Common variation in a long non-coding RNA gene modulates variation of circulating TGF-ß2 levels in metastatic colorectal cancer patients (Alliance).

BACKGROUND: Herein, we report results from a genome-wide study conducted to identify protein quantitative trait loci (pQTL) for circulating angiogenic and inflammatory protein markers in patients with metastatic colorectal cancer (mCRC). The study was conducted using genotype, protein marker, and baseline clinical and demographic data from CALGB/SWOG 80405 (Alliance), a randomized phase III study designed to assess outcomes of adding VEGF or EGFR inhibitors to systemic chemotherapy in mCRC patients. Germline DNA derived from blood was genotyped on whole-genome array platforms. The abundance of protein markers was quantified using a multiplex enzyme-linked immunosorbent assay from plasma derived from peripheral venous blood collected at baseline. A robust rank-based method was used to assess the statistical significance of each variant and protein pair against a strict genome-wide level. A given pQTL was tested for validation in two external datasets of prostate (CALGB 90401) and pancreatic cancer (CALGB 80303) patients. Bioinformatics analyses were conducted to further establish biological bases for these findings. RESULTS: The final analysis was carried out based on data from 540,021 common typed genetic variants and 23 protein markers from 869 genetically estimated European patients with mCRC. Correcting for multiple testing, the analysis discovered a novel cis-pQTL in LINC02869, a long non-coding RNA gene, for circulating TGF-ß2 levels (rs11118119; AAF = 0.11; P-value < 1.4e-14). This finding was validated in a cohort of 538 prostate cancer patients from CALGB 90401 (AAF = 0.10, P-value < 3.3e-25). The analysis also validated a cis-pQTL we had previously reported for VEGF-A in advanced pancreatic cancer, and additionally identified trans-pQTLs for VEGF-R3, and cis-pQTLs for CD73. CONCLUSIONS: This study has provided evidence of a novel cis germline genetic variant that regulates circulating TGF-ß2 levels in plasma of patients with advanced mCRC and prostate cancer. Moreover, the validation of previously identified pQTLs for VEGF-A, CD73, and VEGF-R3, potentiates the validity of these associations.

Pharmacogenetic and clinical risk factors for bevacizumab-related gastrointestinal hemorrhage in prostate cancer patients treated on CALGB 90401 (Alliance).

The objective of this study was to discover clinical and pharmacogenetic factors associated with bevacizumab-related gastrointestinal hemorrhage in Cancer and Leukemia Group B (Alliance) 90401. Patients with metastatic castration-resistant prostate cancer received docetaxel and prednisone ± bevacizumab. Patients were genotyped using Illumina HumanHap610-Quad and assessed using cause-specific risk for association between single nucleotide polymorphisms (SNPs) and gastrointestinal hemorrhage. In 1008 patients, grade 2 or higher gastrointestinal hemorrhage occurred in 9.5% and 3.8% of bevacizumab (n = 503) and placebo (n = 505) treated patients, respectively. Bevacizumab (P < 0.001) and age (P = 0.002) were associated with gastrointestinal hemorrhage. In 616 genetically estimated Europeans (n = 314 bevacizumab and n = 302 placebo treated patients), grade 2 or higher gastrointestinal hemorrhage occurred in 9.6% and 2.0% of patients, respectively. One SNP (rs1478947; HR 6.26; 95% CI 3.19-12.28; P = 9.40 × 10-8) surpassed Bonferroni-corrected significance. Grade 2 or higher gastrointestinal hemorrhage rate was 33.3% and 6.2% in bevacizumab-treated patients with the AA/AG and GG genotypes, versus 2.9% and 1.9% in the placebo arm, respectively. Prospective validation of these findings and functional analyses are needed to better understand the genetic contribution to treatment-related gastrointestinal hemorrhage.

End points in clinical trials in diffuse large B-cell lymphoma: time for more dialogue?

We observed lack of clarity and consistency in end point definitions of large randomized clinical trials in diffuse large B-cell lymphoma. These inconsistencies are such that trials might, in fact, address different clinical questions. They complicate interpretation of results, including comparisons across studies. Problems arise from different ways to account for events occurring after randomization including absence of improvement in disease status, treatment discontinuation or the initiation of new therapy. We call for more dialogue between stakeholders to define with clarity the questions of interest and corresponding end points. We illustrate that assessing different end point rules across a range of plausible patient journeys can be a powerful tool to facilitate such a discussion and contribute to better understanding of patient-relevant end points.

