Statistical models of claim amount distributions in general insurance

This work examines the following statistical distributions as possible models for the distribution of claim amounts in general insurance: 1- The lognormal 2- The Weibull 3- The inverse Gaussian (A new 3-parameter form is introduced) 4- The Pareto 5- The truncated lognormal as a model for large claim amounts) 6- The gamma (as a model for the distribution of the square root of claim amounts) The properties. of the above distributions are investigated and various methods of estimation of their parameters are explored. The method of multinomial maxim mt likelihood for estimating the parameters is favoured because data on claim amounts is generally in grouped frequency format. To find these estimates a computing technique is proposed which avoids solving a complicated set of non-linear equations. A procedure which avoids solving non-linear equations is also suggested for the least squares estimation of the 3-parameter lognormal, 3-param_etor Weibull and the Pareto distribution of the second kind. In order to show how the various methods work in practice they are applied to an actual set of accidental damage claim amounts. Goodness-of-fit tests are used to judge the agreement between the model and sample valuos. The Chi-square and the Kolmogorov-Sriirnov tests are reviewed and a new test statistic is proposed which measures the overall agreement between the model and sample values in monetary terms. The application procedures for all these tests are described. Inflation is likely to be the main cause of the increase in the size of claim over time. Therefore, its effects on the parameters of various models are examined. A method is suggested for predicting the future distribution of claim amounts which uses the parameters of a past model after being adjusted for inflation. This predictive method is demonstrated on the accidental damage data whenever a suitable model is found

Ionic Push–Pull Polythiophenes: A Further Step towards Eco-Friendly BHJ Organic Solar Cells

Four new conjugated polymers alternating benzothiadiazole units and thiophene moieties functionalized with ionic phosphonium or sulfonic acid salts in the side chains were synthesized by a postfunctionalization approach of polymeric precursors. The introduction of ionic groups makes the conjugated polymers soluble in water and/or polar solvents, allowing for the fabrication of bulk heterojunction (BHJ) solar cells using environmentally friendly conditions. All polymers were fully characterized by spectroscopic, thermal, electrochemical, X-ray diffraction, scanning electron, and atomic force techniques. BHJ solar cells were obtained from halogen-free solvents (i.e., ethanol and/or anisole) by blending the synthesized ionic push–pull polymers with a serinol-fullerene derivative or an ionic homopolymer acting as electron-acceptor (EA) or electron-donor (ED) counterparts, respectively. The device with the highest optical density and the smoothest surface of the active layer was the best-performing, showing a 4.76% photoconversion efficiency

Multifunctional platform based on electrospun nanofibers and plasmonic hydrogel. A smart nanostructured pillow for near-infrared light-driven biomedical applications

Multifunctional nanomaterials with the ability to respond to near-infrared (NIR) light stimulation are vital for the development of highly efficient biomedical nanoplatforms with a polytherapeutic approach. Inspired by the mesoglea structure of jellyfish bells, a biomimetic multifunctional nanostructured pillow with fast photothermal responsiveness for NIR light-controlled on-demand drug delivery is developed. We fabricate a nanoplatform with several hierarchical levels designed to generate a series of controlled, rapid, and reversible cascade-like structural changes upon NIR light irradiation. The mechanical contraction of the nanostructured platform, resulting from the increase of temperature to 42 °C due to plasmonic hydrogel-light interaction, causes a rapid expulsion of water from the inner structure, passing through an electrospun membrane anchored onto the hydrogel core. The mutual effects of the rise in temperature and water flow stimulate the release of molecules from the nanofibers. To expand the potential applications of the biomimetic platform, the photothermal responsiveness to reach the typical temperature level for performing photothermal therapy (PTT) is designed. The on-demand drug model penetration into pig tissue demonstrates the efficiency of the nanostructured platform in the rapid and controlled release of molecules, while the high biocompatibility confirms the pillow potential for biomedical applications based on the NIR light-driven multitherapy strategy

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

Demographic, clinical and antibody characteristics of patients with digital ulcers in systemic sclerosis: data from the DUO Registry

