BACKGROUND: Based on the Khorana score, guidelines recommend anticoagulation for primary prophylaxis (PP) in outpatients with cancer with an intermediate-to-high risk of venous thromboembolism (VTE). ONKOTEV score has been prospectively externally validated as novel risk assessment model (RAM) with good discriminatory performances but no direct comparisons with Khorana Score are available.
METHODS: Using the ONKOTEV validation dataset (n = 425), we applied generalized decision curve analysis (gDCA) which integrates the principles of evidence-based medicine with treatment effects, model accuracy and patient preferences (weighted as the relative value [RV] of avoiding VTE versus major bleeding [MB]). The aim is to select the most optimal treatment strategy among multiple options: \"no treatment\", \"treat all patients with DOAC/LMVH\", or \"use ONKOTEV/KHORANA scores to guide PP with DOAC/LMWH\".
RESULTS: Results showed that ONKOTEV-guided PP (using DOAC or LMWH) remained the most optimal strategy for wide range assumption of treatment efficacy and patient\'s preference. For those patients, who value avoiding VTE more than MB, then offering DOAC to all patients represents the best strategy. When MBs are feared more than the morbidity of VTE, ONKOTEV-guided PP (DOAC) represents the best management strategy. In all cases, ONKOTEV outperformed Khorana for individualized VTE prevention.
CONCLUSIONS: When the two predictive models are integrated within a decision analysis framework, ONKOTEV appears superior to Khorana Score in guiding individualized prevention of cancer-related VTE in outpatients with cancer. The findings herein reported provide cutting edge insights in cancer care and support the spread of ONKOTEV score in the ambulatory cancer setting.

BACKGROUND: A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication.
OBJECTIVE: To develop and evaluate a model that could predict the risk of TRS in routine clinical practice.
METHODS: We used data from two UK-based FEP cohorts (GAP and AESOP-10) to develop and internally validate a prognostic model that supports identification of patients at high-risk of TRS soon after FEP diagnosis. Using sociodemographic and clinical predictors, a model for predicting risk of TRS was developed based on penalised logistic regression, with missing data handled using multiple imputation. Internal validation was undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model\'s performance. Interviews and focus groups with clinicians were conducted to establish clinically relevant risk thresholds and understand the acceptability and perceived utility of the model.
RESULTS: We included seven factors in the prediction model that are predominantly assessed in clinical practice in patients with FEP. The model predicted treatment resistance among the 1081 patients with reasonable accuracy; the model\'s C-statistic was 0.727 (95% CI 0.723-0.732) prior to shrinkage and 0.687 after adjustment for optimism. Calibration was good (expected/observed ratio: 0.999; calibration-in-the-large: 0.000584) after adjustment for optimism.
CONCLUSIONS: We developed and internally validated a prediction model with reasonably good predictive metrics. Clinicians, patients and carers were involved in the development process. External validation of the tool is needed followed by co-design methodology to support implementation in early intervention services.

Novel antiobesity medications, particularly glucagon-like peptide-1 receptor agonists (GLP-1RAs), have expanded weight loss (WL) options for kidney transplantation (KT) candidates with obesity beyond lifestyle modifications and bariatric surgery. However, varying effectiveness, risk profiles, and costs make strategy choices challenging. To aid decision-making, we used a Markov model to examine the cost-effectiveness of different WL strategies over a 10-year horizon. A target WL of 15% of total body weight was used for the base case scenario, and we compared these strategies to a \"liberal\" KT strategy of transplanting candidates with obesity. Outcomes included costs (2023 US dollars), quality-adjusted life years, and incremental cost-effectiveness ratios. In analysis, a liberal KT strategy was favored over lifestyle modifications and GLP-1RAs. Among WL strategies, bariatric surgery was the most effective and cost the least, whereas lifestyle modification had the highest cumulative costs and was the least effective. Compared to liberal KT, bariatric surgery costs $45 859 per quality-adjusted life year gained. GLP-1RAs were favored over bariatric surgery only when drug costs were below $5000 per year (base cost $12 077). In conclusion, for KT candidates with obesity, a liberal KT strategy and bariatric surgery are preferred over lifestyle modifications alone and GLP-1RAs based on outcomes and cost-effectiveness.

