Essays On Risk and Time with applications in insurance and finance

The predictions of theoretical models of human decision-making should agree with empir- ical and experimental evidence. In that respect, some fields of economics have embraced more plausible representations of preferences than others. For example, while standard in finance, temporally risk-averse preferences are still uncommon in the life-cycle literature, although they greatly improve its predictions. Chapter I introduces the issues that this dissertation touches on regarding the modeling of intertemporal preferences under uncertainty Chapter II discusses the allocation of aggregate longevity risk within a pension system when insurance markets are perfect. For a given expected budget, temporally risk-averse individuals prefer contributions and benefits to depend on the evolution of aggregate mor- tality rates rather than being fixed. The optimal allocation therefore transfers some risk to individuals, even though pension providers have access to perfect insurance markets. Indeed, this offers a “hedging” strategy where the prospect of a shorter life (e.g. emerging diseases) entails higher consumption while the prospect of a longer life is combined with lower consumption levels. Chapter II illustrates the benefits of applying models borrowed from finance to the life- cycle literature. In addition, empirical and experimental research refines our understand- ing of human behavior, triggering further improvements in the modeling of decision- making processes. Recent experiments indicate that individuals are more averse to im- mediate risk than to delayed ones. Because it involves risk attitudes and temporal delays, this bias may affect the decision to purchase insurance for long-run risks such as long-term care insurance. Chapter III considers individuals whose propensity to take risks decreases when old. Unaware of their changing taste for risk, naives delay the purchase of long-term care insurance, although this is a dominated strategy. Sophisticates, on the other hand, do not delay their purchase and, provided the elasticity of intertemporal substitution is below unity, end up better insured than naives. Delay-dependent risk aversion may also affect the pricing of financial assets. In fact, recent empirical evidence suggests that risk premia are sometimes higher for short-term yields than for long-term ones. Existing asset pricing models cannot reproduce this feature. Chapter IV contains a consumption-based model with a dynamically inconsistent rep- resentative agent whose risk aversion decreases with the delay. When this agent is naive, this model’s achievements are similar to those of existing asset pricing models: Equity risk premia are high and interest rates are low. The innovation is that the term structure of equity premia is decreasing

Would you Prefer your Retirement Income to Depend on your Life Expectancy?

We study the demand for retirement income of agents who gradually learn about their life expectancy. For a given expected budget, temporally risk-averse agents prefer that pension levels respond to incoming information about life ex- pectancy rather than being fixed ex-ante. Indeed, this offers a hedging strategy that couples shorter lives with higher consumption levels, and longer lives with lower consumption levels. A calibrated life-cycle model provides an order of mag- nitude of the effects at play.ISSN:0022-0531ISSN:1095-723

Prognostic factors of toxicity of immune checkpoint inhibitors in nonsmall cell lung cancer and small cell lung cancer patients: The ToxImmune study

Abstract Background Immunotherapy alone or in combination has clearly improved the survival of patients with lung cancer. However, it may also be responsible for adverse events impacting these patients' quality of life. The ToxImmune study aims to identify prognostic factors that can help to predict immune‐related adverse events. Methods We included all patients aged 18 years and older who had received at least one dose of immune checkpoint inhibitors, with or without other therapy, between June 2015 and December 2020 and were diagnosed with nonsmall cell lung cancer or small‐cell lung cancer. Patients' baseline demographic characteristics, biological blood markers, and imaging by PET‐scanner were collected from electronic medical records. All adverse events (AEs) and immune‐related AEs (irAEs) were recorded (Common Terminology Criteria For Adverse Events V.5.0). Results Sixty‐four patients were included, of whom 60 (94%) presented at least one irAE. The incidence of Common Terminology Criteria for Adverse Events (CTCAE) grade 2 and grade 3–4 was 34% and 8% respectively. Female sex, Primitive Tumor Standardized Uptake Value Max (SUVmax) <5, number of metastases ≥3 and immunotherapy received after the first line were found to be significant risk factors for immune‐related adverse events. Based on the number of risk factors, the ToxImmune score predicts the risk of having a grade ≥2 adverse event (primitive tumor SUV ≥ 5 = 0 vs. primitive tumor SUV <5 = 1, number of metastases <3 = 0 vs. number of metastases ≥3 = 1 and L1 = 0 vs. L1 ≥ 1). The incidence of grade ≥2 adverse events was 20%, 55% and 90% with ToxImmune scores 0, 1 and = 2 respectively (p = .003). Median progression‐free survival (PFS) times were 19.2 months, 6.64 months and 2.63 months for ToxImmune scores 0, 1 and = 2 respectively, p = .13. Median overall survival times were 22.6 months, 16.4 months and 9.8 months for ToxImmune scores 0, 1 and ≥2 respectively, p = .24. The disease control rate (DRR) was 78% in ToxIummune score 0 group, and 50% in ToxImmune score 1 and ≥2 groups (p = .363). Conclusion The ToxImmune score, which is grounded on objective clinical parameters, indicates that cases with a high score had an advanced threat of severe adverse events. The ToxImmune score could therefore be used in clinical practice to identify patients treated for lung cancer with immunotherapy and at risk of severe AE

