Risk-based Selection Research Articles

Six-year performance of risk-based selection for lung cancer screening in the Manchester Lung Health Check cohort

ObjectiveRisk prediction models are used to determine eligibility for targeted lung cancer screening. However, prospective data regarding model performance in this setting are limited. Here we report the performance of...

CP1-2 Questionnaire on compliance with Febrile Neutropenia (FN) Guidelines 2nd ed. and risk-based patient selection for outpatient treatment in the 3rd ed.

CP1-2 Questionnaire on compliance with Febrile Neutropenia (FN) Guidelines 2nd ed. and risk-based patient selection for outpatient treatment in the 3rd ed.

The effects of a risk-based approach to tax examinations: evidence from a tax pilot programme in Tanzania

AbstractTechnical assistance and increased use of ICT in tax administrations hold promise for greater revenue collection. Yet, the evidence on how these activities work in the real-world circumstances of developing countries is scant. The paper attempts to fill this gap by evaluating an intervention undertaken jointly by the Finnish and Tanzanian revenue administrations. The programme introduced a new risk-based case selection method for enhancing the effectiveness of firm tax examinations in Tanzania complemented by supplementary staff training and developing management practices. Our results, stemming from a difference-in-differences analysis and administrative data from the Tanzanian Revenue Authority, indicate that the intervention increased the corrected amount of taxable income by approximately 20% during the first year of the new approach.

Evaluation of a reflection-based program for health professional continuing competence

IntroductionHealth professional regulators have a mandate to ensure ongoing competence of their regulated members (registrants). Programs for monitoring and assessing continuing competence are one means of assuring the public of the quality of professional services. More regulators are adopting programs for continuing competence that require registrants to demonstrate reflective practice and practice improvement. More research on the effectiveness of reflection-based programs for continuing competence is needed. This study describes the evaluation of a reflection-based continuing competence program used by a regulator in Alberta, Canada.MethodsSubmission of a Continuing Competence Learning Plan (CCLP) is a requirement for practice permit renewal each year. CCLP submissions were randomly selected over a two-year period and rated according to a rubric. CCLP submission ratings and quality and quantity of content were compared. CCLP submission ratings were also compared to demographic and practice profile variables to identify significant relationships that could be used for risk-based selection of CCLP submissions in the future.ResultsMost registrants selected for review completed acceptable CCLP submissions that included reflective content. There was a relationship between CCLP submission rating and the gender identity of participants. There was no relationship between CCLP submission rating and participants' age, years since graduation, practice area, role or setting, client age range, or geographic location of primary employer.ConclusionsThe absence of statistically significant relationships between demographic and practice profile variables, other than gender identity, suggests that the other factors identified in the literature as risks to competence and professional conduct, are not necessarily risk factors for how registrants complete their CCLP submissions. Further comparison of CCLP submission ratings to other workplace and personal factors is required to identify those that may be useful for risk-based selection for CCLP submission review.

OA07.05 Pre-Recruitment as a Strategy to Address “Near-Miss” Cases in Risk-Based Lung Cancer Screening Selection: An Analysis of ILST Data

OA07.05 Pre-Recruitment as a Strategy to Address “Near-Miss” Cases in Risk-Based Lung Cancer Screening Selection: An Analysis of ILST Data

Intuitionistic Fuzzy Sets with Ordered Pairs and Their Usage in Multi-Attribute Decision Making: A Novel Intuitionistic Fuzzy TOPSIS Method with Ordered Pairs

Intuitionistic Fuzzy Sets with Ordered Pairs (IFSOP) are the recent extension of intuitionistic fuzzy sets by incorporating functional and dysfunctional points of view into the definition of membership functions. This paper extends the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) method to the Intuitionistic Fuzzy TOPSIS (IF TOPSIS) with ordered pairs method and applies it to a multi-criteria risk-based supplier selection problem under fuzziness. IF TOPSIS with ordered pairs involves finding a positive ideal solution and a negative ideal solution, and measuring the distance between each alternative and these solutions. The final ranking of the alternatives is obtained based on the proportion of distances between the positive and negative ideal solutions. By asking functional and dysfunctional questions in this ranking process, the developed IF TOPSIS with ordered pairs method incorporates the accuracy and consistency of expert judgments, enhancing the decision-making process. A sensitivity analysis is also presented in order to show the robustness of the rankings obtained by IF TOPSIS with ordered pairs.

