T-Cell-Inflamed Gene-Expression Profile, Programmed Death Ligand 1 Expression, and Tumor Mutational Burden Predict Efficacy in Patients Treated With Pembrolizumab Across 20 Cancers: KEYNOTE-028.

Purpose: Biomarkers that can predict response to anti-programmed cell death 1 (PD-1) therapy across multiple tumor types include a T-cell-inflamed gene-expression profile (GEP), programmed death ligand 1 (PD-L1) expression, and tumor mutational burden (TMB). Associations between these biomarkers and the clinical efficacy of pembrolizumab were evaluated in a clinical trial that encompassed 20 cohorts of patients with advanced solid tumors.

Methods: KEYNOTE-028 ( ClinicalTrials.

Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy.

Programmed cell death protein-1 (PD-1) and programmed cell death ligand-1 (PD-L1) checkpoint blockade immunotherapy elicits durable antitumor effects in multiple cancers, yet not all patients respond. We report the evaluation of >300 patient samples across 22 tumor types from four KEYNOTE clinical trials. Tumor mutational burden (TMB) and a T cell-inflamed gene expression profile (GEP) exhibited joint predictive utility in identifying responders and nonresponders to the PD-1 antibody pembrolizumab.

Programmed Death-Ligand 1 Expression and Response to the Anti-Programmed Death 1 Antibody Pembrolizumab in Melanoma.

Purpose Expression of programmed death-ligand 1 (PD-L1) is a potential predictive marker for response and outcome after treatment with anti-programmed death 1 (PD-1). This study explored the relationship between anti-PD-1 activity and PD-L1 expression in patients with advanced melanoma who were treated with pembrolizumab in the phase Ib KEYNOTE-001 study (clinical trial information: NCT01295827). Patients and Methods Six hundred fifty-five patients received pembrolizumab10 mg/kg once every 2 weeks or once every 3 weeks, or 2 mg/kg once every 3 weeks.

Pembrolizumab for the treatment of non-small-cell lung cancer.

Background: We assessed the efficacy and safety of programmed cell death 1 (PD-1) inhibition with pembrolizumab in patients with advanced non-small-cell lung cancer enrolled in a phase 1 study. We also sought to define and validate an expression level of the PD-1 ligand 1 (PD-L1) that is associated with the likelihood of clinical benefit.

Methods: We assigned 495 patients receiving pembrolizumab (at a dose of either 2 mg or 10 mg per kilogram of body weight every 3 weeks or 10 mg per kilogram every 2 weeks) to either a training group (182 patients) or a validation group (313 patients).

Clinical utility estimation for assay cutoffs in early phase oncology enrichment trials.

Predictive enrichment strategies use biomarkers to selectively enroll oncology patients into clinical trials to more efficiently demonstrate therapeutic benefit. Because the enriched population differs from the patient population eligible for screening with the biomarker assay, there is potential for bias when estimating clinical utility for the screening eligible population if the selection process is ignored. We write estimators of clinical utility as integrals averaging regression model predictions over the conditional distribution of the biomarker scores defined by the assay cutoff and discuss the conditions under which consistent estimation can be achieved while accounting for some nuances that may arise as the biomarker assay progresses toward a companion diagnostic.

Evaluating surrogate variables for improving microarray multiple testing inference.

The use of surrogate variables has been proposed as a means to capture, for a given observed set of data, sources driving the dependency structure among high-dimensional sets of features and remove the effects of those sources and their potential negative impact on simultaneous inference. In this article we illustrate the potential effects of latent variables on testing dependence and the resulting impact on multiple inference, we briefly review the method of surrogate variable analysis proposed by Leek and Storey (PNAS 2008; 105:18718-18723), and assess that method via simulations intended to mimic the complexity of feature dependence observed in real-world microarray data. The method is also assessed via application to a recent Merck microarray data set.

Statistical performance of cladistic strategies for haplotype grouping in pharmacogenetics.

Haplotypes comprising multiple single nucleotide polymorphisms (SNPs) are popular covariates for capturing the key genetic variation present over a region of interest in the DNA sequence. Although haplotypes can provide a clearer assessment of genetic variation in a region than their component SNPs considered individually, the multi-allelic nature of haplotypes increases the complexity of the statistical models intended to discover association with outcomes of interest. Cladistic methods cluster haplotypes according to the estimates of their genealogical closeness and have been proposed recently as strategies for reducing model complexity and increasing power.

Effect of initial combination therapy with sitagliptin, a dipeptidyl peptidase-4 inhibitor, and metformin on glycemic control in patients with type 2 diabetes.

Objective: To assess the efficacy and safety of initial combination therapy with sitagliptin and metformin in patients with type 2 diabetes and inadequate glycemic control on diet and exercise.

Research Design And Methods: In a 24-week, randomized, double-blind, placebo-controlled, parallel-group study, 1,091 patients with type 2 diabetes and A1C 7.5-11% were randomized to one of six daily treatments: sitagliptin 100 mg/metformin 1,000 mg (S100/M1000 group), sitagliptin 100 mg/metformin 2,000 mg (S100/M2000 group), metformin 1,000 mg (M1000 group), metformin 2,000 mg (M2000 group) (all as divided doses administered twice daily [b.

Effect of the dipeptidyl peptidase-4 inhibitor sitagliptin as monotherapy on glycemic control in patients with type 2 diabetes.

Objective: To examine the efficacy and safety of once-daily oral sitagliptin as monotherapy in patients with type 2 diabetes.

Research Design And Methods: In a randomized, double-blind, placebo-controlled study, 741 patients (baseline HbA(1c) [A1C] 8.0%) were randomized to sitagliptin 100 or 200 mg or placebo for 24 weeks.

Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study.

Estimation of treatment effects with causal interpretation from observational data is complicated because exposure to treatment may be confounded with subject characteristics. The propensity score, the probability of treatment exposure conditional on covariates, is the basis for two approaches to adjusting for confounding: methods based on stratification of observations by quantiles of estimated propensity scores and methods based on weighting observations by the inverse of estimated propensity scores. We review popular versions of these approaches and related methods offering improved precision, describe theoretical properties and highlight their implications for practice, and present extensive comparisons of performance that provide guidance for practical use.

Estimation of survival distributions of treatment policies in two-stage randomization designs in clinical trials.

Some clinical trials follow a design where patients are randomized to a primary therapy at entry followed by another randomization to maintenance therapy contingent upon disease remission. Ideally, analysis would allow different treatment policies, i.e.