Assessing the generalisability of the psychosis metabolic risk calculator (PsyMetRiC) for young people with first-episode psychosis with validation in a Hong Kong Chinese Han population: a 4-year follow-up study.

Background: Metabolic syndrome (MetS) is common following first-episode psychosis (FEP), contributing to substantial morbidity and mortality. The Psychosis Metabolic Risk Calculator (PsyMetRiC), a risk prediction algorithm for MetS following a FEP diagnosis, was developed in the United Kingdom and has been validated in other European populations. However, the predictive accuracy of PsyMetRiC in Chinese populations is unknown. Methods: FEP patients aged 15-35 y, first presented to the Early Assessment Service for Young People with Early Psychosis (EASY) Programme in Hong Kong (HK) between 2012 and 2021 were included. A binary MetS outcome was determined based on the latest available follow-up clinical information between 1 and 12 years after baseline assessment. The PsyMetRiC Full and Partial algorithms were assessed for discrimination, calibration and clinical utility in the HK sample, and logistic calibration was conducted to account for population differences. Sensitivity analysis was performed in patients aged >35 years and using Chinese MetS criteria. Findings: The main analysis included 416 FEP patients (mean age = 23.8 y, male sex = 40.4%, 22.4% MetS prevalence at follow-up). PsyMetRiC showed adequate discriminative performance (full-model C = 0.76, 95% C.I. = 0.69-0.81; partial-model: C = 0.73, 95% C.I. = 0.65-0.8). Systematic risk underestimation in both models was corrected using logistic calibration to refine PsyMetRiC for HK Chinese FEP population (PsyMetRiC-HK). PsyMetRiC-HK provided a greater net benefit than competing strategies. Results remained robust with a Chinese MetS definition, but worse for the older age group. Interpretation: With good predictive performance for incident MetS, PsyMetRiC-HK presents a step forward for personalized preventative strategies of cardiometabolic morbidity and mortality in young Hong Kong Chinese FEP patients. Funding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Understanding decision curve analysis in clinical prediction model research.

BACKGROUND: Many medical graduate students lack a thorough understanding of decision curve analysis (DCA), a valuable tool in clinical research for evaluating diagnostic models. METHODS: This article elucidates the concept and process of DCA through the lens of clinical research practices, exemplified by its application in diagnosing liver cancer using serum alpha-fetoprotein levels and radiomics indices. It covers the calculation of probability thresholds, computation of net benefits for each threshold, construction of decision curves, and comparison of decision curves from different models to identify the one offering the highest net benefit. RESULTS: The paper provides a detailed explanation of DCA, including the creation and comparison of decision curves, and discusses the relationship and differences between decision curves and receiver operating characteristic curves. It highlights the superiority of decision curves in supporting clinical decision-making processes. CONCLUSION: By clarifying the concept of DCA and highlighting its benefits in clinical decisionmaking, this article has improved researchers' comprehension of how DCA is applied and interpreted, thereby enhancing the quality of research in the medical field.

Aspirin for Primary Prevention in Patients With Elevated Coronary Artery Calcium Score: A Systematic Review of Current Evidences.

The 2019 American College of Cardiology and American Heart Association guidelines regarding low-dose aspirin in the primary prevention of atherosclerotic cardiovascular disease (ASCVD) indicate an increased risk of bleeding without a net benefit. The coronary artery calcium (CAC) score could be used to guide aspirin therapy in high-risk patients without an increased risk of bleeding. With this systematic review, we aimed to analyze studies that have investigated the role of CAC in primary prevention with aspirin. A total of 4 relevant studies were identified and the primary outcomes of interest were bleeding events and major adverse cardiac events. The outcomes of interest were stratified into 3 groups based on CAC scoring: 0, 1 to 99, and ≥100. A study concluded from 2,191 patients that with a low bleeding risk, CAC ≥100, and ASCVD risk ≥5% aspirin confers a net benefit, whereas patients with a high bleeding risk would experience a net harm, irrespective of ASCVD risk or CAC. All other studies demonstrated net benefit in patients with CAC ≥100 with a clear benefit. CAC scores correspond to calcified plaque in coronary vessels and are associated with graded increase in adverse cardiovascular events. Our review has found that in the absence of a significant bleeding risk, increased ASCVD risk and CAC score corelate with increased benefit from aspirin. A study demonstrated a decrease in the odds of myocardial infarction from 3 to 0.56 in patients on aspirin. The major drawback of aspirin for primary prevention is the bleeding complication. At present, there is no widely validated tool to predict the bleeding risk with aspirin, which creates difficulties in accurately delineating risk. Barring some discrepancy between studies, evidence shows a net harm for the use of aspirin in low ASCVD risk (<5%), irrespective of CAC score.