What is this article about? This article talks about the lack of clarity and consistency in the definitions of outcomes used in clinical trials that investigate new treatments for diffuse large B-cell lymphoma. This is mainly due to how these different outcome definitions handle events such as absence of improvement in disease status, treatment discontinuation or initiation of new treatment. The authors discuss how these inconsistencies make it hard to interpret the results of individual clinical trials and to compare results across clinical trials.Why is it important? Defining the above events and consequently defining outcomes affects what we can learn from the trials and can lead to different results. Some approaches may not reflect good and bad outcomes for patients appropriately. This makes it challenging for patients, physicians, health authorities and payors to understand the true benefit of treatments under investigation and which one is better.What are the key take-aways? This article serves as a call-to-action for more dialogue among all stakeholders involved in drug development and the decision-making process related to drug evaluations. There is an urgent need for clinical trials to be designed with more clarity and consistency on what is being measured so that relevant questions for patients and prescribing physicians are addressed. Understanding patient journeys will be key to successfully understand what truly matters to patients and how to measure the benefit of new treatments. Such discussions will contribute toward more clarity and consistency in the evaluation of new treatments.

Current issues in dose-finding designs: A response to the US Food and Drug Adminstration's Oncology Center of Excellence Project Optimus.

With the advent of targeted agents and immunological therapies, the medical research community has become increasingly aware that conventional methods for determining the best dose or schedule of a new agent are inadequate. It has been well established that conventional phase I designs cannot reliably identify safe and effective doses. This problem applies, generally, for cytotoxic agents, radiation therapy, targeted agents, and immunotherapies. To address this, the US Food and Drug Administration's Oncology Center of Excellence initiated Project Optimus, with the goal "to reform the dose optimization and dose selection paradigm in oncology drug development." As a response to Project Optimus, the articles in this special issue of Clinical Trials review recent advances in methods for choosing the dose or schedule of a new agent with an overall objective of informing clinical trialists of these innovative designs. This introductory article briefly reviews problems with conventional methods, the regulatory changes that encourage better dose optimization designs, and provides brief summaries of the articles that follow in this special issue.

Quality of life outcomes for patients with metastatic castration-resistant prostate cancer and pretreatment prognostic score.

BACKGROUND: A prognostic risk score (Halabi score) in metastatic castration-resistant prostate cancer (mCRPC) accurately predicts overall survival, but its association with quality of life (QOL) has not been defined. We hypothesize that a higher pretreatment Halabi score is associated with worse QOL outcomes over time in mCRPC patients. METHODS: Patient-level data from the docetaxel plus prednisone control arm of Mainsail, a Phase 3 clinical trial in mCRPC were accessed via ProjectDataSphere. Pretreatment Halabi score included disease-related factors: metastatic site, opioid use, Eastern Cooperative Oncology Group performance status (ECOG-PS), alkaline phosphatase, albumin, hemoglobin, lactic acid dehydrogenase, and PSA, with higher score indicating worse survival. Three QOL scales were created: Functional Assessment of Cancer Therapy-Prostate (FACT-P, higher score = better QOL), Brief Pain Inventory-Short Form Severity score (BPI-SFSS, higher score = higher pain severity), and BPI-SF Interference score (BPI-SFIS, higher score = greater pain interference). Mixed linear model was used to estimate the associations between Halabi score and QOL scores assessed at different time points (baseline, 2 months, and 6 months). RESULTS: This analysis included 412 mCRPC patients (median age = 68 years, 82% white, 5% Black, median log PSA = 4.4 ng/mL). After multivariable adjustment, Halabi score was significantly associated with QOL scores at all time points. At 6 months, multivariable adjusted FACT-P decreased by 10.0 points (worsening), BPI-SFSS increased by 0.8 points (worsening), and BPI-SFIS increased by 0.9 points (worsening) for each unit increase in Halabi risk score. In multivariable analysis of individual components, ECOG-PS, site of metastasis, and opioid use were significantly associated with worse QOL scores at baseline. CONCLUSIONS: Chemotherapy-naïve mCRPC patients with poorer Halabi prognostic risk scores have poorer QOL and greater pain intensity and interference at baseline and during follow-up.

