Experimental design considerations and statistical analyses in preclinical tumor growth inhibition studies.

Animal models are used in cancer pre-clinical research to identify drug targets, select compound candidates for clinical trials, determine optimal drug dosages, identify biomarkers, and ensure compound safety. This tutorial aims to provide an overview of study design and data analysis from animal studies, focusing on tumor growth inhibition (TGI) studies used for prioritization of anticancer compounds. Some of the experimental design aspects discussed here include the selection of the appropriate biological models, the choice of endpoints to be used for the assessment of anticancer activity (tumor volumes, tumor growth rates, events, or categorical endpoints), considerations on measurement errors and potential biases related to this type of study, sample size estimation, and discussions on missing data handling. The tutorial also reviews the statistical analyses employed in TGI studies, considering both continuous endpoints collected at single time-point and continuous endpoints collected longitudinally over multiple time-points. Additionally, time-to-event analysis is discussed for studies focusing on event occurrences such as animal deaths or tumor size reaching a certain threshold. Furthermore, for TGI studies involving categorical endpoints, statistical methodology is outlined to compare outcomes among treatment groups effectively. Lastly, this tutorial also discusses analysis for assessing drug combination synergy in TGI studies, which involves combining treatments to enhance overall treatment efficacy. The tutorial also includes R sample scripts to help users to perform relevant data analysis of this topic.

First-in-human, phase 1 study of PF-06753512, a vaccine-based immunotherapy regimen (VBIR), in non-metastatic hormone-sensitive biochemical recurrence and metastatic castration-resistant prostate cancer (mCRPC).

BACKGROUND: This phase 1 study evaluated PF-06753512, a vaccine-based immunotherapy regimen (PrCa VBIR), in two clinical states of prostate cancer (PC), metastatic castration-resistant PC (mCRPC) and biochemical recurrence (BCR). METHODS: For dose escalation, patients with mCRPC received intramuscular PrCa VBIR (adenovirus vector and plasmid DNA expressing prostate-specific membrane antigen (PSMA), prostate-specific antigen (PSA), and prostate stem cell antigen (PSCA)) with or without immune checkpoint inhibitors (ICIs, tremelimumab 40 or 80 mg with or without sasanlimab 130 or 300 mg, both subcutaneous). For dose expansion, patients with mCRPC received recommended phase 2 dose (RP2D) of PrCa VBIR plus tremelimumab 80 mg and sasanlimab 300 mg; patients with BCR received PrCa VBIR plus tremelimumab 80 mg (Cohort 1B-BCR) or tremelimumab 80 mg plus sasanlimab 130 mg (Cohort 5B-BCR) without androgen deprivation therapy (ADT). The primary endpoint was safety. RESULTS: Ninety-one patients were treated in dose escalation (mCRPC=38) and expansion (BCR=35, mCRPC=18). Overall, treatment-related and immune-related adverse events occurred in 64 (70.3%) and 39 (42.9%) patients, with fatigue (40.7%), influenza-like illness (30.8%), diarrhea (23.1%), and immune-related thyroid dysfunction (19.8%) and rash (15.4%), as the most common. In patients with mCRPC, the objective response rate (ORR, 95% CI) was 5.6% (1.2% to 15.4%) and the median radiographic progression-free survival (rPFS) was 5.6 (3.5 to not estimable) months for all; the ORR was 16.7% (3.6% to 41.4%) and 6-month rPFS rate was 45.5% (24.9% to 64.1%) for those who received RP2D with measurable disease (n=18). 7.4% of patients with mCRPC achieved a ≥50% decline in baseline PSA (PSA-50), with a median duration of 4.6 (1.2-45.2) months. In patients with BCR, 9 (25.7%) achieved PSA-50; the median duration of PSA response was 3.9 (1.9-4.2) and 10.1 (6.9-28.8) months for Cohorts 5B-BCR and 1B-BCR. Overall, antigen specific T-cell response was 88.0% to PSMA, 84.0% to PSA, and 80.0% to PSCA. CONCLUSIONS: PrCa VBIR overall demonstrated safety signals similar to other ICI combination trials; significant side effects were seen in some patients with BCR. It stimulated antigen-specific immunity across all cohorts and resulted in modest antitumor activity in patients with BCR without using ADT. TRIAL REGISTRATION NUMBER: NCT02616185.

Exact simultaneous confidence intervals for logical selection of a biomarker cut-point.