Evaluating the clinical utility of an easily applicable prediction model of suicide attempts, newly developed and validated with a general community sample of adults.

BACKGROUND: A suicide attempt (SA) is a clinically serious action. Researchers have argued that reducing long-term SA risk may be possible, provided that at-risk individuals are identified and receive adequate treatment. Algorithms may accurately identify at-risk individuals. However, the clinical utility of algorithmically estimated long-term SA risk has never been the predominant focus of any study. METHODS: The data of this report stem from CoLaus|PsyCoLaus, a prospective longitudinal study of general community adults from Lausanne, Switzerland. Participants (N = 4,097; Mage = 54 years, range: 36-86; 54% female) were assessed up to four times, starting in 2003, approximately every 4-5 years. Long-term individual SA risk was prospectively predicted, using logistic regression. This algorithm's clinical utility was assessed by net benefit (NB). Clinical utility expresses a tool's benefit after having taken this tool's potential harm into account. Net benefit is obtained, first, by weighing the false positives, e.g., 400 individuals, at the risk threshold, e.g., 1%, using its odds (odds of 1% yields 1/(100-1) = 1/99), then by subtracting the result (400*1/99 = 4.04) from the true positives, e.g., 5 individuals (5-4.04), and by dividing the result (0.96) by the sample size, e.g., 800 (0.96/800). All results are based on 100 internal cross-validations. The predictors used in this study were: lifetime SA, any lifetime mental disorder, sex, and age. RESULTS: SA at any of the three follow-up study assessments was reported by 1.2%. For a range of seven a priori selected threshold probabilities, ranging between 0.5% and 2%, logistic regression showed highest overall NB in 97.4% of all 700 internal cross-validations (100 for each selected threshold probability). CONCLUSION: Despite the strong class imbalance of the outcome (98.8% no, 1.2% yes) and only four predictors, clinical utility was observed. That is, using the logistic regression model for clinical decision making provided the most true positives, without an increase of false positives, compared to all competing decision strategies. Clinical utility is one among several important prerequisites of implementing an algorithm in routine practice, and may possibly guide a clinicians' treatment decision making to reduce long-term individual SA risk. The novel metric NB may become a standard performance measure, because the a priori invested clinical considerations enable clinicians to interpret the results directly.

Aligning opportunity cost and net benefit criteria: the health shadow price.

Given constrained healthcare budgets and many competing demands, public health decision-making requires comparing the expected cost and health outcomes of alternative strategies and associated adoption and financing actions. Opportunity cost (comparing outcomes from the best alternative use of budgets or actions in decision making) and more recently net benefit criteria (relative valuing of effects at a threshold value less costs) have been key concepts and metrics applied toward making such decisions. In an ideal world, opportunity cost and net benefit criteria should be mutually supportive and consistent. However, that requires a threshold value to align net benefit with opportunity cost assessment. This perspective piece shows that using the health shadow price as the ICER threshold aligns net benefit and opportunity cost criteria for joint adoption and financing actions that arise when reimbursing any new strategy or technology under a constrained budget. For an investment strategy with ICER at the health shadow price Bc = 1/(1/n + 1/d-1/m), net benefit of reimbursing (adopting and financing) that strategy given an incremental cost-effectiveness ration (ICER) of actual displacement, d, in financing, is shown to be equivalent to that of the best alternative actions, the most cost-effective expansion of existing programs (ICER = n) funded by the contraction of the least cost-effective programs (ICER = m). Net benefit is correspondingly positive or negative if it is below or above this threshold. Implications are discussed for creating pathways to optimal public health decision-making with appropriate incentives for efficient displacement as well as for adoption actions and related research.