American Joint Committee on Cancer acceptance criteria for inclusion of risk models for individualized prognosis in the practice of precision medicine.

The American Joint Committee on Cancer (AJCC) has increasingly recognized the need for more personalized probabilistic predictions than those delivered by ordinal staging systems, particularly through the use of accurate risk models or calculators. However, judging the quality and acceptability of a risk model is complex. The AJCC Precision Medicine Core conducted a 2-day meeting to discuss characteristics necessary for a quality risk model in cancer patients. More specifically, the committee established inclusion and exclusion criteria necessary for a risk model to potentially be endorsed by the AJCC. This committee reviewed and discussed relevant literature before creating a checklist unique to this need of AJCC risk model endorsement. The committee identified 13 inclusion and 3 exclusion criteria for AJCC risk model endorsement in cancer. The emphasis centered on performance metrics, implementation clarity, and clinical relevance. The facilitation of personalized probabilistic predictions for cancer patients holds tremendous promise, and these criteria will hopefully greatly accelerate this process. Moreover, these criteria might be useful for a general audience when trying to judge the potential applicability of a published risk model in any clinical domain. CA Cancer J Clin 2016;66:370-374. © 2016 American Cancer Society.

Abatacept, Cenicriviroc, or Infliximab for Treatment of Adults Hospitalized With COVID-19 Pneumonia: A Randomized Clinical Trial.

Importance: Immune dysregulation contributes to poorer outcomes in COVID-19. Objective: To investigate whether abatacept, cenicriviroc, or infliximab provides benefit when added to standard care for COVID-19 pneumonia. Design, Setting, and Participants: Randomized, double-masked, placebo-controlled clinical trial using a master protocol to investigate immunomodulators added to standard care for treatment of participants hospitalized with COVID-19 pneumonia. The results of 3 substudies are reported from 95 hospitals at 85 clinical research sites in the US and Latin America. Hospitalized patients 18 years or older with confirmed SARS-CoV-2 infection within 14 days and evidence of pulmonary involvement underwent randomization between October 2020 and December 2021. Interventions: Single infusion of abatacept (10 mg/kg; maximum dose, 1000 mg) or infliximab (5 mg/kg) or a 28-day oral course of cenicriviroc (300-mg loading dose followed by 150 mg twice per day). Main Outcomes and Measures: The primary outcome was time to recovery by day 28 evaluated using an 8-point ordinal scale (higher scores indicate better health). Recovery was defined as the first day the participant scored at least 6 on the ordinal scale. Results: Of the 1971 participants randomized across the 3 substudies, the mean (SD) age was 54.8 (14.6) years and 1218 (61.8%) were men. The primary end point of time to recovery from COVID-19 pneumonia was not significantly different for abatacept (recovery rate ratio [RRR], 1.12 [95% CI, 0.98-1.28]; P = .09), cenicriviroc (RRR, 1.01 [95% CI, 0.86-1.18]; P = .94), or infliximab (RRR, 1.12 [95% CI, 0.99-1.28]; P = .08) compared with placebo. All-cause 28-day mortality was 11.0% for abatacept vs 15.1% for placebo (odds ratio [OR], 0.62 [95% CI, 0.41-0.94]), 13.8% for cenicriviroc vs 11.9% for placebo (OR, 1.18 [95% CI 0.72-1.94]), and 10.1% for infliximab vs 14.5% for placebo (OR, 0.59 [95% CI, 0.39-0.90]). Safety outcomes were comparable between active treatment and placebo, including secondary infections, in all 3 substudies. Conclusions and Relevance: Time to recovery from COVID-19 pneumonia among hospitalized participants was not significantly different for abatacept, cenicriviroc, or infliximab vs placebo. Trial Registration: ClinicalTrials.gov Identifier: NCT04593940.

Prospective clinical trial of disulfiram plus copper in men with metastatic castration-resistant prostate cancer.