This article proposes four new principles for logical biomarker cut-point selection methods to adhere to: subgroup sensibility, sensitivity, specificity, and target monotonicity. At every cut-point value, our method gives confidence intervals not only for the efficacy at that cut-point value, but also efficacies in the marker-positive and marker-negative subgroups defined by that cut-point. These confidence intervals are given simultaneously for all possible cut-point values. Using Alzheimer's disease (AD) and type 2 diabetes (T2DM) as examples, we show our method achieves the four principles. Our method strongly controls familywise type I error rate (FWER) across both levels of multiplicity: the multiplicity of having marker-positive and marker-negative subgroups at each cut-point, and the multiplicity of searching through infinitely many cut-points. This is in contrast to other available methods. The confidence level of our simultaneous confidence intervals is in fact exact (not conservative). An application (app) is available, which implements the method we propose.

Development of a PD-L1 Complementary Diagnostic Immunohistochemistry Assay (SP142) for Atezolizumab.

Cancer immunotherapies, such as atezolizumab, are proving to be a valuable therapeutic strategy across indications, including non-small cell lung cancer (NSCLC) and urothelial cancer (UC). Here, we describe a diagnostic assay that measures programmed-death ligand 1 (PD-L1) expression, via immunohistochemistry, to identify patients who will derive the most benefit from treatment with atezolizumab, a humanized monoclonal anti-PD-L1 antibody. We describe the performance of the VENTANA PD-L1 (SP142) Assay in terms of specificity, sensitivity, and the ability to stain both tumor cells (TC) and tumor-infiltrating immune cells (IC), in NSCLC and UC tissues. The reader precision, repeatability and intermediate precision, interlaboratory reproducibility, and the effectiveness of pathologist training on the assessment of PD-L1 staining on both TC and IC were evaluated. We detail the analytical validation of the VENTANA PD-L1 (SP142) Assay for PD-L1 expression in NSCLC and UC tissues and show that the assay reliably evaluated staining on both TC and IC across multiple expression levels/clinical cut-offs. The reader precision showed high overall agreement when compared with consensus scores. In addition, pathologists met the predefined training criteria (≥85.0% overall percent agreement) for the assessment of PD-L1 expression in NSCLC and UC tissues with an average overall percent agreement ≥95.0%. The assay evaluates PD-L1 staining on both cell types and is robust and precise. In addition, it can help to identify those patients who may benefit the most from treatment with atezolizumab, although treatment benefit has been demonstrated in an all-comer NSCLC and UC patient population.

Time-dependent effects of safflower oil to improve glycemia, inflammation and blood lipids in obese, post-menopausal women with type 2 diabetes: a randomized, double-masked, crossover study.

BACKGROUND & AIMS: Metabolic effects of dietary fat quality in people with type 2 diabetes are not well-understood. The study objective was to evaluate effects of conjugated linoleic acid (CLA) and safflower (SAF) oils on glycemia, blood lipids, and inflammation. The hypothesis we tested is that dietary oils improve glycemia, lipids, and inflammatory markers in a time-dependent way that follows accumulation of linoleic acid and CLA isomers in serum of subjects supplemented with dietary oils. METHODS: Fifty-five post-menopausal, obese women with type 2 diabetes enrolled, and 35 completed this randomized, double-masked crossover study. Treatments were 8 g daily of CLA and SAF for 16 weeks each. We used a multiple testing procedure with pre-determined steps analysis to determine the earliest time that a significant effect was detected. RESULTS: CLA did not alter measured metabolic parameters. SAF decreased HbA1c (-0.64 ± 0.18%, p = 0.0007) and C-reactive protein (-13.6 ± 8.2 mg/L, p = 0.0472), increased QUICKI (0.0077 ± 0.0035, p = 0.0146) with a minimum time to effect observed 16 weeks after treatment. SAF increased HDL cholesterol (0.12 ± 0.05 mmol/L, p = 0.0228) with the minimum time to detect an effect of SAF at 12 weeks. The minimum time to detect an increase of c9t11-CLA, t10c12-CLA, and linoleic acid in serum of women supplemented CLA or SAF, respectively, was four weeks. CONCLUSIONS: We conclude that 8 g of SAF daily improved glycemia, inflammation, and blood lipids, indicating that small changes in dietary fat quality may augment diabetes treatments to improve risk factors for diabetes-related complications.