Efficacy and Safety of Ocriplasmin Use for Vitreomacular Adhesion and Its Predictive Factors: A Systematic Review and Meta-Analysis

Symptomatic vitreomacular adhesion (sVMA) impedes visual acuity and quality. Ocriplasmin is a recombinant protease, which may be injected into the vitreous cavity to treat this condition, yet controversy remains with respect to its effectiveness and safety, particularly its patient selection standard. In this systematic review, the PubMed, Embase, and the Cochrane Library were searched to identify studies published prior to August 2020 on the impact of ocriplasmin treatment on VMA release, macular hole (MH) closure, and/or related adverse events (AEs). Data were pooled using a random-effects model. Risk ratios (RRs) with 95% CIs were calculated. Of 1,186 articles reviewed, 5 randomized controlled trials and 50 cohort studies were ultimately included, representing 4,159 patients. Ocriplasmin significantly increased the rate of VMA release (RR, 3.61; 95% CI, 1.99–6.53; 28 days after treatment) and MH closure (RR, 3.84; 95% CI, 1.62–9.08; 28 days after treatment) and was associated with visual function improvement. No increased risk for overall AEs was seen in ocriplasmin treatment. The proportion of VMA release and MH closure in patients was 0.50 and 0.36, respectively. VMA release was more likely in patients with absence of epiretinal membrane (ERM). Patients with smaller MH diameter were more likely to achieve MH closure. Evidence from included studies suggests that ocriplasmin is a suitable and safe approach for treating sVMA. ERM and MH status are important factors when considering ocriplasmin treatment.

mSHAP: SHAP Values for Two-Part Models

Two-part models are important to and used throughout insurance and actuarial science. Since insurance is required for registering a car, obtaining a mortgage, and participating in certain businesses, it is especially important that the models that price insurance policies are fair and non-discriminatory. Black box models can make it very difficult to know which covariates are influencing the results, resulting in model risk and bias. SHAP (SHapley Additive exPlanations) values enable interpretation of various black box models, but little progress has been made in two-part models. In this paper, we propose mSHAP (or multiplicative SHAP), a method for computing SHAP values of two-part models using the SHAP values of the individual models. This method will allow for the predictions of two-part models to be explained at an individual observation level. After developing mSHAP, we perform an in-depth simulation study. Although the kernelSHAP algorithm is also capable of computing approximate SHAP values for a two-part model, a comparison with our method demonstrates that mSHAP is exponentially faster. Ultimately, we apply mSHAP to a two-part ratemaking model for personal auto property damage insurance coverage. Additionally, an R package (mshap) is available to easily implement the method in a wide variety of applications.

Towards More Realistic Models

This chapter is devoted to the presentation of a more realistic version of the model, Risk and Rumours, which extends the previous, theoretical version (Routes and Rumours) by including additional empirical and experimental information following the process described in Part II of this book. We begin by offering a reflection on the integration of the five elements of the modelling process, followed by a more detailed description of the Risk and Rumours model, and how it differs from the previous version. Subsequently, we present selected results of the uncertainty and sensitivity analysis, enabling us to make further inference on the information gaps and areas for potential data collection. We also present model calibration for an empirically grounded version of the model, Risk and Rumours with Reality. In that way, we can evaluate to what extent the iterative modelling process has enabled a reduction in the uncertainty of the migrant route formation. In the final part of the chapter, we reflect on the model-building process and its implementation.

The Implementation of the POPMAR (Policy, Organising, Planning and Implementing, Measuring Performance, Audit and Reviewing) Model in Occupational Health and Safety Risk Management in an Indonesian Batik Company

Introduction: In 2009, UNESCO declared Batik Indonesia as an Intangible Cultural Heritage of Humanity. This study examines the occupational health and safety hazards and risks that arise in a Batik company based on a case example of a Batik company in Surakarta, Indonesia. In Indonesia, Batik is categorized as traditional attire. Two kinds of Batik are produced - Batik tulis (traditionally handcrafted) and Batik printing, which uses specific printing tools. The UK Health Safety Executive (HSE) risk assessment framework is referred to in this study, which consists of: hazard identification, population exposure, risk evaluation, precaution development, recording findings, and regular appraisal of systems. Methods: Both observation and interviews (of workers) at the Batik company were utilized for this study as well as an independent risk assessment. Results: The findings highlighted physical, ergonomic, chemical, mechanical, and biological hazards, originating from the materials, tools, and working methods utilized in the batik production. Conclusion: Many of the issues highlighted by this study can be addressed via in-depth risk assessment, using the POPMAR model to frame the activities. This approach can create a positive pathway, leading to a continuous cycle of improvement which puts the workers’ health at the forefront of the business activities.Keywords: Batik, workers, hazard identification, HSE Model, risk management