Towards a Risk-Based Continuous Auditing-Based Certification for Machine Learning

Machine learning systems have gained widespread adoption across various industries. This includes highly regulated ones that need to match certain quality requirements based on a given risk exposure. The MLOps paradigm, following a similar approach to DevOps, promises major improvements in quality and speed, with a focus on deploying ML models at a fast pace with high quality on an automated basis. However, traditional point-in-time certifications with manual audits are inadequate for MLOps setups due to frequent changes to the ML system. To overcome this challenge, we propose Continuous Audit-Based Certification (CABC), which uses automated audits to issue or revoke certificates based on an automated assessment of artifacts from the MLOps lifecycle. Our approach utilizes artifacts from the MLOps lifecycle for quality measurements based on standards such as ISO 25012. We propose a risk-based measurement selection, an audit API for standardized retrieval of data for measurement, a tamper-proof data collection process, and an architecture for separation of duties in the certification process. CABC aims to improve efficiency, enhance trust in the ML system, and support highly regulated industries in achieving their quality goals.

Frequency of Iron Deficiency in Heart Failure Patients

Background: People suffering from heart failure frequently face iron deficiency, which has been linked to higher mortality and more frequent hospital stays. People with symptomatic systolic heart failure and iron deficiency, iron supplementation significantly decreased the risk of hospitalization for heart failure and the combined endpoint of hospitalization for heart failure and mortality, Aim: This research sought to determine the prevalence of iron insufficiency in people with chronic heart failure. Design of the study: This study is cross-sectional. Place of the study: Ayub Teaching Hospital Abbottabad from November 2019 to April 2020. Methodology: After obtaining written informed permission, the research participants who met the inclusion criteria were chosen. Patients between the ages of 40 and 70, of either gender, were included in the research group if they had a documented history of CHF for less than six months and an echocardiogram showed an LVEF of less than 45%. Results: Mean age of the patients was 55.79±9.926, ranging from 40 to 70 years and the mean BMI was 29.03±5.043 ranging from 19 to 49kg/m2, mean serum ferritin level was 226.03±160.297 ranging from 70 to 500μg/L and mean transferrin saturation was 23.15±6.449 ranging from 15 to 38%. In the frequency of heart failure, patients of heart failure were 72(48%) and 78(52%) had no HF. In the frequency of iron deficiency, patients found with a deficiency were 82(54.7%) and 68(45.3%) had no deficiency. Practical Implication: Patients with heart failure should have routine iron deficiency screenings regardless of the presence of anaemia or abnormal RCI. In order to improve risk-based selection of participants who are frequently not at risk for iron deficiency Conclusion: Men with functional classes II–III were more likely to have iron deficiency anaemia (72% prevalence). Hypertension was the most prevalent comorbidity. Keywords: Iron deficiency, Heart failure, Anemia

Delaying anti-VEGF therapy during the COVID-19 pandemic: long-term impact on visual outcomes in patients with neovascular age-related macular degeneration

ObjectivesTo evaluate the outcomes of delayed intravitreal injections (IVIs) caused by the outbreak of coronavirus disease 2019 (COVID-19), in patients with neovascular age-related macular degeneration (nAMD).MethodsnAMD patients with scheduled IVIs between March 1st and April 30th, 2020 were stratified through a risk-based selection into a non-adherent group (NA-group) if they skipped at least one IVI and an adherent group (A-group) if they followed their treatment schedule. During the pandemic visit (v0), if a significant worsening of the disease was detected, a rescue therapy of three-monthly IVIs was performed. Multimodal imaging and best-corrected visual acuity (BCVA) findings were evaluated after 6 months (v6), compared between groups and with the visit prior the lockdown (v−1).ResultsTwo hundred fifteen patients (132 females, mean age: 81.89 ± 5.98 years) delayed their scheduled IVI while 83 (53 females, mean age: 77.92 ± 6.06 years) adhered to their protocol. For both groups, BCVA at v0 was significantly worse than v−1 (mean 4.15 ± 7.24 ETDRS letters reduction for the NA-group and 3 ± 7.96 for the A-group) but remained stable at v6. The two groups did not significantly differ in BCVA trends after 6 months and neither for development of atrophy nor fibrosis.ConclusionsA risk-based selection strategy and a rescue therapy may limit the long-term outcomes of an interruption of the treatment protocol in patients with nAMD.

