Knowledge that Transforms

The aim of this study was to retrospectively analyze 18F-FDG positron emission tomography/computed tomography (18F-FDG PET/CT) metabolic variables, programmed death-ligand 1 (PD-L1) and phosphorylated signal transducer and activator of transcription 3 (p-STAT3) tumor expression, and other factors as predictors of disease-free survival (DFS) in patients with lung adenocarcinoma (LUAD) (stage IA-IIIA) who underwent surgical resection. We still lack predictor of immune checkpoint (programmed cell death-1 [PD-1]/PD-L1) inhibitors. Herein, we investigated the correlation between metabolic parameters from 18F-FDG PET/CT and PD-L1 expression in patients with surgically resected LUAD.Seventy-four patients who underwent 18F-FDG PET/CT prior to treatment were consecutively enrolled. The main 18F-FDG PET/CT-derived variables were primary tumor maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). Surgical tumor specimens were analyzed for PD-L1 and p-STAT3 expression using immunohistochemistry. Correlations between immunohistochemistry results and 18F-FDG PET/CT-derived variables were compared. Associations of PD-L1 and p-STAT3 tumor expression, 18F-FDG PET/CT-derived variables, and other factors with DFS in resected LUAD were evaluated.All tumors were FDG-avid. The cutoff values of low and high SUVmax, MTV, and TLG were 12.60, 14.87, and 90.85, respectively. The results indicated that TNM stage, PD-L1 positivity, and high 18F-FDG PET/CT metabolic volume parameters (TLG ≥90.85 or MTV ≥14.87) were independent predictors of worse DFS in resected LUAD. No 18F-FDG metabolic parameters associated with PD-L1 expression were observed (chi-square test), but we found that patients with positive PD-L1 expression have significantly higher SUVmax (P = .01), MTV (P = .00), and TLG (P = .00) than patients with negative PD-L1 expression.18F-FDG PET/CT metabolic volume parameters (TLG ≥90.85 or MTV ≥14.87) were more helpful in prognostication than the conventional parameter (SUVmax), PD-L1 expression was an independent predictor of DFS in patients with resected LUAD. Metabolic parameters on 18F-FDG PET/CT have a potential role for 18F-FDG PET/CT in selecting candidate LUAD for treatment with checkpoint inhibitors.

We study a dynamic continuous-time principal-agent model with endogenous cash flow volatility. The principal supplies the agent with capital for investment, but the agent can misallocate capital for private benefit and has private control over both the volatility of the project and the size of the investment. The optimal incentive-compatible contract can yield either overly risky or overly prudent project selection; it can be implemented as a time-varying cost of capital in the form of a hurdle rate. Our model captures stylized facts about the use of hurdle rates in capital budgeting and helps to reconcile the mixed empirical evidence on the correlations among firm size, risk and managerial compensation.

We show that investors derive nonpecuniary utility from investing in dual-objective Venture Capital (VC) funds, thus sacrificing returns. Impact funds earn 4.7 percentage points (ppts) lower internal rates of return (IRRs) ex-post than traditional VC funds. In random utility/willingness-to-pay (WTP) models investors accept 2.5–3.7 ppts lower IRRs ex ante for impact funds. The positive WTP result is robust to fund access rationing and investor heterogeneity in fund expected returns. Development organizations, foundations, financial institutions, public pensions, Europeans, and United Nations Principles of Responsible Investment signatories have high WTP. Investors with mission objectives and/or facing political pressure exhibit high WTP; those subject to legal restrictions (e.g., Employee Retirement Income Security Act) exhibit low WTP.

We introduce the concept of risk entanglement in a preference-free setting to jointly explain the exchange rate volatility, cyclicality, and currency risk premia in the data. Risk entanglement specifies a subset of incomplete market models, in which nondiffusive or nonlog-normal shocks to exchange rates are not fully spanned by asset returns. When risks are entangled, there exist multiple pricing-consistent exchange rates, but none of them are equal to the ratio of the stochastic discount factors (SDFs) or their projections. Decoupling the exchange rate from the SDFs allows us to address key FX market patterns that are puzzling in international finance.

We represent risk factors as sums of orthogonal components capturing fluctuations with cycles of different length. The representation leads to novel spectral factor models in which systematic risk is allowed—without being forced—to vary across frequencies. Frequency-specific systematic risk is captured by a notion of spectral beta. We show that traditional factor models restrict the spectral betas to be constant across frequencies. The restriction can hide horizon-specific pricing effects that spectral factor models are designed to reveal. We illustrate how the methods may lead to economically meaningful dimensionality reduction in the factor space.