Effects of the Million Hearts Model on Myocardial Infarctions, Strokes, and Medicare Spending: A Randomized Clinical Trial.

Importance: The Million Hearts Model paid health care organizations to assess and reduce cardiovascular disease (CVD) risk. Model effects on long-term outcomes are unknown. Objective: To estimate model effects on first-time myocardial infarctions (MIs) and strokes and Medicare spending over a period up to 5 years. Design, Setting, and Participants: This pragmatic cluster-randomized trial ran from 2017 to 2021, with organizations assigned to a model intervention group or standard care control group. Randomized organizations included 516 US-based primary care and specialty practices, health centers, and hospital-based outpatient clinics participating voluntarily. Of these organizations, 342 entered patients into the study population, which included Medicare fee-for-service beneficiaries aged 40 to 79 years with no previous MI or stroke and with high or medium CVD risk (a 10-year predicted probability of MI or stroke [ie, CVD risk score] ≥15%) in 2017-2018. Intervention: Organizations agreed to perform guideline-concordant care, including routine CVD risk assessment and cardiovascular care management for high-risk patients. The Centers for Medicare & Medicaid Services paid organizations to calculate CVD risk scores for Medicare fee-for-service beneficiaries. CMS further rewarded organizations for reducing risk among high-risk beneficiaries (CVD risk score ≥30%). Main Outcomes and Measures: Outcomes included first-time CVD events (MIs, strokes, and transient ischemic attacks) identified in Medicare claims, combined first-time CVD events from claims and CVD deaths (coronary heart disease or cerebrovascular disease deaths) identified using the National Death Index, and Medicare Parts A and B spending for CVD events and overall. Outcomes were measured through 2021. Results: High- and medium-risk model intervention beneficiaries (n = 130 578) and standard care control beneficiaries (n = 88 286) were similar in age (median age, 72-73 y), sex (58%-59% men), race (7%-8% Black), and baseline CVD risk score (median, 24%). The probability of a first-time CVD event within 5 years was 0.3 percentage points lower for intervention beneficiaries than control beneficiaries (3.3% relative effect; adjusted hazard ratio [HR], 0.97 [90% CI, 0.93-1.00]; P = .09). The 5-year probability of combined first-time CVD events and CVD deaths was 0.4 percentage points lower in the intervention group (4.2% relative effect; HR, 0.96 [90% CI, 0.93-0.99]; P = .02). Medicare spending for CVD events was similar between the groups (effect estimate, -$1.83 per beneficiary per month [90% CI, -$3.97 to -$0.30]; P = .16), as was overall Medicare spending including model payments (effect estimate, $2.11 per beneficiary per month [90% CI, -$16.66 to $20.89]; P = .85). Conclusions and Relevance: The Million Hearts Model, which encouraged and paid for CVD risk assessment and reduction, reduced first-time MIs and strokes. Results support guidelines to use risk scores for CVD primary prevention. Trial Registration: ClinicalTrials.gov Identifier: NCT04047147.

Cost-effectiveness evaluation of risk-based breast cancer screening in Urban Hebei Province.

To evaluate the implementations of Cancer Screening Program in Urban Hebei and to model the cost-effectiveness of a risk-based breast Cancer Screening Program. Women aged 40-74 years were invited to participate the Cancer Screening Program in Urban Hebei form 2016 to 2020 by completing questionnaires to collect information about breast cancer exposure. Clinical screening including ultrasound and mammography examination were performed. We developed a Markov model to estimate the lifetime costs and benefits, in terms of quality-adjusted life years (QALY), of a high-risk breast Cancer Screening Program. Nine screening strategies and no screening were included in the study. The age-specific incidence, transition probability data and lifetime treatment costs were derived and adopted from other researches. Average cost-effectiveness ratios (ACERs) were estimated as the ratios of the additional costs of the screening strategies to the QLYG compared to no screening. Incremental cost-effectiveness ratios (ICERs) were calculated based on the comparison of a lower cost strategies to the next more expensive and effective strategies after excluding dominated strategies and extendedly dominated strategies. ICERs were used to compare with a willingness-to-pay (WTP) threshold. Sensitivity analysis was explored the influence factors. A total of 84,029 women completed a risk assessment questionnaire, from which 20,655 high-risk breast cancer females were evaluated, with a high-risk rate of 24.58%. There were 13,392 high-risk females completed the screening program, with participation rate was 64.84%. Undergoing ultrasound, mammography and combined screening, the suspicious positive detection rates were 15.00%, 9.20% and 19.30%, and the positive detection rates were 2.11%, 2.76% and 3.83%, respectively. According to the results by Markov model, at the end of 45 cycle, the early diagnosis rates were 55.53%, 60.68% and 62.47% underwent the annual screening by ultrasound, mammography and combined, the proportion of advanced cancer were 17.20%, 15.85% and 15.36%, respectively. Different screening method and interval yield varied. In the exploration of various scenarios, annual ultrasound screening is the most cost-effective strategy with the ICER of ¥116,176.15/QALY. Sensitivity analyses demonstrated that the results are robust. Although it was not cost effective, combined ultrasound and mammography screening was an effective strategy for higher positive detection rate of breast cancer. High-risk population-based breast cancer screening by ultrasound annually was the most cost-effective strategy in Urban Hebei Province.