Comparison of the sensitivity of different criteria to select lung cancer patients for screening in a cohort of German patients.

Trials of CT-based screening for lung cancer have shown a mortality advantage for screening in North America and Europe. Before introducing a nationwide lung cancer screening program in Germany, it is important to assess the criteria used in international trials in the German population. We used data from 3623 lung cancer patients from the data warehouse of the German Center for Lung Research (DZL). We compared the sensitivity of the following lung cancer screening criteria overall and stratified by age and histology: the National Lung Screening Trial (NLST), the Danish Lung Cancer Screening Trial (DLCST), the 2013 and 2021 US Preventive Services Task Force (USPSTF), and an adapted version of the Prostate, Lung, Colorectal, and Ovarian no race model (adapted PLCOm2012) with 6-year risk thresholds of 1.0%/6 year and 1.7%/6 year. Overall, the adapted PLCOm2012 model (1%/6 years), selected the highest proportion of lung cancer patients for screening (72.4%), followed by the 2021 USPSTF (70.0%), the adapted PLCOm2012 (1.7%/6 year) (57.4%), the 2013 USPTF (57.0%), DLCST criteria (48.7%), and the NLST (48.5%). The adapted PLCOm2012 risk model (1.0%/6 year) had the highest sensitivity for all histological types except for small-cell and large-cell carcinomas (non-significant), whereas the 2021 USPTF selected a higher proportion of patients. The sensitivity levels were higher in males than in females. Using a risk-based selection score resulted in higher sensitivities compared to criteria using dichotomized age and smoking history. However, gender disparities were apparent in all studied eligibility criteria. In light of increasing lung cancer incidences in women, all selection criteria should be reviewed for ways to close this gender gap, especially when implementing a large-scale lung cancer screening program.

Risk-Based Portfolio Modeling: Kahneman-Tversky Approach

The risk-based portfolio selection problem with investors’ behavioral risk aversion bias under uncertainty is monitored. The main results of this research are developed heuristic approaches for the prospect theory model proposed by Kahneman and Tversky in 1979 as well as an empirical numerical analysis of this model with real data. The main purpose is to impose behavioral features of prospect theory to minimize the risk with a certain level of income to the portfolio selection problem. In this research, the real data of TSE is employed for computational results with regard to the prospect theory model with several stocks as risky assets. In order to investigate empirically the performance of the behaviourally based model, different portfolios are selected with different operating sectors. The aggressive behavior in terms of returns of the prospect theory model with the specific risk has the same output as returns. On the other hand, the certain level of returns as constrained shows minimized risk with the implementation of a behavioral approach in comparison to the conventional approach which is the Markowitz model. The performance of the two behavioral and traditional models are compared and lower risks are obtained by a behavioral approach which shows the optimal portfolio selection and might be used by investors as their investment strategy.

In silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in silico Algorithm Infrastructure and a Vision for Future Enhancements.

The in silico prediction of T cell epitopes within any peptide or biologic drug candidate serves as an important first step for assessing immunogenicity. T cell epitopes bind human leukocyte antigen (HLA) by a well-characterized interaction of amino acid side chains and pockets in the HLA molecule binding groove. Immunoinformatics tools, such as the EpiMatrix algorithm, have been developed to screen natural amino acid sequences for peptides that will bind HLA. In addition to commonly occurring in synthetic peptide impurities, unnatural amino acids (UAA) are also often incorporated into novel peptide therapeutics to improve properties of the drug product. To date, the HLA binding properties of peptides containing UAA are not accurately estimated by most algorithms. Both scenarios warrant the need for enhanced predictive tools. The authors developed an in silico method for modeling the impact of a given UAA on a peptide's likelihood of binding to HLA and, by extension, its immunogenic potential. In silico assessment of immunogenic potential allows for risk-based selection of best candidate peptides in further confirmatory in vitro, ex vivo and in vivo assays, thereby reducing the overall cost of immunogenicity evaluation. Examples demonstrating in silico immunogenicity prediction for product impurities that are commonly found in formulations of the generic peptides teriparatide and semaglutide are provided. Next, this article discusses how HLA binding studies can be used to estimate the binding potentials of commonly encountered UAA and "correct" in silico estimates of binding based on their naturally occurring counterparts. As demonstrated here, these in vitro binding studies are usually performed with known ligands which have been modified to contain UAA in HLA anchor positions. An example using D-amino acids in relative binding position 1 (P1) of the PADRE peptide is presented. As more HLA binding data become available, new predictive models allowing for the direct estimation of HLA binding for peptides containing UAA can be established.