UNASSIGNED: Treatment strategies for a symptomatic accessory navicular include both operative and nonoperative approaches. The primary aim of this study is to define health utility values for 7 health states experienced by those with a symptomatic accessory navicular who undergo operative and/or nonoperative treatment. Secondarily, the study incorporates the health utility values with treatment costs, probabilities of various outcomes, and duration of health states into a cost-effectiveness model comparing the nonoperative treatment protocol at our institution vs surgical excision.
UNASSIGNED: Institutional review board approval was obtained to call parents of patients 10-20 years old at the time of interview who were evaluated for a symptomatic accessory navicular from February 1, 2016, to March 2, 2023, at a single institution by one of 4 pediatric orthopaedic surgeons. Participants were asked to rate 7 health states from 0 to 100, with 0 representing death (if 18 years or older) or the worst health imaginable (if under 18 years) and 100 representing perfect health. Using published values for the probabilities of various treatment outcomes, time spent in various health states, and Medicare costs from the perspective of the payor and society, a decision analysis was constructed.
UNASSIGNED: Health utility values for 7 health states were obtained. Operative treatment was preferred to nonoperative treatment in the base case model. Surgery was more expensive ($16 825) than nonoperative treatment ($7486). Using a willingness-to-pay threshold of <$50 000 per quality-adjusted life year (QALY), surgery was cost-effective compared to nonoperative treatment with an incremental cost-effectiveness ratio of $20 303/QALY. Sensitivity analysis revealed that the only variable that indicated a preference for nonoperative treatment is a 71% likelihood of nonoperative treatment resolving the condition.
UNASSIGNED: Unless a physician suspects at least a 71% chance of a symptomatic accessory navicular resolving without operative treatment, surgical excision is recommended from a cost-effectiveness perspective.

Confronting the continuing risk of an attack, security systems have adopted target-hardening strategies through the allocation of security measures. Most previous work on defensive resource allocation considers the security system as a monolithic architecture. However, systems such as schools are typically characterized by multiple layers, where each layer is interconnected to help prevent single points of failure. In this paper, we study the defensive resource allocation problem in a multilayered system. We develop two new resource allocation models accounting for probabilistic and strategic risks, and provide analytical solutions and illustrative examples. We use real data for school shootings to illustrate the performance of the models, where the optimal investment strategies and sensitivity analysis are presented. We show that the defender would invest more in defending outer layers over inner layers in the face of probabilistic risks. While countering strategic risks, the defender would split resources in each layer to make the attacker feel indifferent between any individual layer. This paper provides new insights on resource allocation in layered systems to better enhance the overall security of the system.

BACKGROUND: Travel-related strategies to reduce the spread of COVID-19 evolved rapidly in response to changes in the understanding of SARS-CoV-2 and newly available tools for prevention, diagnosis, and treatment. Modeling is an important methodology to investigate the range of outcomes that could occur from different disease containment strategies.
METHODS: We examined 43 articles published from December 2019 through September 2022 that used modeling to evaluate travel-related COVID-19 containment strategies. We extracted and synthesized data regarding study objectives, methods, outcomes, populations, settings, strategies, and costs. We used a standardized approach to evaluate each analysis according to 26 criteria for modeling quality and rigor.
RESULTS: The most frequent approaches included compartmental modeling to examine quarantine, isolation, or testing. Early in the pandemic, the goal was to prevent travel-related COVID-19 cases with a focus on individual-level outcomes and assessing strategies such as travel restrictions, quarantine without testing, social distancing, and on-arrival PCR testing. After the development of diagnostic tests and vaccines, modeling studies projected population-level outcomes and investigated these tools to limit COVID-19 spread. Very few published studies included rapid antigen screening strategies, costs, explicit model calibration, or critical evaluation of the modeling approaches.
CONCLUSIONS: Future modeling analyses should leverage open-source data, improve the transparency of modeling methods, incorporate newly available prevention, diagnostics, and treatments, and include costs and cost-effectiveness so that modeling analyses can be informative to address future SARS-CoV-2 variants of concern and other emerging infectious diseases (e.g., mpox and Ebola) for travel-related health policies.