Commentary: Value of information case study strongly supports use of the Threshold of Toxicological Concern (TTC).

A Value of Information (VOI) analysis can play a key role in decision-making for adopting new approach methodologies (NAMs). We applied EPA's recently developed VOI framework to the Threshold of Toxicological Concern (TTC). Obtaining/deriving a TTC value for use as a toxicity reference value (TRV) for substances with limited toxicity data was shown to provide equivalent or greater health protection, immense return on investment (ROI), greater net benefit, and substantially lower costs of delay (CoD) compared with TRVs derived from either traditional human health assessment (THHA) chronic toxicity testing in lab animals or the 5-day in vivo EPA Transcriptomic Assessment Product (ETAP). For all nine exposure scenarios examined, the TTC was more economical terms of CoD and ROI than the ETAP or the THHA; expected net benefit was similar for the TTC and ETAP with both of these more economical than the THHA The TTC ROI was immensely greater (5,000,000-fold on average) than the ROI for THHA and the ETAP ROI (100,000-fold on average). These results support the use of the TTC for substances within its domain of applicability to waive requiring certain in vivo tests, or at a minimum, as an initial screening step before conducting either the ETAP or THHA in vivo studies.

A Tutorial on Net Benefit Regression for Real-World Cost-Effectiveness Analysis Using Censored Data from Randomized or Observational Studies.

HIGHLIGHTS: We illustrate the steps involved in carrying out cost-effectiveness analysis using net benefit regressions with possibly censored demo data by providing step-by-step guidance and code applied to a data set.We demonstrate the importance of these new methods by illustrating how naïve methods for handling censoring can lead to biased cost-effectiveness results.

Weighted thyroid-stimulating hormone disturbance in prognosis of hepatitis B virus-related acute-on-chronic liver failure.

AIM: To weight the prognostic value of thyroid hormones in catastrophic acute-on-chronic liver failure (ACLF). METHODS: A retrospective cohort (n = 635) and two prospective cohorts (n = 353, and 198) were enrolled in this study. The performance of a novel developed prognostic score was assessed from aspects of reliability, discrimination, and clinical net benefit. RESULTS: Thyroid-stimulating hormone (TSH) was identified to have the most potential as a prognostic predictor for hepatitis B virus-related ACLF among thyroid hormones. The novel score (modified chronic liver failure-organ failure score [mCLIF-OFs]) was developed with weighted TSH and other scored organs in the CLIF-OFs using the retrospective cohort (n = 635). The predicted risk and observed probabilities of death were comparable across the deciles of mCLIF-OFs (Hosmer-Lemeshow χ2  = 4.28, p = 0.83; Brier scaled = 11.9). The C-index of mCLIF-OFs (0.885 [0.883-0.887]) for 30-day mortality was significantly higher than that of the CLIF-OFs, chronic liver failure-sequential organ failure assessment score (CLIF-SOFAs), CLIF-C ACLFs, Model of End-stage Liver Disease (MELD), and Child-Pugh (all p < 0.001). The absolute improvements of prediction error rates of the mCLIF-OFs compared to the above five scores were from 19.0% to 61.1%. After the analysis of probability density function, the mCLIF-OFs showed the least overlapping coefficients (27.9%) among the above prognostic scores. Additionally, the mCLIF-OFs showed greater net benefit than the above five prognostic scores over a wide range of risk threshold of death. Similar results were validated in two prospective ACLF cohorts with HBV and non-HBV etiologies. CONCLUSION: Weighted TSH portended the outcome of ACLF patients, which could be treated as a "damaged organ" of the hypothalamic-pituitary-thyroid axis. The novel mCLIF-OFs is a reliable prognostic score with better discrimination power and clinical net benefit than CLIF-OFs, CLIF-SOFAs, CLIF-C ACLFs, MELD, and Child-Pugh.

Generalized pairwise comparisons of prioritized outcomes are a powerful and patient-centric analysis of multi-domain scores.

