 US dollars)), and the effect was worse (the incremental utility was -0.31). Compared with no screening, the incremental cost-effectiveness ratio (ICER) of AI-based DR screening was 112,146.99 RMB (15,595.47 US dollars)/QALY, which was less than the threshold for the ICER (< 3 times the per capita gross domestic product (GDP), 217,341.00 RMB (30,224.03 US dollars)). Therefore, AI-based screening was cost-effective, which meant that the increased cost for each additional quality-adjusted life year was merited. Compared with no screening and ophthalmologist screening for DR, AI-based screening was the most cost-effective, which not only saved costs but also improved the quality of life of diabetes patients. Popularizing AI-based DR screening strategies in rural areas would be economically effective and feasible and can provide a scientific basis for the further formulation of early screening programs for diabetic retinopathy.

Abstract 17494: The Incremental Risk Prediction of Cardiac CTA-Derived Quantitative Atherosclerosis in the International Advance Registry

Background: We sought to assess the incremental prognostic utility of AI-enabled quantitative coronary plaque assessment (AI-QCPA) beyond stenosis severity and FFR CT , for the prediction of late revascularization and MACE in the large prospective international ADVANCE registry. Methods: 4737 participants were submitted for AI-QCPA evaluation. Total plaque volume (TPV), calcified plaque volume (CPV), non-calcified plaque volume (NCPV), and low attenuated plaque volume (LAPV) were quantified. In addition, total percent plaque volume (TPAV) and its components were calculated (PV/Vessel Volume * 100). Demographics, stenosis severity, lowest FFR CT , and Delta FFR CT were also recorded. To explore the relationship between plaque measures and MACE (death, myocardial infarction, and unplanned hospitalization leading to revascularization) and late revascularization (&gt;90 days) we performed Kaplan Meier event free outcomes analyses following adjustments for stenosis severity, FFR CT and Delta FFR CT . Results: AI-QCPA was available in 4430 subjects. Mean (SD) TPV was 542.4 ± 522.5 mm 3 . Optimal cutpoints of plaque metrics were predictive of MACE and/or late revascularization when adjusted-TPV (HR- 1.45 CI- 1.06-1.98; P=0.02); CPV (HR- 1.65 CI- 1.21- 2.26; p=0.002); NCPV (HR 1.43 CI- 1.02-1.99; P=0.04) and LAPV (HR- 2.23 CI 1.62-3.07; P=0.03 . Stronger risk prediction was achieved by plaque measures adjusted for vessel volume: TPAV (HR 1.92 CI 1.40- 2.64 P&lt;0.001). This incremental risk discrimination of quantitative plaque measures remained significant as a predictor of MACE alone- TPV- (HR 1.84 CI 1.02- 3.29 P=0.04) TPAV (HR 3.33 CI- 1.85- 6.02 P&lt;0.0001) (Figure 1). Conclusions: In this large prospective international registry, AI-QCPA provided incremental risk discrimination for MACE and late revascularization beyond stenosis severity and FFR CT .