Fatigue self-management behaviors in patients with advanced cancer: A prospective longitudinal survey

Purpose: To explore the fatigue self-management behaviors and factors associated with effectiveness of these behaviors in patients with advanced cancer. Design: Prospective longitudinal interviewer-administered survey. Setting: A tertiary cancer center in Queensland Australia. Sample: One hundred fifty two outpatients with metastatic breast, lung, colorectal and prostate cancer experiencing fatigue (>3/10) were recruited. Main Research Variables: Fatigue self-management behaviors outcomes (perceived effectiveness, self-efficacy and frequency), medical/demographic characteristics (including sites of primary cancer and metastasis, comorbidity, performance status), social support, depressive, anxiety, and other symptoms were assessed. Findings: The participants reported moderate levels of fatigue at baseline (M=5.85, SD 1.44), and maintained moderate levels at 4 weeks and 8 weeks. On average, participants consistently used approximately nine behaviors at each time point. Factors significantly associated with higher levels of perceived effectiveness of fatigue self-management behaviors were higher self-efficacy (p<.001), higher education level (p=.02), and lower levels of depressive symptoms (p=.04). Conclusions: The findings of this study demonstrate that patients with cancer, even with advanced disease, still want and are able to use a number of behaviors to control their fatigue. Self-management interventions that aim to enhance self-efficacy and address any concurrent depressive symptoms have the potential to reduce fatigue severity. Implications for Nursing: Nurses are well positioned to play a key role in supporting patients in their fatigue self-management. Knowledge Translation: This study particularly focused on the perspectives of patients about fatigue self-management, highlighting a number of issues requiring further attention in clinical practice and the potential for future research.

Corporate philanthropy, reputation risk management and shareholder value: A study of Australian corporate giving

This study examines the role of corporate philanthropy in the management of reputation risk and shareholder value of the top 100 ASX listed Australian firms for the three years 2011-2013. The results of this study demonstrate the business case for corporate philanthropy and hence encourage corporate philanthropy by showing increasing firms’ investment in corporate giving as a percentage of profit before tax, increases the likelihood of an increase in shareholder value. However, the proviso is that firms must also manage their reputation risk at the same time. There is a negative association between corporate giving and shareholder value (Tobin’s Q) which is mitigated by firms’ management of reputation. The economic significance of this result is that for every cent in the dollar the firm spends on corporate giving, Tobin’s Q will decrease by 0.413%. In contrast, if the firm increase their reputation by 1 point then Tobin’s Q will increase by 0.267%. Consequently, the interaction of corporate giving and reputation risk management is positively associated with shareholder value. These results are robust while controlling for potential endogeneity and reverse causality. This paper assists both academics and practitioners by demonstrating that the benefits of corporate philanthropy extend beyond a gesture to improve reputation or an attempt to increase financial performance, to a direct collaboration between all the factors where the benefits far outweigh the costs.

Modeling and Forecasting Implied Volatility: Implications for Trading, Pricing, and Risk Management

