Differences in Time to Disease Progression Do Not Predict for Cancer-specific Survival in Patients Receiving Immediate or Deferred Androgen-deprivation Therapy for Prostate Cancer: Final Results of EORTC Randomized Trial 30891 with 12 Years of Follow-up

BACKGROUND Trials assessing the benefit of immediate androgen-deprivation therapy (ADT) for treating prostate cancer (PCa) have often done so based on differences in detectable prostate-specific antigen (PSA) relapse or metastatic disease rates at a specific time after randomization. OBJECTIVE Based on the long-term results of European Organization for Research and Treatment of Cancer (EORTC) trial 30891, we questioned if differences in time to progression predict for survival differences. DESIGN, SETTING, AND PARTICIPANTS EORTC trial 30891 compared immediate ADT (n=492) with orchiectomy or luteinizing hormone-releasing hormone analog with deferred ADT (n=493) initiated upon symptomatic disease progression or life-threatening complications in randomly assigned T0-4 N0-2 M0 PCa patients. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Time to first objective progression (documented metastases, ureteric obstruction, not PSA rise) and time to objective castration-resistant progressive disease were compared as well as PCa mortality and overall survival. RESULTS AND LIMITATIONS After a median of 12.8 yr, 769 of the 985 patients had died (78%), 269 of PCa (27%). For patients receiving deferred ADT, the overall treatment time was 31% of that for patients on immediate ADT. Deferred ADT was significantly worse than immediate ADT for time to first objective disease progression (p<0.0001; 10-yr progression rates 42% vs 30%). However, time to objective castration-resistant disease after deferred ADT did not differ significantly (p=0.42) from that after immediate ADT. In addition, PCa mortality did not differ significantly, except in patients with aggressive PCa resulting in death within 3-5 yr after diagnosis. Deferred ADT was inferior to immediate ADT in terms of overall survival (hazard ratio: 1.21; 95% confidence interval, 1.05-1.39; p [noninferiority]=0.72, p [difference] = 0.0085). CONCLUSIONS This study shows that if hormonal manipulation is used at different times during the disease course, differences in time to first disease progression cannot predict differences in disease-specific survival. A deferred ADT policy may substantially reduce the time on treatment, but it is not suitable for patients with rapidly progressing disease.

Drivers of collaboration to mitigate climate change: An illustration of Swiss climate policy over 15 years

Climate change mitigation policy is driven by scientific knowledge and involves actors from the international, national and local decision-making levels. This multi-level and cross-sectoral context requires collaborative management when designing mitigation solutions over time and space. But collaboration in general policymaking settings, and particularly in the complex domain of climate mitigation, is not an easy task. This paper addresses the question of what drives collaboration among collective actors involved in climate mitigation policy. We wish to investigate whether common beliefs or power structures influence collaboration among actors. We adopt a longitudinal approach to grasp differences between the early and more advanced stages of mitigation policy design. We use survey data to investigate actors’ collaboration, beliefs and power, and apply a Stochastic Actor-oriented Model for network dynamics to three subsequent networks in Swiss climate policy between 1995 and 2012. Results show that common beliefs among actors, as well as formal power structures, have a higher impact on collaboration relations than perceived power structures. Furthermore, those effects hold true for decision-making about initial mitigation strategies, but less so for the implementation of those measures.

Quantifying differences in land use emission estimates implied by definition discrepancies

The quantification of CO2 emissions from anthropogenic land use and land use change (eLUC) is essential to understand the drivers of the atmospheric CO2 increase and to inform climate change mitigation policy. Reported values in synthesis reports are commonly derived from different approaches (observation-driven bookkeeping and process-modelling) but recent work has emphasized that inconsistencies between methods may imply substantial differences in eLUC estimates. However, a consistent quantification is lacking and no concise modelling protocol for the separation of primary and secondary components of eLUC has been established. Here, we review differences of eLUC quantification methods and apply an Earth System Model (ESM) of Intermediate Complexity to quantify them. We find that the magnitude of effects due to merely conceptual differences between ESM and offline vegetation model-based quantifications is ~ 20 % for today. Under a future business-as-usual scenario, differences tend to increase further due to slowing land conversion rates and an increasing impact of altered environmental conditions on land-atmosphere fluxes. We establish how coupled Earth System Models may be applied to separate secondary component fluxes of eLUC arising from the replacement of potential C sinks/sources and the land use feedback and show that secondary fluxes derived from offline vegetation models are conceptually and quantitatively not identical to either, nor their sum. Therefore, we argue that synthesis studies should resort to the "least common denominator" of different methods, following the bookkeeping approach where only primary land use emissions are quantified under the assumption of constant environmental boundary conditions.

Managing social policy under federalism: The challenges of hybrid funding and program delivery

This paper discusses generally the question of the level of government that should be used to administer different social policies. The chapter focuses on the Medicaid program, looking at recent state-level changes in health insurance for the poor and long-term care policy. Particular attention will be paid to the question of how states have used their new freedoms to outsource public insurance to the private sector and on the consequent differences in outcomes across states. Notably, this paper will be drawn from my forthcoming book “The American Myth of Markets in Social Policy” (Palgrave, MacMillan, November, 2015).

Looking beneath the Surface: Differences in Decision-Making Structures across Processes

The previous chapter presented the overall decision-making structure in Swiss politics at the beginning of the 21st century. This provides us with a general picture and allows for a comparison over time with the decision-making structure in the 1970s. However, the analysis of the overall decision-making structure potentially neglects important differences between policy domains (Atkinson and Coleman 1989; Knoke et al. 1996; Kriesi et al. 2006a; Sabatier 1987). Policy issues vary across policy domains, as do the political actors involved. In addition, actors may hold different policy preferences from one policy domain to the next, and they may also collaborate with other partners depending on the policy domain at stake. Examining differences between policy domains is particularly appropriate in Switzerland. Because no fixed coalitions of government and opposition exist, actors create different coalitions in each policy domain (Linder and Schwarz 2008). Whereas important parts of the institutional setting are similar across policy domains, decision-making structures might still vary. As was the case with the cross-time analysis conducted in the two previous chapters, a stability of 'rules-in-form' might hide important variations in 'rules-in-use' also across different policy domains.

Differences Between Monetary and Multidimensional Poverty in the Lao PDR: Implications for Targeting of Poverty Reduction Policies and Interventions

This study compares monetary and multidimensional poverty measures for the Lao People’s Democratic Republic. Using household data of 2007/2008, we compare the empirical outcomes of the country’s current official monetary poverty measure with those of a multidimensional poverty measure. We analyze which population subgroups are identified as poor by both measures and thus belong to the category of the poorest of the poor; and we look at which subgroups are identified as poor by only one of the measures and belong either to the category of the income-poor (identified as poor only by the monetary measure) or to that of the overlooked poor (identified as poor only by the multidimensional poverty measure). Furthermore, we examined drivers of these differences using a multinomial regression model and found that monetary poverty does not capture the multiple deprivations of ethnic minorities, who are only identified as poor when using a multidimensional poverty measure. We conclude that complementing the monetary poverty measure with a multidimensional poverty index would enable more effective targeting of poverty reduction efforts.