Limited clinical activity of palbociclib and ribociclib monotherapy in advanced cancers with cyclin D-CDK4/6 pathway alterations in the Dutch DRUP and Australian MoST trials

The Dutch Drug Rediscovery Protocol (DRUP) and the Australian Cancer Molecular Screening and Therapeutic (MoST) Program are similar nonrandomized, multidrug, pan-cancer trial platforms that aim to identify signals of clinical activity of molecularly matched targeted therapies or immunotherapies outside their approved indications. Here, we report results for advanced or metastatic cancer patients with tumors harboring cyclin D-CDK4/6 pathway alterations treated with CDK4/6 inhibitors palbociclib or ribociclib. We included adult patients that had therapy-refractory solid malignancies with the following alterations: amplifications of CDK4, CDK6, CCND1, CCND2 or CCND3, or complete loss of CDKN2A or SMARCA4. Within MoST, all patients were treated with palbociclib, whereas in DRUP, palbociclib and ribociclib were assigned to different cohorts (defined by tumor type and alteration). The primary endpoint for this combined analysis was clinical benefit, defined as confirmed objective response or stable disease ≥16 weeks. We treated 139 patients with a broad variety of tumor types; 116 with palbociclib and 23 with ribociclib. In 112 evaluable patients, the objective response rate was 0% and clinical benefit rate at 16 weeks was 15%. Median progression-free survival was 4 months (95% CI: 3-5 months), and median overall survival 5 months (95% CI: 4-6 months). In conclusion, only limited clinical activity of palbociclib and ribociclib monotherapy in patients with pretreated cancers harboring cyclin D-CDK4/6 pathway alterations was observed. Our findings indicate that monotherapy use of palbociclib or ribociclib is not recommended and that merging data of two similar precision oncology trials is feasible.Experimentele farmacotherapi

Track A Basic Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138319/1/jia218438.pd

An Introduction to Volatility Models with Indices

AbstractThis paper considers a class of volatility models generated by autoregressive (AR) type models with indices. Some results associated with the autocorrelation function (acf) of this class are given and the spectral density is obtained in terms of the kurtosis of the error distribution and model parameters

Random coefficient volatility models

In financial modeling, the moments of the observed process, the kurtosis and the moments of the conditional volatility play important roles. They are very important in model identification and in forecasting the volatility (see Thavaneswaran et al. [(2005b). Forecasting volatility. Statist. Probab. Lett. 75, 1-10.]). This paper introduces random coefficient GARCH models including the class random coefficient GARCH (RC-GARCH) models and derive their higher order moments and kurtosis.Stochastic volatility Random coefficient Kurtosis Sign-switching

Forecasting volatility

This paper studies the problem of volatility forecasting for some financial time series models. We consider several stochastic volatility models including GARCH, Power GARCH and non-stationary GARCH for illustration. In particular, a martingale representation is used to obtain the l-steps-ahead forecast error variance for the class of GARCH models. Some closed-form expressions for the variance of l-steps-ahead forecasts errors are given in terms of [psi] weights and the kurtosis of the error distribution.Forecasting GARCH models Stochastic volatility Innovations Heteroscedasticity Random Conditional expectation

Recent developments in volatility modeling and applications

In financial modeling, it has been constantly pointed out that volatility clustering and conditional nonnormality induced leptokurtosis observed in high frequency data. Financial time series data are not adequately modeled by normal distribution, and empirical evidence on the non-normality assumption is well documented in the financial literature (details are illustrated by Engle (1982) and Bollerslev (1986)). An ARMA representation has been used by Thavaneswaran et al., in 2005, to derive the kurtosis of the various class of GARCH models such as power GARCH, non-Gaussian GARCH, nonstationary and random coefficient GARCH. Several empirical studies have shown that mixture distributions are more likely to capture heteroskedasticity observed in high frequency data than normal distribution. In this paper, some results on moment properties are generalized to stationary ARMA process with GARCH errors. Application to volatility forecasts and option pricing are also discussed in some detail

Organophotocatalytic N‐Demethylation of Oxycodone Using Molecular Oxygen

peer reviewedN-Demethylation of oxycodone is one of the key steps in the synthesis of important opioid antagonists like naloxone or analgesics like nalbuphine. The reaction is typically carried out using stoichiometric amounts of toxic and corrosive reagents. Herein, we present a green and scalable organophotocatalytic procedure that accomplishes the N-demethylation step using molecular oxygen as the terminal oxidant and an organic dye (rose bengal) as an effective photocatalyst. Optimization of the reaction conditions under continuous flow conditions using visible-light irradiation led to an efficient, reliable, and scalable process, producing noroxycodone hydrochloride in high isolated yield and purity after a simple workup