Internal quality control in clinical chemistry laboratories are based on analyzing samples of stable control materials among the patient samples. The control results are interpreted by using quality control rules that usually are designed to detect systematic errors. The best rules have a high probability of error detection (Ped), i.e. to detect the maximal allowable (critical) systematic error and a low probability of false rejection (Pfr, false alarm). In this work we show that quality control rules can be represented by points on a ROC curve which appears when Ped is plotted against Pfr and only the control limit is varied. Further, we introduce a new method for choosing the optimal control limit, analogous to choosing the optimal operating point on the ROC curve of a diagnostic test. This decision needs knowledge of the pretest probability of a critical systematic error, the benefit of detecting it when it occurs and the cost of false alarm. The ROC curve analysis showed that if rules based on N = 2 are used, mean rules outperform Westgard rules because the ROC curve of the mean rules was lying above the ROC curves of the Westgard rules. A mean rule also had a lower maximum expected increase in the number of unacceptable patient results reported during the presence of an out-of-control error condition (Max E(NUF)) than comparable Westgard rules.

Contemporary wildlife disease management is complex because managers need to respond to a wide range of stakeholders, multiple uncertainties, and difficult trade-offs that characterize the interconnected challenges of today. Despite general acknowledgment of these complexities, managing wildlife disease tends to be framed as a scientific problem, in which the major challenge is lack of knowledge. The complex and multifactorial process of decision-making is collapsed into a scientific endeavor to reduce uncertainty. As a result, contemporary decision-making may be oversimplified, rely on simple heuristics, and fail to account for the broader legal, social, and economic context in which the decisions are made. Concurrently, scientific research on wildlife disease may be distant from this decision context, resulting in information that may not be directly relevant to the pertinent management questions. We propose reframing wildlife disease management challenges as decision problems and addressing them with decision analytical tools to divide the complex problems into more cognitively manageable elements. In particular, structured decision-making has the potential to improve the quality, rigor, and transparency of decisions about wildlife disease in a variety of systems. Examples of management of severe acute respiratory syndrome coronavirus 2, white-nose syndrome, avian influenza, and chytridiomycosis illustrate the most common impediments to decision-making, including competing objectives, risks, prediction uncertainty, and limited resources.
Replanteamiento del manejo de problemas por enfermedades de fauna mediante el análisis de decisiones Resumen El manejo actual de las enfermedades de la fauna es complejo debido a que los gestores necesitan responder a una amplia gama de actores, varias incertidumbres y compensaciones difíciles que caracterizan los retos interconectados del día de hoy. A pesar de que en general se reconocen estas complejidades, el manejo de las enfermedades tiende a plantearse como un problema científico en el que el principal obstáculo es la falta de conocimiento. El proceso complejo y multifactorial de la toma decisiones está colapsado dentro de un esfuerzo científico para reducir la incertidumbre. Como resultado de esto, las decisiones contemporáneas pueden estar simplificadas en exceso, depender de métodos heurísticos simples y no considerar el contexto legal, social y económico más amplio en el que se toman las decisiones. De manera paralela, las investigaciones científicas sobre las enfermedades de la fauna pueden estar lejos de este contexto de decisiones, lo que deriva en información que puede no ser directamente relevante para las preguntas pertinentes de manejo. Proponemos replantear los obstáculos para el manejo de enfermedades de fauna como problemas de decisión y abordarlos con herramientas analíticas de decisión para dividir los problemas complejos en elementos más manejables de manera cognitiva. En particular, las decisiones estructuradas tienen el potencial de mejorar la calidad, el rigor y la transparencia de las decisiones sobre las enfermedades de la fauna en una variedad de sistemas. Ejemplos como el manejo del coronavirus del síndrome de respiración agudo tipo 2, el síndrome de nariz blanca, la influenza aviar y la quitridiomicosis ilustran los impedimentos más comunes para la toma de decisiones, incluyendo los objetivos en competencia, riesgos, incertidumbre en las predicciones y recursos limitados.
【摘要】 野生动物疾病管理者需应对多方利益相关者、多种不确定性和艰难的利弊权衡, 这导致当代野生动物疾病管理问题十分复杂, 面临相互关联的挑战。尽管人们普遍承认这些复杂性, 但野生动物疾病管理往往被视为一个科学问题, 其主要挑战为知识缺乏。而复杂且多因素的决策过程被简化为减少不确定性的科学工作。这导致当前的决策可能被过于简化, 依赖于简单的启发式方法, 而没有考虑到决策所面临的更广泛的法律、社会和经济背景。同时, 关于野生动物疾病的科学研究可能与决策背景相去甚远, 并产出与管理问题并不直接相关的信息。我们建议将野生动物疾病管理方面的挑战重新定义为决策问题, 并利用决策分析工具来解决这些问题, 从而将复杂的问题划分为更易于认知和管理的要素。结构化决策还有潜力在各种系统中提高野生动物疾病决策的质量、严谨性和透明度。管理严重急性呼吸系统综合征冠状病毒2(SARS‐CoV‐2)、白鼻综合征、禽流感和壶菌病的案例进一步说明了决策过程中最常见的障碍, 包括目标相互竞争、风险、预测的不确定性和资源有限等。【翻译:胡怡思;审校:聂永刚】.