Linkages between share pledging, stock price risk and profitability: Evidence from the P.R. China.

Share pledging has become popular as a method of loan collateral among Chinese shareholders. Our research used a sample of Chinese listed firms between 2008-2018 and produced two main findings. Firstly, we found a negative association between stock price risk and firm profitability. Our second finding was that the interaction effect of share pledging and stock price risk is greater on firm profitability than the effect of stock price risk itself. We examined the role of share pledging by modeling pooled OLS and fixed effects using share pledging behavior, controlling shareholders' share pledging and the share pledging ratio to reinforce the robustness of our results. Furthermore, we investigated the Davis Double Play effect of share pledging to analyze how share pledging affects stock price risk. We found that higher EPS and investor expectations cannot mitigate the positive impact of share pledging on stock price risk. That is, the reduction of EPS and the deterioration of investor expectations caused by share pledging risk will not further aggravate the stock price risk, as shareholders may have taken some managerial actions to affect the transmission mechanism.

Outcomes of a Presurgical Optimization Program for Elective Hernia Repairs Among High-risk Patients.

Importance: Preoperative optimization is an important clinical strategy for reducing morbidity; however, nearly 25% of persons undergoing elective abdominal hernia repairs are not optimized with respect to weight or substance use. Although the preoperative period represents a unique opportunity to motivate patient health behavior changes, fear of emergent presentation and financial concerns are often cited as clinician barriers to optimization. Objective: To evaluate the feasibility of evidence-based patient optimization before surgery by implementing a low-cost preoperative optimization clinic. Design, Setting, and Participants: This quality improvement study was conducted 1 year after a preoperative optimization clinic was implemented for high-risk patients seeking elective hernia repair. The median (range) follow-up was 197 (39-378) days. A weekly preoperative optimization clinic was implemented in 2019 at a single academic center. Referral occurred for persons seeking elective hernia repair with a body mass index greater than or equal to 40, age 75 years or older, or active tobacco use. Data analysis was performed from February to July 2020. Exposures: Enrolled patients were provided health resources and longitudinal multidisciplinary care. Main Outcomes and Measures: The primary outcomes were safety and eligibility for surgery after participating in the optimization clinic. The hypothesis was that the optimization clinic could preoperatively mitigate patient risk factors, without increasing patient risk. Safety was defined as the occurrence of complications during participation in the optimization clinic. The secondary outcome metric centered on the financial impact of implementing the preoperative optimization program. Results: Of the 165 patients enrolled in the optimization clinic, most were women (90 patients [54.5%]) and White (145 patients [87.9%]). The mean (SD) age was 59.4 (15.8) years. Patients' eligibility for the clinic was distributed across high-risk criteria: 37.0% (61 patients) for weight, 26.1% (43 patients) for tobacco use, and 23.6% (39 patients) for age. Overall, 9.1% of persons (15 patients) were successfully optimized for surgery, and tobacco cessation was achieved in 13.8% of smokers (8 patients). The rate of hernia incarceration requiring emergent surgery was 3.0% (5 patients). Economic evaluation found increased operative yield from surgical clinics, with a 58% increase in hernia-attributed relative value units without altering surgeon workflow. Conclusions and Relevance: In this quality improvement study, a hernia optimization clinic safely improved management of high-risk patients and increased operative yield for the institution. This represents an opportunity to create sustainable and scalable models that provide longitudinal care and optimize patients to improve outcomes of hernia repair.

Simplifying the ISCHEMIA trial algorithm for clinical practice: Identifying left main coronary artery disease using coronary artery calcium scans.