BACKGROUND: In preclinical models of prostate cancer (PC), disulfiram (DSF) reduced tumor growth only when co-administered with copper (Cu), and Cu uptake in tumors is partially regulated by androgen-receptor signaling. However, prior trials of DSF in PC used DSF as monotherapy. OBJECTIVE: To assess the safety and efficacy of concurrent administration of DSF with Cu, we conducted a phase 1b clinical trial of patients with metastatic castration-resistant prostate cancer (mCRPC) receiving Cu with DSF. DESIGN, SETTING, AND PARTICIPANTS: Patients with mCRPC were treated in two cohorts: mCRPC with nonliver/peritoneal metastases (A), and mCRPC with liver and/or peritoneal metastases (B). Baseline Cu avidity was measured by 64 CuCl2 PET scan. Intravenous (IV) CuCl2 was given weekly for three doses with oral daily DSF followed by daily oral Cu gluconate and DSF until disease progression. DSF and metabolite diethyldithiocarbamic acid methyl ester (Me-DDC) levels in plasma were measured. DSF and Me-DDC were then assessed for cytotoxicity in vitro. RESULTS: We treated nine patients with mCRPC (six on cohort A and three on cohort B). Bone and nodal metastases showed differential and heterogeneous Cu uptake on 64 CuCl2 PET scans. No confirmed PSA declines or radiographic responses were observed. Median PFS was 2.8 months and median OS was 8.3 months. Common adverse events included fatigue and psychomotor depression; no Grade 4/5 AEs were observed. Me-DDC was measurable in all samples (LOQ = 0.512 ng/ml), whereas DSF was not (LOQ = 0.032 ng/ml, LOD = 0.01 ng/ml); Me-DDC was not cytotoxic in vitro. CONCLUSIONS: Oral DSF is not an effective treatment for mCRPC due to rapid metabolism into an inactive metabolite, Me-DDC. This trial has stopped enrollment and further work is needed to identify a stable DSF formulation for treatment of mCRPC.

Penalized weighted proportional hazards model for robust variable selection and outlier detection.

Identifying exceptional responders or nonresponders is an area of increased research interest in precision medicine as these patients may have different biological or molecular features and therefore may respond differently to therapies. Our motivation stems from a real example from a clinical trial where we are interested in characterizing exceptional prostate cancer responders. We investigate the outlier detection and robust regression problem in the sparse proportional hazards model for censored survival outcomes. The main idea is to model the irregularity of each observation by assigning an individual weight to the hazard function. By applying a LASSO-type penalty on both the model parameters and the log transformation of the weight vector, our proposed method is able to perform variable selection and outlier detection simultaneously. The optimization problem can be transformed to a typical penalized maximum partial likelihood problem and thus it is easy to implement. We further extend the proposed method to deal with the potential outlier masking problem caused by censored outcomes. The performance of the proposed estimator is demonstrated with extensive simulation studies and real data analyses in low-dimensional and high-dimensional settings.

Landscape of coronavirus disease 2019 clinical trials: New frontiers and challenges.

BACKGROUND/AIM: The number of coronavirus disease 2019 deaths and cases continues to increase globally. Novel therapies are urgently needed to treat patients with coronavirus disease 2019. We sought to provide a critical review of trials designed during the coronavirus disease 2019 pandemic. Our primary goal was to provide a critical review of the landscape of clinical trials designed to address the coronavirus disease 2019 pandemic. Specifically, we were interested in assessing the design of phase II/III and phase III interventional trials. METHODS: We utilized the ClinicalTrials.gov database to include trials registered between 1 December 2019 and 11 April 2021 to survey the current landscape of clinical trials for coronavirus disease 2019. Variables extracted included: National Clinical Trial number, title, location, sponsor, study type, start date, completion date, gender group, age group, primary outcome, secondary outcome, overall status, and associated references. RESULTS: About 57% of studies were interventional, 14.5% were phase III trials, and the majority of the therapeutic trials included hospitalized patients. There were 52 primary composite outcomes and 285 unique interventions spanning 10 drug classes. The outcomes, disease severity, and comparators varied substantially across trials, and the trials were often too small to be definitive. CONCLUSION: These findings are relevant as we strongly advocate for global coordination of efforts through the use of common platforms that enable harmonizing of endpoints, collection of common key variables and clear definition of disease severity to have clinically meaningful results from clinical trials.

Intermediate clinical endpoints for surrogacy in localised prostate cancer: an aggregate meta-analysis.