Antifungal use via outpatient parenteral antimicrobial therapy.

Antifungal administration via outpatient parenteral antimicrobial therapy (OPAT) is infrequent. As patients with invasive fungal infections (IFIs) receiving OPAT are at high risk of readmissions, careful, risk-based patient selection and monitoring is important. To describe our experience managing IFIs via OPAT, including assessment of risk factors associated with unplanned readmissions. A retrospective cohort study of outpatients from two tertiary hospitals in Western Australia managed with parenteral antifungals for the treatment of IFIs from 2012 to 2020. Outcomes assessed were unplanned OPAT-related readmissions; adverse events and achievement of treatment aim at the completion of OPAT. Forty-six patients were included, encompassing 696 OPAT days. Twenty-three (50%) patients received intravenous (IV) liposomal amphotericin B (L-AmB), 23 (50%) received IV echinocandins and one (2%) patient received IV fluconazole. One patient received both IV L-AmB and an echinocandin. Unplanned OPAT-related readmissions occurred in 13 (28%) patients and any adverse event occurred in 19 (41%), most commonly nephrotoxicity amongst patients receiving L-AmB. On univariate analysis, unplanned OPAT-related readmissions were more common in Mucorales infection, L-AmB doses of ≥5mg/kg and otorhinolaryngologic (ENT) infections. At the completion of OPAT, attainment of treatment aims occurred in 28 (61%) patients. Patients receiving parenteral antifungals via OPAT experience high rates of unplanned readmissions and adverse events. Risk factor identification may facilitate optimal patient selection and establishment of treatment aims.

Risk-Based Selection of Inspection Method for External Post-Tensioning System of Bridges

The increasing complexity associated with the maintenance of bridges with post-tensioning tendons, along with growing public awareness to ensure higher levels of safety in bridges, has put additional pressure on the designers and the owners to find innovative solutions to ensure safe as well as economically viable solutions. Risk-based inspection and maintenance helps in finding such solutions and, thus, it is gaining more importance in the field of infrastructure management. Within the framework of current risk-based inspection methodologies, it is normally assumed that the method by which the inspection is performed is known beforehand. However, the selection of the inspection method by itself should be given importance and viewed as the first key step for any inspection. The lack of quantitative data in the initiation step makes this selection uncertain and the decision making rather subjective. Despite recent release of comprehensive reports and other publications on condition assessment of bridges with post-tensioning systems, a quantitative approach and a decision-making framework for the selection of the inspection method and associated protocol are still missing, and the inspection strategy and methods are determined purely by the experience of the inspector or the owner. In this paper, a simple and structured risk-based selection methodology is presented that can bridge the existing knowledge gap. The proposed methodology uses a statistical approach to quantify the likelihood of the inspection error utilizing a variety of applicable NDE (Non-destructive Evaluation) methods. To give the methodology both accuracy and practicality, the specifications for the national bridge inventory (SNBI) condition rating was incorporated in this methodology and the accuracy of the inspection methods are measured against determining the correct SNBI condition. Application and effectiveness of the proposed methodology are demonstrated using a case study inspection conducted earlier by the authors. The results, in this case, converged to the selection of one of the NDE methods, which consequently was accepted by the bridge stakeholders.

Impact and benefit-cost ratio of a program for the management of latent tuberculosis infection among refugees in a region of Canada.