OBJECTIVE: In 2019, a BMJ Rapid Recommendation advised against colorectal cancer (CRC) screening for adults with a predicted 15-year CRC risk below 3%. Using Switzerland as a case study, we estimated the population-level impact of this recommendation.
METHODS: We predicted the CRC risk of all respondents to the population-based Swiss Health Survey. We derived the distribution of risk-based screening start age, assuming predicted risk was calculated every 5 years between ages 25 and 70 and screening started when this risk exceeded 3%. Next, the MISCAN-Colon microsimulation model evaluated biennial faecal immunochemical test (FIT) screening with this risk-based start age. As a comparison, we simulated screening initiation based on age and sex.
RESULTS: Starting screening only when predicted risk exceeded 3% meant 82% of women and 90% of men would not start screening before age 65 and 60, respectively. This would require 43%-57% fewer tests, result in 8%-16% fewer CRC deaths prevented and yield 19%-33% fewer lifeyears gained compared with screening from age 50. Screening women from age 65 and men from age 60 had a similar impact as screening only when predicted risk exceeded 3%.
CONCLUSIONS: With the recommended risk prediction tool, the population impact of the BMJ Rapid Recommendation would be similar to screening initiation based on age and sex only. It would delay screening initiation by 10-15 years. Although halving the screening burdens, screening benefits would be reduced substantially compared with screening initiation at age 50. This suggests that the 3% risk threshold to start CRC screening might be too high.

OBJECTIVE: Chemoradiation followed by esophagectomy is a standard treatment option for patients with locally advanced esophageal cancer (LAEC). Esophagectomy is a high-risk procedure, and recent evidence suggests select patients may benefit from omitting or delaying surgery. This study aims to compare surgery versus active surveillance for LAEC patients with complete clinical response (cCR) after neoadjuvant chemoradiotherapy (nCRT).
METHODS: Decision analysis with Markov modeling was used. The base case was a 60-year-old man with T3N0M0 esophageal cancer with cCR after nCRT. The decision was modeled for a 5-year time horizon. Primary outcomes were life-years and quality-adjusted life-years (QALY). Probabilities and utilities were derived through the literature. Deterministic sensitivity analyses were performed using ranges from the literature with consideration for clinical plausibility.
RESULTS: Surgery was favored for survival with an expected life-years of 2.89 versus 2.64. After incorporating quality of life, active surveillance was favored, with an expected QALY of 1.70 versus 1.56. The model was sensitive to probability of recurrence on active surveillance (threshold value 0.598), probability of recurrence being resectable (0.318), and disutility of previous esophagectomy (-0.091). The model was not sensitive to perioperative morbidity and mortality.
CONCLUSIONS: Our study finds that surgery increases life expectancy but decreases QALY. Although the incremental change in QALY for either modality is insufficient to make broad clinical recommendations, our study demonstrates that either approach is acceptable. As probabilities of key factors are further defined in the literature, treatment decisions for patients with LAEC and a cCR after nCRT should consider histology, patient values, and quality of life.