BACKGROUND: Several recent trials have evaluated invasive versus medical therapy for stable ischemic heart disease. Importantly, patients with significant left main coronary stenosis (LMCS) were excluded from these trials. In the ISCHEMIA trial, these patients were identified by a coronary CT angiogram (CCTA), which adds time, expense, and contrast exposure. We tested whether a coronary artery calcium scan (CACS), a simpler, less expensive test, could replace CCTA to exclude significant LMCS. METHODS: We hypothesized that patients with ≥50% LMCS would have a LM CACS score > 0. As a corollary, we postulated that a LM CACS = 0 would exclude patients with LMCS. To test this, we searched Intermountain Healthcare's electronic medical records database for all adult patients who had undergone non-contrast cardiac CT for quantitative CACS scoring prior to invasive coronary angiography (ICA). Patients aged <50 and those with a heart transplant were excluded. Cases with incomplete (qualitative) angiographic reports for LMCS and those with incomplete or discrepant LM CACS results were reviewed and reassessed blinded to CACS or ICA findings, respectively. RESULTS: Among 669 candidate patients with CACS followed by ICA, 36 qualifying patients were identified who had a quantitative CACS score and LMCS ≥ 50%. Their age averaged 71.8 years, and 81% were men. Angiographic LMCS averaged 72% (range 50%-99%). Median time between CACS and ICA was 6 days. Total CACS score averaged 2,383 Agatston Units (AU), range 571-6,636. LM CACS score averaged 197 AU, range 31-610. Importantly, no LMCS patient had a LM CACS score of 0 vs 57% (362/633) of non-LMCS controls (P < .00001). CONCLUSIONS: Our results support the hypothesis that an easily administered, inexpensive, low radiation CACS can identify a large subset of patients with a very low risk of LMCS who would not have the need for routine CCTA. Using CACS to exclude LMCS may efficiently allow for safe implementation of an initial medical therapy strategy of patients with stable ischemic heart disease in clinical practice. These promising results deserve validation in larger data sets.

Modelling the cost effectiveness of non-alcoholic fatty liver disease risk stratification strategies in the community setting.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent worldwide. Identifying high-risk patients is critical to best utilize limited health care resources. We established a community-based care pathway using 2D ultrasound shear wave elastography (SWE) to identify high risk patients with NAFLD. Our objective was to assess the cost-effectiveness of various non-invasive strategies to correctly identify high-risk patients. METHODS: A decision-analytic model was created using a payer's perspective for a hypothetical patient with NAFLD. FIB-4 [≥1.3], NAFLD fibrosis score (NFS) [≥-1.455], SWE [≥8 kPa], transient elastography (TE) [≥8 kPa], and sequential strategies with FIB-4 or NFS followed by either SWE or TE were compared to identify patients with either significant (≥F2) or advanced fibrosis (≥F3). Model inputs were obtained from local data and published literature. The cost/correct diagnosis of advanced NAFLD was obtained and univariate sensitivity analysis was performed. RESULTS: For ≥F2 fibrosis, FIB-4/SWE cost $148.75/correct diagnosis while SWE cost $276.42/correct diagnosis, identifying 84% of patients correctly. For ≥F3 fibrosis, using FIB-4/SWE correctly identified 92% of diagnoses and dominated all other strategies. The ranking of strategies was unchanged when stratified by normal or abnormal ALT. For ≥F3 fibrosis, the cost/correct diagnosis was less in the normal ALT group. CONCLUSIONS: SWE based strategies were the most cost effective for diagnosing ≥F2 fibrosis. For ≥F3 fibrosis, FIB-4 followed by SWE was the most effective and least costly strategy. Further evaluation of the timing of repeating non-invasive strategies are required to enhance the cost-effective management of NAFLD.

Accuracy Requirements for Cost-effective Suicide Risk Prediction Among Primary Care Patients in the US.

Importance: Several statistical models for predicting suicide risk have been developed, but how accurate such models must be to warrant implementation in clinical practice is not known. Objective: To identify threshold values of sensitivity, specificity, and positive predictive value that a suicide risk prediction method must attain to cost-effectively target a suicide risk reduction intervention to high-risk individuals. Design, Setting, and Participants: This economic evaluation incorporated published data on suicide epidemiology, the health care and societal costs of suicide, and the costs and efficacy of suicide risk reduction interventions into a novel decision analytic model. The model projected suicide-related health economic outcomes over a lifetime horizon among a population of US adults with a primary care physician. Data analysis was performed from September 19, 2019, to July 5, 2020. Interventions: Two possible interventions were delivered to individuals at high predicted risk: active contact and follow-up (ACF; relative risk of suicide attempt, 0.83; annual health care cost, $96) and cognitive behavioral therapy (CBT; relative risk of suicide attempt, 0.47; annual health care cost, $1088). Main Outcomes and Measures: Fatal and nonfatal suicide attempts, quality-adjusted life-years (QALYs), health care sector costs and societal costs (in 2016 US dollars), and incremental cost-effectiveness ratios (ICERs) (with ICERs ≤$150 000 per QALY designated cost-effective). Results: With a specificity of 95% and a sensitivity of 25%, primary care-based suicide risk prediction could reduce suicide death rates by 0.5 per 100 000 person-years (if used to target ACF) or 1.6 per 100 000 person-years (if used to target CBT) from a baseline of 15.3 per 100 000 person-years. To be cost-effective from a health care sector perspective at a specificity of 95%, a risk prediction method would need to have a sensitivity of 17.0% or greater (95% CI, 7.4%-37.3%) if used to target ACF and 35.7% or greater (95% CI, 23.1%-60.3%) if used to target CBT. To achieve cost-effectiveness, ACF required positive predictive values of 0.8% for predicting suicide attempt and 0.07% for predicting suicide death; CBT required values of 1.7% for suicide attempt and 0.2% for suicide death. Conclusions and Relevance: These findings suggest that with sufficient accuracy, statistical suicide risk prediction models can provide good health economic value in the US. Several existing suicide risk prediction models exceed the accuracy thresholds identified in this analysis and thus may warrant pilot implementation in US health care systems.