The identification and treatment of latent tuberculosis infection (LTBI) among immigrants from high-incidence regions who move to low-incidence countries is generally considered an ineffective strategy because only ≈14% of them comply with the multiple steps of the 'cascade of care' and complete treatment. In the Estrie region of Canada, a refugee clinic was opened in 2009. One of its goals is LTBI management. Key components of this intervention included: close collaboration with community organizations, integration within a comprehensive package of medical care for the whole family, timely delivery following arrival, shorter treatment through preferential use of rifampin, and risk-based selection of patients to be treated. Between 2009-2020, 5131 refugees were evaluated. To determine the efficacy and benefit-cost ratio of this intervention, records of refugees seen in 2010-14 (n = 1906) and 2018-19 (n = 1638) were reviewed. Cases of tuberculosis (TB) among our foreign-born population occurring before (1997-2008) and after (2009-2020) setting up the clinic were identified. All costs associated with TB or LTBI were measured. Out of 441 patients offered LTBI treatment, 374 (85%) were compliant. Adding other losses, overall compliance was 69%. To prevent one case of TB, 95.1 individuals had to be screened and 11.9 treated, at a cost of $16,056. After discounting, each case of TB averted represented $32,631, for a benefit-cost ratio of 2.03. Among nationals of the 20 countries where refugees came from, incidence of TB decreased from 68.2 (1997-2008) to 26.3 per 100,000 person-years (2009-2020). Incidence among foreign-born persons from all other countries not targeted by the intervention did not change. Among refugees settling in our region, 69% completed the LTBI cascade of care, leading to a 61% reduction in TB incidence. This intervention was cost-beneficial. Current defeatism towards LTBI management among immigrants and refugees is misguided. Compliance can be enhanced through simple measures.

Advances in lung cancer screening and early detection.

Lung cancer is associated with a heavy cancer-related burden in terms of patients’ physical and mental health worldwide. Two randomized controlled trials, the US-National Lung Screening Trial (NLST) and Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON), indicated that low-dose CT (LDCT) screening results in a statistically significant decrease in mortality in patients with lung cancer, LDCT has become the standard approach for lung cancer screening. However, many issues in lung cancer screening remain unresolved, such as the screening criteria, high false-positive rate, and radiation exposure. This review first summarizes recent studies on lung cancer screening from the US, Europe, and Asia, and discusses risk-based selection for screening and the related issues. Second, an overview of novel techniques for the differential diagnosis of pulmonary nodules, including artificial intelligence and molecular biomarker-based screening, is presented. Third, current explorations of strategies for suspected malignancy are summarized. Overall, this review aims to help clinicians understand recent progress in lung cancer screening and alleviate the burden of lung cancer.

Risk-based maintenance strategy selection for wind turbine composite blades

Blades are one of the most important components, in terms of capital and operational costs, of wind turbines. In contrast with some other elements of the turbine, the knowledge regarding the failure modes and processes of the composite materials that form the blade are less known. Therefore, providing a systematic study breaking down the individual components of the blade and analysing the criticality of each of the failure modes affecting them is the first step toward the implementation of measures reducing operational and maintenance costs. The scarce information that is publicly available regarding wind turbine blade failures and their constant evolution inclines risk analysis toward studies based on expert opinion. In this study, the criticality of the failure modes is determined through a failure mode and effects analysis (FMEA) that examines the severity and likelihood of occurrence of the failure modes identified. In light of the results of criticality, the current and potential maintenance strategies covering the different failure modes will be identified, along with the applicable monitoring techniques found in the literature, to propose risk mitigation strategies. The results of this study may be utilized for further exploration of operation and maintenance analysis toward the development of dynamic decision support systems.

XBRL Open Information Model for Risk Based Tax Audit using Machine Learning

Tax audit is an effective instrument for preserving tax compliance, and risk-based tax audit selection can optimize it. Risk-based tax audit selection selectively auditing on high financial risk wealthy taxpayers. In contrast, manually selecting amid the plethora of taxpayer data is difficult, prone to human error, costly and time-consuming. Fortunately, using Extensible Business Report Language (XBRL) as a well-known financial statement reporting standard enables automation. This project proposed software named XAFR as a model for extracting, transforming, and loading the latest XBRL Open Information Model (OIM) 1.0 standard US-SEC dataset and provided it as a data source for risk classification using rule-based risk scoring and Machine Learning. Several thorough testing exposed Random Forest classifier as the best model for Machine Learning risk classification with high accuracy, revealing the excellent collaboration of rule-based risk scoring approach with Machine Learning for risk classification and the importance of XBRL as a transparent but robust report standard that tax authorities can utilize. The excellent system integration resulted in the ability to expose wealthy high-risk taxpayers and high-risk industries and predict risk classification based on two-year financial statements. Moreover, this report introduces the critical importance of RCA (Risk, Current Ratio, Assets) analysis and SIC (Standard Industry Classification) utilization to generate risk classification, rank and explanation. This project utilizes financial indicators in the limited year and leaves the semantic analysis for future works because of time and hardware limitations. The possibility of predicting the possible tax debt prediction are promising Machine Learning future developments