OBJECTIVES: The Digital Ulcers Outcome (DUO) Registry was designed to describe the clinical and antibody characteristics, disease course and outcomes of patients with digital ulcers associated with systemic sclerosis (SSc). METHODS: The DUO Registry is a European, prospective, multicentre, observational, registry of SSc patients with ongoing digital ulcer disease, irrespective of treatment regimen. Data collected included demographics, SSc duration, SSc subset, internal organ manifestations, autoantibodies, previous and ongoing interventions and complications related to digital ulcers. RESULTS: Up to 19 November 2010 a total of 2439 patients had enrolled into the registry. Most were classified as either limited cutaneous SSc (lcSSc; 52.2%) or diffuse cutaneous SSc (dcSSc; 36.9%). Digital ulcers developed earlier in patients with dcSSc compared with lcSSc. Almost all patients (95.7%) tested positive for antinuclear antibodies, 45.2% for anti-scleroderma-70 and 43.6% for anticentromere antibodies (ACA). The first digital ulcer in the anti-scleroderma-70-positive patient cohort occurred approximately 5 years earlier than the ACA-positive patient group. CONCLUSIONS: This study provides data from a large cohort of SSc patients with a history of digital ulcers. The early occurrence and high frequency of digital ulcer complications are especially seen in patients with dcSSc and/or anti-scleroderma-70 antibodies

Absolute risk and predictors of the growth of acute spontaneous intracerebral haemorrhage: a systematic review and meta-analysis of individual patient data.

Background Intracerebral haemorrhage growth is associated with poor clinical outcome and is a therapeutic target for improving outcome. We aimed to determine the absolute risk and predictors of intracerebral haemorrhage growth, develop and validate prediction models, and evaluate the added value of CT angiography. Methods In a systematic review of OVID MEDLINE—with additional hand-searching of relevant studies' bibliographies— from Jan 1, 1970, to Dec 31, 2015, we identified observational cohorts and randomised trials with repeat scanning protocols that included at least ten patients with acute intracerebral haemorrhage. We sought individual patient-level data from corresponding authors for patients aged 18 years or older with data available from brain imaging initially done 0·5–24 h and repeated fewer than 6 days after symptom onset, who had baseline intracerebral haemorrhage volume of less than 150 mL, and did not undergo acute treatment that might reduce intracerebral haemorrhage volume. We estimated the absolute risk and predictors of the primary outcome of intracerebral haemorrhage growth (defined as >6 mL increase in intracerebral haemorrhage volume on repeat imaging) using multivariable logistic regression models in development and validation cohorts in four subgroups of patients, using a hierarchical approach: patients not taking anticoagulant therapy at intracerebral haemorrhage onset (who constituted the largest subgroup), patients taking anticoagulant therapy at intracerebral haemorrhage onset, patients from cohorts that included at least some patients taking anticoagulant therapy at intracerebral haemorrhage onset, and patients for whom both information about anticoagulant therapy at intracerebral haemorrhage onset and spot sign on acute CT angiography were known. Findings Of 4191 studies identified, 77 were eligible for inclusion. Overall, 36 (47%) cohorts provided data on 5435 eligible patients. 5076 of these patients were not taking anticoagulant therapy at symptom onset (median age 67 years, IQR 56–76), of whom 1009 (20%) had intracerebral haemorrhage growth. Multivariable models of patients with data on antiplatelet therapy use, data on anticoagulant therapy use, and assessment of CT angiography spot sign at symptom onset showed that time from symptom onset to baseline imaging (odds ratio 0·50, 95% CI 0·36–0·70; p<0·0001), intracerebral haemorrhage volume on baseline imaging (7·18, 4·46–11·60; p<0·0001), antiplatelet use (1·68, 1·06–2·66; p=0·026), and anticoagulant use (3·48, 1·96–6·16; p<0·0001) were independent predictors of intracerebral haemorrhage growth (C-index 0·78, 95% CI 0·75–0·82). Addition of CT angiography spot sign (odds ratio 4·46, 95% CI 2·95–6·75; p<0·0001) to the model increased the C-index by 0·05 (95% CI 0·03–0·07). Interpretation In this large patient-level meta-analysis, models using four or five predictors had acceptable to good discrimination. These models could inform the location and frequency of observations on patients in clinical practice, explain treatment effects in prior randomised trials, and guide the design of future trials