Early detection of lung cancer in Czech high-risk asymptomatic individuals (ELEGANCE): A study protocol.

BACKGROUND: Lung cancer screening in high-risk population increases the proportion of patients diagnosed at a resectable stage. AIMS: To optimize the selection criteria and quality indicators for lung cancer screening by low-dose CT (LDCT) in the Czech population of high-risk individuals. To compare the influence of screening on the stage of lung cancer at the time of the diagnosis with the stage distribution in an unscreened population. To estimate the impact on life-years lost according to the stage-specific cancer survival and stage distribution in the screened population. To calculate the cost-effectiveness of the screening program. METHODS: Based on the evidence from large national trials - the National Lung Screening Trial in the USA (NLST), the NELSON study, the recent recommendations of the Fleischner society, the American College of Radiology, and I-ELCAP action group, we developed a protocol for a single-arm prospective study in the Czech Republic for the screening of high-risk asymptomatic individuals. The study commenced in August 2020. RESULTS: The inclusion criteria are: age 55 to 74 years; smoking: ≥30 pack-years; smoker or ex-smoker <15 years; performance status (0-1). The screening timepoints are at baseline and 1 year. The LDCT acquisition has a target CTDIvol ≤0.5mGy and effective dose ≤0.2mSv for a standard-size patient. The interpretation of findings is primarily based on nodule volumetry, volume doubling time (and related risk of malignancy). The management includes follow-up LDCT, contrast enhanced CT, PET/CT, tissue sampling. The primary outcome is the number of cancers detected at a resectable stage, secondary outcomes include the average cost per diagnosis of lung cancer, the number, cost, complications of secondary examinations, and the number of potentially important secondary findings. CONCLUSIONS: A study protocol for early detection of lung cancer in Czech high-risk asymptomatic individuals (ELEGANCE) study using LDCT has been described.

International cost-effectiveness analysis evaluating endoscopic screening for gastric cancer for populations with low and high risk.

BACKGROUND: Gastric cancer remains one of the 3 most common causes of cancer death worldwide. Understanding the health and economic factors that affect screening cost-effectiveness in different countries will help address when and where it makes most sense to screen for gastric cancer. METHODS: We performed a cost-effectiveness analysis using a Markov model to compare screening and surveillance strategies for gastric cancer in Brazil, France, Japan, Nigeria, and the United States. Primary outcome was the incremental cost-effectiveness ratio. We then performed a sensitivity analysis to determine how each variable affected the overall model. RESULTS: In all countries, the most cost-effective strategies, measured by incremental cost-effectiveness ratio relative to no screening, were screening every 10 years, surveillance of high- and low-risk patients every 5 and 10 years, respectively, and screening every 5 years. Only Japan had at least one cost-effective screening strategy. The most important variables across different screening strategies and countries were starting age of screening, cost of endoscopy, and baseline probability of local gastric cancer at time of diagnosis. CONCLUSIONS: Our model suggests that screening for gastric cancer is cost-effective in countries with higher incidence and lower costs of screening, but screening may still be a viable option in high-risk populations within low incidence countries.

Value-based assessment of implementing a Pulmonary Embolism Response Team (PERT).