Modeling and forecasting of implied volatility (IV) is important to both practitioners and academics, especially in trading, pricing, hedging, and risk management activities, all of which require an accurate volatility. However, it has become challenging since the 1987 stock market crash, as implied volatilities (IVs) recovered from stock index options present two patterns: volatility smirk(skew) and volatility term-structure, if the two are examined at the same time, presents a rich implied volatility surface (IVS). This implies that the assumptions behind the Black-Scholes (1973) model do not hold empirically, as asset prices are mostly influenced by many underlying risk factors. This thesis, consists of four essays, is modeling and forecasting implied volatility in the presence of options markets’ empirical regularities. The first essay is modeling the dynamics IVS, it extends the Dumas, Fleming and Whaley (DFW) (1998) framework; for instance, using moneyness in the implied forward price and OTM put-call options on the FTSE100 index, a nonlinear optimization is used to estimate different models and thereby produce rich, smooth IVSs. Here, the constant-volatility model fails to explain the variations in the rich IVS. Next, it is found that three factors can explain about 69-88% of the variance in the IVS. Of this, on average, 56% is explained by the level factor, 15% by the term-structure factor, and the additional 7% by the jump-fear factor. The second essay proposes a quantile regression model for modeling contemporaneous asymmetric return-volatility relationship, which is the generalization of Hibbert et al. (2008) model. The results show strong negative asymmetric return-volatility relationship at various quantiles of IV distributions, it is monotonically increasing when moving from the median quantile to the uppermost quantile (i.e., 95%); therefore, OLS underestimates this relationship at upper quantiles. Additionally, the asymmetric relationship is more pronounced with the smirk (skew) adjusted volatility index measure in comparison to the old volatility index measure. Nonetheless, the volatility indices are ranked in terms of asymmetric volatility as follows: VIX, VSTOXX, VDAX, and VXN. The third essay examines the information content of the new-VDAX volatility index to forecast daily Value-at-Risk (VaR) estimates and compares its VaR forecasts with the forecasts of the Filtered Historical Simulation and RiskMetrics. All daily VaR models are then backtested from 1992-2009 using unconditional, independence, conditional coverage, and quadratic-score tests. It is found that the VDAX subsumes almost all information required for the volatility of daily VaR forecasts for a portfolio of the DAX30 index; implied-VaR models outperform all other VaR models. The fourth essay models the risk factors driving the swaption IVs. It is found that three factors can explain 94-97% of the variation in each of the EUR, USD, and GBP swaption IVs. There are significant linkages across factors, and bi-directional causality is at work between the factors implied by EUR and USD swaption IVs. Furthermore, the factors implied by EUR and USD IVs respond to each others’ shocks; however, surprisingly, GBP does not affect them. Second, the string market model calibration results show it can efficiently reproduce (or forecast) the volatility surface for each of the swaptions markets.

Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.

Risk management plan and pharmacovigilance system - biopharmaceuticals: biosimilars.

Editor literario del libro, Giancarlo Nota - All chapters are Open Access articles distributed under the Creative Commons Non Commercial-Share Alike-Attribution 3.0 license, which permits to copy, distribute, transmit, and adapt the work in any medium, so long as the original work is properly cited.

Flood risk management: What are the main drivers of prevention?

4 p.

Participatory action research on climate risk management, Bangladesh

The rural populations of southern Bangladesh are some of the most vulnerable communities in the world to the future impacts of climate change. They are particularly at risk from floods, waterlogged soils, and increasing salinity of both land and water. The objective of this project was to analyze the vulnerability of people in four villages that are experiencing different levels of soil salinity. The study evaluated the strengths and weaknesses of current coping strategies and assessed the potential of an index-based insurance scheme, designed diversification and better information products to improve adaptive capacity.

Regulation: A Burden in Biopharmaceutical Industry? The Case of EU-Risk Management Plans

The generation of new medicinal products is both a contributor to global economic growth and a source of valuable benefits to human health. Given their direct responsibility for public health, regulatory authorities monitor closely both the development and exploitation of the underlying technologies and the products derived from them. The manner in which such regulation is implemented can result in regulators constraining or facilitating the generation of new products. This paper will study as an example the impact of EU Risk Management Plans (EU-RMPs), which have been mandatory for the approval of new medicines since 2005, on both the industry and regulatory authorities. In interviews, the responses of those who had experience of the implementation of EU-RMPs were mixed. Although the benefits of a more structured and predictable approach to the evaluation of risk were appreciated, some respondents perceived the regulation as an excessive burden on their organisations. The exploration of factors that influence how EU-RMP regulation affects individual firms provides new insights for both regulators and managers, and demonstrates one aspect of the complexity of the process by which new medicinal products are brought to market.

Regulation: A burden in biopharmaceutical industry? The case of EU-risk management plans

The generation of new medicinal products is both a contributor to global economic growth and a source of valuable benefits to human health. Given their direct responsibility for public health, regulatory authorities monitor closely both the development and exploitation of the underlying technologies and the products derived from them. The manner in which such regulation is implemented can result in regulators constraining or facilitating the generation of new products. This paper will study as an example the impact of EU Risk Management Plans (EU-RMPs), which have been mandatory for the approval of new medicines since 2005, on both the industry and regulatory authorities. In interviews, the responses of those who had experience of the implementation of EU-RMPs were mixed. Although the benefits of a more structured and predictable approach to the evaluation of risk were appreciated, some respondents perceived the regulation as an excessive burden on their organisations. The exploration of factors that influence how EU-RMP regulation affects individual firms provides new insights for both regulators and managers, and demonstrates one aspect of the complexity of the process by which new medicinal products are brought to market. © 2010 IEEE.