BACKGROUND: The international Intermediate Clinical Endpoints in Cancer of the Prostate working group has established metastasis-free survival as a surrogate for overall survival in localised prostate cancer based on the findings of 19 predominantly radiotherapy-based trials. We sought to comprehensively assess aggregate trial-level performance of commonly reported intermediate clinical endpoints across all randomised trials in localised prostate cancer. METHODS: For this meta-analysis, we searched PubMed for all trials in localised or biochemically recurrent prostate cancer published between Jan 1, 1970, and Jan 15, 2020. Eligible trials had to be randomised, therapeutic, reporting overall survival and at least one intermediate clinical endpoint, and with a sample size of at least 70 participants. Trials of metastatic disease were excluded. Intermediate clinical endpoints included biochemical failure, local failure, distant metastases, biochemical failure-free survival, progression-free survival, and metastasis-free survival. Candidacy for surrogacy was assessed using the second condition of the meta-analytical approach (ie, correlation of the treatment effect of the intermediate clinical endpoint and overall survival), using R2 weighted by the inverse variance of the log intermediate clinical endpoint hazard ratio. The intermediate clinical endpoint was deemed to be a surrogate for overall survival if R2 was 0·7 or greater. FINDINGS: 75 trials (53 631 patients) were included in our analysis. Median follow-up was 9·1 years (IQR 5·7-10·6). Biochemical failure (R2 0·38 [95% CI 0·11-0·64]), biochemical failure-free survival (R2 0·12 [0·0030-0·33]), biochemical failure and clinical failure (R2 0·28 [0·0045-0·65]), and local failure (R2 0·085 [0·00-0·37]) correlated poorly with overall survival. Progression-free survival (R2 0·46 [95% CI 0·22-0·67]) showed moderate correlation with overall survival, and metastasis-free survival (R2 0·78 [0·59-0·89]) correlated strongly. INTERPRETATION: Intermediate clinical endpoints based on biochemical and local failure did not meet the second condition of the meta-analytical approach and are not surrogate endpoints for overall survival in localised prostate cancer. Our findings validate metastasis-free survival as the only identified surrogate endpoint for overall survival to date. FUNDING: Prostate Cancer Foundation and National Institutes of Health.

A prospective trial of abiraterone acetate plus prednisone in Black and White men with metastatic castrate-resistant prostate cancer.

BACKGROUND: Retrospective analyses of randomized trials suggest that Black men with metastatic castration-resistant prostate cancer (mCRPC) have longer survival than White men. The authors conducted a prospective study of abiraterone acetate plus prednisone to explore outcomes by race. METHODS: This race-stratified, multicenter study estimated radiographic progression-free survival (rPFS) in Black and White men with mCRPC. Secondary end points included prostate-specific antigen (PSA) kinetics, overall survival (OS), and safety. Exploratory analysis included genome-wide genotyping to identify single nucleotide polymorphisms associated with progression in a model incorporating genetic ancestry. One hundred patients self-identified as White (n = 50) or Black (n = 50) were enrolled. Eligibility criteria were modified to facilitate the enrollment of individual Black patients. RESULTS: The median rPFS for Black and White patients was 16.6 and 16.8 months, respectively; their times to PSA progression (TTP) were 16.6 and 11.5 months, respectively; and their OS was 35.9 and 35.7 months, respectively. Estimated rates of PSA decline by ≥50% in Black and White patients were 74% and 66%, respectively; and PSA declines to <0.2 ng/mL were 26% and 10%, respectively. Rates of grade 3 and 4 hypertension, hypokalemia, and hyperglycemia were higher in Black men. CONCLUSIONS: Multicenter prospective studies by race are feasible in men with mCRPC but require less restrictive eligibility. Despite higher comorbidity rates, Black patients demonstrated rPFS and OS similar to those of White patients and trended toward greater TTP and PSA declines, consistent with retrospective reports. Importantly, Black men may have higher side-effect rates than White men. This exploratory genome-wide analysis of TTP identified a possible candidate marker of ancestry-dependent treatment outcomes.

Indirect Comparison of Darolutamide versus Apalutamide and Enzalutamide for Nonmetastatic Castration-Resistant Prostate Cancer.