PERTs are a new, multidisciplinary approach to PE care. They were conceived to efficiently identify and risk stratify PE patients and standardize care delivery. More research needs to be conducted to assess the effects that PERTs have had on PE care. This study sought to determine the effects of a PERT on quality and overall value of care. This was a retrospective study of all patients 18 years of age or older who presented with a principal diagnosis of an acute PE based on available ICD codes from January 1, 2010 to December 31, 2018. Patients who did not have an imaging study, i.e., CTPA or ECHO, available were excluded. Patients were divided into pre- (before October 2015) and post-PERT eras (after October 2015) and stratified based on the presence of right heart strain/dysfunction on imaging. All quality outcomes were extracted from the EMR, and cost outcomes were provided by the financial department. 530 individuals (226 pre-PERT and 304 post-PERT) were identified for analysis. Quality outcomes improved between the eras; most notably in-hospital mortality decreased (16.5 vs. 9.6) and hospital LOS decreased (7.7 vs. 4.4) (p < 0.05). Total cost of care also decreased a statistically significant amount between the eras. The implementation of a PERT improved quality and cost of care, resulting in improved value. We hypothesize that this may be due to more timely identification and risk stratification leading to earlier interventions and streamlined decision making, but further research is required to validate these findings in larger cohorts.

Cost-effectiveness Analysis of Anatomic vs Functional Index Testing in Patients With Low-Risk Stable Chest Pain.

Importance: Both noninvasive anatomic and functional testing strategies are now routinely used as initial workup in patients with low-risk stable chest pain (SCP). Objective: To determine whether anatomic approaches (ie, coronary computed tomography angiography [CTA] and coronary CTA supplemented with noninvasive fractional flow reserve [FFRCT], performed in patients with 30% to 69% stenosis) are cost-effective compared with functional testing for the assessment of low-risk SCP. Design, Setting, and Participants: This cost-effectiveness analysis used an individual-based Markov microsimulation model for low-risk SCP. The model was developed using patient data from the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) trial. The model was validated by comparing model outcomes with outcomes observed in the PROMISE trial for anatomic (coronary CTA) and functional (stress testing) strategies, including diagnostic test results, referral to invasive coronary angiography (ICA), coronary revascularization, incident major adverse cardiovascular event (MACE), and costs during 60 days and 2 years. The validated model was used to determine whether anatomic approaches are cost-effective over a lifetime compared with functional testing. Exposure: Choice of index test for evaluation of low-risk SCP. Main Outcomes and Measures: Downstream ICA and coronary revascularization, MACE (death, nonfatal myocardial infarction), cost, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER) of competing strategies. Results: The model cohort included 10 003 individual patients (median [interquartile range] age, 60.0 [54.4-65.9] years; 5270 [52.7%] women; 7693 [77.4%] White individuals), who entered the model 100 times. The Markov model accurately estimated the test assignment, results of anatomic and functional index testing, referral to ICA, revascularization, MACE, and costs at 60 days and 2 years compared with observed data in PROMISE (eg, coronary CTA: ICA, 12.2% [95% CI, 10.9%-13.5%] vs 12.3% [95% CI, 12.2%-12.4%]; revascularization, 6.2% [95% CI, 5.5%-6.9%] vs 6.4% [95% CI, 6.3%-6.5%]; functional strategy: ICA, 8.1% [95% CI, 7.4%-8.9%] vs 8.2% [95% CI, 8.1%-8.3%]; revascularization, 3.2% [95% CI, 2.7%-3.7%] vs 3.3% [95% CI, 3.2%-3.4%]; 2-year MACE rates: coronary CTA, 2.1% [95% CI, 1.7%-2.5%] vs 2.3% [95% CI, 2.2%-2.4%]; functional strategy, 2.2% [95% CI, 1.8%-2.6%] vs 2.4% [95% CI, 2.3%-2.4%]). Anatomic approaches led to higher ICA and revascularization rates at 60 days, 2 years, and 5 years compared with functional testing but were more effective in patient selection for ICA (eg, 60-day revascularization-to-ICA ratio, CTA: 53.7% [95% CI, 53.3%-54.0%]; CTA with FFRCT: 59.5% [95% CI, 59.2%-59.8%]; functional testing: 40.7% [95% CI, 40.4%-50.0%]). Over a lifetime, anatomic approaches gained an additional 6 months in perfect health compared with functional testing (CTA, 25.16 [95% CI, 25.14-25.19] QALYs; CTA with FFRCT, 25.14 [95% CI, 25.12-25.17] QALYs; functional testing, 24.68 [95% CI, 24.66-24.70] QALYs). Anatomic strategies were less costly and more effective; thus, CTA with FFRCT dominated and CTA alone was cost-effective (ICERs ranged from $1912/QALY for women and $3,559/QALY for men) compared with functional testing. In probabilistic sensitivity analyses, anatomic approaches were cost-effective in more than 65% of scenarios, assuming a willingness-to-pay threshold of $100 000/QALY. Conclusions and Relevance: The results of this study suggest that anatomic strategies may present a more favorable initial diagnostic option in the evaluation of low-risk SCP compared with functional testing.