Correlation Between Serum and Urine Biomarkers and the Intensity of Acute Radiation Cystitis in Patients Treated With Radiation Therapy for Localized Prostate Cancer: Protocol for the Radiotoxicity Bladder Biomarkers (RABBIO) Study

BackgroundDespite improvements in radiation techniques, pelvic radiotherapy is responsible for acute and delayed bladder adverse events, defined as radiation cystitis. The initial symptoms of bladder injury secondary to pelvic irradiation are likely to occur during treatment or within 3 months of radiotherapy in approximately 50% of irradiated patients, and have a significant impact on their quality of life. The pathophysiology of radiation cystitis is not well understood, particularly because of the risk of complications associated with access to bladder tissue after irradiation, which limits our ability to study this process and develop treatments. ObjectiveIt is an original study combining digital data collection to monitor patients’ symptoms and biological markers during irradiation. The main objective of our study is to evaluate the correlation of biological biomarkers with the intensity of acute radiation cystitis and the quality of life of patients, assessed with the digital telemonitoring platform Cureety. MethodsPatients with intermediate-risk localized prostate cancer who are eligible for localized radiotherapy will be included. Inflammatory biomarkers will be analyzed in urine and blood samples before the start of radiotherapy and at weeks 4, 12, and 48 of irradiation, through quantitative methods such as a multiplex Luminex assay, flow cytometry, and enzyme-linked immunosorbent assay. We will also characterize the patients’ gut and urine microbiota composition using 16S ribosomal RNA sequencing technology. Between sample collection visits, patients will complete various questionnaires related to radiation cystitis symptoms (using the International Prostate Symptom Score), adverse events, and quality of life (using the Functional Assessment of Cancer Therapy–Prostate questionnaire), using the Cureety digital remote monitoring platform. Upon receipt of the questionnaires, an algorithm will process the information and classify patients in accordance with the severity of symptoms and adverse events reported on the basis of Common Terminology Criteria for Adverse Events and International Prostate Symptom Score standards. This will allow us to correlate levels of urinary, blood, and fecal biomarkers with the severity of acute radiation cystitis symptoms and patient-reported quality of life. ResultsThe study started in March 2022. We estimate a recruitment period of approximately 18 months, and the final results are expected in 2024. ConclusionsThis prospective study is the first to explore the overexpression of inflammatory proteins in fluid biopsies from patients with symptoms of acute radiation cystitis. In addition, the 1-year follow-up after treatment will allow us to predict which patients are at risk of late radiation cystitis and to refer them for radioprotective treatment. The results of this study will allow us to develop strategies to limit radiation damage to the bladder and improve the quality of life of patients. Trial RegistrationClinicalTrials.gov NCT05246774; https://clinicaltrials.gov/ct2/show/NCT05246774?term=NCT05246774 International Registered Report Identifier (IRRID)DERR1-10.2196/3836