Risk-stratified selection to colonoscopy in FIT colorectal cancer screening: development and temporal validation of a prediction model.

Faecal immunochemical tests (FITs) yield many false positives and challenge colonoscopy capacity in colorectal cancer (CRC) screening programmes. We aimed to develop a risk-based selection of participants to undergo diagnostic colonoscopy. The study was observational and used registry data from the Danish CRC screening programme. We included all participants invited 2014-2016 with a positive FIT (≥ 20 μg fHb/g) who underwent colonoscopy (n = 56,459). We predicted the risk of CRC or advanced neoplasia (AN) from age, gender and FIT value using logistic regression. We evaluated calibration and discrimination and conducted temporal validation. We compared the number of CRCs and adenomas identified by risk cut-offs and by a corresponding FIT cut-off. AUCs were 74.9% (95% CI: 73.6; 76.3) and 67.4% (95% CI: 66.8%; 68.0%) for the models predicting CRC and AN in the validation dataset. The cut-off of CRC risk calculated from age, gender and FIT value identified 1.03 times (95% CI: 1.02; 1.05) more CRCs and 1.01 times (95% CI: 1.01; 1.01) more medium/high-risk adenomas compared with the corresponding FIT cut-off. With existing data, risk-stratified FIT screening using a risk cut-off instead of a FIT cut-off can slightly improve the selection to colonoscopy of those at highest risk of cancer and adenomas.

Improving Antibiotic Stewardship in Acute Appendicitis through Risk-Based Empiric Treatment Selection.

Background: Empiric antimicrobial treatment selection for management of appendicitis is based on patient risk of infection with drug-resistant pathogens. Per Surgical Infection Society (SIS) guidelines, only high-risk patients should receive extended spectrum antibiotics. After observing substantial use of piperacillin-tazobactam at an academic medical center, a quality improvement initiative was developed targeting standardization of antibiotics for uncomplicated appendicitis. Patients and Methods: A project was performed to improve antibiotic stewardship in acute appendicitis treatment using plan-do-study-act methodology. We designed educational materials to guide risk-based empiric antimicrobial treatment selection for adult patients presenting with appendicitis. Implementation began January 1, 2020. High-risk criteria included presence of sepsis, presence of one or more comorbidities, and health-care-associated appendicitis. Retrospective chart review included adult patients admitted for appendectomy between January 1, 2019 and December 1, 2020. Pre-/post-implementation analysis and run chart analysis were performed. Primary outcome was the proportion of patients receiving the correct antibiotic. Secondary outcomes included antibiotic cost. Patients treated pre-/post-implementation were compared using univariable analysis, with statistical significance set at p < 0.05. Results: Of the 138 patients, 85 patients were in the pre-implementation group and 53 in the implementation group. The implementation group was 19.1% more likely to receive the correct antibiotic (pre = 31.8%; post = 50.9%; p = 0.03). Average cost per patient was reduced $13.25 (pre = $23.68 ± $18.76; post = $10.43 ± $8.45; p ≤ 0.0001). There were no differences in complications (pre = 2.4%; post = 0%; p = 0.26) or re-admissions (pre = 2.34%; post = 1.9%; p = 0.86). Conclusions: After an educational initiative to raise awareness about SIS guidelines for empiric antibiotic treatment for acute appendicitis, we observed an increase in the number of patients receiving the appropriate antibiotic. Prescribing habits were altered with no adverse impact on clinical outcomes. The next phase will address sustainability by incorporating an electronic medical record order set to integrate just-in-time education within the provider workflow.