Health economic impact of a biopsy-based cell cycle gene expression assay in localized prostate cancer.

Background: Prior studies have established that broader incorporation of active surveillance, guided by additional prognostic tools, may mitigate the growing economic burden of localized prostate cancer in the USA. This study sought to further explore the potential of a particular gene expression-based prognostic tool to address this unmet need. Materials & methods: A deterministic, decision-analytic model was developed to estimate the economic impact of the Prolaris® test on a US commercial health plan. Results & conclusion: When adopted in patients classified by the American Urological Association as low or intermediate risk, the assay was projected to reduce costs by $1894 and $2129 per patient over 3 and 10 years, respectively, largely through the increased use of active surveillance.

Active testing of groups at increased risk of acquiring SARS-CoV-2 in Canada: costs and human resource needs.

BACKGROUND: Testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is largely passive, which impedes epidemic control. We defined active testing strategies for SARS-CoV-2 using reverse transcription polymerase chain reaction (RT-PCR) for groups at increased risk of acquiring SARS-CoV-2 in all Canadian provinces. METHODS: We identified 5 groups who should be prioritized for active RT-PCR testing: contacts of people who are positive for SARS-CoV-2, and 4 at-risk populations - hospital employees, community health care workers and people in long-term care facilities, essential business employees, and schoolchildren and staff. We estimated costs, human resources and laboratory capacity required to test people in each group or to perform surveillance testing in random samples. RESULTS: During July 8-17, 2020, across all provinces in Canada, an average of 41 751 RT-PCR tests were performed daily; we estimated this required 5122 personnel and cost $2.4 million per day ($67.8 million per month). Systematic contact tracing and testing would increase personnel needs 1.2-fold and monthly costs to $78.9 million. Conducted over a month, testing all hospital employees would require 1823 additional personnel, costing $29.0 million; testing all community health care workers and persons in long-term care facilities would require 11 074 additional personnel and cost $124.8 million; and testing all essential employees would cost $321.7 million, requiring 25 965 added personnel. Testing the larger population within schools over 6 weeks would require 46 368 added personnel and cost $816.0 million. Interventions addressing inefficiencies, including saliva-based sampling and pooling samples, could reduce costs by 40% and personnel by 20%. Surveillance testing in population samples other than contacts would cost 5% of the cost of a universal approach to testing at-risk populations. INTERPRETATION: Active testing of groups at increased risk of acquiring SARS-CoV-2 appears feasible and would support the safe reopening of the economy and schools more broadly. This strategy also appears affordable compared with the $169.2 billion committed by the federal government as a response to the pandemic as of June 2020.

Assessment of SARS-CoV-2 Screening Strategies to Permit the Safe Reopening of College Campuses in the United States.

Importance: The coronavirus disease 2019 (COVID-19) pandemic poses an existential threat to many US residential colleges; either they open their doors to students in September or they risk serious financial consequences. Objective: To define severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) screening performance standards that would permit the safe return of students to US residential college campuses for the fall 2020 semester. Design, Setting, and Participants: This analytic modeling study included a hypothetical cohort of 4990 students without SARS-CoV-2 infection and 10 with undetected, asymptomatic SARS-CoV-2 infection at the start of the semester. The decision and cost-effectiveness analyses were linked to a compartmental epidemic model to evaluate symptom-based screening and tests of varying frequency (ie, every 1, 2, 3, and 7 days), sensitivity (ie, 70%-99%), specificity (ie, 98%-99.7%), and cost (ie, $10/test-$50/test). Reproductive numbers (Rt) were 1.5, 2.5, and 3.5, defining 3 epidemic scenarios, with additional infections imported via exogenous shocks. The model assumed a symptomatic case fatality risk of 0.05% and a 30% probability that infection would eventually lead to observable COVID-19-defining symptoms in the cohort. Model projections were for an 80-day, abbreviated fall 2020 semester. This study adhered to US government guidance for parameterization data. Main Outcomes and Measures: Cumulative tests, infections, and costs; daily isolation dormitory census; incremental cost-effectiveness; and budget impact. Results: At the start of the semester, the hypothetical cohort of 5000 students included 4990 (99.8%) with no SARS-CoV-2 infection and 10 (0.2%) with SARS-CoV-2 infection. Assuming an Rt of 2.5 and daily screening with 70% sensitivity, a test with 98% specificity yielded 162 cumulative student infections and a mean isolation dormitory daily census of 116, with 21 students (18%) with true-positive results. Screening every 2 days resulted in 243 cumulative infections and a mean daily isolation census of 76, with 28 students (37%) with true-positive results. Screening every 7 days resulted in 1840 cumulative infections and a mean daily isolation census of 121 students, with 108 students (90%) with true-positive results. Across all scenarios, test frequency was more strongly associated with cumulative infection than test sensitivity. This model did not identify symptom-based screening alone as sufficient to contain an outbreak under any of the scenarios we considered. Cost-effectiveness analysis selected screening with a test with 70% sensitivity every 2, 1, or 7 days as the preferred strategy for an Rt of 2.5, 3.5, or 1.5, respectively, implying screening costs of $470, $910, or $120, respectively, per student per semester. Conclusions and Relevance: In this analytic modeling study, screening every 2 days using a rapid, inexpensive, and even poorly sensitive (>70%) test, coupled with strict behavioral interventions to keep Rt less than 2.5, is estimated to maintain a controllable number of COVID-19 infections and permit the safe return of students to campus.