Validation of Corporate Probability of Default Models Considering Alternative Use Cases

In this study, we consider the construction of through-the-cycle (“TTC”) PD models designed for credit underwriting uses and point-in-time (“PIT”) PD models suitable for early warning uses, considering which validation elements should be emphasized in each case. We build PD models using a long history of large corporate firms sourced from Moody’s, with a large number of financial, equity market and macroeconomic variables as candidate explanatory variables. We construct a Merton model-style distance-to-default (“DTD”) measure and build hybrid structural reduced-form models to compare with the financial ratio and macroeconomic variable-only models. In the hybrid models, the financial and macroeconomic explanatory variables still enter significantly and improve the predictive accuracy of the TTC models, which generally lag behind the PIT models in that performance measure. We conclude that care must be taken to judiciously choose the manner in which we validate TTC vs. PIT models, as criteria may be rather different and be apart from standards such as discriminatory power. This study contributes to the literature by providing expert guidance to credit risk modeling, model validation and supervisory practitioners in controlling the model risk associated with such modeling efforts.

Payment Accuracy in Value-Based Care Contracts

Reimbursement for health care services is transferring more risk away from payers and toward health care providers in the form of Alternative Payment Models (APMs), also known as Value-Based Care (VBC) models. VBC models cover a wide variety of forms but all include guarantees by providers of services to improve quality of care and/or reduce cost. Types of risk include performance risk, contract design risk or stochastic risk (because of the random variation in health care services and costs). A form of contract risk that can be a significant driver of cost is model risk, defined as the probability that the savings calculated at contract reconciliation will deviate from the actual savings generated. To estimate the degree of risk we quantify the potential variance in outcomes in a naïve population prior to intervention and the components that could affect outcomes, using examples of maternity and type 2 diabetes. This analysis has implications for both participants in, and designers of value-based contracts.

Normative data and percentile curves for axial length and axial length/corneal curvature in Chinese children and adolescents aged 4–18 years

PurposeTo develop age-specific and gender-specific reference percentile charts for axial length (AL) and AL/corneal radius of curvature (AL/CR) and, to use percentiles to determine probability of myopia and estimate refractive error (RE).MethodsAnalysis of AL, cycloplegic RE and CR of 14 127 Chinese participants aged 4–18 years from 3 studies. AL and AL/CR percentiles estimated using Lambda-Mu-Sigma method and compared for agreement using intraclass correlation (ICC). Logistic regression was used to model risk of myopia based on age, gender, AL and AL/CR percentiles. Accuracy of AL progression and RE estimated using percentiles was validated using an independent sample of 5742 eyes of children aged 7–10 years.ResultsAge-specific and gender-specific AL and AL/CR (3rd, 5th, 10th, 25th, 50th, 75th, 90th and 95th) percentiles are presented. Concordance between AL and AL/CR percentiles improved with age (0.13 at 4 years to >0.75 from 13 years) and a year-to-year change was observed for all except <10th percentile from 15 years. Increasing age, AL and AL/CR was associated with a more myopic RE (r2=0.45,0.70 and 0.83, respectively). The sensitivity and specificity of the model to estimate probability of myopia was 86.0% and 84.5%, respectively. Estimation of 1-year change in AL using percentiles correlated highly with actual AL (ICC=0.98). Concordance of estimated to actual RE was high (ICC=0.80) and within ±0.50D and ±1.0D of actual RE for 47.4% and 78.9% of eyes, respectively.ConclusionAge-specific and gender-specific AL and AL/CR percentiles provide reference data, aid in identifying and monitoring individuals at risk of myopia and have utility in screening for myopia. AL/CR percentiles were more accurate in estimating probability of myopia in younger children.