BACKGROUND: Generalized pairwise comparisons (GPC) can be used to assess the net benefit of new treatments for rare diseases. We show the potential of GPC through simulations based on data from a natural history study in mucopolysaccharidosis type IIIA (MPS IIIA). METHODS: Using data from a historical series of untreated children with MPS IIIA aged 2 to 9 years at the time of enrolment and followed for 2 years, we performed simulations to assess the operating characteristics of GPC to detect potential (simulated) treatment effects on a multi-domain symptom assessment. Two approaches were used for GPC: one in which the various domains were prioritized, the other with all domains weighted equally. The net benefit was used as a measure of treatment effect. We used increasing thresholds of clinical relevance to reflect the magnitude of the desired treatment effects, relative to the standard deviation of the measurements in each domain. RESULTS: GPC were shown to have adequate statistical power (80% or more), even with small sample sizes, to detect treatment effects considered to be clinically worthwhile on a symptom assessment covering five domains (expressive language, daily living skills, and gross-motor, sleep and pain). The prioritized approach generally led to higher power as compared with the non-prioritized approach. CONCLUSIONS: GPC of prioritized outcomes is a statistically powerful as well as a patient-centric approach for the analysis of multi-domain scores in MPS IIIA and could be applied to other heterogeneous rare diseases.

The first external validation of the Dallas steatosis index in biopsy-proven Non-alcoholic fatty liver Disease: A multicenter study.

AIMS: A new non-invasive tool (NIT) for non-alcoholic fatty liver disease (NAFLD) proposed in 2022 by the multi-ethnic Dallas Heart Study, i.e. the Dallas Steatosis Index (DSI), was validated herein using for the first time the gold standard i.e. liver biopsy-proven NAFLD. METHODS: This is a multicenter study based on samples and data from two Gastroenterology-Hepatology Clinics (Greece and Australia) and one Bariatric-Metabolic Surgery Clinic (Italy). Overall, n = 455 patients with biopsy-proven NAFLD (n = 374) and biopsy-proven controls (n = 81) were recruited. RESULTS: The ability of DSI to correctly classify participants as NAFLD or controls was very good, reaching an Area Under the Curve (AUC) = 0.887. The cut-off point that could best differentiate the presence vs. absence of NAFLD corresponded to DSI = 0.0 (risk threshold: 50% | Sensitivity: 0.88; Positive Predictive Value (PPV): 93.0%; F1-score = 0.91). DSI demonstrated significantly better performance characteristics than other liver steatosis indexes. Decision curve analysis revealed that the benefit of DSI as a marker to indicate the need for invasive liver assessment was confirmed only when higher DSI values, i.e. ≥ 1.4, were used as risk thresholds. DSI performance to differentiate disease progression was inadequate (all AUCs < 0.700). CONCLUSIONS: DSI is more useful for disease screening (NAFLD vs. controls) than to differentiate diseases stages or progression. The value of any inclusion of DSI to guidelines needs to be further studied.

Moderators of the cost-effectiveness of transdiagnostic CBT for anxiety disorders over an 8-month time horizon using a net-benefit regression framework.

BACKGROUND: Access to evidence-based psychological treatment is a concern in many parts of the globe due to government-level financial constraints and patient-level barriers. Transdiagnostic cognitive behavioural therapy (tCBT) is an effective treatment approach that uses a single protocol for anxiety disorders which could enhance the dissemination of evidence-based psychotherapy. In a context of limited resources, the study of treatment moderators can allow to identify subgroups for which the cost-effectiveness of an intervention differs, information that could impact decision-making. So far, there has been no economic evaluation of tCBT for different subpopulations. The objectives of this study, using the net-benefit regression framework, were to explore clinical and sociodemographic factors as potential moderators of the cost-effectiveness of tCBT compared to treatment-as-usual (TAU). METHODS: This is a secondary data analysis of a pragmatic randomized controlled trial opposing tCBT added to TAU (n = 117) to TAU only (n = 114). Data on costs from the health system and the limited societal perspectives, as well as anxiety-free days, an effectiveness measure based on the Beck Anxiety Inventory, were collected over an 8-month time horizon and used to derive individual net-benefits. The net-benefit regression framework was used to assess moderators of the cost-effectiveness of tCBT + TAU as opposed to TAU alone. Variables of sociodemographic and clinical nature were assessed. RESULTS: Results showed that the number of comorbid anxiety disorders significantly moderated the cost-effectiveness of tCBT + TAU compared to TAU from the limited societal perspective. CONCLUSIONS: The number of comorbid anxiety disorders was identified as a moderator affecting the cost-effectiveness of tCBT + TAU compared to TAU from the limited societal perspective. More research is needed to strengthen the case of tCBT from an economic standpoint for large-scale dissemination. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02811458, 23/06/2016.