Cost-effectiveness of consensus guideline based management of pancreatic cysts: The sensitivity and specificity required for guidelines to be cost-effective.

BACKGROUND: Detection of cystic lesions of the pancreas has outpaced our ability to stratify low-grade cystic lesions from those at greater risk for pancreatic cancer, raising a concern for overtreatment. METHODS: We developed a Markov decision model to determine the cost-effectiveness of guideline-based management for asymptomatic pancreatic cysts. Incremental costs per quality-adjusted life year gained and survival were calculated for current management guidelines. A sensitivity analysis estimated the effect on cost-effectiveness and mortality if overtreatment of low-grade cysts is avoided, and the sensitivity and specificity thresholds required of methods of cyst stratification to improve costs expended. RESULTS: "Surveillance" using current management guidelines had an incremental cost-effectiveness ratio of $171,143/quality adjusted life year compared with no surveillance or operative treatment ("do nothing"). An incremental cost-effectiveness ratio for surveillance decreases to $80,707/quality adjusted life year if the operative overtreatment of low-grade cysts was avoided. Assuming a societal willingness-to-pay of $100,000/quality adjusted life year, the diagnostic specificity for high-risk cysts must be >67% for surveillance to be preferred over surgery and "do nothing." Changes in sensitivity alone cannot make surveillance cost-effective. Most importantly, survival in surveillance is worse than "do nothing" for 3 years after cyst diagnosis, although long-term survival is improved. The disadvantage is eliminated when overtreatment of low-grade cysts is avoided. CONCLUSION: Current management of pancreatic cystic lesions is not cost-effective and may increase mortality owing to overtreatment of low-grade cysts. The specificity for risk stratification for high-risk cysts must be greater than 67% to make surveillance cost-effective.

Association of 21-Gene Assay (OncotypeDX) Testing and Receipt of Chemotherapy in the Medicare Breast Cancer Patient Population Following Initial Adoption.

BACKGROUND: Our objective was to investigate why early studies regarding adoption of the 21-gene recurrence score (RS) assay did not show an initial reduction in the number of patients with breast cancer receiving real-world chemotherapy. MATERIALS AND METHODS: We addressed 2 sources of confounding suspected in previous studies: (1) the early time frame during the initial adoption phase of the RS assay, and (2) suspected selective, increased administration to patients more likely to have been chemotherapy candidates. To address selective use during initial adoption, we used updated SEER-Medicare data from 2004 and 2011. To address individual selection bias, we examined whether RS test utilization was negatively associated with rates of local chemotherapy use assessed at the hospital referral region level using conventional ordinary least squares and instrumental variable approaches to adjust for selection bias. RESULTS: A total of 26,009 patients met inclusion criteria. Assay use was associated with a decrease in absolute percentage use of chemotherapy of 4.5% (95% confidence interval [CI], 3.2%-5.7%), which was even more pronounced in sensitivity analyses limited to later study years (2008-2011), with a decrease of 6.8% (95% CI, 5.3%-8.3%). Instrumental variable models yielded similar point estimates but were insufficiently powered to draw conclusions. CONCLUSION: Receipt of the 21-gene assay was associated with decreased utilization of chemotherapy by 2008.

Personalized surveillance for hepatocellular carcinoma in cirrhosis - using machine learning adapted to HCV status.