PURPOSE: No published head-to-head randomized trials have compared the safety and efficacy of darolutamide vs apalutamide or enzalutamide in nonmetastatic castration-resistant prostate cancer. This study compares prespecified adverse events and metastasis-free survival associated with darolutamide vs apalutamide, and darolutamide vs enzalutamide, via matching-adjusted indirect comparisons. MATERIALS AND METHODS: Individual patient data from the phase III ARAMIS trial (NPLACEBO=553; NDAROLUTAMIDE=943) were selected and reweighted to match the inclusion criteria and baseline characteristics published for the phase III SPARTAN (NPLACEBO=401; NAPALUTAMIDE=806) and PROSPER (NPLACEBO=468; NENZALUTAMIDE=933) trials. Only baseline factors consistently reported across trials were included as matching covariates. Both indirect comparisons matched on age, prostate specific antigen level and doubling time, Eastern Cooperative Oncology Group performance status, Gleason score, and bone-sparing agent use. Darolutamide vs apalutamide also matched on prior surgery and darolutamide vs enzalutamide also matched on region. Risk differences and odds ratios were calculated for adverse events and hazard ratios for metastasis-free survival. RESULTS: No differences in metastasis-free survival hazard ratios were found after matching in either comparison. However, fall, fracture and rash rates were statistically significantly lower in favor of darolutamide vs apalutamide. Fall, dizziness, mental impairment, fatigue and severe fatigue rates were statistically significantly lower in favor of darolutamide vs enzalutamide. CONCLUSIONS: While metastasis-free survival did not differ across drugs in these cross-trial indirect comparisons, darolutamide showed a favorable safety and tolerability profile in prespecified adverse events vs apalutamide and enzalutamide. Consideration of these adverse events is important in clinical decision-making and treatment selection in nonmetastatic castration-resistant prostate cancer.

On the design and the analysis of stratified biomarker trials in the presence of measurement error.

A major emphasis in precision medicine is to optimally treat subgroups of patients who may benefit from certain therapeutic agents. And as such, enormous resources and innovative clinical trials designs in oncology are devoted to identifying predictive biomarkers. Predictive biomarkers are ones that will identify patients that are more likely to respond to specific therapies and they are usually discovered through retrospective analysis from large randomized phase II or phase III trials. One important design to consider is the stratified biomarker design, where patients will have their specimens obtained at baseline and the biomarker status will be assessed prior to random assignment. Regardless of their biomarker status, patients will be randomized to either an experimental arm or the standard of care arm. The stratified biomarker design can be used to test for a treatment-biomarker interaction in predicting a time-to event outcome. Many biomarkers, however, are derived from tissues from patients, and their levels may be heterogeneous. As a result, biomarker levels may be measured with error and this would have an adverse impact on the power of a stratified biomarker clinical trial. We present a trial design and an analysis framework for the stratified biomarker design. We show that the naïve test is biased and provide bias-corrected estimators for computing the sample size and the 95% confidence interval when testing for a treatment-biomarker interaction in predicting a time to event outcome. We propose a sample size formula that adjusts for misclassification and apply it in the design of a phase III clinical trial in renal cancer.

A semiparametric modeling approach for analyzing clinical biomarkers restricted to limits of detection.

Before biomarkers can be used in clinical trials or patients' management, the laboratory assays that measure their levels have to go through development and analytical validation. One of the most critical performance metrics for validation of any assay is related to the minimum amount of values that can be detected and any value below this limit is referred to as below the limit of detection (LOD). Most of the existing approaches that model such biomarkers, restricted by LOD, are parametric in nature. These parametric models, however, heavily depend on the distributional assumptions, and can result in loss of precision under the model or the distributional misspecifications. Using an example from a prostate cancer clinical trial, we show how a critical relationship between serum androgen biomarker and a prognostic factor of overall survival is completely missed by the widely used parametric Tobit model. Motivated by this example, we implement a semiparametric approach, through a pseudo-value technique, that effectively captures the important relationship between the LOD restricted serum androgen and the prognostic factor. Our simulations show that the pseudo-value based semiparametric model outperforms a commonly used parametric model for modeling below LOD biomarkers by having lower mean square errors of estimation.

Estimand framework: Are we asking the right questions? A case study in the solid tumor setting.