Impact of Magnetic Resonance Imaging Targeting on Pathologic Upgrading and Downgrading at Prostatectomy: A Systematic Review and Meta-analysis.

CONTEXT: The evidence supporting multiparametric magnetic resonance imaging (MRI) targeting for biopsy is nearly exclusively based on biopsy pathologic outcomes. This is problematic, as targeting likely allows preferential identification of small high-grade areas of questionable oncologic significance, raising the likelihood of overdiagnosis and overtreatment. OBJECTIVE: To estimate the impact of MRI-targeted, systematic, and combined biopsies on radical prostatectomy (RP) grade group concordance. EVIDENCE ACQUISITION: PubMed MEDLINE and Cochrane Library were searched from July 2018 to January 2022. Studies that conducted systematic and MRI-targeted prostate biopsies and compared biopsy results with pathology after RP were included. We performed a meta-analysis to assess whether pathologic upgrading and downgrading were influenced by biopsy type and a net-benefit analysis using pooled risk difference estimates. EVIDENCE SYNTHESIS: Both targeted only and combined biopsies were less likely to result in upgrading (odds ratio [OR] vs systematic of 0.70, 95% confidence interval [CI] 0.63-0.77, p < 0.001, and 0.50, 95% CI 0.45-0.55, p < 0.001), respectively). Targeted only and combined biopsies increased the odds of downgrading (1.24 (95% CI 1.05-1.46), p = 0.012, and 1.96 (95% CI 1.68-2.27, p < 0.001) compared with systematic biopsies, respectively. The net benefit of targeted and combined biopsies is 8 and 7 per 100 if harms of up- and downgrading are considered equal, but 7 and -1 per 100 if the harm of downgrading is considered twice that of upgrading. CONCLUSIONS: The addition of MRI-targeting results in lower rates of upgrading as compared to systematic biopsy at RP (27% vs 42%). However, combined MRI-targeted and systematic biopsies are associated with more downgrading at RP (19% v 11% for combined vs systematic). Strong heterogeneity suggests further research into factors that influence the rates of up- and downgrading and that distinguishes clinically relevant from irrelevant grade changes is needed. Until then, the benefits and harms of combined MRI-targeted and systematic biopsies cannot be fully assessed. PATIENT SUMMARY: We reviewed the ability of magnetic resonance imaging (MRI)-targeted biopsies to predict cancer grade at prostatectomy. We found that combined MRI-targeted and systematic biopsies result in more cancers being downgraded than systematic biopsies.

Exposure-based treatments for childhood abuse-related post-traumatic stress disorder in adults: a health-economic evaluation.

