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One of the key aspects of designing a clinical trial is sample size estimation. The quantity ' I nc i ' is also a function of sample size, and therefore, the required sample size can be obtained by solving this equation for the sample size. The introductory Chapter 1 provides an excellent description of the basic principles for the sample size calculation and the factors that influence sample size. [Extracted from the article]

Roychoudhury et al. recently proposed a robust MaxCombo test that considers the maximum of four "correlated" test statistics from FH(0, 0), FH(0, 1), FH(1, 0), and FH(1, 1) tests. Their formulation needs estimation of correlations of these test statistics, and they obtained the correlation matrix via simulation. I have described a closed-form solution to obtain this correlation matrix under the "no censoring" assumption that depends only on sample size and planned number of events. This approach has been extended for group-sequential design as well. Our correlation matrix is very close to the one obtained by Roychoudhury et al. via simulation. In addition, we have also made remarks on the work of Roychoudhury et al. [ABSTRACT FROM AUTHOR]

This phase I study aimed at determining the maximum tolerated dose (MTD) and characterizing the safety, tolerability, pharmacokinetics (PKs), and efficacy of pasireotide in patients with advanced neuroendocrine tumors (NETs). Patients were enrolled in two phases: dose-escalation phase (to determine the MTD) at a starting dose of 80 mg pasireotide long-acting release (LAR) i.m. followed by a dose-expansion phase (to evaluate safety and preliminary efficacy). Associations between PK/pharmacodynamic parameters and clinical outcomes were evaluated using linear regression analysis. A total of 29 patients were treated with 80 mg (n=13) and 120 mg (n=16) doses. Most common primary tumor sites included small intestine (44.8%), pancreas (24.1%), and lung (17.2%). No protocol-defined dose-limiting toxicities were observed in the study; however, in post hoc analysis, a higher incidence of bradycardia (heart rate [HR],40 beats per minute [bpm]) was observed with 120 mg (31.3%) vs 80 mg (0%). Two partial responses (PRs) were observed, both in the 120 mg dose cohort. Pasireotide concentrations correlated with tumor shrinkage, although the association was not statistically significant (P=0.08). Among the biomarkers analyzed, insulin-like growth factor 1 (IGF-1) showed a decreasing trend with increasing pasireotide concentration, while chromogranin A (CgA) and neuron-specific enolase (NSE) levels did not show any dose-response relationship. The most common adverse events in any dose group were hyperglycemia, fatigue, and nausea. MTD was defined at 120 mg for pasireotide LAR in patients with advanced NETs. Although objective radiographic responses were rarely observed with somatostatin analogs, two PRs were observed among 16 patients in the 120 mg cohort. Bradycardia (HR,40 bpm) appears to be a dose-limiting effect; however, the mechanism and clinical significance are uncertain. This study was registered with clinicaltrials.gov (NCT01364415). [ABSTRACT FROM AUTHOR]

Tikhonov regularization was recently proposed for multivariate calibration. We use this framework for modeling the statistical association between spectroscopy data and a scalar outcome. In both the calibration and regression settings, this regularization process has advantages over methods of spectral preprocessing and dimension-reduction approaches such as feature extraction or principal component regression. We propose an extension of this penalized regression framework by adaptively refining the penalty term to optimally focus the regularization process. We illustrate the approach using simulated spectra and compare it with other penalized regression models and with a 2-step method that first preprocesses the spectra then fits a dimension-reduced model using the processed data. The methods are also applied to magnetic resonance spectroscopy data to identify brain metabolites that are associated with cognitive function. [ABSTRACT FROM AUTHOR]

Purpose: Safety, efficacy, and exploratory biomarker analyses were evaluated in patients with advanced HER2-negative germline breast cancer susceptibility gene (g BRCA )-associated breast cancer enrolled in the BROCADE3 trial who received crossover veliparib monotherapy after disease progression on placebo plus carboplatin/paclitaxel., Patients and Methods: Eligible patients ( N = 513) were randomized 2:1 to veliparib plus carboplatin/paclitaxel or placebo plus carboplatin/paclitaxel; patients had variable platinum-free intervals (PFI) at progression. In the placebo arm, patients were eligible to receive crossover veliparib monotherapy (300-400 mg twice daily continuous). Antitumor activity and adverse events were assessed during crossover veliparib treatment. BRCA reversion mutations at crossover were analyzed retrospectively using next-generation sequencing on plasma circulating tumor DNA (ctDNA)., Results: Seventy-five patients in the placebo plus carboplatin/paclitaxel arm received ≥1 dose of crossover veliparib postprogression (mean treatment duration: 154 days). Eight of 50 (16%) patients with measurable disease had a RECIST v1.1 response. Activity was greater in patients with PFI ≥180 days compared with <180 days [responses in 23.1% (3/13) vs. 13.5% (5/37) of patients]. BRCA reversion mutations that restored protein function were detected in ctDNA from 4 of 28 patients tested, and the mean duration of crossover veliparib monotherapy was <1 month in these 4 patients versus 7.49 months in patients lacking reversion mutations. The most frequent adverse events were nausea (61%), vomiting (29%), and fatigue (24%)., Conclusions: Crossover veliparib monotherapy demonstrated limited antitumor activity in patients who experienced disease progression on placebo plus carboplatin/paclitaxel. PFI appeared to affect veliparib activity. BRCA reversion mutations may promote cross-resistance and limit veliparib activity following progression on platinum., (©2021 The Authors; Published by the American Association for Cancer Research.)