The estimand framework requires a precise definition of the clinical question of interest (the estimand) as different ways of accounting for "intercurrent" events post randomization may result in different scientific questions. The initiation of subsequent therapy is common in oncology clinical trials and is considered an intercurrent event if the start of such therapy occurs prior to a recurrence or progression event. Three possible ways to account for this intercurrent event in the analysis are to censor at initiation, consider recurrence or progression events (including death) that occur before and after the initiation of subsequent therapy, or consider the start of subsequent therapy as an event in and of itself. The new estimand framework clarifies that these analyses address different questions ("does the drug delay recurrence if no patient had received subsequent therapy?" vs "does the drug delay recurrence with or without subsequent therapy?" vs "does the drug delay recurrence or start of subsequent therapy?"). The framework facilitates discussions during clinical trial planning and design to ensure alignment between the key question of interest, the analysis, and interpretation. This article is a result of a cross-industry collaboration to connect the International Council for Harmonisation E9 addendum concepts to applications. Data from previously reported randomized phase 3 studies in the renal cell carcinoma setting are used to consider common intercurrent events in solid tumor studies, and to illustrate different scientific questions and the consequences of the estimand choice for study design, data collection, analysis, and interpretation.

Discordant and heterogeneous clinically relevant genomic alterations in circulating tumor cells vs plasma DNA from men with metastatic castration resistant prostate cancer.

Circulating tumor cell (CTC) and cell-free (cf) DNA-based genomic alterations are increasingly being used for clinical decision-making in oncology. However, the concordance and discordance between paired CTC and cfDNA genomic profiles remain largely unknown. We performed comparative genomic hybridization (CGH) on CTCs and cfDNA, and low-pass whole genome sequencing (lpWGS) on cfDNA to characterize genomic alterations (CNA) and tumor content in two independent prospective studies of 93 men with mCRPC treated with enzalutamide/abiraterone, or radium-223. Comprehensive analysis of 69 patient CTCs and 72 cfDNA samples from 93 men with mCRPC, including 64 paired samples, identified common concordant gains in FOXA1, AR, and MYC, and losses in BRCA1, PTEN, and RB1 between CTCs and cfDNA. Concordant PTEN loss and discordant BRCA2 gain were associated with significantly worse outcomes in Epic AR-V7 negative men with mCRPC treated with abiraterone/enzalutamide. We identified and externally validated CTC-specific genomic alternations that were discordant in paired cfDNA, even in samples with high tumor content. These CTC/cfDNA-discordant regions included key genomic regulators of lineage plasticity, osteomimicry, and cellular differentiation, including MYCN gain in CTCs (31%) that was rarely detected in cfDNA. CTC MYCN gain was associated with poor clinical outcomes in AR-V7 negative men and small cell transformation. In conclusion, we demonstrated concordance of multiple genomic alterations across CTC and cfDNA platforms; however, some genomic alterations displayed substantial discordance between CTC DNA and cfDNA despite the use of identical copy number analysis methods, suggesting tumor heterogeneity and divergent evolution associated with poor clinical outcomes.

Challenges and Opportunities to Updating Prescribing Information for Longstanding Oncology Drugs.

A number of important drugs used to treat cancer-many of which serve as the backbone of modern chemotherapy regimens-have outdated prescribing information in their drug labeling. The Food and Drug Administration is undertaking a pilot project to develop a process and criteria for updating prescribing information for longstanding oncology drugs, based on the breadth of knowledge the cancer community has accumulated with the use of these drugs over time. This article highlights a number of considerations for labeling updates, including selecting priorities for updating; data sources and evidentiary criteria; as well as the risks, challenges, and opportunities for iterative review to ensure prescribing information for oncology drugs remains relevant to current clinical practice.

Score and deviance residuals based on the full likelihood approach in survival analysis.

Assuming the proportional hazards model and non-informative censoring, the full likelihood approach is used to obtain two new residuals. The first residual is based on the ideas used in obtaining score-type residuals similar to the partial likelihood approach. The second type of residual is based on the concept of deviance residuals. Extensive simulations are conducted to compare the performance of the residuals from the full likelihood-based approach with those of the partial likelihood method. We demonstrate through simulation studies that the full likelihood-based residuals are more efficient than their partial likelihood counterpart in identifying potential outliers when the censoring proportion is high. The graphical techniques are used to illustrate the applications of these residuals using some examples.