Background: Prolonged exposure (PE) is an effective treatment for post-traumatic stress disorder (PTSD).Objective: This study aimed to analyse the cost-effectiveness of three exposure-based treatments in patients with childhood abuse-related PTSD.Method: A net-benefit analysis was conducted alongside a pragmatic randomized controlled trial with participants (N = 149) randomized to three conditions: PE (n = 48), intensified PE (i-PE, n = 51), and phase-based PE [Skills Training in Affective and Interpersonal Regulation (STAIR) + PE, n = 50]. Assessments took place at baseline (T0), post-treatment (T3), 6 month follow-up (T4), and 12 month follow-up (T5). Costs stemming from healthcare utilization and productivity losses were estimated using the Trimbos/iMTA questionnaire for Costs associated with Psychiatric Illness. Quality-adjusted life-years (QALYs) were based on the 5-level EuroQoL 5 Dimensions (EQ-5D-5L) using the Dutch tariff. Missing values of costs and utilities were multiply imputed. To compare i-PE to PE and STAIR + PE to PE, pair-wise unequal-variance t-tests were conducted. Net-benefit analysis was used to relate costs to QALYs and to draw acceptability curves.Results: Intervention costs did not differ across the three treatment conditions. Total medical costs, productivity losses, total societal costs, and EQ-5D-5L-based QALYs did not differ between treatment conditions either (all p > .10). At the relevant €50,000/QALY threshold, the probability of one treatment being more cost-effective than another was 32%, 28%, and 40% for PE, i-PE, and STAIR-PE, respectively.Conclusion: Three equally effective treatments were compared and no differences in cost-effectiveness between treatments were found. Therefore, we advocate the implementation and adoption of any of the treatments and endorse shared decision making.

This is the first study to compare cost-effectiveness of three exposure-based treatments in patients with CA-PTSD alongside a randomized controlled clinical trial (N = 149).The three exposure-based treatments did not differ in terms of outcomes and costs.Findings underline that any of these treatments can be implemented, and we endorse shared decision making to meet patient treatment preference.

Incremental net monetary benefit of biologic therapies in moderate to severe asthma: a systematic review and meta-analysis of economic evaluation studies.

OBJECTIVES: This meta-analysis was conducted to quantitatively pool the incremental net benefit (INB) of using biologic therapies as an add-on treatment to standard therapy in patients with moderate to severe asthma. METHODS: We performed a comprehensive search in several databases published until April 2022. Studies were included if they were cost-effectiveness analyses reporting cost per quality-adjusted life-year or life-year on any biologic therapies as an add-on treatment for moderate to severe asthma in patients of all ages. Various monetary units were converted to purchasing power parity, adjusted to 2021 US dollars. The INBs were pooled across studies using a random-effects model, stratified by country income level (high-income countries (HICs) and low- and middle-income countries (LMICs)) and perspectives (health care or payer perspective (HCPP) and societal perspective (SP)) and age group (>12 years and 6-11 years). Heterogeneity was assessed using the I2 statistic. RESULTS: A total of 32 comparisons from 25 studies were included. Pooled INB indicated that the use of omalizumab as an add-on treatment to standard therapy in those aged >12 years was not cost-effective in HICs from the HCPP (n = 8, INB, -6,341 (95% CI, -$25,000 to $12,210), I2=86.18%) and SP (n = 5, -$14,000 (-$170,000 to $140,000), I2=75.64%). A similar finding was observed in those aged 6-11 years from the HCPP in LMICs (n = 2, -$45,000 (-$73,000 to $17,000), I2=00.00%). Subgroup analyses provided no explanations of the potential sources of heterogeneity. CONCLUSION: The use of biologic therapies in moderate to severe asthma is not cost-effective compared to standard treatment alone.

Assessing the net benefit of machine learning models in the presence of resource constraints.

OBJECTIVE: The objective of this study is to provide a method to calculate model performance measures in the presence of resource constraints, with a focus on net benefit (NB). MATERIALS AND METHODS: To quantify a model's clinical utility, the Equator Network's TRIPOD guidelines recommend the calculation of the NB, which reflects whether the benefits conferred by intervening on true positives outweigh the harms conferred by intervening on false positives. We refer to the NB achievable in the presence of resource constraints as the realized net benefit (RNB), and provide formulae for calculating the RNB. RESULTS: Using 4 case studies, we demonstrate the degree to which an absolute constraint (eg, only 3 available intensive care unit [ICU] beds) diminishes the RNB of a hypothetical ICU admission model. We show how the introduction of a relative constraint (eg, surgical beds that can be converted to ICU beds for very high-risk patients) allows us to recoup some of the RNB but with a higher penalty for false positives. DISCUSSION: RNB can be calculated in silico before the model's output is used to guide care. Accounting for the constraint changes the optimal strategy for ICU bed allocation. CONCLUSIONS: This study provides a method to account for resource constraints when planning model-based interventions, either to avoid implementations where constraints are expected to play a larger role or to design more creative solutions (eg, converted ICU beds) to overcome absolute constraints when possible.