BACKGROUND & AIMS: Refining hepatocellular carcinoma (HCC) surveillance programs requires improved individual risk prediction. Thus, we aimed to develop algorithms based on machine learning approaches to predict the risk of HCC more accurately in patients with HCV-related cirrhosis, according to their virological status. METHODS: Patients with compensated biopsy-proven HCV-related cirrhosis from the French ANRS CO12 CirVir cohort were included in a semi-annual HCC surveillance program. Three prognostic models for HCC occurrence were built, using (i) Fine-Gray regression as a benchmark, (ii) single decision tree (DT), and (iii) random survival forest for competing risks survival (RSF). Model performance was evaluated from C-indexes validated externally in the ANRS CO22 Hepather cohort (n = 668 enrolled between 08/2012-01/2014). RESULTS: Out of 836 patients analyzed, 156 (19%) developed HCC and 434 (52%) achieved sustained virological response (SVR) (median follow-up 63 months). Fine-Gray regression models identified 6 independent predictors of HCC occurrence in patients before SVR (past excessive alcohol intake, genotype 1, elevated AFP and GGT, low platelet count and albuminemia) and 3 in patients after SVR (elevated AST, low platelet count and shorter prothrombin time). DT analysis confirmed these associations but revealed more complex interactions, yielding 8 patient groups with varying cancer risks and predictors depending on SVR achievement. On RSF analysis, the most important predictors of HCC varied by SVR status (non-SVR: platelet count, GGT, AFP and albuminemia; SVR: prothrombin time, ALT, age and platelet count). Externally validated C-indexes before/after SVR were 0.64/0.64 [Fine-Gray], 0.60/62 [DT] and 0.71/0.70 [RSF]. CONCLUSIONS: Risk factors for hepatocarcinogenesis differ according to SVR status. Machine learning algorithms can refine HCC risk assessment by revealing complex interactions between cancer predictors. Such approaches could be used to develop more cost-effective tailored surveillance programs. LAY SUMMARY: Patients with HCV-related cirrhosis must be included in liver cancer surveillance programs, which rely on ultrasound examination every 6 months. Hepatocellular carcinoma (HCC) screening is hampered by sensitivity issues, leading to late cancer diagnoses in a substantial number of patients. Refining surveillance periodicity and modality using more sophisticated imaging techniques such as MRI may only be cost-effective in patients with the highest HCC incidence. Herein, we demonstrate how machine learning algorithms (i.e. data-driven mathematical models to make predictions or decisions), can refine individualized risk prediction.

What are the benefits and harms of risk stratified screening as part of the NHS breast screening Programme? Study protocol for a multi-site non-randomised comparison of BC-predict versus usual screening (NCT04359420).

BACKGROUND: In principle, risk-stratification as a routine part of the NHS Breast Screening Programme (NHSBSP) should produce a better balance of benefits and harms. The main benefit is the offer of NICE-approved more frequent screening and/ or chemoprevention for women who are at increased risk, but are unaware of this. We have developed BC-Predict, to be offered to women when invited to NHSBSP which collects information on risk factors (self-reported information on family history and hormone-related factors via questionnaire; mammographic density; and in a sub-sample, Single Nucleotide Polymorphisms). BC-Predict produces risk feedback letters, inviting women at high risk (≥8% 10-year) or moderate risk (≥5 to < 8% 10-year) to have discussion of prevention and early detection options at Family History, Risk and Prevention Clinics. Despite the promise of systems such as BC-Predict, there are still too many uncertainties for a fully-powered definitive trial to be appropriate or ethical. The present research aims to identify these key uncertainties regarding the feasibility of integrating BC-Predict into the NHSBSP. Key objectives of the present research are to quantify important potential benefits and harms, and identify key drivers of the relative cost-effectiveness of embedding BC-Predict into NHSBSP. METHODS: A non-randomised fully counterbalanced study design will be used, to include approximately equal numbers of women offered NHSBSP (n = 18,700) and BC-Predict (n = 18,700) from selected screening sites (n = 7). In the initial 8-month time period, women eligible for NHSBSP will be offered BC-Predict in four screening sites. Three screening sites will offer women usual NHSBSP. In the following 8-months the study sites offering usual NHSBSP switch to BC-Predict and vice versa. Key potential benefits including uptake of risk consultations, chemoprevention and additional screening will be obtained for both groups. Key potential harms such as increased anxiety will be obtained via self-report questionnaires, with embedded qualitative process analysis. A decision-analytic model-based cost-effectiveness analysis will identify the key uncertainties underpinning the relative cost-effectiveness of embedding BC-Predict into NHSBSP. DISCUSSION: We will assess the feasibility of integrating BC-Predict into the NHSBSP, and identify the main uncertainties for a definitive evaluation of the clinical and cost-effectiveness of BC-Predict. TRIAL REGISTRATION: Retrospectively registered with clinicaltrials.gov (NCT04359420).