The stratified win statistics (win ratio, win odds, and net benefit).

The win odds and the net benefit are related directly to each other and indirectly, through ties, to the win ratio. These three win statistics test the same null hypothesis of equal win probabilities between two groups. They provide similar p-values and powers, because the Z-values of their statistical tests are approximately equal. Thus, they can complement one another to show the strength of a treatment effect. In this article, we show that the estimated variances of the win statistics are also directly related regardless of ties or indirectly related through ties. Since its introduction in 2018, the stratified win ratio has been applied in designs and analyses of clinical trials, including Phase III and Phase IV studies. This article generalizes the stratified method to the win odds and the net benefit. As a result, the relations of the three win statistics and the approximate equivalence of their statistical tests also hold for the stratified win statistics.

Cost effectiveness of ultrasound-guided long peripheral catheters in difficult vascular access patients.

OBJECTIVE: Peripheral intravenous catheter (PIVC) placement is a routinely performed invasive procedure in hospital settings with an unacceptably high failure rate that can result in significant costs. This investigation aimed to determine the cost-effectiveness of using long peripheral catheters (LPC) versus standard short peripheral catheters (SPC) in the difficult vascular access (DVA) population. METHODS: A secondary analysis was performed of a randomized control trial that compared a 20-gauge 4.78 cm SPC to a 20-gauge 6.35 cm SPC for the endpoint of survival. This study assessed cost-effectiveness of the comparative interventions. Costs associated with increased hospitalization length of stay due to PIVC failure, including labor, materials, equipment, and treatment delays were estimated by utilizing healthcare resource utilization data. Cost-effectiveness of the LPC was analyzed through the incremental cost-effectiveness ratio, the cost-effectiveness acceptability curve, and the incremental net benefit. A sensitivity analysis was conducted to evaluate the robustness of the results during the time interval of PIVC insertion. RESULTS: Among the 257 patients, the average total cost for therapy was lower in the LPC group compared to the SPC group ($400 vs $521; mean difference -$121, 95% bootstrapped CI -$461 to $225). A marginally significant absolute difference of complication averted was found for LPC versus SPC (10.8%, p = 0.07). The estimated incremental cost-effectiveness ratio (ICER) for LPC as compared with SPC was -$1123 (95% bootstrapped CI -$8652 to $5964) per complication averted. In a willingness to pay (WTP) analysis, as WTP = $0, the incremental net benefit (INB) $121 was positive, indicating LPC was less costly. Analysis of PIVCs that survived ⩽48 h (n = 134) demonstrated a lower average total cost for therapy among the LPC group ($418 vs $531; mean difference -$113, 95% bootstrapped CI -$507 to $282). Forty-seven of 66 (71.2%) LPCs did not experience a complication, compared with 37 of 68 (54.4%) SPCs, resulting in a significant absolute difference of complication adverted of 16.8% (p = 0.04). In addition, with a positive slope, the INB $113 was positive as WTP = $0, indicating LPC was estimated to be cost-effective. CONCLUSIONS: When using ultrasound guidance for vascular access, LPCs are potentially a cost-effective strategy for reducing PIVC complications in DVA patients compared to SPCs. Given this finding, ultrasound-guided LPCs should be routinely considered as first-line among the DVA population in order to improve their overall care and wellbeing.

Clinical utility gains from incorporating comorbidity and geographic location information into risk estimation equations for atherosclerotic cardiovascular disease.

OBJECTIVE: There are over 363 customized risk models of the American College of Cardiology and the American Heart Association (ACC/AHA) pooled cohort equations (PCE) in the literature, but their gains in clinical utility are rarely evaluated. We build new risk models for patients with specific comorbidities and geographic locations and evaluate whether performance improvements translate to gains in clinical utility. MATERIALS AND METHODS: We retrain a baseline PCE using the ACC/AHA PCE variables and revise it to incorporate subject-level information of geographic location and 2 comorbidity conditions. We apply fixed effects, random effects, and extreme gradient boosting (XGB) models to handle the correlation and heterogeneity induced by locations. Models are trained using 2 464 522 claims records from Optum©'s Clinformatics® Data Mart and validated in the hold-out set (N = 1 056 224). We evaluate models' performance overall and across subgroups defined by the presence or absence of chronic kidney disease (CKD) or rheumatoid arthritis (RA) and geographic locations. We evaluate models' expected utility using net benefit and models' statistical properties using several discrimination and calibration metrics. RESULTS: The revised fixed effects and XGB models yielded improved discrimination, compared to baseline PCE, overall and in all comorbidity subgroups. XGB improved calibration for the subgroups with CKD or RA. However, the gains in net benefit are negligible, especially under low exchange rates. CONCLUSIONS: Common approaches to revising risk calculators incorporating extra information or applying flexible models may enhance statistical performance; however, such improvement does not necessarily translate to higher clinical utility. Thus, we recommend future works to quantify the consequences of using risk calculators to guide clinical decisions.

Effect of some agricultural treatments on the Egyptian alfalfa weevil, Hypera brunneipennis and their economic evaluation on yield and yield components in Egypt.

BACKGROUND: The Egyptian alfalfa weevil, Hypera brunneipennis causes damage on different parts of alfalfa plants. Therefore, four agricultural treatments are carried out included calcium super phosphate addition (15.5% P2 O5 ), potassium sulphate addition (50% K2 O), microelements spraying and hand removing of weeds to reduce the population of the Egyptian alfalfa weevil and increase both the final yield and obtain a healthy plant. RESULTS: The treatment of calcium super phosphate (15.5% P2 O5 ), potassium sulphate (50% K2 O), microelements spraying and hand removing of weeds gave less infestation of Egyptian alfalfa weevil [4.38 and 4.89 (larvae and adults/m2 )] and the highest total fresh (70.08 and 74.52 ton/feddan), dry yield (19.37 and 19.70 ton/feddan) and plant height yield (60.00 and 61. 17 cm) in first and second seasons, respectively, with significant differences compared with the other treatments and the untreated check. Also, the same treatment gave the highest net benefit over untreated check 29.06 and 31.93 (thousand L.E./feddan) and net benefit/costs ratio/feddan (1.77 and 2.22) in first and second seasons, respectively. CONCLUSIONS: Good agricultural treatments of calcium super phosphate addition (15.5% P2 O5 ), potassium sulphate addition (50% K2 O), microelements spraying and hand removing of weeds play an important role in obtaining a healthy plant, reducing Egyptian alfalfa weevil infestation, and increasing total fresh yield, total dry yield, and plant height of alfalfa. © 2023 Society of Chemical Industry.

Impact of correlations between prioritized outcomes on the net benefit and its estimate by generalized pairwise comparisons.

Benefit-risk balance is gaining interest in clinical trials. For the comprehensive assessment of benefits and risks, generalized pairwise comparisons are increasingly used to estimate the net benefit based on multiple prioritized outcomes. Although previous research has demonstrated that the correlations between the outcomes impact the net benefit and its estimate, the direction and magnitude of this impact remain unclear. In this study, we investigated the impact of correlations between two binary or Gaussian variables on the true net benefit values via theoretical and numerical analyses. We also explored the impact of correlations between survival and categorical variables on the net benefit estimates based on four existing methods (Gehan, Péron, Gehan with correction, and Péron with correction) in the presence of right censoring via simulation and application to actual oncology clinical trial data. Our theoretical and numerical analyses revealed that the true net benefit values were impacted by the correlations in various directions depending on the outcome distributions. With binary endpoints, this direction was governed by a simple rule with a threshold of 50% for a favorable outcome. Our simulation showed that the net benefit estimates based on Gehan's or Péron's scoring rule could be substantially biased in the presence of right censoring, and that the direction and magnitude of this bias were associated with the outcome correlations. The recently proposed correction method greatly reduced this bias, even in the presence of strong outcome correlations. The impact of correlations should be carefully considered when interpreting the net benefit and its estimate.